Compare commits
2 Commits
| Author | SHA1 | Date | |
|---|---|---|---|
 coderabbitai[bot]
|
54d72f8f57 | ||
|
camilleAND
|
dfb7fb81a6 |
@@ -9,11 +9,9 @@ skip =
|
||||
**/e2e/report/**,
|
||||
*.tsbuildinfo,
|
||||
**/uv.lock,
|
||||
./docker/files/etc/mime.types,
|
||||
check-filenames = true
|
||||
ignore-words-list =
|
||||
afterAll,
|
||||
statics,
|
||||
exclude-file =
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||||
./src/backend/chat/agent_rag/web_search/mocked.py,
|
||||
|
||||
|
||||
@@ -200,7 +200,7 @@ jobs:
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- name: Install gettext (required to compile messages) and MIME support
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run: |
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||||
sudo apt-get install -y gettext pandoc shared-mime-info
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||||
sudo cp $GITHUB_WORKSPACE/docker/files/etc/mime.types /etc/mime.types
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||||
sudo wget https://svn.apache.org/repos/asf/httpd/httpd/trunk/docs/conf/mime.types -O /etc/mime.types
|
||||
|
||||
- name: Generate a MO file from strings extracted from the project
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run: uv run python manage.py compilemessages
|
||||
|
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+2
-35
@@ -10,44 +10,13 @@ and this project adheres to
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||||
|
||||
### Added
|
||||
|
||||
- ✨(waffle) hide the waffle if not fr theme
|
||||
- ✨(front) allow pasting an attachment from clipboard
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||||
- ✨(array) temporarily adjust array
|
||||
- ✨(tools) add basic translate tool
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||||
|
||||
### Changed
|
||||
|
||||
- ⚡️(front) optimize streaming markdown rendering performance
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||||
- ⬆️(back) update pydantic-ai
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- ♻️(chat) refactor AIAgentService for readability and maintainability
|
||||
|
||||
### Fixed
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||||
|
||||
- 💚(docker) vendor mime.types file instead of fetching from Apache SVN
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||||
- 🐛(front) fix math formulas and carousel translations
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- 🐛(helm) reverse liveness and readiness for backend deployment
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|
||||
## [0.0.13] - 2026-02-09
|
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|
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### Added
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||||
|
||||
- 💄(front) ui fix : update ui-kit
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||||
- ✨(front) add persistent darkmode
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- ✨(front) add ui kit #240
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- 🧱(files) allow to use S3 storage without external access #849
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- ✨(backend) add FindRagBackend #209
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- ⬆️(back) update dependencies
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- ✨(back) use adaptive parsing for pdf documents
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|
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### Changed
|
||||
|
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- 💄(darkmode) change color feedback button
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- 🏗️(back) migrate to uv
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- ♻️(front) optimize syntax highlighting bundle size
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|
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### Fixed
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|
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- 🐛(back) cast collection Ids to API expected types
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|
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## [0.0.12] - 2026-01-27
|
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@@ -65,7 +34,7 @@ and this project adheres to
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### Changed
|
||||
|
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- 📦️(front) update react
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- ✨(chat) generate and edit conversation title
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- ✨(chat) Generate and edit conversation title
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||||
|
||||
|
||||
### Fixed
|
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@@ -75,7 +44,6 @@ and this project adheres to
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- ⚰️(back) remove dead code and unused files
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- 🐛(back) prevent tool call timeouts
|
||||
|
||||
|
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### Removed
|
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|
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- 🔥(chat) remove thinking part from frontend #227
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@@ -234,8 +202,7 @@ and this project adheres to
|
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- 💄(chat) add code highlighting for LLM responses #67
|
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|
||||
|
||||
[unreleased]: https://github.com/suitenumerique/conversations/compare/v0.0.13...main
|
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[0.0.13]: https://github.com/suitenumerique/conversations/releases/v0.0.13
|
||||
[unreleased]: https://github.com/suitenumerique/conversations/compare/v0.0.12...main
|
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[0.0.12]: https://github.com/suitenumerique/conversations/releases/v0.0.12
|
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[0.0.11]: https://github.com/suitenumerique/conversations/releases/v0.0.11
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[0.0.10]: https://github.com/suitenumerique/conversations/releases/v0.0.10
|
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|
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+1
-1
@@ -93,7 +93,7 @@ RUN apk add \
|
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pango \
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shared-mime-info
|
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|
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COPY ./docker/files/etc/mime.types /etc/mime.types
|
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RUN wget https://svn.apache.org/repos/asf/httpd/httpd/trunk/docs/conf/mime.types -O /etc/mime.types
|
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|
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# Copy entrypoint
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COPY ./docker/files/usr/local/bin/entrypoint /usr/local/bin/entrypoint
|
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File diff suppressed because it is too large
Load Diff
@@ -1,15 +1,11 @@
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"""Document parsers for RAG backends."""
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import base64
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import logging
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import time
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from io import BytesIO
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from urllib.parse import urljoin
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from django.conf import settings
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import requests
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from pypdf import PdfReader, PdfWriter
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from chat.agent_rag.document_converter.markitdown import DocumentConverter
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@@ -67,214 +63,3 @@ class AlbertParser(BaseParser):
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return DocumentConverter().convert_raw(
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name=name, content_type=content_type, content=content
|
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)
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|
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|
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METHOD_TEXT_EXTRACTION = "text_extraction"
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METHOD_OCR = "ocr"
|
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|
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|
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def analyze_pdf(pdf_data: bytes) -> dict:
|
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"""
|
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Analyze a PDF to determine if it needs OCR or can use direct text extraction.
|
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"""
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reader = PdfReader(BytesIO(pdf_data))
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total_pages = len(reader.pages)
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if total_pages == 0:
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logger.info("No page found in pdf")
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return {
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"total_pages": 0,
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"pages_with_text": 0,
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"avg_chars_per_page": 0,
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"text_coverage": 0,
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"recommended_method": METHOD_TEXT_EXTRACTION,
|
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}
|
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|
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total_chars = 0
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pages_with_text = 0
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for page in reader.pages:
|
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text = (page.extract_text() or "").strip()
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char_count = len(text)
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total_chars += char_count
|
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|
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if char_count > 50:
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pages_with_text += 1
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avg_chars = total_chars / total_pages
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text_coverage = pages_with_text / total_pages
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# Decision logic
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if (
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avg_chars > settings.MIN_AVG_CHARS_FOR_TEXT_EXTRACTION
|
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and text_coverage > settings.MIN_TEXT_COVERAGE_FOR_TEXT_EXTRACTION
|
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):
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method = METHOD_TEXT_EXTRACTION
|
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|
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else:
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method = METHOD_OCR
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|
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return {
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"total_pages": total_pages,
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"pages_with_text": pages_with_text,
|
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"avg_chars_per_page": round(avg_chars),
|
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"text_coverage": round(text_coverage, 2),
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"recommended_method": method,
|
||||
}
|
||||
|
||||
|
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class AdaptiveParserMixin:
|
||||
"""
|
||||
Mixin that adds adaptive PDF parsing behavior.
|
||||
|
||||
Analyzes PDF content to choose between direct text extraction (fast) and OCR
|
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(for scanned/image PDFs). Subclasses must implement `parse_pdf_document_with_ocr`.
|
||||
"""
|
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|
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def parse_pdf_document(self, name: str, content_type: str, content: bytes) -> str:
|
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"""Analyze PDF and route to text extraction or OCR based on content."""
|
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analysis = analyze_pdf(content)
|
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|
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logger.info(
|
||||
"Pdf analysis - pages: %s, pages with text: %s, text_coverage: %s, "
|
||||
"recommended method: %s",
|
||||
analysis["total_pages"],
|
||||
analysis["pages_with_text"],
|
||||
analysis["text_coverage"],
|
||||
analysis["recommended_method"],
|
||||
)
|
||||
|
||||
method = analysis["recommended_method"]
|
||||
if method == METHOD_TEXT_EXTRACTION:
|
||||
return self.extract_text_from_pdf(name=name, content_type=content_type, content=content)
|
||||
return self.parse_pdf_document_with_ocr(name=name, content=content)
|
||||
|
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def extract_text_from_pdf(self, name: str, content_type: str, content: bytes) -> str:
|
||||
"""Extract text directly from PDF without OCR (for text-based PDFs)."""
|
||||
logger.info("Parsing pdf with text extraction")
|
||||
return DocumentConverter().convert_raw(
|
||||
name=name, content_type=content_type, content=content
|
||||
)
|
||||
|
||||
def parse_pdf_document_with_ocr(self, name: str, content: bytes) -> str:
|
||||
"""Process PDF through OCR. Must be implemented by subclass."""
|
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raise NotImplementedError("Subclass must implement parse_pdf_document_with_ocr")
|
||||
|
||||
|
||||
class AdaptivePdfParser(AdaptiveParserMixin, BaseParser):
|
||||
"""
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PDF parser with adaptive text extraction / OCR routing.
|
||||
|
||||
Uses Mistral OCR API for scanned/image PDFs, processed in batches with retry logic.
|
||||
"""
|
||||
|
||||
def __init__(self):
|
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super().__init__()
|
||||
|
||||
self.endpoint = urljoin(
|
||||
settings.LLM_CONFIGURATIONS[settings.OCR_HRID].provider.base_url, "/v1/ocr"
|
||||
)
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||||
self.max_retries = settings.OCR_MAX_RETRIES
|
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self.retry_delay = settings.OCR_RETRY_DELAY
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api_key = settings.LLM_CONFIGURATIONS[settings.OCR_HRID].provider.api_key
|
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|
||||
self.headers = {
|
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"Authorization": f"Bearer {api_key}",
|
||||
"Content-Type": "application/json",
|
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}
|
||||
|
||||
def extract_page_batch(self, reader: PdfReader, start_index: int, end_index: int) -> bytes:
|
||||
"""Extract a range of pages from PDF as a new PDF bytes object."""
|
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writer = PdfWriter()
|
||||
for i in range(start_index, end_index):
|
||||
writer.add_page(reader.pages[i])
|
||||
output = BytesIO()
|
||||
writer.write(output)
|
||||
return output.getvalue()
|
||||
|
||||
def ocr_page_batch(
|
||||
self,
|
||||
name: str,
|
||||
page_content: bytes,
|
||||
start_index: int,
|
||||
end_index: int,
|
||||
) -> list[str]:
|
||||
"""Send page batch to Mistral OCR API with static delay retry."""
|
||||
file_data = base64.standard_b64encode(page_content).decode("utf-8")
|
||||
payload = {
|
||||
"document": {
|
||||
"type": "document_url",
|
||||
"document_name": f"{name}_pages_{start_index + 1}_to_{end_index}",
|
||||
"document_url": f"data:application/pdf;base64,{file_data}",
|
||||
},
|
||||
"model": settings.OCR_MODEL,
|
||||
}
|
||||
|
||||
last_exception = None
|
||||
for attempt in range(self.max_retries):
|
||||
try:
|
||||
response = requests.post(
|
||||
self.endpoint,
|
||||
headers=self.headers,
|
||||
json=payload,
|
||||
timeout=settings.OCR_TIMEOUT,
|
||||
)
|
||||
response.raise_for_status()
|
||||
|
||||
pages = response.json().get("pages", [])
|
||||
return [page.get("markdown", "") for page in pages]
|
||||
|
||||
except (requests.Timeout, requests.RequestException) as e:
|
||||
last_exception = e
|
||||
if attempt < self.max_retries - 1:
|
||||
logger.warning(
|
||||
"OCR attempt %d/%d failed for pages %d-%d: %s. Retrying in %.1fs...",
|
||||
attempt + 1,
|
||||
self.max_retries,
|
||||
start_index + 1,
|
||||
end_index,
|
||||
str(e),
|
||||
self.retry_delay,
|
||||
)
|
||||
time.sleep(self.retry_delay)
|
||||
|
||||
logger.error(
|
||||
"OCR failed for pages %d-%d after %d attempts: %s",
|
||||
start_index + 1,
|
||||
end_index,
|
||||
self.max_retries,
|
||||
str(last_exception),
|
||||
)
|
||||
raise last_exception
|
||||
|
||||
def parse_pdf_document_with_ocr(self, name: str, content: bytes) -> str:
|
||||
"""Process PDF through OCR in batches, returning concatenated markdown."""
|
||||
reader = PdfReader(BytesIO(content))
|
||||
total_pages = len(reader.pages)
|
||||
batch_size = settings.OCR_BATCH_PAGES
|
||||
|
||||
logger.info("Parsing pdf with OCR (%d pages, batch size %d)", total_pages, batch_size)
|
||||
|
||||
results = []
|
||||
for start_index in range(0, total_pages, batch_size):
|
||||
end_index = min(start_index + batch_size, total_pages)
|
||||
batch_content = self.extract_page_batch(reader, start_index, end_index)
|
||||
try:
|
||||
batch_results = self.ocr_page_batch(name, batch_content, start_index, end_index)
|
||||
results.extend(batch_results)
|
||||
logger.debug(
|
||||
"Completed OCR for pages %d-%d/%d", start_index + 1, end_index, total_pages
|
||||
)
|
||||
except Exception as e: # pylint: disable=broad-except #noqa: BLE001
|
||||
logger.error("Failed to OCR pages %d-%d: %s", start_index + 1, end_index, str(e))
|
||||
# Preserve page count with empty placeholders to maintain correct ordering
|
||||
results.extend([""] * (end_index - start_index))
|
||||
|
||||
return "\n\n".join(results)
|
||||
|
||||
def parse_document(self, name: str, content_type: str, content: bytes) -> str:
|
||||
"""Route to PDF parser or DocumentConverter based on content type."""
|
||||
if content_type == "application/pdf":
|
||||
return self.parse_pdf_document(name=name, content_type=content_type, content=content)
|
||||
|
||||
return DocumentConverter().convert_raw(
|
||||
name=name, content_type=content_type, content=content
|
||||
)
|
||||
|
||||
@@ -7,13 +7,13 @@ from typing import List, Optional
|
||||
from urllib.parse import urljoin
|
||||
|
||||
from django.conf import settings
|
||||
from django.utils.module_loading import import_string
|
||||
|
||||
import httpx
|
||||
import requests
|
||||
|
||||
from chat.agent_rag.albert_api_constants import Searches
|
||||
from chat.agent_rag.constants import RAGWebResult, RAGWebResults, RAGWebUsage
|
||||
from chat.agent_rag.document_converter.parser import AlbertParser
|
||||
from chat.agent_rag.document_rag_backends.base_rag_backend import BaseRagBackend
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
@@ -45,13 +45,7 @@ class AlbertRagBackend(BaseRagBackend): # pylint: disable=too-many-instance-att
|
||||
self._documents_endpoint = urljoin(self._base_url, "/v1/documents")
|
||||
self._search_endpoint = urljoin(self._base_url, "/v1/search")
|
||||
self._default_collection_description = "Temporary collection for RAG document search"
|
||||
parser_class = import_string(settings.RAG_DOCUMENT_PARSER)
|
||||
self.parser = parser_class()
|
||||
|
||||
@staticmethod
|
||||
def cast_collection_id(collection_id):
|
||||
"""Albert API expects int Ids."""
|
||||
return int(collection_id)
|
||||
self.parser = AlbertParser()
|
||||
|
||||
def create_collection(self, name: str, description: Optional[str] = None) -> str:
|
||||
"""
|
||||
|
||||
@@ -41,11 +41,6 @@ class BaseRagBackend(ABC):
|
||||
self._default_collection_description = "Temporary collection for RAG document search"
|
||||
self.parser: BaseParser = BaseParser()
|
||||
|
||||
@staticmethod
|
||||
def cast_collection_id(collection_id):
|
||||
"""Dummy method to be overridden when needed."""
|
||||
return collection_id
|
||||
|
||||
def get_all_collection_ids(self) -> List[str]:
|
||||
"""
|
||||
Get all collection IDs, including the main collection ID and read-only collection IDs.
|
||||
@@ -60,13 +55,10 @@ class BaseRagBackend(ABC):
|
||||
|
||||
collection_ids = []
|
||||
if self.collection_id:
|
||||
collection_ids.append(self.cast_collection_id(self.collection_id))
|
||||
collection_ids.append(self.collection_id)
|
||||
if self.read_only_collection_id:
|
||||
collection_ids.extend(
|
||||
[
|
||||
self.cast_collection_id(collection_id)
|
||||
for collection_id in self.read_only_collection_id
|
||||
]
|
||||
[int(collection_id) for collection_id in self.read_only_collection_id]
|
||||
)
|
||||
return collection_ids
|
||||
|
||||
|
||||
@@ -1,27 +0,0 @@
|
||||
"""Build the translation agent."""
|
||||
|
||||
import dataclasses
|
||||
import logging
|
||||
|
||||
from django.conf import settings
|
||||
|
||||
from .base import BaseAgent
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
@dataclasses.dataclass(init=False)
|
||||
class TranslationAgent(BaseAgent):
|
||||
"""Create a Pydantic AI translation Agent instance with the configured settings"""
|
||||
|
||||
def __init__(self, **kwargs):
|
||||
"""Initialize the agent with the configured model."""
|
||||
super().__init__(
|
||||
model_hrid=settings.LLM_DEFAULT_MODEL_HRID,
|
||||
output_type=str,
|
||||
**kwargs,
|
||||
)
|
||||
|
||||
def get_tools(self) -> list:
|
||||
"""Translation does not need any tools."""
|
||||
return []
|
||||
File diff suppressed because it is too large
Load Diff
@@ -1,161 +0,0 @@
|
||||
%PDF-1.4
|
||||
%âãÏÓ
|
||||
1 0 obj
|
||||
<<
|
||||
/Producer (pypdf)
|
||||
>>
|
||||
endobj
|
||||
2 0 obj
|
||||
<<
|
||||
/Type /Pages
|
||||
/Count 10
|
||||
/Kids [ 4 0 R 7 0 R 8 0 R 9 0 R 10 0 R 11 0 R 12 0 R 13 0 R 14 0 R 15 0 R ]
|
||||
>>
|
||||
endobj
|
||||
3 0 obj
|
||||
<<
|
||||
/Type /Catalog
|
||||
/Pages 2 0 R
|
||||
>>
|
||||
endobj
|
||||
4 0 obj
|
||||
<<
|
||||
/Type /Page
|
||||
/MediaBox [ 0 0 612 792 ]
|
||||
/Contents 5 0 R
|
||||
/Resources <<
|
||||
/Font <<
|
||||
/F1 6 0 R
|
||||
>>
|
||||
>>
|
||||
/Parent 2 0 R
|
||||
>>
|
||||
endobj
|
||||
5 0 obj
|
||||
<<
|
||||
/Length 132
|
||||
>>
|
||||
stream
|
||||
BT /F1 12 Tf 100 700 Td (AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA) Tj ET
|
||||
endstream
|
||||
endobj
|
||||
6 0 obj
|
||||
<<
|
||||
/Type /Font
|
||||
/Subtype /Type1
|
||||
/BaseFont /Helvetica
|
||||
/Encoding /WinAnsiEncoding
|
||||
>>
|
||||
endobj
|
||||
7 0 obj
|
||||
<<
|
||||
/Type /Page
|
||||
/MediaBox [ 0 0 612 792 ]
|
||||
/Contents 5 0 R
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>>
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startxref
|
||||
6345
|
||||
%%EOF
|
||||
Binary file not shown.
@@ -1,310 +0,0 @@
|
||||
"""Tests for AdaptivePdfParser and AdaptiveParserMixin."""
|
||||
|
||||
from io import BytesIO
|
||||
from pathlib import Path
|
||||
from unittest.mock import MagicMock, patch
|
||||
|
||||
import pytest
|
||||
import requests
|
||||
from pypdf import PdfReader
|
||||
|
||||
from chat.agent_rag.document_converter.parser import (
|
||||
METHOD_OCR,
|
||||
METHOD_TEXT_EXTRACTION,
|
||||
AdaptivePdfParser,
|
||||
analyze_pdf,
|
||||
)
|
||||
|
||||
FIXTURES_DIR = Path(__file__).parent / "fixtures"
|
||||
|
||||
|
||||
@pytest.fixture(name="text_pdf_1_page")
|
||||
def provide_text_pdf_1_page():
|
||||
"""Load a 1 page PDF with extractable text."""
|
||||
return (FIXTURES_DIR / "text_pdf_1_page.pdf").read_bytes()
|
||||
|
||||
|
||||
@pytest.fixture(name="text_pdf_10_pages")
|
||||
def provide_text_pdf_10_pages():
|
||||
"""Load a 10-page PDF with extractable text (~300 chars per page)."""
|
||||
return (FIXTURES_DIR / "text_10_pages.pdf").read_bytes()
|
||||
|
||||
|
||||
@pytest.fixture(name="mixed_pdf_10_pages")
|
||||
def provide_mixed_pdf_10_pages():
|
||||
"""Load a 10-page PDF with 2 pages of text and 8 blank pages."""
|
||||
return (FIXTURES_DIR / "mixed_10_pages.pdf").read_bytes()
|
||||
|
||||
|
||||
MIN_AVG_CHARS_FOR_TEXT_EXTRACTION = 200
|
||||
OCR_RETRY_DELAY = 1
|
||||
OCR_MAX_RETRIES = 3
|
||||
|
||||
|
||||
@pytest.fixture(autouse=True)
|
||||
def ai_settings(settings):
|
||||
"""Mock Django settings for OCR configuration."""
|
||||
settings.MIN_AVG_CHARS_FOR_TEXT_EXTRACTION = MIN_AVG_CHARS_FOR_TEXT_EXTRACTION
|
||||
settings.MIN_TEXT_COVERAGE_FOR_TEXT_EXTRACTION = 0.7
|
||||
settings.OCR_HRID = "test-ocr-hrid"
|
||||
settings.OCR_MODEL = "test-ocr-model"
|
||||
settings.OCR_TIMEOUT = 60
|
||||
settings.OCR_MAX_RETRIES = OCR_MAX_RETRIES
|
||||
settings.OCR_RETRY_DELAY = OCR_RETRY_DELAY
|
||||
settings.OCR_BATCH_PAGES = 10
|
||||
settings.LLM_CONFIGURATIONS = {
|
||||
"test-ocr-hrid": MagicMock(
|
||||
provider=MagicMock(
|
||||
base_url="https://ocr.example.com",
|
||||
api_key="test-api-key",
|
||||
)
|
||||
)
|
||||
}
|
||||
return settings
|
||||
|
||||
|
||||
def test_analyze_pdf_returns_correct_structure(text_pdf_10_pages):
|
||||
"""analyze_pdf should return dict with expected keys."""
|
||||
result = analyze_pdf(text_pdf_10_pages)
|
||||
|
||||
assert "total_pages" in result
|
||||
assert "pages_with_text" in result
|
||||
assert "avg_chars_per_page" in result
|
||||
assert "text_coverage" in result
|
||||
assert "recommended_method" in result
|
||||
|
||||
|
||||
def test_analyze_pdf_with_text_recommends_extraction(text_pdf_1_page):
|
||||
"""PDF with sufficient text should recommend text extraction."""
|
||||
result = analyze_pdf(text_pdf_1_page)
|
||||
|
||||
assert result["total_pages"] == 1
|
||||
assert result["pages_with_text"] == 1
|
||||
assert result["text_coverage"] == pytest.approx(1.0)
|
||||
assert result["avg_chars_per_page"] > MIN_AVG_CHARS_FOR_TEXT_EXTRACTION
|
||||
assert result["recommended_method"] == METHOD_TEXT_EXTRACTION
|
||||
|
||||
|
||||
def test_analyze_multi_page_pdf_with_text_recommends_extraction(text_pdf_10_pages):
|
||||
"""PDF with sufficient text should recommend text extraction."""
|
||||
result = analyze_pdf(text_pdf_10_pages)
|
||||
|
||||
assert result["total_pages"] == 10
|
||||
assert result["pages_with_text"] == 10
|
||||
assert result["text_coverage"] == pytest.approx(1.0)
|
||||
assert result["avg_chars_per_page"] > MIN_AVG_CHARS_FOR_TEXT_EXTRACTION
|
||||
assert result["recommended_method"] == METHOD_TEXT_EXTRACTION
|
||||
|
||||
|
||||
def test_analyze_pdf_mixed_content_recommends_ocr(mixed_pdf_10_pages):
|
||||
"""PDF with low text coverage should recommend OCR."""
|
||||
result = analyze_pdf(mixed_pdf_10_pages)
|
||||
|
||||
assert result["total_pages"] == 10
|
||||
assert result["pages_with_text"] == 2
|
||||
assert result["text_coverage"] == pytest.approx(0.2)
|
||||
assert result["recommended_method"] == METHOD_OCR
|
||||
|
||||
|
||||
def test_extract_page_batch_single_page(text_pdf_10_pages):
|
||||
"""Should extract a single page correctly."""
|
||||
parser = AdaptivePdfParser()
|
||||
reader = PdfReader(BytesIO(text_pdf_10_pages))
|
||||
|
||||
result = parser.extract_page_batch(reader, 0, 1)
|
||||
|
||||
result_reader = PdfReader(BytesIO(result))
|
||||
assert len(result_reader.pages) == 1
|
||||
|
||||
|
||||
def test_extract_page_batch_multiple_pages(text_pdf_10_pages):
|
||||
"""Should extract multiple pages correctly."""
|
||||
parser = AdaptivePdfParser()
|
||||
reader = PdfReader(BytesIO(text_pdf_10_pages))
|
||||
|
||||
result = parser.extract_page_batch(reader, 2, 7)
|
||||
|
||||
result_reader = PdfReader(BytesIO(result))
|
||||
assert len(result_reader.pages) == 5
|
||||
|
||||
|
||||
def test_extract_page_batch_last_batch(text_pdf_10_pages):
|
||||
"""Should handle last batch with fewer pages."""
|
||||
parser = AdaptivePdfParser()
|
||||
reader = PdfReader(BytesIO(text_pdf_10_pages))
|
||||
|
||||
result = parser.extract_page_batch(reader, 7, 10)
|
||||
|
||||
result_reader = PdfReader(BytesIO(result))
|
||||
assert len(result_reader.pages) == 3
|
||||
|
||||
|
||||
def test_ocr_page_batch_success(text_pdf_1_page):
|
||||
"""Should return markdown content on successful OCR."""
|
||||
parser = AdaptivePdfParser()
|
||||
|
||||
with patch("chat.agent_rag.document_converter.parser.requests.post") as mock_post:
|
||||
mock_post.return_value.json.return_value = {
|
||||
"pages": [
|
||||
{"markdown": "# Page 1 content"},
|
||||
]
|
||||
}
|
||||
mock_post.return_value.raise_for_status = MagicMock()
|
||||
|
||||
result = parser.ocr_page_batch("test.pdf", text_pdf_1_page, 0, 1)
|
||||
|
||||
assert result == ["# Page 1 content"]
|
||||
mock_post.assert_called_once()
|
||||
|
||||
|
||||
def test_ocr_page_batch_retry_on_timeout(text_pdf_1_page):
|
||||
"""Should retry on timeout with static delay."""
|
||||
parser = AdaptivePdfParser()
|
||||
|
||||
with patch("chat.agent_rag.document_converter.parser.requests.post") as mock_post:
|
||||
with patch("chat.agent_rag.document_converter.parser.time.sleep") as mock_sleep:
|
||||
mock_post.side_effect = [
|
||||
requests.Timeout("Connection timed out"),
|
||||
MagicMock(
|
||||
json=MagicMock(return_value={"pages": [{"markdown": "# Content"}]}),
|
||||
raise_for_status=MagicMock(),
|
||||
),
|
||||
]
|
||||
|
||||
result = parser.ocr_page_batch("test.pdf", text_pdf_1_page, 0, 1)
|
||||
|
||||
assert result == ["# Content"]
|
||||
assert mock_post.call_count == 2
|
||||
mock_sleep.assert_called_once_with(OCR_RETRY_DELAY)
|
||||
|
||||
|
||||
def test_ocr_page_batch_fails_after_max_retries(text_pdf_1_page):
|
||||
"""Should raise exception after max retries exceeded."""
|
||||
parser = AdaptivePdfParser()
|
||||
|
||||
with patch("chat.agent_rag.document_converter.parser.requests.post") as mock_post:
|
||||
with patch("chat.agent_rag.document_converter.parser.time.sleep"):
|
||||
mock_post.side_effect = requests.Timeout("Connection timed out")
|
||||
|
||||
with pytest.raises(requests.Timeout):
|
||||
parser.ocr_page_batch("test.pdf", text_pdf_1_page, 0, 1)
|
||||
|
||||
assert mock_post.call_count == OCR_MAX_RETRIES
|
||||
|
||||
|
||||
def test_ocr_page_batch_retry_on_request_exception(text_pdf_1_page):
|
||||
"""Should retry on general request exceptions."""
|
||||
parser = AdaptivePdfParser()
|
||||
|
||||
with patch("chat.agent_rag.document_converter.parser.requests.post") as mock_post:
|
||||
with patch("chat.agent_rag.document_converter.parser.time.sleep"):
|
||||
mock_post.side_effect = [
|
||||
requests.RequestException("Network error"),
|
||||
requests.RequestException("Network error"),
|
||||
MagicMock(
|
||||
json=MagicMock(return_value={"pages": [{"markdown": "# Content"}]}),
|
||||
raise_for_status=MagicMock(),
|
||||
),
|
||||
]
|
||||
|
||||
result = parser.ocr_page_batch("test.pdf", text_pdf_1_page, 0, 1)
|
||||
|
||||
assert result == ["# Content"]
|
||||
assert mock_post.call_count == 3
|
||||
|
||||
|
||||
def test_parse_pdf_with_ocr_single_batch(text_pdf_10_pages):
|
||||
"""Should process PDF in single batch when pages <= batch size."""
|
||||
parser = AdaptivePdfParser()
|
||||
|
||||
with patch("chat.agent_rag.document_converter.parser.requests.post") as mock_post:
|
||||
mock_post.return_value.json.return_value = {
|
||||
"pages": [{"markdown": f"Page {i}"} for i in range(1, 11)]
|
||||
}
|
||||
mock_post.return_value.raise_for_status = MagicMock()
|
||||
|
||||
result = parser.parse_pdf_document_with_ocr("test.pdf", text_pdf_10_pages)
|
||||
|
||||
assert "Page 1" in result
|
||||
assert "Page 10" in result
|
||||
mock_post.assert_called_once()
|
||||
|
||||
|
||||
def test_parse_pdf_with_ocr_multiple_batches(text_pdf_10_pages, settings):
|
||||
"""Should process PDF in multiple batches when pages > batch size."""
|
||||
settings.OCR_BATCH_PAGES = 4 # Force multiple batches
|
||||
parser = AdaptivePdfParser()
|
||||
|
||||
with patch("chat.agent_rag.document_converter.parser.requests.post") as mock_post:
|
||||
mock_post.return_value.json.side_effect = [
|
||||
{"pages": [{"markdown": f"Page {i}"} for i in range(1, 5)]},
|
||||
{"pages": [{"markdown": f"Page {i}"} for i in range(5, 9)]},
|
||||
{"pages": [{"markdown": f"Page {i}"} for i in range(9, 11)]},
|
||||
]
|
||||
mock_post.return_value.raise_for_status = MagicMock()
|
||||
|
||||
result = parser.parse_pdf_document_with_ocr("test.pdf", text_pdf_10_pages)
|
||||
|
||||
assert mock_post.call_count == 3
|
||||
assert "Page 1" in result
|
||||
assert "Page 10" in result
|
||||
|
||||
|
||||
def test_parse_pdf_with_ocr_partial_failure(text_pdf_10_pages, settings):
|
||||
"""Should insert empty placeholders for failed batches."""
|
||||
settings.OCR_BATCH_PAGES = 4 # Force multiple batches
|
||||
parser = AdaptivePdfParser()
|
||||
|
||||
success_response = MagicMock()
|
||||
success_response.json.return_value = {"pages": [{"markdown": f"Page {i}"} for i in range(1, 5)]}
|
||||
success_response.raise_for_status = MagicMock()
|
||||
|
||||
with patch("chat.agent_rag.document_converter.parser.requests.post") as mock_post:
|
||||
with patch("chat.agent_rag.document_converter.parser.time.sleep"):
|
||||
# First batch succeeds, then all retries fail for remaining batches
|
||||
mock_post.side_effect = [
|
||||
success_response,
|
||||
requests.Timeout("OCR failed"),
|
||||
requests.Timeout("OCR failed"),
|
||||
requests.Timeout("OCR failed"),
|
||||
requests.Timeout("OCR failed"),
|
||||
requests.Timeout("OCR failed"),
|
||||
requests.Timeout("OCR failed"),
|
||||
]
|
||||
|
||||
result = parser.parse_pdf_document_with_ocr("test.pdf", text_pdf_10_pages)
|
||||
|
||||
parts = result.split("\n\n")
|
||||
# First batch succeeded (4 pages), remaining batches failed (6 pages as placeholders)
|
||||
assert len(parts) == 10
|
||||
assert parts[0] == "Page 1"
|
||||
assert parts[3] == "Page 4"
|
||||
assert parts[4] == "" # Failed batch placeholder
|
||||
|
||||
|
||||
def test_parse_document_pdf_routed_correctly(text_pdf_1_page):
|
||||
"""Should route PDF content type to PDF parser."""
|
||||
parser = AdaptivePdfParser()
|
||||
|
||||
with patch.object(parser, "parse_pdf_document", return_value="pdf content") as mock_parse:
|
||||
result = parser.parse_document("test.pdf", "application/pdf", text_pdf_1_page)
|
||||
|
||||
assert result == "pdf content"
|
||||
mock_parse.assert_called_once_with(
|
||||
name="test.pdf",
|
||||
content_type="application/pdf",
|
||||
content=text_pdf_1_page,
|
||||
)
|
||||
|
||||
|
||||
def test_parse_document_non_pdf_uses_document_converter():
|
||||
"""Should route non-PDF content to DocumentConverter."""
|
||||
parser = AdaptivePdfParser()
|
||||
|
||||
with patch("chat.agent_rag.document_converter.parser.DocumentConverter") as mock_converter:
|
||||
mock_converter.return_value.convert_raw.return_value = "docx content"
|
||||
|
||||
result = parser.parse_document("test.docx", "application/vnd.openxmlformats", b"content")
|
||||
|
||||
assert result == "docx content"
|
||||
mock_converter.return_value.convert_raw.assert_called_once()
|
||||
@@ -15,13 +15,12 @@ import core.urls
|
||||
import chat.views
|
||||
import conversations.urls
|
||||
from chat.agents.summarize import SummarizationAgent
|
||||
from chat.agents.translate import TranslationAgent
|
||||
from chat.clients.pydantic_ai import AIAgentService
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
@pytest.fixture(name="today_prompt_date")
|
||||
@pytest.fixture(name="today_promt_date")
|
||||
def today_prompt_date_fixture():
|
||||
"""Fixture to mock date the system prompt when useless to test it."""
|
||||
_formatted_date = formats.date_format(timezone.now(), "l d/m/Y", use_l10n=False)
|
||||
@@ -92,34 +91,6 @@ def mock_summarization_agent_fixture():
|
||||
yield _mock_agent
|
||||
|
||||
|
||||
@pytest.fixture(name="mock_translation_agent")
|
||||
def mock_translation_agent_fixture():
|
||||
"""Fixture to mock TranslationAgent with a custom model."""
|
||||
|
||||
@contextmanager
|
||||
def _mock_agent(model):
|
||||
"""Context manager to mock TranslationAgent with a custom model."""
|
||||
with ExitStack() as stack:
|
||||
|
||||
class TranslationAgentMock(TranslationAgent):
|
||||
"""Mocked TranslationAgent to override the model."""
|
||||
|
||||
def __init__(self, **kwargs):
|
||||
super().__init__(**kwargs)
|
||||
logger.info("Overriding TranslationAgent model with %s", model)
|
||||
self._model = model # pylint: disable=protected-access
|
||||
|
||||
stack.enter_context(
|
||||
patch("chat.agents.translate.TranslationAgent", new=TranslationAgentMock)
|
||||
)
|
||||
stack.enter_context(
|
||||
patch("chat.tools.document_translate.TranslationAgent", new=TranslationAgentMock)
|
||||
)
|
||||
yield
|
||||
|
||||
yield _mock_agent
|
||||
|
||||
|
||||
PIXEL_PNG = (
|
||||
b"\x89PNG\r\n\x1a\n\x00\x00\x00\rIHDR\x00\x00\x00\x01\x00\x00\x00\x01\x08\x06\x00"
|
||||
b"\x00\x00\x1f\x15\xc4\x89\x00\x00\x00\nIDATx\x9cc\xf8\xff\xff?\x00\x05\xfe\x02\xfe"
|
||||
|
||||
@@ -1,318 +0,0 @@
|
||||
"""Tests for document_translate functionality."""
|
||||
|
||||
import io
|
||||
from unittest import mock
|
||||
|
||||
from django.core.files.storage import default_storage
|
||||
|
||||
import pytest
|
||||
from pydantic_ai import ModelResponse, RunContext, TextPart
|
||||
from pydantic_ai.exceptions import ModelRetry
|
||||
from pydantic_ai.models.function import FunctionModel
|
||||
from pydantic_ai.usage import RunUsage
|
||||
|
||||
from chat.llm_configuration import LLModel, LLMProvider
|
||||
from chat.tools.document_translate import document_translate
|
||||
|
||||
|
||||
@pytest.fixture(autouse=True)
|
||||
def fixture_translation_agent_config(settings):
|
||||
"""Fixture to set used settings for agent configuration."""
|
||||
settings.TRANSLATION_MAX_CHARS = 100_000
|
||||
settings.LLM_CONFIGURATIONS = {
|
||||
settings.LLM_DEFAULT_MODEL_HRID: LLModel(
|
||||
hrid="mistral-model",
|
||||
model_name="mistral-medium-2508",
|
||||
human_readable_name="Mistral Medium 2508",
|
||||
profile=None,
|
||||
provider=LLMProvider(
|
||||
hrid="mistral-medium-2508",
|
||||
kind="mistral",
|
||||
base_url="https://api.mistral.ai/v1",
|
||||
api_key="testkey",
|
||||
),
|
||||
is_active=True,
|
||||
system_prompt="direct",
|
||||
tools=[],
|
||||
),
|
||||
}
|
||||
|
||||
|
||||
@pytest.fixture(name="mocked_context")
|
||||
def fixture_mocked_context():
|
||||
"""Fixture for a mocked RunContext."""
|
||||
mock_ctx = mock.Mock(spec=RunContext)
|
||||
mock_ctx.usage = RunUsage(input_tokens=0, output_tokens=0)
|
||||
mock_ctx.max_retries = 2
|
||||
mock_ctx.retries = {}
|
||||
return mock_ctx
|
||||
|
||||
|
||||
def _mock_attachments_queryset(attachment):
|
||||
"""Create a mock queryset that chains .filter().order_by().afirst() returning the attachment."""
|
||||
mock_qs = mock.Mock()
|
||||
mock_qs.order_by.return_value = mock_qs
|
||||
mock_qs.afirst = mock.AsyncMock(return_value=attachment)
|
||||
|
||||
mock_attachments = mock.Mock()
|
||||
mock_attachments.filter.return_value = mock_qs
|
||||
return mock_attachments
|
||||
|
||||
|
||||
def mocked_translation(_messages, _info=None):
|
||||
"""Mocked translation response."""
|
||||
return ModelResponse(parts=[TextPart(content="Ceci est une traduction du document.")])
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_document_translate_single_document(mocked_context, mock_translation_agent):
|
||||
"""Test document_translate with a single document."""
|
||||
mock_attachment = mock.Mock()
|
||||
mock_attachment.key = "test_doc.txt"
|
||||
mock_attachment.file_name = "test_doc.txt"
|
||||
mock_attachment.content_type = "text/plain"
|
||||
mock_attachment.size = None
|
||||
|
||||
mock_conversation = mock.Mock()
|
||||
mock_conversation.attachments = _mock_attachments_queryset(mock_attachment)
|
||||
|
||||
file_content = "This is a test document. " * 20
|
||||
|
||||
with mock.patch.object(
|
||||
default_storage, "open", return_value=io.BytesIO(file_content.encode("utf-8"))
|
||||
):
|
||||
mocked_context.deps = mock.Mock()
|
||||
mocked_context.deps.conversation = mock_conversation
|
||||
|
||||
def mocked_translate_full(_message, _info=None):
|
||||
"""Mocked translation for full flow."""
|
||||
return ModelResponse(parts=[TextPart(content="Ceci est un document de test.")])
|
||||
|
||||
with mock_translation_agent(FunctionModel(mocked_translate_full)):
|
||||
result = await document_translate(
|
||||
mocked_context, target_language="French", instructions=None
|
||||
)
|
||||
|
||||
assert "Ceci est un document de test." in result.return_value
|
||||
assert result.metadata["sources"] == {"test_doc.txt"}
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_document_translate_uses_last_document(mocked_context, mock_translation_agent):
|
||||
"""Test document_translate uses the last uploaded document."""
|
||||
mock_attachment = mock.Mock()
|
||||
mock_attachment.key = "latest_doc.txt"
|
||||
mock_attachment.file_name = "latest_doc.txt"
|
||||
mock_attachment.content_type = "text/plain"
|
||||
mock_attachment.size = None
|
||||
|
||||
mock_conversation = mock.Mock()
|
||||
mock_conversation.attachments = _mock_attachments_queryset(mock_attachment)
|
||||
|
||||
file_content = "Content of the latest document."
|
||||
|
||||
with mock.patch.object(
|
||||
default_storage, "open", return_value=io.BytesIO(file_content.encode("utf-8"))
|
||||
):
|
||||
mocked_context.deps = mock.Mock()
|
||||
mocked_context.deps.conversation = mock_conversation
|
||||
|
||||
with mock_translation_agent(FunctionModel(mocked_translation)):
|
||||
result = await document_translate(
|
||||
mocked_context, target_language="French", instructions=None
|
||||
)
|
||||
|
||||
assert result.metadata["sources"] == {"latest_doc.txt"}
|
||||
# Verify order_by was called with -created_at
|
||||
mock_conversation.attachments.filter.return_value.order_by.assert_called_once_with(
|
||||
"-created_at"
|
||||
)
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_document_translate_with_custom_instructions(mocked_context, mock_translation_agent):
|
||||
"""Test document_translate with custom instructions."""
|
||||
mock_attachment = mock.Mock()
|
||||
mock_attachment.key = "test.txt"
|
||||
mock_attachment.file_name = "test.txt"
|
||||
mock_attachment.content_type = "text/plain"
|
||||
mock_attachment.size = None
|
||||
|
||||
mock_conversation = mock.Mock()
|
||||
mock_conversation.attachments = _mock_attachments_queryset(mock_attachment)
|
||||
|
||||
file_content = "Test content " * 20
|
||||
|
||||
with mock.patch.object(
|
||||
default_storage, "open", return_value=io.BytesIO(file_content.encode("utf-8"))
|
||||
):
|
||||
mocked_context.deps = mock.Mock()
|
||||
mocked_context.deps.conversation = mock_conversation
|
||||
|
||||
captured_prompts = []
|
||||
|
||||
def mocked_translate_with_instructions(messages, _info=None):
|
||||
"""Mocked translation that captures prompt."""
|
||||
messages_text = messages[0].parts[-1].content
|
||||
captured_prompts.append(messages_text)
|
||||
return ModelResponse(parts=[TextPart(content="Traduction formelle")])
|
||||
|
||||
with mock_translation_agent(FunctionModel(mocked_translate_with_instructions)):
|
||||
result = await document_translate(
|
||||
mocked_context, target_language="French", instructions="Use formal tone"
|
||||
)
|
||||
|
||||
assert result.return_value is not None
|
||||
assert len(captured_prompts) == 1
|
||||
assert "Use formal tone" in captured_prompts[0]
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
@pytest.mark.parametrize("target_language", [None, ""])
|
||||
async def test_document_translate_no_target_language(
|
||||
target_language, mocked_context, mock_translation_agent
|
||||
):
|
||||
"""Test document_translate asks the user for language when target_language is not specified."""
|
||||
mocked_context.deps = mock.Mock()
|
||||
|
||||
with mock_translation_agent(FunctionModel(mocked_translation)):
|
||||
result = await document_translate(
|
||||
mocked_context, target_language=target_language, instructions=None
|
||||
)
|
||||
|
||||
assert "target language is not specified" in result
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_document_translate_no_text_attachments(mocked_context, mock_translation_agent):
|
||||
"""Test document_translate returns error message when no text documents found."""
|
||||
mock_conversation = mock.Mock()
|
||||
mock_conversation.attachments = _mock_attachments_queryset(None)
|
||||
|
||||
mocked_context.deps = mock.Mock()
|
||||
mocked_context.deps.conversation = mock_conversation
|
||||
|
||||
with mock_translation_agent(FunctionModel(mocked_translation)):
|
||||
result = await document_translate(
|
||||
mocked_context, target_language="French", instructions=None
|
||||
)
|
||||
|
||||
assert "No text documents found in the conversation" in result
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_document_translate_error_reading_document(mocked_context, mock_translation_agent):
|
||||
"""Test document_translate handles errors when reading documents."""
|
||||
mock_attachment = mock.Mock()
|
||||
mock_attachment.key = "test.txt"
|
||||
mock_attachment.file_name = "test.txt"
|
||||
mock_attachment.content_type = "text/plain"
|
||||
mock_attachment.size = None
|
||||
|
||||
mock_conversation = mock.Mock()
|
||||
mock_conversation.attachments = _mock_attachments_queryset(mock_attachment)
|
||||
|
||||
with mock.patch.object(default_storage, "open", side_effect=IOError("File read error")):
|
||||
mocked_context.deps = mock.Mock()
|
||||
mocked_context.deps.conversation = mock_conversation
|
||||
|
||||
with mock_translation_agent(FunctionModel(mocked_translation)):
|
||||
result = await document_translate(
|
||||
mocked_context, target_language="French", instructions=None
|
||||
)
|
||||
|
||||
assert "An unexpected error occurred during document translation" in result
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_document_translate_error_during_translation(mocked_context, mock_translation_agent):
|
||||
"""Test document_translate handles ModelRetry during translation."""
|
||||
mock_attachment = mock.Mock()
|
||||
mock_attachment.key = "test.txt"
|
||||
mock_attachment.file_name = "test.txt"
|
||||
mock_attachment.content_type = "text/plain"
|
||||
mock_attachment.size = None
|
||||
|
||||
mock_conversation = mock.Mock()
|
||||
mock_conversation.attachments = _mock_attachments_queryset(mock_attachment)
|
||||
|
||||
file_content = "Test content " * 20
|
||||
|
||||
with mock.patch.object(
|
||||
default_storage, "open", return_value=io.BytesIO(file_content.encode("utf-8"))
|
||||
):
|
||||
mocked_context.deps = mock.Mock()
|
||||
mocked_context.deps.conversation = mock_conversation
|
||||
|
||||
def mocked_translate_error(_messages, _info=None):
|
||||
"""Mocked translation that raises an error."""
|
||||
raise ValueError("Translation error")
|
||||
|
||||
with mock_translation_agent(FunctionModel(mocked_translate_error)):
|
||||
with pytest.raises(ModelRetry):
|
||||
await document_translate(
|
||||
mocked_context, target_language="French", instructions=None
|
||||
)
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_document_translate_too_large(settings, mocked_context, mock_translation_agent):
|
||||
"""Test document_translate rejects documents exceeding max chars."""
|
||||
settings.TRANSLATION_MAX_CHARS = 100 # Very small limit
|
||||
|
||||
mock_attachment = mock.Mock()
|
||||
mock_attachment.key = "large_doc.txt"
|
||||
mock_attachment.file_name = "large_doc.txt"
|
||||
mock_attachment.content_type = "text/plain"
|
||||
mock_attachment.size = None
|
||||
|
||||
mock_conversation = mock.Mock()
|
||||
mock_conversation.attachments = _mock_attachments_queryset(mock_attachment)
|
||||
|
||||
file_content = "This is a word. " * 100 # Much larger than 100 chars
|
||||
|
||||
with mock.patch.object(
|
||||
default_storage, "open", return_value=io.BytesIO(file_content.encode("utf-8"))
|
||||
):
|
||||
mocked_context.deps = mock.Mock()
|
||||
mocked_context.deps.conversation = mock_conversation
|
||||
|
||||
with mock_translation_agent(FunctionModel(mocked_translation)):
|
||||
result = await document_translate(
|
||||
mocked_context, target_language="French", instructions=None
|
||||
)
|
||||
|
||||
assert "too large to translate" in result
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_document_translate_empty_result(mocked_context, mock_translation_agent):
|
||||
"""Test document_translate raises ModelRetry when translation produces empty result."""
|
||||
mock_attachment = mock.Mock()
|
||||
mock_attachment.key = "test.txt"
|
||||
mock_attachment.file_name = "test.txt"
|
||||
mock_attachment.content_type = "text/plain"
|
||||
mock_attachment.size = None
|
||||
|
||||
mock_conversation = mock.Mock()
|
||||
mock_conversation.attachments = _mock_attachments_queryset(mock_attachment)
|
||||
|
||||
file_content = "Test content " * 20
|
||||
|
||||
with mock.patch.object(
|
||||
default_storage, "open", return_value=io.BytesIO(file_content.encode("utf-8"))
|
||||
):
|
||||
mocked_context.deps = mock.Mock()
|
||||
mocked_context.deps.conversation = mock_conversation
|
||||
|
||||
def mocked_empty_translation(_messages, _info=None):
|
||||
"""Mocked translation that returns empty."""
|
||||
return ModelResponse(parts=[TextPart(content=" ")])
|
||||
|
||||
with mock_translation_agent(FunctionModel(mocked_empty_translation)):
|
||||
with pytest.raises(ModelRetry) as exc_info:
|
||||
await document_translate(
|
||||
mocked_context, target_language="French", instructions=None
|
||||
)
|
||||
|
||||
assert "produced an empty result" in str(exc_info.value)
|
||||
@@ -190,7 +190,6 @@ def test_post_conversation_data_protocol(api_client, mock_openai_stream):
|
||||
"Today is Friday 25/07/2025.\n\nAnswer in english."
|
||||
),
|
||||
"kind": "request",
|
||||
"metadata": None,
|
||||
"parts": [
|
||||
{
|
||||
"content": ["Hello"],
|
||||
@@ -199,29 +198,15 @@ def test_post_conversation_data_protocol(api_client, mock_openai_stream):
|
||||
},
|
||||
],
|
||||
"run_id": _run_id,
|
||||
"timestamp": "2025-07-25T10:36:35.297675Z",
|
||||
},
|
||||
{
|
||||
"finish_reason": "stop",
|
||||
"kind": "response",
|
||||
"metadata": None,
|
||||
"model_name": "test-model",
|
||||
"parts": [
|
||||
{
|
||||
"content": "Hello there",
|
||||
"id": None,
|
||||
"part_kind": "text",
|
||||
"provider_details": None,
|
||||
"provider_name": None,
|
||||
}
|
||||
],
|
||||
"provider_details": {
|
||||
"finish_reason": "stop",
|
||||
"timestamp": "2025-07-25T10:36:35.297675Z",
|
||||
},
|
||||
"parts": [{"content": "Hello there", "id": None, "part_kind": "text"}],
|
||||
"provider_details": {"finish_reason": "stop"},
|
||||
"provider_name": "openai",
|
||||
"provider_response_id": "chatcmpl-1234567890",
|
||||
"provider_url": "https://www.external-ai-service.com/",
|
||||
"timestamp": "2025-07-25T10:36:35.297675Z",
|
||||
"usage": {
|
||||
"cache_audio_read_tokens": 0,
|
||||
@@ -332,7 +317,6 @@ def test_post_conversation_data_protocol_triggers_keepalives(
|
||||
"Answer in english."
|
||||
),
|
||||
"kind": "request",
|
||||
"metadata": None,
|
||||
"parts": [
|
||||
{
|
||||
"content": ["Hello"],
|
||||
@@ -341,29 +325,15 @@ def test_post_conversation_data_protocol_triggers_keepalives(
|
||||
},
|
||||
],
|
||||
"run_id": _run_id,
|
||||
"timestamp": "2025-07-25T10:36:35.297675Z",
|
||||
},
|
||||
{
|
||||
"finish_reason": "stop",
|
||||
"kind": "response",
|
||||
"metadata": None,
|
||||
"model_name": "test-model",
|
||||
"parts": [
|
||||
{
|
||||
"content": "Hello there",
|
||||
"id": None,
|
||||
"part_kind": "text",
|
||||
"provider_details": None,
|
||||
"provider_name": None,
|
||||
}
|
||||
],
|
||||
"provider_details": {
|
||||
"finish_reason": "stop",
|
||||
"timestamp": "2025-07-25T10:36:35.297675Z",
|
||||
},
|
||||
"parts": [{"content": "Hello there", "id": None, "part_kind": "text"}],
|
||||
"provider_details": {"finish_reason": "stop"},
|
||||
"provider_name": "openai",
|
||||
"provider_response_id": "chatcmpl-1234567890",
|
||||
"provider_url": "https://www.external-ai-service.com/",
|
||||
"timestamp": "2025-07-25T10:36:35.297675Z",
|
||||
"usage": {
|
||||
"cache_audio_read_tokens": 0,
|
||||
@@ -468,7 +438,6 @@ def test_post_conversation_text_protocol(api_client, mock_openai_stream):
|
||||
"Today is Friday 25/07/2025.\n\nAnswer in english."
|
||||
),
|
||||
"kind": "request",
|
||||
"metadata": None,
|
||||
"parts": [
|
||||
{
|
||||
"content": ["Hello"],
|
||||
@@ -477,29 +446,15 @@ def test_post_conversation_text_protocol(api_client, mock_openai_stream):
|
||||
},
|
||||
],
|
||||
"run_id": _run_id,
|
||||
"timestamp": "2025-07-25T10:36:35.297675Z",
|
||||
},
|
||||
{
|
||||
"finish_reason": "stop",
|
||||
"kind": "response",
|
||||
"metadata": None,
|
||||
"model_name": "test-model",
|
||||
"parts": [
|
||||
{
|
||||
"content": "Hello there",
|
||||
"id": None,
|
||||
"part_kind": "text",
|
||||
"provider_details": None,
|
||||
"provider_name": None,
|
||||
}
|
||||
],
|
||||
"provider_details": {
|
||||
"finish_reason": "stop",
|
||||
"timestamp": "2025-07-25T10:36:35.297675Z",
|
||||
},
|
||||
"parts": [{"content": "Hello there", "id": None, "part_kind": "text"}],
|
||||
"provider_details": {"finish_reason": "stop"},
|
||||
"provider_name": "openai",
|
||||
"provider_response_id": "chatcmpl-1234567890",
|
||||
"provider_url": "https://www.external-ai-service.com/",
|
||||
"timestamp": "2025-07-25T10:36:35.297675Z",
|
||||
"usage": {
|
||||
"cache_audio_read_tokens": 0,
|
||||
@@ -669,7 +624,6 @@ def test_post_conversation_with_image(api_client, mock_openai_stream_image):
|
||||
"Today is Friday 25/07/2025.\n\nAnswer in english."
|
||||
),
|
||||
"kind": "request",
|
||||
"metadata": None,
|
||||
"parts": [
|
||||
{
|
||||
"content": [
|
||||
@@ -690,29 +644,15 @@ def test_post_conversation_with_image(api_client, mock_openai_stream_image):
|
||||
},
|
||||
],
|
||||
"run_id": _run_id,
|
||||
"timestamp": "2025-07-25T10:36:35.297675Z",
|
||||
},
|
||||
{
|
||||
"finish_reason": "stop",
|
||||
"kind": "response",
|
||||
"metadata": None,
|
||||
"model_name": "test-model",
|
||||
"parts": [
|
||||
{
|
||||
"content": "I see a cat in the picture.",
|
||||
"id": None,
|
||||
"part_kind": "text",
|
||||
"provider_details": None,
|
||||
"provider_name": None,
|
||||
}
|
||||
],
|
||||
"provider_details": {
|
||||
"finish_reason": "stop",
|
||||
"timestamp": "2025-07-25T10:36:35.297675Z",
|
||||
},
|
||||
"parts": [{"content": "I see a cat in the picture.", "id": None, "part_kind": "text"}],
|
||||
"provider_details": {"finish_reason": "stop"},
|
||||
"provider_name": "openai",
|
||||
"provider_response_id": "chatcmpl-1234567890",
|
||||
"provider_url": "https://www.external-ai-service.com/",
|
||||
"timestamp": "2025-07-25T10:36:35.297675Z",
|
||||
"usage": {
|
||||
"cache_audio_read_tokens": 0,
|
||||
@@ -850,7 +790,6 @@ def test_post_conversation_tool_call(api_client, mock_openai_stream_tool, settin
|
||||
"Today is Friday 25/07/2025.\n\nAnswer in english."
|
||||
),
|
||||
"kind": "request",
|
||||
"metadata": None,
|
||||
"parts": [
|
||||
{
|
||||
"content": ["Weather in Paris?"],
|
||||
@@ -859,31 +798,23 @@ def test_post_conversation_tool_call(api_client, mock_openai_stream_tool, settin
|
||||
},
|
||||
],
|
||||
"run_id": _run_id,
|
||||
"timestamp": "2025-07-25T10:36:35.297675Z",
|
||||
},
|
||||
{
|
||||
"finish_reason": "tool_call",
|
||||
"kind": "response",
|
||||
"metadata": None,
|
||||
"model_name": "test-model",
|
||||
"parts": [
|
||||
{
|
||||
"args": '{"location":"Paris", "unit":"celsius"}',
|
||||
"id": None,
|
||||
"part_kind": "tool-call",
|
||||
"provider_details": None,
|
||||
"provider_name": None,
|
||||
"tool_call_id": "xLDcIljdsDrz0idal7tATWSMm2jhMj47",
|
||||
"tool_name": "get_current_weather",
|
||||
}
|
||||
],
|
||||
"provider_details": {
|
||||
"finish_reason": "tool_calls",
|
||||
"timestamp": "2025-07-25T10:36:35.297675Z",
|
||||
},
|
||||
"provider_details": {"finish_reason": "tool_calls"},
|
||||
"provider_name": "openai",
|
||||
"provider_response_id": "chatcmpl-tool-call",
|
||||
"provider_url": "https://www.external-ai-service.com/",
|
||||
"timestamp": "2025-07-25T10:36:35.297675Z",
|
||||
"usage": {
|
||||
"cache_audio_read_tokens": 0,
|
||||
@@ -903,7 +834,6 @@ def test_post_conversation_tool_call(api_client, mock_openai_stream_tool, settin
|
||||
"Today is Friday 25/07/2025.\n\nAnswer in english."
|
||||
),
|
||||
"kind": "request",
|
||||
"metadata": None,
|
||||
"parts": [
|
||||
{
|
||||
"content": {"location": "Paris", "temperature": 22, "unit": "celsius"},
|
||||
@@ -915,29 +845,17 @@ def test_post_conversation_tool_call(api_client, mock_openai_stream_tool, settin
|
||||
}
|
||||
],
|
||||
"run_id": _run_id,
|
||||
"timestamp": "2025-07-25T10:36:35.297675Z",
|
||||
},
|
||||
{
|
||||
"finish_reason": "stop",
|
||||
"kind": "response",
|
||||
"metadata": None,
|
||||
"model_name": "test-model",
|
||||
"parts": [
|
||||
{
|
||||
"content": "The current weather in Paris is nice",
|
||||
"id": None,
|
||||
"part_kind": "text",
|
||||
"provider_details": None,
|
||||
"provider_name": None,
|
||||
}
|
||||
{"content": "The current weather in Paris is nice", "id": None, "part_kind": "text"}
|
||||
],
|
||||
"provider_details": {
|
||||
"finish_reason": "stop",
|
||||
"timestamp": "2025-07-25T10:36:35.297675Z",
|
||||
},
|
||||
"provider_details": {"finish_reason": "stop"},
|
||||
"provider_name": "openai",
|
||||
"provider_response_id": "chatcmpl-final",
|
||||
"provider_url": "https://www.external-ai-service.com/",
|
||||
"timestamp": "2025-07-25T10:36:35.297675Z",
|
||||
"usage": {
|
||||
"cache_audio_read_tokens": 0,
|
||||
@@ -1074,7 +992,6 @@ def test_post_conversation_tool_call_fails(api_client, mock_openai_stream_tool,
|
||||
"Today is Friday 25/07/2025.\n\nAnswer in french."
|
||||
),
|
||||
"kind": "request",
|
||||
"metadata": None,
|
||||
"parts": [
|
||||
{
|
||||
"content": ["Weather in Paris?"],
|
||||
@@ -1083,31 +1000,23 @@ def test_post_conversation_tool_call_fails(api_client, mock_openai_stream_tool,
|
||||
},
|
||||
],
|
||||
"run_id": _run_id,
|
||||
"timestamp": "2025-07-25T10:36:35.297675Z",
|
||||
},
|
||||
{
|
||||
"finish_reason": "tool_call",
|
||||
"kind": "response",
|
||||
"metadata": None,
|
||||
"model_name": "test-model",
|
||||
"parts": [
|
||||
{
|
||||
"args": '{"location":"Paris", "unit":"celsius"}',
|
||||
"id": None,
|
||||
"part_kind": "tool-call",
|
||||
"provider_details": None,
|
||||
"provider_name": None,
|
||||
"tool_call_id": "xLDcIljdsDrz0idal7tATWSMm2jhMj47",
|
||||
"tool_name": "get_current_weather",
|
||||
}
|
||||
],
|
||||
"provider_details": {
|
||||
"finish_reason": "tool_calls",
|
||||
"timestamp": "2025-07-25T10:36:35.297675Z",
|
||||
},
|
||||
"provider_details": {"finish_reason": "tool_calls"},
|
||||
"provider_name": "openai",
|
||||
"provider_response_id": "chatcmpl-tool-call",
|
||||
"provider_url": "https://www.external-ai-service.com/",
|
||||
"timestamp": "2025-07-25T10:36:35.297675Z",
|
||||
"usage": {
|
||||
"cache_audio_read_tokens": 0,
|
||||
@@ -1127,7 +1036,6 @@ def test_post_conversation_tool_call_fails(api_client, mock_openai_stream_tool,
|
||||
"Today is Friday 25/07/2025.\n\nAnswer in french."
|
||||
),
|
||||
"kind": "request",
|
||||
"metadata": None,
|
||||
"parts": [
|
||||
{
|
||||
"content": "Unknown tool name: 'get_current_weather'. No tools available.",
|
||||
@@ -1138,29 +1046,17 @@ def test_post_conversation_tool_call_fails(api_client, mock_openai_stream_tool,
|
||||
}
|
||||
],
|
||||
"run_id": _run_id,
|
||||
"timestamp": "2025-07-25T10:36:35.297675Z",
|
||||
},
|
||||
{
|
||||
"finish_reason": "stop",
|
||||
"kind": "response",
|
||||
"metadata": None,
|
||||
"model_name": "test-model",
|
||||
"parts": [
|
||||
{
|
||||
"content": "I cannot give you an answer to that.",
|
||||
"id": None,
|
||||
"part_kind": "text",
|
||||
"provider_details": None,
|
||||
"provider_name": None,
|
||||
}
|
||||
{"content": "I cannot give you an answer to that.", "id": None, "part_kind": "text"}
|
||||
],
|
||||
"provider_details": {
|
||||
"finish_reason": "stop",
|
||||
"timestamp": "2025-07-25T10:36:35.297675Z",
|
||||
},
|
||||
"provider_details": {"finish_reason": "stop"},
|
||||
"provider_name": "openai",
|
||||
"provider_response_id": "chatcmpl-final",
|
||||
"provider_url": "https://www.external-ai-service.com/",
|
||||
"timestamp": "2025-07-25T10:36:35.297675Z",
|
||||
"usage": {
|
||||
"cache_audio_read_tokens": 0,
|
||||
@@ -1406,7 +1302,6 @@ def test_post_conversation_data_protocol_no_stream(
|
||||
"You are an amazing assistant.\n\nToday is Friday 25/07/2025.\n\nAnswer in english."
|
||||
),
|
||||
"kind": "request",
|
||||
"metadata": None,
|
||||
"parts": [
|
||||
{
|
||||
"content": ["Why the sky is blue?"],
|
||||
@@ -1415,12 +1310,10 @@ def test_post_conversation_data_protocol_no_stream(
|
||||
},
|
||||
],
|
||||
"run_id": _run_id,
|
||||
"timestamp": "2025-07-25T10:36:35.297675Z",
|
||||
},
|
||||
{
|
||||
"finish_reason": "stop",
|
||||
"kind": "response",
|
||||
"metadata": None,
|
||||
"model_name": "mistralai/Mistral-Small-3.2-24B-Instruct-2506",
|
||||
"parts": [
|
||||
{
|
||||
@@ -1428,18 +1321,12 @@ def test_post_conversation_data_protocol_no_stream(
|
||||
"Rayleigh scattering.",
|
||||
"id": None,
|
||||
"part_kind": "text",
|
||||
"provider_details": None,
|
||||
"provider_name": None,
|
||||
}
|
||||
],
|
||||
"provider_details": {
|
||||
"finish_reason": "stop",
|
||||
"timestamp": "2025-09-22T14:13:49Z",
|
||||
},
|
||||
"provider_details": {"finish_reason": "stop"},
|
||||
"provider_name": "openai",
|
||||
"provider_response_id": "chatcmpl-92c413bb5a45426299335d0621324654",
|
||||
"provider_url": "https://www.external-ai-service.com",
|
||||
"timestamp": "2025-07-25T10:36:35.297675Z",
|
||||
"timestamp": "2025-09-22T14:13:49Z",
|
||||
"usage": {
|
||||
"cache_audio_read_tokens": 0,
|
||||
"cache_read_tokens": 0,
|
||||
@@ -1555,7 +1442,6 @@ async def test_post_conversation_async(api_client, mock_openai_stream, monkeypat
|
||||
"Today is Friday 25/07/2025.\n\nAnswer in english."
|
||||
),
|
||||
"kind": "request",
|
||||
"metadata": None,
|
||||
"parts": [
|
||||
{
|
||||
"content": ["Hello"],
|
||||
@@ -1564,29 +1450,15 @@ async def test_post_conversation_async(api_client, mock_openai_stream, monkeypat
|
||||
},
|
||||
],
|
||||
"run_id": _run_id,
|
||||
"timestamp": "2025-07-25T10:36:35.297675Z",
|
||||
},
|
||||
{
|
||||
"finish_reason": "stop",
|
||||
"kind": "response",
|
||||
"metadata": None,
|
||||
"model_name": "test-model",
|
||||
"parts": [
|
||||
{
|
||||
"content": "Hello there",
|
||||
"id": None,
|
||||
"part_kind": "text",
|
||||
"provider_details": None,
|
||||
"provider_name": None,
|
||||
}
|
||||
],
|
||||
"provider_details": {
|
||||
"finish_reason": "stop",
|
||||
"timestamp": "2025-07-25T10:36:35.297675Z",
|
||||
},
|
||||
"parts": [{"content": "Hello there", "id": None, "part_kind": "text"}],
|
||||
"provider_details": {"finish_reason": "stop"},
|
||||
"provider_name": "openai",
|
||||
"provider_response_id": "chatcmpl-1234567890",
|
||||
"provider_url": "https://www.external-ai-service.com/",
|
||||
"timestamp": "2025-07-25T10:36:35.297675Z",
|
||||
"usage": {
|
||||
"cache_audio_read_tokens": 0,
|
||||
@@ -1710,7 +1582,6 @@ async def test_post_conversation_async_triggers_keepalive(
|
||||
"Today is Friday 25/07/2025.\n\nAnswer in english."
|
||||
),
|
||||
"kind": "request",
|
||||
"metadata": None,
|
||||
"parts": [
|
||||
{
|
||||
"content": ["Hello"],
|
||||
@@ -1719,29 +1590,15 @@ async def test_post_conversation_async_triggers_keepalive(
|
||||
},
|
||||
],
|
||||
"run_id": _run_id,
|
||||
"timestamp": ANY,
|
||||
},
|
||||
{
|
||||
"finish_reason": "stop",
|
||||
"kind": "response",
|
||||
"metadata": None,
|
||||
"model_name": "test-model",
|
||||
"parts": [
|
||||
{
|
||||
"content": "Hello there",
|
||||
"id": None,
|
||||
"part_kind": "text",
|
||||
"provider_details": None,
|
||||
"provider_name": None,
|
||||
}
|
||||
],
|
||||
"provider_details": {
|
||||
"finish_reason": "stop",
|
||||
"timestamp": ANY,
|
||||
},
|
||||
"parts": [{"content": "Hello there", "id": None, "part_kind": "text"}],
|
||||
"provider_details": {"finish_reason": "stop"},
|
||||
"provider_name": "openai",
|
||||
"provider_response_id": "chatcmpl-1234567890",
|
||||
"provider_url": "https://www.external-ai-service.com/",
|
||||
"timestamp": ANY,
|
||||
"usage": {
|
||||
"cache_audio_read_tokens": 0,
|
||||
|
||||
+7
-35
@@ -273,7 +273,7 @@ def test_post_conversation_with_document_upload(
|
||||
api_client,
|
||||
mock_document_api, # pylint: disable=unused-argument
|
||||
sample_pdf_content,
|
||||
today_prompt_date,
|
||||
today_promt_date,
|
||||
mock_ai_agent_service,
|
||||
):
|
||||
"""
|
||||
@@ -409,7 +409,7 @@ def test_post_conversation_with_document_upload(
|
||||
|
||||
assert chat_conversation.pydantic_messages[0] == {
|
||||
"instructions": "You are a helpful test assistant :)\n\n"
|
||||
f"{today_prompt_date}\n\n"
|
||||
f"{today_promt_date}\n\n"
|
||||
"Answer in english.\n\n"
|
||||
"Use document_search_rag ONLY to retrieve specific passages from "
|
||||
"attached documents. Do NOT use it to summarize; for summaries, "
|
||||
@@ -424,7 +424,6 @@ def test_post_conversation_with_document_upload(
|
||||
"Do not request re-upload of documents; consider them already "
|
||||
"available via the internal store.",
|
||||
"kind": "request",
|
||||
"metadata": None,
|
||||
"parts": [
|
||||
{
|
||||
"content": ["What does the document say?"],
|
||||
@@ -433,12 +432,10 @@ def test_post_conversation_with_document_upload(
|
||||
},
|
||||
],
|
||||
"run_id": _run_id,
|
||||
"timestamp": timezone_now,
|
||||
}
|
||||
assert chat_conversation.pydantic_messages[1] == {
|
||||
"finish_reason": None,
|
||||
"kind": "response",
|
||||
"metadata": None,
|
||||
"model_name": "function::agent_model",
|
||||
"parts": [
|
||||
{
|
||||
@@ -447,14 +444,11 @@ def test_post_conversation_with_document_upload(
|
||||
"part_kind": "tool-call",
|
||||
"tool_call_id": chat_conversation.pydantic_messages[1]["parts"][0]["tool_call_id"],
|
||||
"tool_name": "document_search_rag",
|
||||
"provider_details": None,
|
||||
"provider_name": None,
|
||||
}
|
||||
],
|
||||
"provider_details": None,
|
||||
"provider_name": None,
|
||||
"provider_response_id": None,
|
||||
"provider_url": None,
|
||||
"timestamp": timezone_now,
|
||||
"usage": {
|
||||
"cache_audio_read_tokens": 0,
|
||||
@@ -471,7 +465,7 @@ def test_post_conversation_with_document_upload(
|
||||
assert chat_conversation.pydantic_messages[2] == {
|
||||
"instructions": (
|
||||
"You are a helpful test assistant :)\n\n"
|
||||
f"{today_prompt_date}\n\n"
|
||||
f"{today_promt_date}\n\n"
|
||||
"Answer in english.\n\n"
|
||||
"Use document_search_rag ONLY to retrieve specific passages from "
|
||||
"attached documents. Do NOT use it to summarize; for summaries, "
|
||||
@@ -487,7 +481,6 @@ def test_post_conversation_with_document_upload(
|
||||
"available via the internal store."
|
||||
),
|
||||
"kind": "request",
|
||||
"metadata": None,
|
||||
"parts": [
|
||||
{
|
||||
"content": [
|
||||
@@ -505,26 +498,21 @@ def test_post_conversation_with_document_upload(
|
||||
}
|
||||
],
|
||||
"run_id": _run_id,
|
||||
"timestamp": timezone_now,
|
||||
}
|
||||
assert chat_conversation.pydantic_messages[3] == {
|
||||
"finish_reason": None,
|
||||
"kind": "response",
|
||||
"metadata": None,
|
||||
"model_name": "function::agent_model",
|
||||
"parts": [
|
||||
{
|
||||
"content": "From the document, I can see that it says 'Hello PDF'.",
|
||||
"id": None,
|
||||
"part_kind": "text",
|
||||
"provider_details": None,
|
||||
"provider_name": None,
|
||||
}
|
||||
],
|
||||
"provider_details": None,
|
||||
"provider_name": None,
|
||||
"provider_response_id": None,
|
||||
"provider_url": None,
|
||||
"timestamp": timezone_now,
|
||||
"usage": {
|
||||
"cache_audio_read_tokens": 0,
|
||||
@@ -614,7 +602,7 @@ def test_post_conversation_with_document_upload_summarize( # pylint: disable=to
|
||||
api_client,
|
||||
mock_document_api, # pylint: disable=unused-argument
|
||||
sample_pdf_content,
|
||||
today_prompt_date,
|
||||
today_promt_date,
|
||||
mock_ai_agent_service,
|
||||
mock_summarization_agent, # pylint: disable=unused-argument
|
||||
):
|
||||
@@ -751,7 +739,7 @@ def test_post_conversation_with_document_upload_summarize( # pylint: disable=to
|
||||
assert chat_conversation.pydantic_messages[0] == {
|
||||
"instructions": (
|
||||
"You are a helpful test assistant :)\n\n"
|
||||
f"{today_prompt_date}\n\n"
|
||||
f"{today_promt_date}\n\n"
|
||||
"Answer in english.\n\n"
|
||||
"Use document_search_rag ONLY to retrieve specific passages from "
|
||||
"attached documents. Do NOT use it to summarize; for summaries, "
|
||||
@@ -767,7 +755,6 @@ def test_post_conversation_with_document_upload_summarize( # pylint: disable=to
|
||||
"available via the internal store."
|
||||
),
|
||||
"kind": "request",
|
||||
"metadata": None,
|
||||
"parts": [
|
||||
{
|
||||
"content": ["Make a summary of this document."],
|
||||
@@ -776,12 +763,10 @@ def test_post_conversation_with_document_upload_summarize( # pylint: disable=to
|
||||
},
|
||||
],
|
||||
"run_id": _run_id,
|
||||
"timestamp": timezone_now,
|
||||
}
|
||||
assert chat_conversation.pydantic_messages[1] == {
|
||||
"finish_reason": None,
|
||||
"kind": "response",
|
||||
"metadata": None,
|
||||
"model_name": "function::agent_model",
|
||||
"parts": [
|
||||
{
|
||||
@@ -790,14 +775,11 @@ def test_post_conversation_with_document_upload_summarize( # pylint: disable=to
|
||||
"part_kind": "tool-call",
|
||||
"tool_call_id": chat_conversation.pydantic_messages[1]["parts"][0]["tool_call_id"],
|
||||
"tool_name": "summarize",
|
||||
"provider_details": None,
|
||||
"provider_name": None,
|
||||
}
|
||||
],
|
||||
"provider_details": None,
|
||||
"provider_name": None,
|
||||
"provider_response_id": None,
|
||||
"provider_url": None,
|
||||
"timestamp": timezone_now,
|
||||
"usage": {
|
||||
"cache_audio_read_tokens": 0,
|
||||
@@ -814,7 +796,7 @@ def test_post_conversation_with_document_upload_summarize( # pylint: disable=to
|
||||
assert chat_conversation.pydantic_messages[2] == {
|
||||
"instructions": (
|
||||
"You are a helpful test assistant :)\n\n"
|
||||
f"{today_prompt_date}\n\n"
|
||||
f"{today_promt_date}\n\n"
|
||||
"Answer in english.\n\n"
|
||||
"Use document_search_rag ONLY to retrieve specific passages from "
|
||||
"attached documents. Do NOT use it to summarize; for summaries, "
|
||||
@@ -830,7 +812,6 @@ def test_post_conversation_with_document_upload_summarize( # pylint: disable=to
|
||||
"available via the internal store."
|
||||
),
|
||||
"kind": "request",
|
||||
"metadata": None,
|
||||
"parts": [
|
||||
{
|
||||
"content": "The document discusses various topics.",
|
||||
@@ -842,26 +823,17 @@ def test_post_conversation_with_document_upload_summarize( # pylint: disable=to
|
||||
}
|
||||
],
|
||||
"run_id": _run_id,
|
||||
"timestamp": timezone_now,
|
||||
}
|
||||
assert chat_conversation.pydantic_messages[3] == {
|
||||
"finish_reason": None,
|
||||
"kind": "response",
|
||||
"metadata": None,
|
||||
"model_name": "function::agent_model",
|
||||
"parts": [
|
||||
{
|
||||
"content": "The document discusses various topics.",
|
||||
"id": None,
|
||||
"part_kind": "text",
|
||||
"provider_details": None,
|
||||
"provider_name": None,
|
||||
}
|
||||
{"content": "The document discusses various topics.", "id": None, "part_kind": "text"}
|
||||
],
|
||||
"provider_details": None,
|
||||
"provider_name": None,
|
||||
"provider_response_id": None,
|
||||
"provider_url": None,
|
||||
"timestamp": timezone_now,
|
||||
"usage": {
|
||||
"cache_audio_read_tokens": 0,
|
||||
|
||||
+10
-35
@@ -73,13 +73,12 @@ def test_post_conversation_with_local_pdf_document_url(
|
||||
# pylint: disable=too-many-arguments,too-many-positional-arguments
|
||||
api_client,
|
||||
sample_document_content,
|
||||
today_prompt_date,
|
||||
today_promt_date,
|
||||
mock_ai_agent_service,
|
||||
):
|
||||
"""
|
||||
Test POST to /api/v1/chats/{pk}/conversation/ with a document URL.
|
||||
"""
|
||||
|
||||
responses.post(
|
||||
"https://albert.api.etalab.gouv.fr/v1/collections",
|
||||
json={"id": 123, "object": "collection"},
|
||||
@@ -141,7 +140,7 @@ def test_post_conversation_with_local_pdf_document_url(
|
||||
],
|
||||
instructions=(
|
||||
"You are a helpful test assistant :)\n\n"
|
||||
f"{today_prompt_date}\n\n"
|
||||
f"{today_promt_date}\n\n"
|
||||
"Answer in english.\n\n"
|
||||
"Use document_search_rag ONLY to retrieve specific passages from attached "
|
||||
"documents. Do NOT use it to summarize; for summaries, call the summarize "
|
||||
@@ -157,7 +156,6 @@ def test_post_conversation_with_local_pdf_document_url(
|
||||
"via the internal store."
|
||||
),
|
||||
run_id=messages[0].run_id,
|
||||
timestamp=timezone.now(),
|
||||
)
|
||||
]
|
||||
yield "This is a document about a single pixel."
|
||||
@@ -231,7 +229,7 @@ def test_post_conversation_with_local_pdf_document_url(
|
||||
assert chat_conversation.pydantic_messages == [
|
||||
{
|
||||
"instructions": "You are a helpful test assistant :)\n\n"
|
||||
f"{today_prompt_date}\n\n"
|
||||
f"{today_promt_date}\n\n"
|
||||
"Answer in english.\n"
|
||||
"\n"
|
||||
"Use document_search_rag ONLY to retrieve specific passages "
|
||||
@@ -251,7 +249,6 @@ def test_post_conversation_with_local_pdf_document_url(
|
||||
"conversation. Do not request re-upload of documents; "
|
||||
"consider them already available via the internal store.",
|
||||
"kind": "request",
|
||||
"metadata": None,
|
||||
"parts": [
|
||||
{
|
||||
"content": [
|
||||
@@ -262,26 +259,21 @@ def test_post_conversation_with_local_pdf_document_url(
|
||||
},
|
||||
],
|
||||
"run_id": _run_id,
|
||||
"timestamp": timestamp,
|
||||
},
|
||||
{
|
||||
"finish_reason": None,
|
||||
"kind": "response",
|
||||
"metadata": None,
|
||||
"model_name": "function::agent_model",
|
||||
"parts": [
|
||||
{
|
||||
"content": "This is a document about a single pixel.",
|
||||
"id": None,
|
||||
"part_kind": "text",
|
||||
"provider_details": None,
|
||||
"provider_name": None,
|
||||
}
|
||||
],
|
||||
"provider_details": None,
|
||||
"provider_name": None,
|
||||
"provider_response_id": None,
|
||||
"provider_url": None,
|
||||
"timestamp": timestamp,
|
||||
"usage": {
|
||||
"cache_audio_read_tokens": 0,
|
||||
@@ -553,7 +545,6 @@ def test_post_conversation_with_local_document_url_in_history( # pylint: disabl
|
||||
assert presigned_url.find("X-Amz-Signature=") != -1
|
||||
assert presigned_url.find("X-Amz-Date=") != -1
|
||||
assert presigned_url.find("X-Amz-Expires=") != -1
|
||||
timestamp_now = timezone.now()
|
||||
|
||||
assert messages == [
|
||||
ModelRequest(
|
||||
@@ -567,7 +558,7 @@ def test_post_conversation_with_local_document_url_in_history( # pylint: disabl
|
||||
identifier="sample.pdf",
|
||||
),
|
||||
],
|
||||
timestamp=timestamp_now,
|
||||
timestamp=timezone.now(),
|
||||
),
|
||||
],
|
||||
instructions="You are a helpful test assistant :)\n\n"
|
||||
@@ -579,7 +570,7 @@ def test_post_conversation_with_local_document_url_in_history( # pylint: disabl
|
||||
parts=[TextPart(content="This is a document about a single pixel.")],
|
||||
usage=RequestUsage(input_tokens=50, output_tokens=9),
|
||||
model_name="function::agent_model",
|
||||
timestamp=timestamp_now,
|
||||
timestamp=timezone.now(),
|
||||
run_id=messages[1].run_id,
|
||||
),
|
||||
ModelRequest(
|
||||
@@ -588,10 +579,9 @@ def test_post_conversation_with_local_document_url_in_history( # pylint: disabl
|
||||
content=[
|
||||
"Give more details about this document.",
|
||||
],
|
||||
timestamp=timestamp_now,
|
||||
timestamp=timezone.now(),
|
||||
)
|
||||
],
|
||||
timestamp=timestamp_now,
|
||||
instructions="You are a helpful test assistant :)\n\n"
|
||||
"Today is Saturday 18/10/2025.\n\n"
|
||||
"Answer in english.",
|
||||
@@ -748,7 +738,6 @@ def test_post_conversation_with_local_document_url_in_history( # pylint: disabl
|
||||
"instructions": "You are a helpful test assistant :)\n\n"
|
||||
"Today is Saturday 18/10/2025.\n\n"
|
||||
"Answer in english.",
|
||||
"metadata": None,
|
||||
"kind": "request",
|
||||
"parts": [
|
||||
{
|
||||
@@ -758,26 +747,21 @@ def test_post_conversation_with_local_document_url_in_history( # pylint: disabl
|
||||
}
|
||||
],
|
||||
"run_id": _run_id,
|
||||
"timestamp": "2025-10-18T20:48:20.286204Z",
|
||||
},
|
||||
{
|
||||
"finish_reason": None,
|
||||
"kind": "response",
|
||||
"metadata": None,
|
||||
"model_name": "function::agent_model",
|
||||
"parts": [
|
||||
{
|
||||
"content": "This is a document of square, very small and nice.",
|
||||
"id": None,
|
||||
"part_kind": "text",
|
||||
"provider_details": None,
|
||||
"provider_name": None,
|
||||
}
|
||||
],
|
||||
"provider_details": None,
|
||||
"provider_name": None,
|
||||
"provider_response_id": None,
|
||||
"provider_url": None,
|
||||
"timestamp": "2025-10-18T20:48:20.286204Z",
|
||||
"usage": {
|
||||
"cache_audio_read_tokens": 0,
|
||||
@@ -807,7 +791,7 @@ def test_post_conversation_with_local_document_url_in_history( # pylint: disabl
|
||||
def test_post_conversation_with_local_not_pdf_document_url(
|
||||
# pylint: disable=too-many-arguments,too-many-positional-arguments
|
||||
api_client,
|
||||
today_prompt_date,
|
||||
today_promt_date,
|
||||
mock_ai_agent_service,
|
||||
file_name,
|
||||
content_type,
|
||||
@@ -869,8 +853,6 @@ def test_post_conversation_with_local_not_pdf_document_url(
|
||||
)
|
||||
|
||||
async def agent_model(messages: list[ModelMessage], _info: AgentInfo):
|
||||
timestamp_now = timezone.now()
|
||||
|
||||
assert messages == [
|
||||
ModelRequest(
|
||||
parts=[
|
||||
@@ -879,13 +861,12 @@ def test_post_conversation_with_local_not_pdf_document_url(
|
||||
"What is in this document?",
|
||||
# No presigned URL for non-PDF documents (not supporter by LLM)
|
||||
],
|
||||
timestamp=timestamp_now,
|
||||
timestamp=timezone.now(),
|
||||
),
|
||||
],
|
||||
timestamp=timestamp_now,
|
||||
instructions=(
|
||||
"You are a helpful test assistant :)\n\n"
|
||||
f"{today_prompt_date}\n\n"
|
||||
f"{today_promt_date}\n\n"
|
||||
"Answer in english.\n\n"
|
||||
"Use document_search_rag ONLY to retrieve specific passages from "
|
||||
"attached documents. Do NOT use it to summarize; for summaries, "
|
||||
@@ -976,7 +957,7 @@ def test_post_conversation_with_local_not_pdf_document_url(
|
||||
{
|
||||
"instructions": (
|
||||
"You are a helpful test assistant :)\n\n"
|
||||
f"{today_prompt_date}\n\n"
|
||||
f"{today_promt_date}\n\n"
|
||||
"Answer in english.\n\n"
|
||||
"Use document_search_rag ONLY to retrieve specific passages from "
|
||||
"attached documents. Do NOT use it to summarize; for summaries, "
|
||||
@@ -993,7 +974,6 @@ def test_post_conversation_with_local_not_pdf_document_url(
|
||||
"consider them already available via the internal store."
|
||||
),
|
||||
"kind": "request",
|
||||
"metadata": None,
|
||||
"parts": [
|
||||
{
|
||||
"content": [
|
||||
@@ -1004,26 +984,21 @@ def test_post_conversation_with_local_not_pdf_document_url(
|
||||
},
|
||||
],
|
||||
"run_id": _run_id,
|
||||
"timestamp": timestamp,
|
||||
},
|
||||
{
|
||||
"finish_reason": None,
|
||||
"kind": "response",
|
||||
"metadata": None,
|
||||
"model_name": "function::agent_model",
|
||||
"parts": [
|
||||
{
|
||||
"content": "This is a document about you.",
|
||||
"id": None,
|
||||
"part_kind": "text",
|
||||
"provider_details": None,
|
||||
"provider_name": None,
|
||||
}
|
||||
],
|
||||
"provider_details": None,
|
||||
"provider_name": None,
|
||||
"provider_response_id": None,
|
||||
"provider_url": None,
|
||||
"timestamp": timestamp,
|
||||
"usage": {
|
||||
"cache_audio_read_tokens": 0,
|
||||
|
||||
+90
-223
@@ -29,10 +29,6 @@ from chat.tests.utils import replace_uuids_with_placeholder
|
||||
pytestmark = pytest.mark.django_db(transaction=True)
|
||||
|
||||
|
||||
PYAI_CURRENT = "current"
|
||||
PYAI_V1_17 = "v1.17"
|
||||
|
||||
|
||||
@pytest.fixture(autouse=True)
|
||||
def ai_settings(settings):
|
||||
"""Fixture to set AI service URLs for testing."""
|
||||
@@ -45,9 +41,17 @@ def ai_settings(settings):
|
||||
return settings
|
||||
|
||||
|
||||
def build__history_conversation_ui_messages(history_timestamp):
|
||||
"""Build ui messages list for fixtures."""
|
||||
return [
|
||||
@pytest.fixture(name="history_conversation")
|
||||
def history_conversation_fixture():
|
||||
"""Create a conversation with existing message history."""
|
||||
# Create a timestamp for the first message
|
||||
history_timestamp = timezone.now().replace(year=2025, month=6, day=15, hour=10, minute=30)
|
||||
|
||||
# Create a conversation with pre-existing messages
|
||||
conversation = ChatConversationFactory()
|
||||
|
||||
# Add previous user and assistant messages
|
||||
conversation.messages = [
|
||||
UIMessage(
|
||||
id="prev-user-msg-1",
|
||||
createdAt=history_timestamp,
|
||||
@@ -116,205 +120,94 @@ def build__history_conversation_ui_messages(history_timestamp):
|
||||
),
|
||||
]
|
||||
|
||||
|
||||
@pytest.fixture(name="history_conversation")
|
||||
def history_conversation_fixture(request):
|
||||
"""Create a conversation with existing message history according to pydantic ai version."""
|
||||
|
||||
# Create a timestamp for the first message
|
||||
history_timestamp = timezone.now().replace(year=2025, month=6, day=15, hour=10, minute=30)
|
||||
|
||||
# Create a conversation with pre-existing messages
|
||||
conversation = ChatConversationFactory()
|
||||
pyai_version = getattr(request, "param", PYAI_CURRENT)
|
||||
# Add previous user and assistant messages
|
||||
if pyai_version == PYAI_V1_17:
|
||||
conversation.pydantic_messages = [
|
||||
{
|
||||
"instructions": None,
|
||||
"kind": "request",
|
||||
"parts": [
|
||||
{
|
||||
"content": "You are a helpful test assistant :)",
|
||||
"dynamic_ref": None,
|
||||
"part_kind": "system-prompt",
|
||||
"timestamp": "2025-06-15T10:30:00.000000Z",
|
||||
},
|
||||
{
|
||||
"content": ["How does machine learning work?"],
|
||||
"part_kind": "user-prompt",
|
||||
"timestamp": "2025-06-15T10:30:00.000000Z",
|
||||
},
|
||||
],
|
||||
},
|
||||
{
|
||||
"kind": "response",
|
||||
"model_name": "test-model",
|
||||
"parts": [
|
||||
{
|
||||
"content": (
|
||||
"Machine learning is a branch of artificial intelligence that "
|
||||
"focuses on building systems that learn from data."
|
||||
),
|
||||
"part_kind": "text",
|
||||
}
|
||||
],
|
||||
"timestamp": "2025-06-15T10:31:00.000000Z",
|
||||
"usage": {
|
||||
"details": None,
|
||||
"request_tokens": 10,
|
||||
"requests": 1,
|
||||
"response_tokens": 20,
|
||||
"total_tokens": 30,
|
||||
},
|
||||
"vendor_details": None,
|
||||
"vendor_id": None,
|
||||
},
|
||||
{
|
||||
"instructions": None,
|
||||
"kind": "request",
|
||||
"parts": [
|
||||
{
|
||||
"content": ["What are neural networks?"],
|
||||
"part_kind": "user-prompt",
|
||||
"timestamp": "2025-06-15T10:32:00.000000Z",
|
||||
},
|
||||
],
|
||||
},
|
||||
{
|
||||
"kind": "response",
|
||||
"model_name": "test-model",
|
||||
"parts": [
|
||||
{
|
||||
"content": (
|
||||
"Neural networks are computing systems inspired by the "
|
||||
"biological neural networks in animal brains."
|
||||
),
|
||||
"part_kind": "text",
|
||||
}
|
||||
],
|
||||
"timestamp": "2025-06-15T10:33:00.000000Z",
|
||||
"usage": {
|
||||
"details": None,
|
||||
"request_tokens": 5,
|
||||
"requests": 1,
|
||||
"response_tokens": 15,
|
||||
"total_tokens": 20,
|
||||
},
|
||||
"vendor_details": None,
|
||||
"vendor_id": None,
|
||||
},
|
||||
]
|
||||
else:
|
||||
conversation.pydantic_messages = [
|
||||
{
|
||||
"instructions": None,
|
||||
"kind": "request",
|
||||
"parts": [
|
||||
{
|
||||
"content": "You are a helpful test assistant :)",
|
||||
"dynamic_ref": None,
|
||||
"part_kind": "system-prompt",
|
||||
"timestamp": "2025-06-15T10:30:00.000000Z",
|
||||
},
|
||||
{
|
||||
"content": ["How does machine learning work?"],
|
||||
"part_kind": "user-prompt",
|
||||
"timestamp": "2025-06-15T10:30:00.000000Z",
|
||||
},
|
||||
],
|
||||
},
|
||||
{
|
||||
"kind": "response",
|
||||
"model_name": "test-model",
|
||||
"parts": [
|
||||
{
|
||||
"content": (
|
||||
"Machine learning is a branch of artificial intelligence that "
|
||||
"focuses on building systems that learn from data."
|
||||
),
|
||||
"part_kind": "text",
|
||||
"provider_details": {
|
||||
"finish_reason": "stop",
|
||||
"timestamp": "2025-07-25T10:36:35.297675Z",
|
||||
},
|
||||
"provider_name": "some model",
|
||||
}
|
||||
],
|
||||
"timestamp": "2025-06-15T10:31:00.000000Z",
|
||||
"usage": {
|
||||
"details": None,
|
||||
"request_tokens": 10,
|
||||
"requests": 1,
|
||||
"response_tokens": 20,
|
||||
"total_tokens": 30,
|
||||
},
|
||||
"provider_details": None,
|
||||
"vendor_id": None,
|
||||
},
|
||||
{
|
||||
"instructions": None,
|
||||
"kind": "request",
|
||||
"parts": [
|
||||
{
|
||||
"content": ["What are neural networks?"],
|
||||
"part_kind": "user-prompt",
|
||||
"timestamp": "2025-06-15T10:32:00.000000Z",
|
||||
},
|
||||
],
|
||||
},
|
||||
{
|
||||
"kind": "response",
|
||||
"metadata": None,
|
||||
"model_name": "test-model",
|
||||
"finish_reason": "stop",
|
||||
"parts": [
|
||||
{
|
||||
"content": (
|
||||
"Neural networks are computing systems inspired by the "
|
||||
"biological neural networks in animal brains."
|
||||
),
|
||||
"part_kind": "text",
|
||||
"provider_details": {
|
||||
"finish_reason": "stop",
|
||||
"timestamp": "2025-07-25T10:36:35.297675Z",
|
||||
},
|
||||
"provider_name": "test-model",
|
||||
"provider_url": "https://www.external-ai-service.com/",
|
||||
}
|
||||
],
|
||||
"timestamp": "2025-06-15T10:33:00.000000Z",
|
||||
"usage": {
|
||||
"details": None,
|
||||
"request_tokens": 5,
|
||||
"requests": 1,
|
||||
"response_tokens": 15,
|
||||
"total_tokens": 20,
|
||||
},
|
||||
"provider_details": {
|
||||
"timestamp": "2025-07-25T10:36:35.297675Z",
|
||||
"finish_reason": "stop",
|
||||
},
|
||||
"provider_name": "test-model",
|
||||
"provider_response_id": "xyz",
|
||||
},
|
||||
]
|
||||
|
||||
# Set up the OpenAI message format as well
|
||||
conversation.messages = build__history_conversation_ui_messages(history_timestamp)
|
||||
conversation.pydantic_messages = [
|
||||
{
|
||||
"instructions": None,
|
||||
"kind": "request",
|
||||
"parts": [
|
||||
{
|
||||
"content": "You are a helpful test assistant :)",
|
||||
"dynamic_ref": None,
|
||||
"part_kind": "system-prompt",
|
||||
"timestamp": "2025-06-15T10:30:00.000000Z",
|
||||
},
|
||||
{
|
||||
"content": ["How does machine learning work?"],
|
||||
"part_kind": "user-prompt",
|
||||
"timestamp": "2025-06-15T10:30:00.000000Z",
|
||||
},
|
||||
],
|
||||
},
|
||||
{
|
||||
"kind": "response",
|
||||
"model_name": "test-model",
|
||||
"parts": [
|
||||
{
|
||||
"content": (
|
||||
"Machine learning is a branch of artificial intelligence that "
|
||||
"focuses on building systems that learn from data."
|
||||
),
|
||||
"part_kind": "text",
|
||||
}
|
||||
],
|
||||
"timestamp": "2025-06-15T10:31:00.000000Z",
|
||||
"usage": {
|
||||
"details": None,
|
||||
"request_tokens": 10,
|
||||
"requests": 1,
|
||||
"response_tokens": 20,
|
||||
"total_tokens": 30,
|
||||
},
|
||||
"vendor_details": None,
|
||||
"vendor_id": None,
|
||||
},
|
||||
{
|
||||
"instructions": None,
|
||||
"kind": "request",
|
||||
"parts": [
|
||||
{
|
||||
"content": ["What are neural networks?"],
|
||||
"part_kind": "user-prompt",
|
||||
"timestamp": "2025-06-15T10:32:00.000000Z",
|
||||
},
|
||||
],
|
||||
},
|
||||
{
|
||||
"kind": "response",
|
||||
"model_name": "test-model",
|
||||
"parts": [
|
||||
{
|
||||
"content": (
|
||||
"Neural networks are computing systems inspired by the "
|
||||
"biological neural networks in animal brains."
|
||||
),
|
||||
"part_kind": "text",
|
||||
}
|
||||
],
|
||||
"timestamp": "2025-06-15T10:33:00.000000Z",
|
||||
"usage": {
|
||||
"details": None,
|
||||
"request_tokens": 5,
|
||||
"requests": 1,
|
||||
"response_tokens": 15,
|
||||
"total_tokens": 20,
|
||||
},
|
||||
"vendor_details": None,
|
||||
"vendor_id": None,
|
||||
},
|
||||
]
|
||||
|
||||
conversation.save()
|
||||
return conversation
|
||||
|
||||
|
||||
@pytest.mark.parametrize("history_conversation", [PYAI_CURRENT, PYAI_V1_17], indirect=True)
|
||||
@freeze_time("2025-07-25T10:36:35.297675Z")
|
||||
@respx.mock
|
||||
def test_post_conversation_data_protocol_with_history(
|
||||
api_client, mock_openai_stream, history_conversation
|
||||
):
|
||||
"""Test posting messages to a conversation with history using the 'data' protocol."""
|
||||
|
||||
url = f"/api/v1.0/chats/{history_conversation.pk}/conversation/?protocol=data"
|
||||
data = {
|
||||
"messages": [
|
||||
@@ -1135,7 +1028,6 @@ def history_conversation_with_tool_fixture():
|
||||
},
|
||||
{
|
||||
"kind": "response",
|
||||
"metadata": None,
|
||||
"model_name": "test-model",
|
||||
"parts": [
|
||||
{
|
||||
@@ -1177,7 +1069,6 @@ def history_conversation_with_tool_fixture():
|
||||
},
|
||||
{
|
||||
"kind": "response",
|
||||
"metadata": None,
|
||||
"model_name": "test-model",
|
||||
"parts": [
|
||||
{
|
||||
@@ -1211,7 +1102,6 @@ def history_conversation_with_tool_fixture():
|
||||
},
|
||||
{
|
||||
"kind": "response",
|
||||
"metadata": None,
|
||||
"model_name": "test-model",
|
||||
"parts": [
|
||||
{
|
||||
@@ -1258,7 +1148,6 @@ def history_conversation_with_tool_fixture():
|
||||
},
|
||||
{
|
||||
"kind": "response",
|
||||
"metadata": None,
|
||||
"model_name": "test-model",
|
||||
"parts": [
|
||||
{
|
||||
@@ -1495,7 +1384,6 @@ def test_post_conversation_with_existing_tool_history(
|
||||
"Today is Friday 25/07/2025.\n\n"
|
||||
"Answer in dutch.",
|
||||
"kind": "request",
|
||||
"metadata": None,
|
||||
"parts": [
|
||||
{
|
||||
"content": ["How about Paris weather?"],
|
||||
@@ -1504,32 +1392,24 @@ def test_post_conversation_with_existing_tool_history(
|
||||
}
|
||||
],
|
||||
"run_id": _run_id,
|
||||
"timestamp": "2025-07-25T10:36:35.297675Z",
|
||||
}
|
||||
|
||||
assert history_conversation_with_tool.pydantic_messages[9] == {
|
||||
"finish_reason": "tool_call",
|
||||
"kind": "response",
|
||||
"metadata": None,
|
||||
"model_name": "test-model",
|
||||
"parts": [
|
||||
{
|
||||
"args": '{"location":"Paris", "unit":"celsius"}',
|
||||
"id": None,
|
||||
"part_kind": "tool-call",
|
||||
"provider_details": None,
|
||||
"provider_name": None,
|
||||
"tool_call_id": "xLDcIljdsDrz0idal7tATWSMm2jhMj47",
|
||||
"tool_name": "get_current_weather",
|
||||
}
|
||||
],
|
||||
"provider_details": {
|
||||
"finish_reason": "tool_calls",
|
||||
"timestamp": "2025-07-25T10:36:35.297675Z",
|
||||
},
|
||||
"provider_details": {"finish_reason": "tool_calls"},
|
||||
"provider_name": "openai",
|
||||
"provider_response_id": "chatcmpl-tool-call",
|
||||
"provider_url": "https://www.external-ai-service.com/",
|
||||
"timestamp": "2025-07-25T10:36:35.297675Z",
|
||||
"usage": {
|
||||
"cache_audio_read_tokens": 0,
|
||||
@@ -1549,7 +1429,6 @@ def test_post_conversation_with_existing_tool_history(
|
||||
"Today is Friday 25/07/2025.\n\n"
|
||||
"Answer in dutch.",
|
||||
"kind": "request",
|
||||
"metadata": None,
|
||||
"parts": [
|
||||
{
|
||||
"content": {"location": "Paris", "temperature": 22, "unit": "celsius"},
|
||||
@@ -1561,30 +1440,18 @@ def test_post_conversation_with_existing_tool_history(
|
||||
}
|
||||
],
|
||||
"run_id": _run_id,
|
||||
"timestamp": "2025-07-25T10:36:35.297675Z",
|
||||
}
|
||||
|
||||
assert history_conversation_with_tool.pydantic_messages[11] == {
|
||||
"finish_reason": "stop",
|
||||
"kind": "response",
|
||||
"metadata": None,
|
||||
"model_name": "test-model",
|
||||
"parts": [
|
||||
{
|
||||
"content": "The current weather in Paris is nice",
|
||||
"id": None,
|
||||
"part_kind": "text",
|
||||
"provider_details": None,
|
||||
"provider_name": None,
|
||||
}
|
||||
{"content": "The current weather in Paris is nice", "id": None, "part_kind": "text"}
|
||||
],
|
||||
"provider_details": {
|
||||
"finish_reason": "stop",
|
||||
"timestamp": "2025-07-25T10:36:35.297675Z",
|
||||
},
|
||||
"provider_details": {"finish_reason": "stop"},
|
||||
"provider_name": "openai",
|
||||
"provider_response_id": "chatcmpl-final",
|
||||
"provider_url": "https://www.external-ai-service.com/",
|
||||
"timestamp": "2025-07-25T10:36:35.297675Z",
|
||||
"usage": {
|
||||
"cache_audio_read_tokens": 0,
|
||||
|
||||
+11
-34
@@ -92,7 +92,6 @@ def test_post_conversation_with_local_image_url(
|
||||
assert presigned_url.find("X-Amz-Date=") != -1
|
||||
assert presigned_url.find("X-Amz-Expires=") != -1
|
||||
formatted_date = formats.date_format(timezone.now(), "l d/m/Y", use_l10n=False)
|
||||
|
||||
assert messages == [
|
||||
ModelRequest(
|
||||
parts=[
|
||||
@@ -111,7 +110,6 @@ def test_post_conversation_with_local_image_url(
|
||||
instructions="You are a helpful test assistant :)\n\nToday is "
|
||||
f"{formatted_date}.\n\nAnswer in english.",
|
||||
run_id=messages[0].run_id,
|
||||
timestamp=timezone.now(),
|
||||
)
|
||||
]
|
||||
yield "This is an image of a single pixel."
|
||||
@@ -183,7 +181,6 @@ def test_post_conversation_with_local_image_url(
|
||||
"instructions": "You are a helpful test assistant :)\n\n"
|
||||
"Today is Saturday 18/10/2025.\n\nAnswer in english.",
|
||||
"kind": "request",
|
||||
"metadata": None,
|
||||
"parts": [
|
||||
{
|
||||
"content": [
|
||||
@@ -202,26 +199,17 @@ def test_post_conversation_with_local_image_url(
|
||||
},
|
||||
],
|
||||
"run_id": _run_id,
|
||||
"timestamp": "2025-10-18T20:48:20.286204Z",
|
||||
},
|
||||
{
|
||||
"finish_reason": None,
|
||||
"kind": "response",
|
||||
"metadata": None,
|
||||
"model_name": "function::agent_model",
|
||||
"parts": [
|
||||
{
|
||||
"content": "This is an image of a single pixel.",
|
||||
"id": None,
|
||||
"part_kind": "text",
|
||||
"provider_details": None,
|
||||
"provider_name": None,
|
||||
}
|
||||
{"content": "This is an image of a single pixel.", "id": None, "part_kind": "text"}
|
||||
],
|
||||
"provider_details": None,
|
||||
"provider_name": None,
|
||||
"provider_response_id": None,
|
||||
"provider_url": None,
|
||||
"timestamp": "2025-10-18T20:48:20.286204Z",
|
||||
"usage": {
|
||||
"cache_audio_read_tokens": 0,
|
||||
@@ -241,7 +229,7 @@ def test_post_conversation_with_local_image_url(
|
||||
@freeze_time()
|
||||
def test_post_conversation_with_local_image_wrong_url(
|
||||
api_client,
|
||||
today_prompt_date,
|
||||
today_promt_date,
|
||||
mock_ai_agent_service,
|
||||
):
|
||||
"""
|
||||
@@ -287,8 +275,7 @@ def test_post_conversation_with_local_image_wrong_url(
|
||||
timestamp=timezone.now(),
|
||||
),
|
||||
],
|
||||
timestamp=timezone.now(),
|
||||
instructions=f"You are a helpful test assistant :)\n\n{today_prompt_date}"
|
||||
instructions=f"You are a helpful test assistant :)\n\n{today_promt_date}"
|
||||
"\n\nAnswer in english.",
|
||||
run_id=messages[0].run_id,
|
||||
)
|
||||
@@ -327,7 +314,7 @@ def test_post_conversation_with_local_image_wrong_url(
|
||||
@freeze_time()
|
||||
def test_post_conversation_with_remote_image_url(
|
||||
api_client,
|
||||
today_prompt_date,
|
||||
today_promt_date,
|
||||
mock_ai_agent_service,
|
||||
):
|
||||
"""
|
||||
@@ -374,9 +361,8 @@ def test_post_conversation_with_remote_image_url(
|
||||
),
|
||||
],
|
||||
instructions="You are a helpful test assistant :)\n\n"
|
||||
f"{today_prompt_date}\n\nAnswer in english.",
|
||||
f"{today_promt_date}\n\nAnswer in english.",
|
||||
run_id=messages[0].run_id,
|
||||
timestamp=timezone.now(),
|
||||
)
|
||||
]
|
||||
yield "This is an image of a single pixel."
|
||||
@@ -446,7 +432,7 @@ def test_post_conversation_with_remote_image_url(
|
||||
@freeze_time("2025-10-18T20:48:20.286204Z")
|
||||
def test_post_conversation_with_local_image_url_in_history(
|
||||
api_client,
|
||||
today_prompt_date,
|
||||
today_promt_date,
|
||||
mock_ai_agent_service,
|
||||
):
|
||||
"""
|
||||
@@ -489,7 +475,7 @@ def test_post_conversation_with_local_image_url_in_history(
|
||||
],
|
||||
pydantic_messages=[
|
||||
{
|
||||
"instructions": f"You are a helpful test assistant :)\n\n{today_prompt_date}"
|
||||
"instructions": f"You are a helpful test assistant :)\n\n{today_promt_date}"
|
||||
"\n\nAnswer in english.",
|
||||
"kind": "request",
|
||||
"parts": [
|
||||
@@ -561,8 +547,6 @@ def test_post_conversation_with_local_image_url_in_history(
|
||||
assert presigned_url.find("X-Amz-Date=") != -1
|
||||
assert presigned_url.find("X-Amz-Expires=") != -1
|
||||
|
||||
timestamp_now = timezone.now()
|
||||
|
||||
assert messages == [
|
||||
ModelRequest(
|
||||
parts=[
|
||||
@@ -575,11 +559,11 @@ def test_post_conversation_with_local_image_url_in_history(
|
||||
identifier="sample.png",
|
||||
),
|
||||
],
|
||||
timestamp=timestamp_now,
|
||||
timestamp=timezone.now(),
|
||||
),
|
||||
],
|
||||
instructions="You are a helpful test assistant :)\n\n"
|
||||
f"{today_prompt_date}\n\nAnswer in english.",
|
||||
f"{today_promt_date}\n\nAnswer in english.",
|
||||
),
|
||||
ModelResponse(
|
||||
parts=[TextPart(content="This is an image of a single pixel.")],
|
||||
@@ -593,13 +577,12 @@ def test_post_conversation_with_local_image_url_in_history(
|
||||
content=[
|
||||
"Give more details about this image.",
|
||||
],
|
||||
timestamp=timestamp_now,
|
||||
timestamp=timezone.now(),
|
||||
)
|
||||
],
|
||||
run_id=messages[2].run_id,
|
||||
instructions="You are a helpful test assistant :)\n\n"
|
||||
"Today is Saturday 18/10/2025.\n\nAnswer in english.",
|
||||
timestamp=timestamp_now,
|
||||
),
|
||||
]
|
||||
yield "This is an image of square, very small and nice."
|
||||
@@ -698,7 +681,7 @@ def test_post_conversation_with_local_image_url_in_history(
|
||||
_run_id = chat_conversation.pydantic_messages[2]["run_id"]
|
||||
assert chat_conversation.pydantic_messages == [
|
||||
{
|
||||
"instructions": f"You are a helpful test assistant :)\n\n{today_prompt_date}"
|
||||
"instructions": f"You are a helpful test assistant :)\n\n{today_promt_date}"
|
||||
"\n\nAnswer in english.",
|
||||
"kind": "request",
|
||||
"parts": [
|
||||
@@ -745,7 +728,6 @@ def test_post_conversation_with_local_image_url_in_history(
|
||||
"instructions": "You are a helpful test assistant :)\n\nToday is Saturday 18/10/2025."
|
||||
"\n\nAnswer in english.",
|
||||
"kind": "request",
|
||||
"metadata": None,
|
||||
"parts": [
|
||||
{
|
||||
"content": ["Give more details about this image."],
|
||||
@@ -754,26 +736,21 @@ def test_post_conversation_with_local_image_url_in_history(
|
||||
}
|
||||
],
|
||||
"run_id": _run_id,
|
||||
"timestamp": "2025-10-18T20:48:20.286204Z",
|
||||
},
|
||||
{
|
||||
"finish_reason": None,
|
||||
"kind": "response",
|
||||
"metadata": None,
|
||||
"model_name": "function::agent_model",
|
||||
"parts": [
|
||||
{
|
||||
"content": "This is an image of square, very small and nice.",
|
||||
"id": None,
|
||||
"part_kind": "text",
|
||||
"provider_details": None,
|
||||
"provider_name": None,
|
||||
}
|
||||
],
|
||||
"provider_details": None,
|
||||
"provider_name": None,
|
||||
"provider_response_id": None,
|
||||
"provider_url": None,
|
||||
"timestamp": "2025-10-18T20:48:20.286204Z",
|
||||
"usage": {
|
||||
"cache_audio_read_tokens": 0,
|
||||
|
||||
@@ -4,6 +4,7 @@ import asyncio
|
||||
import logging
|
||||
|
||||
from django.conf import settings
|
||||
from django.core.files.storage import default_storage
|
||||
|
||||
import semchunk
|
||||
from asgiref.sync import sync_to_async
|
||||
@@ -13,11 +14,18 @@ from pydantic_ai.messages import ToolReturn
|
||||
|
||||
from chat.agents.summarize import SummarizationAgent
|
||||
from chat.tools.exceptions import ModelCannotRetry
|
||||
from chat.tools.utils import last_model_retry_soft_fail, read_document_content
|
||||
from chat.tools.utils import last_model_retry_soft_fail
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
@sync_to_async
|
||||
def read_document_content(doc):
|
||||
"""Read document content asynchronously."""
|
||||
with default_storage.open(doc.key) as f:
|
||||
return doc.file_name, f.read().decode("utf-8")
|
||||
|
||||
|
||||
async def summarize_chunk(idx, chunk, total_chunks, summarization_agent, ctx):
|
||||
"""Summarize a single chunk of text."""
|
||||
sum_prompt = (
|
||||
@@ -43,26 +51,33 @@ async def summarize_chunk(idx, chunk, total_chunks, summarization_agent, ctx):
|
||||
|
||||
|
||||
@last_model_retry_soft_fail
|
||||
async def document_summarize( # pylint: disable=too-many-locals
|
||||
ctx: RunContext, *, instructions: str | None = None
|
||||
async def document_summarize( # pylint: disable=too-many-locals, too-many-statements
|
||||
ctx: RunContext,
|
||||
*,
|
||||
instructions: str | None = None,
|
||||
doc_index: int | None = None,
|
||||
) -> ToolReturn:
|
||||
"""
|
||||
Generate a complete, ready-to-use summary of the documents in context
|
||||
(do not request the documents to the user).
|
||||
Return this summary directly to the user WITHOUT any modification,
|
||||
or additional summarization.
|
||||
The summary is already optimized and MUST be presented as-is in the final response
|
||||
or translated preserving the information.
|
||||
|
||||
Instructions are optional but should reflect the user's request.
|
||||
|
||||
Examples:
|
||||
"Summarize this doc in 2 paragraphs" -> instructions = "summary in 2 paragraphs"
|
||||
"Summarize this doc in English" -> instructions = "In English"
|
||||
"Summarize this doc" -> instructions = "" (default)
|
||||
|
||||
Args:
|
||||
instructions (str | None): The instructions the user gave to use for the summarization
|
||||
Produce a final, user-ready summary for one or more text documents from the conversation.
|
||||
|
||||
Builds per-chunk summaries for the selected documents, synthesizes them into a single coherent
|
||||
markdown-formatted summary that is intended to be returned to the user verbatim.
|
||||
|
||||
Parameters:
|
||||
instructions (str | None): Optional user instructions to guide the summary (e.g., length,
|
||||
language, style). When omitted, a default hint is used.
|
||||
doc_index (int | None): If provided, summarize only the document at this index (0-based;
|
||||
negative indices allowed, e.g. -1 for the last document). If `None`, all text documents
|
||||
found in the conversation are summarized.
|
||||
|
||||
Returns:
|
||||
str: The final synthesized summary formatted in Markdown.
|
||||
|
||||
Raises:
|
||||
ModelCannotRetry: If no text documents are found in the conversation or on unexpected errors
|
||||
that should stop processing and be reported to the user.
|
||||
ModelRetry: For retryable errors such as an out-of-range `doc_index`, errors during chunk
|
||||
processing, merge-generation failures, or when the summarization produces an empty result.
|
||||
"""
|
||||
try:
|
||||
instructions_hint = (
|
||||
@@ -83,6 +98,15 @@ async def document_summarize( # pylint: disable=too-many-locals
|
||||
"You must explain this to the user and ask them to provide documents."
|
||||
)
|
||||
|
||||
if doc_index is not None:
|
||||
try:
|
||||
text_attachment = [text_attachment[doc_index]]
|
||||
except IndexError as exc:
|
||||
raise ModelRetry(
|
||||
f"Document index {doc_index} is out of range. "
|
||||
f"There are {len(text_attachment)} documents available."
|
||||
) from exc
|
||||
|
||||
documents = [await read_document_content(doc) for doc in text_attachment]
|
||||
|
||||
# Chunk documents and summarize each chunk
|
||||
@@ -178,4 +202,4 @@ async def document_summarize( # pylint: disable=too-many-locals
|
||||
raise ModelCannotRetry(
|
||||
f"An unexpected error occurred during document summarization: {type(exc).__name__}. "
|
||||
"You must explain this to the user and not try to answer based on your knowledge."
|
||||
) from exc
|
||||
) from exc
|
||||
@@ -1,136 +0,0 @@
|
||||
"""Translation tool used for uploaded documents."""
|
||||
|
||||
import logging
|
||||
|
||||
from django.conf import settings
|
||||
|
||||
from pydantic_ai import RunContext
|
||||
from pydantic_ai.exceptions import ModelRetry
|
||||
from pydantic_ai.messages import ToolReturn
|
||||
|
||||
from chat.agents.translate import TranslationAgent
|
||||
from chat.tools.exceptions import ModelCannotRetry
|
||||
from chat.tools.utils import last_model_retry_soft_fail, read_document_content
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
@last_model_retry_soft_fail
|
||||
async def document_translate(
|
||||
ctx: RunContext,
|
||||
*,
|
||||
target_language: str | None = None,
|
||||
instructions: str | None = None,
|
||||
) -> ToolReturn:
|
||||
"""
|
||||
Translate the full content of the last uploaded document into the specified target language.
|
||||
Preserve the original markdown formatting unless the instructions say otherwise.
|
||||
Return this translation directly to the user WITHOUT any modification
|
||||
or additional summarization.
|
||||
The translation is already complete and MUST be presented as-is in the final response.
|
||||
|
||||
If target_language isn't specified or unknown, the target language should be asked
|
||||
to the user.
|
||||
|
||||
Instructions are optional but should reflect the user's request.
|
||||
|
||||
Examples:
|
||||
"Translate this doc to English" -> target_language = "English", instructions = ""
|
||||
"Translate to Spanish, in formal tone" -> target_language = "Spanish",
|
||||
instructions = "Use formal tone"
|
||||
"Traduis ce document en français" -> target_language = "French", instructions = ""
|
||||
"Translate to German, keep technical terms in English" -> target_language = "German",
|
||||
instructions = "Keep technical terms in English"
|
||||
"Translate this" -> ask the user: "Which language would you like the document
|
||||
translated into?"
|
||||
|
||||
Args:
|
||||
target_language (str | None): The language to translate the document into.
|
||||
If None, ask the user.
|
||||
instructions (str | None): Optional instructions for the translation style or preferences
|
||||
"""
|
||||
try:
|
||||
if not target_language:
|
||||
raise ModelCannotRetry(
|
||||
"The target language is not specified. "
|
||||
"You must ask the user which language they want the document translated into."
|
||||
)
|
||||
instructions_hint = (
|
||||
f"Follow these instructions: {instructions.strip()}" if instructions else ""
|
||||
)
|
||||
translation_agent = TranslationAgent()
|
||||
|
||||
# Get the last uploaded text document
|
||||
last_attachment = await (
|
||||
ctx.deps.conversation.attachments.filter(
|
||||
content_type__startswith="text/",
|
||||
)
|
||||
.order_by("-created_at")
|
||||
.afirst()
|
||||
)
|
||||
|
||||
if not last_attachment:
|
||||
raise ModelCannotRetry(
|
||||
"No text documents found in the conversation. "
|
||||
"You must explain this to the user and ask them to provide documents."
|
||||
)
|
||||
|
||||
doc_name, content = await read_document_content(last_attachment)
|
||||
|
||||
max_chars = settings.TRANSLATION_MAX_CHARS
|
||||
if len(content) > max_chars:
|
||||
raise ModelCannotRetry(
|
||||
f"The document is too large to translate ({len(content):,} characters, "
|
||||
f"limit is {max_chars:,}). "
|
||||
"You must explain this to the user, without providing numerical details. "
|
||||
"Suggest them to reduce the document size by summarizing it or "
|
||||
"by splitting it into smaller parts. "
|
||||
"Also offer them to summarize the document in the target language instead, "
|
||||
"which can be a good alternative to translation for large documents."
|
||||
)
|
||||
|
||||
logger.info(
|
||||
"[translate] translating '%s', %s chars, target_language='%s', instructions='%s'",
|
||||
doc_name,
|
||||
len(content),
|
||||
target_language,
|
||||
instructions_hint,
|
||||
)
|
||||
|
||||
# Translate the document directly
|
||||
translate_prompt = (
|
||||
f"You are an agent specializing in text translation. "
|
||||
f"Translate the following document to {target_language}. "
|
||||
f"Preserve all markdown formatting exactly as-is. "
|
||||
f"{instructions_hint}\n\n"
|
||||
f"'''\n{content}\n'''\n\n"
|
||||
f"Respond directly with the translated text only, no commentary."
|
||||
)
|
||||
|
||||
logger.debug("[translate] prompt for '%s'=> %s", doc_name, translate_prompt[:100] + "...")
|
||||
|
||||
try:
|
||||
resp = await translation_agent.run(translate_prompt, usage=ctx.usage)
|
||||
except Exception as exc:
|
||||
logger.warning("Error during translation of '%s': %s", doc_name, exc, exc_info=True)
|
||||
raise ModelRetry(f"An error occurred while translating document '{doc_name}'.") from exc
|
||||
|
||||
translated_text = (resp.output or "").strip()
|
||||
if not translated_text:
|
||||
raise ModelRetry(f"The translation of '{doc_name}' produced an empty result.")
|
||||
|
||||
logger.debug("[translate] final translation length: %s chars", len(translated_text))
|
||||
|
||||
return ToolReturn(
|
||||
return_value=translated_text,
|
||||
metadata={"sources": {doc_name}},
|
||||
)
|
||||
|
||||
except (ModelCannotRetry, ModelRetry):
|
||||
raise
|
||||
except Exception as exc:
|
||||
logger.exception("Unexpected error in document_translate: %s", exc)
|
||||
raise ModelCannotRetry(
|
||||
f"An unexpected error occurred during document translation: {type(exc).__name__}. "
|
||||
"You must explain this to the user and not try to answer based on your knowledge."
|
||||
) from exc
|
||||
@@ -4,9 +4,6 @@ import functools
|
||||
import logging
|
||||
from typing import Any, Callable
|
||||
|
||||
from django.core.files.storage import default_storage
|
||||
|
||||
from asgiref.sync import sync_to_async
|
||||
from pydantic_ai import ModelRetry, RunContext
|
||||
|
||||
from chat.tools.exceptions import ModelCannotRetry
|
||||
@@ -51,10 +48,3 @@ def last_model_retry_soft_fail(
|
||||
raise # Re-raise to allow retrying
|
||||
|
||||
return wrapper
|
||||
|
||||
|
||||
@sync_to_async
|
||||
def read_document_content(doc):
|
||||
"""Read document content asynchronously."""
|
||||
with default_storage.open(doc.key) as f:
|
||||
return doc.file_name, f.read().decode("utf-8")
|
||||
|
||||
@@ -743,11 +743,6 @@ class Base(BraveSettings, Configuration):
|
||||
environ_name="RAG_DOCUMENT_SEARCH_BACKEND",
|
||||
environ_prefix=None,
|
||||
)
|
||||
RAG_DOCUMENT_PARSER = values.Value(
|
||||
"chat.agent_rag.document_converter.parser.AlbertParser",
|
||||
environ_name="RAG_DOCUMENT_PARSER",
|
||||
environ_prefix=None,
|
||||
)
|
||||
SPECIFIC_RAG_DOCUMENT_SEARCH_TOOLS = values.DictValue(
|
||||
default={},
|
||||
environ_name="SPECIFIC_RAG_DOCUMENT_SEARCH_TOOLS",
|
||||
@@ -813,51 +808,6 @@ USER QUESTION:
|
||||
environ_prefix=None,
|
||||
)
|
||||
|
||||
# OCR settings for AdaptivePdfParser
|
||||
OCR_HRID = values.Value(
|
||||
default="etalab-plateform-mistral-medium-2508",
|
||||
environ_name="OCR_HRID",
|
||||
environ_prefix=None,
|
||||
)
|
||||
# Specific Mistral OCR model - Designates which Mistral vision model to use for OCR
|
||||
OCR_MODEL = values.Value(
|
||||
default="mistral-ocr-2512",
|
||||
environ_name="OCR_MODEL",
|
||||
environ_prefix=None,
|
||||
)
|
||||
OCR_TIMEOUT = values.PositiveIntegerValue(
|
||||
default=240,
|
||||
environ_name="OCR_TIMEOUT",
|
||||
environ_prefix=None,
|
||||
)
|
||||
OCR_MAX_RETRIES = values.PositiveIntegerValue(
|
||||
default=3,
|
||||
environ_name="OCR_MAX_RETRIES",
|
||||
environ_prefix=None,
|
||||
)
|
||||
|
||||
OCR_RETRY_DELAY = values.PositiveIntegerValue(
|
||||
default=5,
|
||||
environ_name="OCR_RETRY_DELAY",
|
||||
environ_prefix=None,
|
||||
)
|
||||
|
||||
OCR_BATCH_PAGES = values.PositiveIntegerValue(
|
||||
default=10,
|
||||
environ_name="OCR_BATCH_PAGES",
|
||||
environ_prefix=None,
|
||||
)
|
||||
MIN_AVG_CHARS_FOR_TEXT_EXTRACTION = values.PositiveIntegerValue(
|
||||
default=200,
|
||||
environ_name="MIN_AVG_CHARS_FOR_TEXT_EXTRACTION",
|
||||
environ_prefix=None,
|
||||
)
|
||||
MIN_TEXT_COVERAGE_FOR_TEXT_EXTRACTION = values.FloatValue(
|
||||
default=0.7,
|
||||
environ_name="MIN_TEXT_COVERAGE_FOR_TEXT_EXTRACTION",
|
||||
environ_prefix=None,
|
||||
)
|
||||
|
||||
# Summarization
|
||||
SUMMARIZATION_SYSTEM_PROMPT = values.Value(
|
||||
(
|
||||
@@ -883,13 +833,6 @@ USER QUESTION:
|
||||
environ_prefix=None,
|
||||
)
|
||||
|
||||
# Translation
|
||||
TRANSLATION_MAX_CHARS = values.PositiveIntegerValue(
|
||||
default=100_000, # ~100k characters, roughly half a 128k context window
|
||||
environ_name="TRANSLATION_MAX_CHARS",
|
||||
environ_prefix=None,
|
||||
)
|
||||
|
||||
# Tavily API
|
||||
TAVILY_API_KEY = values.Value(
|
||||
None, # Tavily API key is not set by default
|
||||
@@ -1171,17 +1114,6 @@ USER QUESTION:
|
||||
"OIDC_STORE_ACCESS_TOKEN and OIDC_STORE_REFRESH_TOKEN to be set."
|
||||
)
|
||||
|
||||
# OCR configuration validation
|
||||
# Note: we call load_llm_configuration directly because LLM_CONFIGURATIONS is a
|
||||
# @property returning a lazy object, which cannot be accessed via cls in a classmethod.
|
||||
if cls.RAG_DOCUMENT_PARSER == "chat.agent_rag.document_converter.parser.AdaptivePdfParser":
|
||||
llm_configs = load_llm_configuration(cls._llm_configuration_file_path)
|
||||
if cls.OCR_HRID not in llm_configs:
|
||||
raise ValueError(
|
||||
f"OCR_HRID '{cls.OCR_HRID}' not found in LLM_CONFIGURATIONS. "
|
||||
"Please add a matching provider entry or set OCR_HRID to an existing key."
|
||||
)
|
||||
|
||||
# Langfuse initialization
|
||||
if cls.LANGFUSE_ENABLED:
|
||||
if not cls.LANGFUSE_MEDIA_UPLOAD_ENABLED:
|
||||
|
||||
@@ -3,7 +3,7 @@ msgstr ""
|
||||
"Project-Id-Version: la-suite-conversations\n"
|
||||
"Report-Msgid-Bugs-To: \n"
|
||||
"POT-Creation-Date: 2025-10-20 21:48+0000\n"
|
||||
"PO-Revision-Date: 2026-02-09 13:05\n"
|
||||
"PO-Revision-Date: 2026-01-27 15:38\n"
|
||||
"Last-Translator: \n"
|
||||
"Language-Team: German\n"
|
||||
"Language: de_DE\n"
|
||||
|
||||
@@ -3,7 +3,7 @@ msgstr ""
|
||||
"Project-Id-Version: la-suite-conversations\n"
|
||||
"Report-Msgid-Bugs-To: \n"
|
||||
"POT-Creation-Date: 2025-10-20 21:48+0000\n"
|
||||
"PO-Revision-Date: 2026-02-09 13:05\n"
|
||||
"PO-Revision-Date: 2026-01-27 15:38\n"
|
||||
"Last-Translator: \n"
|
||||
"Language-Team: English\n"
|
||||
"Language: en_US\n"
|
||||
|
||||
@@ -3,7 +3,7 @@ msgstr ""
|
||||
"Project-Id-Version: la-suite-conversations\n"
|
||||
"Report-Msgid-Bugs-To: \n"
|
||||
"POT-Creation-Date: 2025-10-20 21:48+0000\n"
|
||||
"PO-Revision-Date: 2026-02-09 13:05\n"
|
||||
"PO-Revision-Date: 2026-01-27 15:38\n"
|
||||
"Last-Translator: \n"
|
||||
"Language-Team: French\n"
|
||||
"Language: fr_FR\n"
|
||||
|
||||
@@ -3,7 +3,7 @@ msgstr ""
|
||||
"Project-Id-Version: la-suite-conversations\n"
|
||||
"Report-Msgid-Bugs-To: \n"
|
||||
"POT-Creation-Date: 2025-10-20 21:48+0000\n"
|
||||
"PO-Revision-Date: 2026-02-09 13:05\n"
|
||||
"PO-Revision-Date: 2026-01-27 15:38\n"
|
||||
"Last-Translator: \n"
|
||||
"Language-Team: Dutch\n"
|
||||
"Language: nl_NL\n"
|
||||
|
||||
@@ -3,7 +3,7 @@ msgstr ""
|
||||
"Project-Id-Version: la-suite-conversations\n"
|
||||
"Report-Msgid-Bugs-To: \n"
|
||||
"POT-Creation-Date: 2025-10-20 21:48+0000\n"
|
||||
"PO-Revision-Date: 2026-02-09 13:05\n"
|
||||
"PO-Revision-Date: 2026-01-27 15:38\n"
|
||||
"Last-Translator: \n"
|
||||
"Language-Team: Russian\n"
|
||||
"Language: ru_RU\n"
|
||||
|
||||
@@ -3,7 +3,7 @@ msgstr ""
|
||||
"Project-Id-Version: la-suite-conversations\n"
|
||||
"Report-Msgid-Bugs-To: \n"
|
||||
"POT-Creation-Date: 2025-10-20 21:48+0000\n"
|
||||
"PO-Revision-Date: 2026-02-09 13:05\n"
|
||||
"PO-Revision-Date: 2026-01-27 15:38\n"
|
||||
"Last-Translator: \n"
|
||||
"Language-Team: Ukrainian\n"
|
||||
"Language: uk_UA\n"
|
||||
|
||||
@@ -7,7 +7,7 @@ build-backend = "setuptools.build_meta"
|
||||
|
||||
[project]
|
||||
name = "conversations"
|
||||
version = "0.0.13"
|
||||
version = "0.0.12"
|
||||
authors = [{ "name" = "DINUM", "email" = "dev@mail.numerique.gouv.fr" }]
|
||||
classifiers = [
|
||||
"Development Status :: 5 - Production/Stable",
|
||||
@@ -39,7 +39,7 @@ dependencies = [
|
||||
"django-redis==6.0.0",
|
||||
"django-storages[s3]==1.14.6",
|
||||
"django-timezone-field>=5.1",
|
||||
"django==5.2.11",
|
||||
"django==5.2.9",
|
||||
"djangorestframework==3.16.1",
|
||||
"drf_spectacular==0.29.0",
|
||||
"dockerflow==2024.4.2",
|
||||
@@ -56,7 +56,7 @@ dependencies = [
|
||||
"nested-multipart-parser==1.6.0",
|
||||
"posthog==7.0.0",
|
||||
"pydantic==2.12.4",
|
||||
"pydantic-ai-slim[openai,mistral,mcp,evals,logfire]==1.56.0",
|
||||
"pydantic-ai-slim[openai,mistral,mcp,evals,logfire]==1.17.0",
|
||||
"psycopg[binary]==3.2.12",
|
||||
"PyJWT==2.10.1",
|
||||
"python-magic==0.4.27",
|
||||
@@ -67,7 +67,6 @@ dependencies = [
|
||||
"trafilatura==2.0.0",
|
||||
"uvicorn==0.38.0",
|
||||
"whitenoise==6.11.0",
|
||||
"pypdf>=6.6.2",
|
||||
]
|
||||
|
||||
[project.urls]
|
||||
@@ -108,11 +107,6 @@ zip-safe = true
|
||||
[tool.distutils.bdist_wheel]
|
||||
universal = true
|
||||
|
||||
[tool.uv]
|
||||
override-dependencies = [
|
||||
"cryptography>=46.0.5", # CVE-2026-26007
|
||||
]
|
||||
|
||||
[tool.uv.build-backend]
|
||||
module-root = ""
|
||||
source-exclude = [
|
||||
@@ -152,8 +146,8 @@ select = [
|
||||
]
|
||||
|
||||
[tool.ruff.lint.isort]
|
||||
section-order = ["future", "standard-library", "django", "third-party", "conversations", "first-party", "local-folder"]
|
||||
sections = { conversations = ["core"], django = ["django"] }
|
||||
section-order = ["future","standard-library","django","third-party","conversations","first-party","local-folder"]
|
||||
sections = { conversations=["core"], django=["django"] }
|
||||
extra-standard-library = ["tomllib"]
|
||||
|
||||
[tool.ruff.lint.per-file-ignores]
|
||||
|
||||
Generated
+47
-86
@@ -7,9 +7,6 @@ resolution-markers = [
|
||||
"sys_platform != 'emscripten' and sys_platform != 'win32'",
|
||||
]
|
||||
|
||||
[manifest]
|
||||
overrides = [{ name = "cryptography", specifier = ">=46.0.5" }]
|
||||
|
||||
[[package]]
|
||||
name = "amqp"
|
||||
version = "5.3.1"
|
||||
@@ -394,7 +391,7 @@ wheels = [
|
||||
|
||||
[[package]]
|
||||
name = "conversations"
|
||||
version = "0.0.13"
|
||||
version = "0.0.12"
|
||||
source = { editable = "." }
|
||||
dependencies = [
|
||||
{ name = "beautifulsoup4" },
|
||||
@@ -431,7 +428,6 @@ dependencies = [
|
||||
{ name = "pydantic" },
|
||||
{ name = "pydantic-ai-slim", extra = ["evals", "logfire", "mcp", "mistral", "openai"] },
|
||||
{ name = "pyjwt" },
|
||||
{ name = "pypdf" },
|
||||
{ name = "python-magic" },
|
||||
{ name = "redis" },
|
||||
{ name = "requests" },
|
||||
@@ -474,7 +470,7 @@ requires-dist = [
|
||||
{ name = "brotli", specifier = "==1.2.0" },
|
||||
{ name = "deprecated" },
|
||||
{ name = "dirty-equals", marker = "extra == 'dev'", specifier = "==0.10.0" },
|
||||
{ name = "django", specifier = "==5.2.11" },
|
||||
{ name = "django", specifier = "==5.2.9" },
|
||||
{ name = "django-configurations", specifier = "==2.5.1" },
|
||||
{ name = "django-cors-headers", specifier = "==4.9.0" },
|
||||
{ name = "django-countries", specifier = "==8.1.0" },
|
||||
@@ -508,13 +504,12 @@ requires-dist = [
|
||||
{ name = "posthog", specifier = "==7.0.0" },
|
||||
{ name = "psycopg", extras = ["binary"], specifier = "==3.2.12" },
|
||||
{ name = "pydantic", specifier = "==2.12.4" },
|
||||
{ name = "pydantic-ai-slim", extras = ["openai", "mistral", "mcp", "evals", "logfire"], specifier = "==1.56.0" },
|
||||
{ name = "pydantic-ai-slim", extras = ["openai", "mistral", "mcp", "evals", "logfire"], specifier = "==1.17.0" },
|
||||
{ name = "pyfakefs", marker = "extra == 'dev'", specifier = "==5.10.2" },
|
||||
{ name = "pyjwt", specifier = "==2.10.1" },
|
||||
{ name = "pylint", marker = "extra == 'dev'", specifier = "==3.3.9" },
|
||||
{ name = "pylint-django", marker = "extra == 'dev'", specifier = "==2.6.1" },
|
||||
{ name = "pylint-pydantic", marker = "extra == 'dev'", specifier = "==0.4.1" },
|
||||
{ name = "pypdf", specifier = ">=6.6.2" },
|
||||
{ name = "pytest", marker = "extra == 'dev'", specifier = "==9.0.1" },
|
||||
{ name = "pytest-asyncio", marker = "extra == 'dev'", specifier = "==1.3.0" },
|
||||
{ name = "pytest-cov", marker = "extra == 'dev'", specifier = "==7.0.0" },
|
||||
@@ -587,41 +582,43 @@ wheels = [
|
||||
|
||||
[[package]]
|
||||
name = "cryptography"
|
||||
version = "46.0.5"
|
||||
version = "46.0.3"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "cffi", marker = "platform_python_implementation != 'PyPy'" },
|
||||
]
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/60/04/ee2a9e8542e4fa2773b81771ff8349ff19cdd56b7258a0cc442639052edb/cryptography-46.0.5.tar.gz", hash = "sha256:abace499247268e3757271b2f1e244b36b06f8515cf27c4d49468fc9eb16e93d", size = 750064, upload-time = "2026-02-10T19:18:38.255Z" }
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/9f/33/c00162f49c0e2fe8064a62cb92b93e50c74a72bc370ab92f86112b33ff62/cryptography-46.0.3.tar.gz", hash = "sha256:a8b17438104fed022ce745b362294d9ce35b4c2e45c1d958ad4a4b019285f4a1", size = 749258, upload-time = "2025-10-15T23:18:31.74Z" }
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/f7/81/b0bb27f2ba931a65409c6b8a8b358a7f03c0e46eceacddff55f7c84b1f3b/cryptography-46.0.5-cp311-abi3-macosx_10_9_universal2.whl", hash = "sha256:351695ada9ea9618b3500b490ad54c739860883df6c1f555e088eaf25b1bbaad", size = 7176289, upload-time = "2026-02-10T19:17:08.274Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/ff/9e/6b4397a3e3d15123de3b1806ef342522393d50736c13b20ec4c9ea6693a6/cryptography-46.0.5-cp311-abi3-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:c18ff11e86df2e28854939acde2d003f7984f721eba450b56a200ad90eeb0e6b", size = 4275637, upload-time = "2026-02-10T19:17:10.53Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/63/e7/471ab61099a3920b0c77852ea3f0ea611c9702f651600397ac567848b897/cryptography-46.0.5-cp311-abi3-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:4d7e3d356b8cd4ea5aff04f129d5f66ebdc7b6f8eae802b93739ed520c47c79b", size = 4424742, upload-time = "2026-02-10T19:17:12.388Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/37/53/a18500f270342d66bf7e4d9f091114e31e5ee9e7375a5aba2e85a91e0044/cryptography-46.0.5-cp311-abi3-manylinux_2_28_aarch64.whl", hash = "sha256:50bfb6925eff619c9c023b967d5b77a54e04256c4281b0e21336a130cd7fc263", size = 4277528, upload-time = "2026-02-10T19:17:13.853Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/22/29/c2e812ebc38c57b40e7c583895e73c8c5adb4d1e4a0cc4c5a4fdab2b1acc/cryptography-46.0.5-cp311-abi3-manylinux_2_28_ppc64le.whl", hash = "sha256:803812e111e75d1aa73690d2facc295eaefd4439be1023fefc4995eaea2af90d", size = 4947993, upload-time = "2026-02-10T19:17:15.618Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/6b/e7/237155ae19a9023de7e30ec64e5d99a9431a567407ac21170a046d22a5a3/cryptography-46.0.5-cp311-abi3-manylinux_2_28_x86_64.whl", hash = "sha256:3ee190460e2fbe447175cda91b88b84ae8322a104fc27766ad09428754a618ed", size = 4456855, upload-time = "2026-02-10T19:17:17.221Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/2d/87/fc628a7ad85b81206738abbd213b07702bcbdada1dd43f72236ef3cffbb5/cryptography-46.0.5-cp311-abi3-manylinux_2_31_armv7l.whl", hash = "sha256:f145bba11b878005c496e93e257c1e88f154d278d2638e6450d17e0f31e558d2", size = 3984635, upload-time = "2026-02-10T19:17:18.792Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/84/29/65b55622bde135aedf4565dc509d99b560ee4095e56989e815f8fd2aa910/cryptography-46.0.5-cp311-abi3-manylinux_2_34_aarch64.whl", hash = "sha256:e9251e3be159d1020c4030bd2e5f84d6a43fe54b6c19c12f51cde9542a2817b2", size = 4277038, upload-time = "2026-02-10T19:17:20.256Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/bc/36/45e76c68d7311432741faf1fbf7fac8a196a0a735ca21f504c75d37e2558/cryptography-46.0.5-cp311-abi3-manylinux_2_34_ppc64le.whl", hash = "sha256:47fb8a66058b80e509c47118ef8a75d14c455e81ac369050f20ba0d23e77fee0", size = 4912181, upload-time = "2026-02-10T19:17:21.825Z" },
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@@ -1,6 +1,6 @@
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|
||||
"name": "app-conversations",
|
||||
"version": "0.0.13",
|
||||
"version": "0.0.12",
|
||||
"private": true,
|
||||
"scripts": {
|
||||
"dev": "next dev",
|
||||
@@ -16,6 +16,7 @@
|
||||
"test:watch": "jest --watch"
|
||||
},
|
||||
"dependencies": {
|
||||
"@ag-media/react-pdf-table": "2.0.3",
|
||||
"@ai-sdk/react": "1.2.12",
|
||||
"@ai-sdk/ui-utils": "1.2.11",
|
||||
"@emoji-mart/data": "1.2.1",
|
||||
@@ -23,10 +24,10 @@
|
||||
"@fontsource/material-icons": "5.2.5",
|
||||
"@gouvfr-lasuite/cunningham-tokens": "^3.1.0",
|
||||
"@gouvfr-lasuite/integration": "1.0.3",
|
||||
"@gouvfr-lasuite/ui-kit": "0.18.7",
|
||||
"@gouvfr-lasuite/ui-kit": "0.18.4",
|
||||
"@openfun/cunningham-react": "4.0.0",
|
||||
"@react-pdf/renderer": "4.3.0",
|
||||
"@sentry/nextjs": "9.26.0",
|
||||
"@shikijs/rehype": "^3.21.0",
|
||||
"@tanstack/react-query": "5.80.5",
|
||||
"canvg": "4.0.3",
|
||||
"clsx": "2.1.1",
|
||||
@@ -36,7 +37,7 @@
|
||||
"i18next": "25.2.1",
|
||||
"i18next-browser-languagedetector": "8.1.0",
|
||||
"idb": "8.0.3",
|
||||
"lodash": "4.17.23",
|
||||
"lodash": "4.17.21",
|
||||
"lottie-react": "^2.4.1",
|
||||
"luxon": "3.6.1",
|
||||
"micromark-extension-llm-math": "3.1.1-20250610",
|
||||
@@ -48,10 +49,12 @@
|
||||
"react-i18next": "15.5.2",
|
||||
"react-intersection-observer": "9.16.0",
|
||||
"react-markdown": "10.1.0",
|
||||
"react-select": "5.10.1",
|
||||
"rehype-katex": "7.0.1",
|
||||
"rehype-pretty-code": "^0.14.1",
|
||||
"remark-gfm": "4.0.1",
|
||||
"remark-math": "6.0.0",
|
||||
"shiki": "^3.21.0",
|
||||
"shiki": "^3.13.0",
|
||||
"styled-components": "6.1.18",
|
||||
"use-debounce": "10.0.4",
|
||||
"zod": "^3.25.67",
|
||||
|
||||
File diff suppressed because one or more lines are too long
|
Before Width: | Height: | Size: 34 KiB |
@@ -1,5 +1,4 @@
|
||||
@import url('@gouvfr-lasuite/ui-kit/style');
|
||||
@import url('@gouvfr-lasuite/ui-kit/fonts/Marianne');
|
||||
@import url('./cunningham-tokens.css');
|
||||
|
||||
:root {
|
||||
|
||||
@@ -1,8 +1,8 @@
|
||||
:root {
|
||||
--c--globals--colors--logo-1-light: #377fdb;
|
||||
--c--globals--colors--logo-2-light: #377fdb;
|
||||
--c--globals--colors--logo-1-dark: #c1d6f2;
|
||||
--c--globals--colors--logo-2-dark: #c1d6f2;
|
||||
--c--globals--colors--logo-1-light: #4844ad;
|
||||
--c--globals--colors--logo-2-light: #4844ad;
|
||||
--c--globals--colors--logo-1-dark: #bec5f0;
|
||||
--c--globals--colors--logo-2-dark: #bec5f0;
|
||||
--c--globals--colors--brand-050: #eef1fa;
|
||||
--c--globals--colors--brand-100: #dde2f5;
|
||||
--c--globals--colors--brand-150: #ced3f1;
|
||||
@@ -332,8 +332,6 @@
|
||||
--c--globals--colors--white-900: #f8f8f9e5;
|
||||
--c--globals--colors--white-950: #f8f8f9f2;
|
||||
--c--globals--colors--white-975: #f8f8f9f9;
|
||||
--c--globals--colors--logo-1: #4844ad;
|
||||
--c--globals--colors--logo-2: #4844ad;
|
||||
--c--globals--transitions--ease-in: cubic-bezier(0.32, 0, 0.67, 0);
|
||||
--c--globals--transitions--ease-out: cubic-bezier(0.33, 1, 0.68, 1);
|
||||
--c--globals--transitions--ease-in-out: cubic-bezier(0.65, 0, 0.35, 1);
|
||||
@@ -895,10 +893,10 @@
|
||||
}
|
||||
|
||||
.cunningham-theme--dark {
|
||||
--c--globals--colors--logo-1-light: #377fdb;
|
||||
--c--globals--colors--logo-2-light: #377fdb;
|
||||
--c--globals--colors--logo-1-dark: #c1d6f2;
|
||||
--c--globals--colors--logo-2-dark: #c1d6f2;
|
||||
--c--globals--colors--logo-1-light: #4844ad;
|
||||
--c--globals--colors--logo-2-light: #4844ad;
|
||||
--c--globals--colors--logo-1-dark: #bec5f0;
|
||||
--c--globals--colors--logo-2-dark: #bec5f0;
|
||||
--c--globals--colors--brand-050: #eef1fa;
|
||||
--c--globals--colors--brand-100: #dde2f5;
|
||||
--c--globals--colors--brand-150: #ced3f1;
|
||||
@@ -1228,8 +1226,6 @@
|
||||
--c--globals--colors--white-900: #f8f8f9e5;
|
||||
--c--globals--colors--white-950: #f8f8f9f2;
|
||||
--c--globals--colors--white-975: #f8f8f9f9;
|
||||
--c--globals--colors--logo-1: #4844ad;
|
||||
--c--globals--colors--logo-2: #4844ad;
|
||||
--c--globals--transitions--ease-in: cubic-bezier(0.32, 0, 0.67, 0);
|
||||
--c--globals--transitions--ease-out: cubic-bezier(0.33, 1, 0.68, 1);
|
||||
--c--globals--transitions--ease-in-out: cubic-bezier(0.65, 0, 0.35, 1);
|
||||
@@ -2661,7 +2657,7 @@
|
||||
.cunningham-theme--dsfr-dark {
|
||||
--c--globals--components--la-gaufre: true;
|
||||
--c--globals--components--home-proconnect: true;
|
||||
--c--globals--components--logo--src: /assets/logo-gouv-darkmode.svg;
|
||||
--c--globals--components--logo--src: /assets/logo-gouv.svg;
|
||||
--c--globals--components--logo--widthHeader: 110px;
|
||||
--c--globals--components--logo--widthFooter: 220px;
|
||||
--c--globals--components--logo--alt: gouvernement logo;
|
||||
@@ -4858,14 +4854,6 @@
|
||||
color: var(--c--globals--colors--white-975);
|
||||
}
|
||||
|
||||
.clr-logo-1 {
|
||||
color: var(--c--globals--colors--logo-1);
|
||||
}
|
||||
|
||||
.clr-logo-2 {
|
||||
color: var(--c--globals--colors--logo-2);
|
||||
}
|
||||
|
||||
.bg-logo-1-light {
|
||||
background-color: var(--c--globals--colors--logo-1-light);
|
||||
}
|
||||
@@ -6198,14 +6186,6 @@
|
||||
background-color: var(--c--globals--colors--white-975);
|
||||
}
|
||||
|
||||
.bg-logo-1 {
|
||||
background-color: var(--c--globals--colors--logo-1);
|
||||
}
|
||||
|
||||
.bg-logo-2 {
|
||||
background-color: var(--c--globals--colors--logo-2);
|
||||
}
|
||||
|
||||
.bg-surface-primary {
|
||||
background-color: var(--c--contextuals--background--surface--primary);
|
||||
}
|
||||
|
||||
@@ -3,10 +3,10 @@ export const tokens = {
|
||||
default: {
|
||||
globals: {
|
||||
colors: {
|
||||
'logo-1-light': '#377FDB',
|
||||
'logo-2-light': '#377FDB',
|
||||
'logo-1-dark': '#C1D6F2',
|
||||
'logo-2-dark': '#C1D6F2',
|
||||
'logo-1-light': '#4844AD',
|
||||
'logo-2-light': '#4844AD',
|
||||
'logo-1-dark': '#BEC5F0',
|
||||
'logo-2-dark': '#BEC5F0',
|
||||
'brand-050': '#EEF1FA',
|
||||
'brand-100': '#DDE2F5',
|
||||
'brand-150': '#CED3F1',
|
||||
@@ -336,8 +336,6 @@ export const tokens = {
|
||||
'white-900': '#F8F8F9E5',
|
||||
'white-950': '#F8F8F9F2',
|
||||
'white-975': '#F8F8F9F9',
|
||||
'logo-1': '#4844AD',
|
||||
'logo-2': '#4844AD',
|
||||
},
|
||||
transitions: {
|
||||
'ease-in': 'cubic-bezier(0.32, 0, 0.67, 0)',
|
||||
@@ -549,8 +547,8 @@ export const tokens = {
|
||||
},
|
||||
},
|
||||
content: {
|
||||
logo1: '#377FDB',
|
||||
logo2: '#377FDB',
|
||||
logo1: '#4844AD',
|
||||
logo2: '#4844AD',
|
||||
semantic: {
|
||||
contextual: { primary: '#F8F8F9F2' },
|
||||
overlay: { primary: '#F8F8F9F2' },
|
||||
@@ -683,10 +681,10 @@ export const tokens = {
|
||||
dark: {
|
||||
globals: {
|
||||
colors: {
|
||||
'logo-1-light': '#377FDB',
|
||||
'logo-2-light': '#377FDB',
|
||||
'logo-1-dark': '#C1D6F2',
|
||||
'logo-2-dark': '#C1D6F2',
|
||||
'logo-1-light': '#4844AD',
|
||||
'logo-2-light': '#4844AD',
|
||||
'logo-1-dark': '#BEC5F0',
|
||||
'logo-2-dark': '#BEC5F0',
|
||||
'brand-050': '#EEF1FA',
|
||||
'brand-100': '#DDE2F5',
|
||||
'brand-150': '#CED3F1',
|
||||
@@ -1016,8 +1014,6 @@ export const tokens = {
|
||||
'white-900': '#F8F8F9E5',
|
||||
'white-950': '#F8F8F9F2',
|
||||
'white-975': '#F8F8F9F9',
|
||||
'logo-1': '#4844AD',
|
||||
'logo-2': '#4844AD',
|
||||
},
|
||||
transitions: {
|
||||
'ease-in': 'cubic-bezier(0.32, 0, 0.67, 0)',
|
||||
@@ -1229,8 +1225,8 @@ export const tokens = {
|
||||
},
|
||||
},
|
||||
content: {
|
||||
logo1: '#C1D6F2',
|
||||
logo2: '#C1D6F2',
|
||||
logo1: '#BEC5F0',
|
||||
logo2: '#BEC5F0',
|
||||
semantic: {
|
||||
contextual: { primary: '#1B1B23D9' },
|
||||
overlay: { primary: '#1B1B23D9' },
|
||||
@@ -1880,8 +1876,8 @@ export const tokens = {
|
||||
},
|
||||
},
|
||||
content: {
|
||||
logo1: '#377FDB',
|
||||
logo2: '#377FDB',
|
||||
logo1: '#4844AD',
|
||||
logo2: '#4844AD',
|
||||
semantic: {
|
||||
contextual: { primary: '#F8F8F9F2' },
|
||||
overlay: { primary: '#F8F8F9F2' },
|
||||
@@ -2017,7 +2013,7 @@ export const tokens = {
|
||||
'la-gaufre': true,
|
||||
'home-proconnect': true,
|
||||
logo: {
|
||||
src: '/assets/logo-gouv-darkmode.svg',
|
||||
src: '/assets/logo-gouv.svg',
|
||||
widthHeader: '110px',
|
||||
widthFooter: '220px',
|
||||
alt: 'Gouvernement Logo',
|
||||
@@ -2531,8 +2527,8 @@ export const tokens = {
|
||||
},
|
||||
},
|
||||
content: {
|
||||
logo1: '#C1D6F2',
|
||||
logo2: '#C1D6F2',
|
||||
logo1: '#BEC5F0',
|
||||
logo2: '#BEC5F0',
|
||||
semantic: {
|
||||
contextual: { primary: '#1B1B23D9' },
|
||||
overlay: { primary: '#1B1B23D9' },
|
||||
|
||||
@@ -2,9 +2,6 @@ import merge from 'lodash/merge';
|
||||
import { create } from 'zustand';
|
||||
import { persist } from 'zustand/middleware';
|
||||
|
||||
import { useChatPreferencesStore } from '@/features/chat/stores/useChatPreferencesStore';
|
||||
import { safeLocalStorage } from '@/utils/storages';
|
||||
|
||||
import { tokens } from './cunningham-tokens';
|
||||
|
||||
type Tokens = typeof tokens.themes.default &
|
||||
@@ -29,7 +26,6 @@ interface ThemeStore {
|
||||
setTheme: (theme: Theme) => void;
|
||||
spacingsTokens: Partial<SpacingsTokens>;
|
||||
theme: Theme;
|
||||
baseTheme: Theme; // 'default' or 'dsfr' (not persisted)
|
||||
themeTokens: Partial<Tokens['globals']>;
|
||||
isDarkMode: boolean;
|
||||
toggleDarkMode: () => void;
|
||||
@@ -53,15 +49,6 @@ const getComponentTokens = (
|
||||
const DEFAULT_THEME: Theme = 'default';
|
||||
const defaultTokens = getMergedTokens(DEFAULT_THEME);
|
||||
|
||||
// Helper to get isDarkMode from useChatPreferencesStore
|
||||
const getIsDarkModeFromPreferences = (): boolean => {
|
||||
try {
|
||||
return useChatPreferencesStore.getState().isDarkModePreference ?? false;
|
||||
} catch {
|
||||
return false;
|
||||
}
|
||||
};
|
||||
|
||||
const initialState: ThemeStore = {
|
||||
colorsTokens: defaultTokens.globals.colors,
|
||||
componentTokens: getComponentTokens(defaultTokens),
|
||||
@@ -71,9 +58,8 @@ const initialState: ThemeStore = {
|
||||
setTheme: () => {},
|
||||
spacingsTokens: defaultTokens.globals.spacings,
|
||||
theme: DEFAULT_THEME,
|
||||
baseTheme: DEFAULT_THEME,
|
||||
themeTokens: defaultTokens.globals,
|
||||
isDarkMode: getIsDarkModeFromPreferences(),
|
||||
isDarkMode: false,
|
||||
toggleDarkMode: () => {},
|
||||
};
|
||||
|
||||
@@ -82,51 +68,30 @@ export const useCunninghamTheme = create<ThemeStore>()(
|
||||
(set) => ({
|
||||
...initialState,
|
||||
setTheme: (theme: Theme) => {
|
||||
// Extract base theme (default or dsfr)
|
||||
const baseTheme: Theme =
|
||||
theme === 'dark' || theme === 'dsfr-dark'
|
||||
? theme === 'dark'
|
||||
? 'default'
|
||||
: 'dsfr'
|
||||
: theme;
|
||||
|
||||
const isDarkMode =
|
||||
getIsDarkModeFromPreferences() ??
|
||||
(theme === 'dark' || theme === 'dsfr-dark');
|
||||
|
||||
// Apply dark mode based on stored preference or theme
|
||||
const finalTheme: Theme = isDarkMode
|
||||
? baseTheme === 'dsfr'
|
||||
? 'dsfr-dark'
|
||||
: 'dark'
|
||||
: baseTheme;
|
||||
|
||||
const newTokens = getMergedTokens(finalTheme);
|
||||
const newTokens = getMergedTokens(theme);
|
||||
|
||||
set({
|
||||
colorsTokens: newTokens.globals.colors,
|
||||
componentTokens: getComponentTokens(newTokens),
|
||||
contextualTokens: newTokens.contextuals,
|
||||
currentTokens: tokens.themes[finalTheme] as Partial<Tokens>,
|
||||
currentTokens: tokens.themes[theme] as Partial<Tokens>,
|
||||
fontSizesTokens: newTokens.globals.font.sizes,
|
||||
spacingsTokens: newTokens.globals.spacings,
|
||||
theme: finalTheme,
|
||||
baseTheme,
|
||||
theme,
|
||||
themeTokens: newTokens.globals,
|
||||
isDarkMode,
|
||||
isDarkMode: theme === 'dark' || theme === 'dsfr-dark',
|
||||
});
|
||||
},
|
||||
toggleDarkMode: () => {
|
||||
useChatPreferencesStore.getState().toggleDarkModePreferences();
|
||||
|
||||
set((state) => {
|
||||
const newIsDarkMode = getIsDarkModeFromPreferences();
|
||||
const newTheme: Theme = newIsDarkMode
|
||||
? state.baseTheme === 'dsfr'
|
||||
? 'dsfr-dark'
|
||||
: 'dark'
|
||||
: state.baseTheme;
|
||||
|
||||
const newTheme =
|
||||
state.theme === 'default'
|
||||
? 'dark'
|
||||
: state.theme === 'dark'
|
||||
? 'default'
|
||||
: state.theme === 'dsfr'
|
||||
? 'dsfr-dark'
|
||||
: 'dsfr';
|
||||
const newTokens = getMergedTokens(newTheme);
|
||||
|
||||
return {
|
||||
@@ -137,27 +102,15 @@ export const useCunninghamTheme = create<ThemeStore>()(
|
||||
fontSizesTokens: newTokens.globals.font.sizes,
|
||||
spacingsTokens: newTokens.globals.spacings,
|
||||
theme: newTheme,
|
||||
baseTheme: state.baseTheme,
|
||||
themeTokens: newTokens.globals,
|
||||
isDarkMode: newIsDarkMode,
|
||||
isDarkMode: newTheme === 'dark' || newTheme === 'dsfr-dark',
|
||||
};
|
||||
});
|
||||
},
|
||||
}),
|
||||
{
|
||||
name: 'cunningham-theme',
|
||||
// eslint-disable-next-line @typescript-eslint/no-explicit-any, @typescript-eslint/no-unsafe-assignment
|
||||
storage: safeLocalStorage as any,
|
||||
partialize: (state) => ({ isDarkMode: state.isDarkMode }),
|
||||
onRehydrateStorage: () => (state, error) => {
|
||||
if (error) {
|
||||
console.error('[useCunninghamTheme] Rehydration error:', error);
|
||||
return;
|
||||
}
|
||||
if (state) {
|
||||
state.isDarkMode = getIsDarkModeFromPreferences();
|
||||
}
|
||||
},
|
||||
},
|
||||
),
|
||||
);
|
||||
|
||||
@@ -1,13 +1,18 @@
|
||||
import { Message, SourceUIPart } from '@ai-sdk/ui-utils';
|
||||
import { Message, SourceUIPart, ToolInvocationUIPart } from '@ai-sdk/ui-utils';
|
||||
import { Modal, ModalSize } from '@openfun/cunningham-react';
|
||||
import 'katex/dist/katex.min.css'; // `rehype-katex` does not import the CSS for you
|
||||
import { useRouter } from 'next/router';
|
||||
import { useCallback, useEffect, useMemo, useRef, useState } from 'react';
|
||||
import { useCallback, useEffect, useRef, useState } from 'react';
|
||||
import type { ChangeEvent, FormEvent } from 'react';
|
||||
import { useTranslation } from 'react-i18next';
|
||||
import { MarkdownHooks } from 'react-markdown';
|
||||
import rehypeKatex from 'rehype-katex';
|
||||
import rehypePrettyCode from 'rehype-pretty-code';
|
||||
import remarkGfm from 'remark-gfm';
|
||||
import remarkMath from 'remark-math';
|
||||
|
||||
import { APIError, errorCauses, fetchAPI } from '@/api';
|
||||
import { Box, Loader, Text } from '@/components';
|
||||
import { Box, Icon, Loader, Text } from '@/components';
|
||||
import { useUploadFile } from '@/features/attachments/hooks/useUploadFile';
|
||||
import { useChat } from '@/features/chat/api/useChat';
|
||||
import { getConversation } from '@/features/chat/api/useConversation';
|
||||
@@ -16,9 +21,13 @@ import {
|
||||
LLMModel,
|
||||
useLLMConfiguration,
|
||||
} from '@/features/chat/api/useLLMConfiguration';
|
||||
import { AttachmentList } from '@/features/chat/components/AttachmentList';
|
||||
import { ChatError } from '@/features/chat/components/ChatError';
|
||||
import { CodeBlock } from '@/features/chat/components/CodeBlock';
|
||||
import { FeedbackButtons } from '@/features/chat/components/FeedbackButtons';
|
||||
import { InputChat } from '@/features/chat/components/InputChat';
|
||||
import { MessageItem } from '@/features/chat/components/MessageItem';
|
||||
import { SourceItemList } from '@/features/chat/components/SourceItemList';
|
||||
import { ToolInvocationItem } from '@/features/chat/components/ToolInvocationItem';
|
||||
import { useClipboard } from '@/hook';
|
||||
import { useResponsiveStore } from '@/stores';
|
||||
|
||||
@@ -280,21 +289,21 @@ export const Chat = ({
|
||||
// eslint-disable-next-line react-hooks/exhaustive-deps
|
||||
}, [messages]);
|
||||
|
||||
const openSources = useCallback((messageId: string) => {
|
||||
// Source-parts guard is handled at the call site (MessageItem only shows the button when sourceParts.length > 0),
|
||||
// so we just toggle it here.
|
||||
setIsSourceOpen((prev) => (prev === messageId ? null : messageId));
|
||||
}, []);
|
||||
|
||||
// Memoize the last assistant message index to avoid recalculating in render
|
||||
const lastAssistantMessageIndex = useMemo(() => {
|
||||
return messages.findLastIndex((msg) => msg.role === 'assistant');
|
||||
}, [messages]);
|
||||
|
||||
// Memoize whether this is the first conversation (2 or fewer messages)
|
||||
const isFirstConversationMessage = useMemo(() => {
|
||||
return messages.length <= 2;
|
||||
}, [messages.length]);
|
||||
const openSources = (messageId: string) => {
|
||||
if (isSourceOpen === messageId) {
|
||||
setIsSourceOpen(null);
|
||||
return;
|
||||
}
|
||||
const message = messages.find((msg) => msg.id === messageId);
|
||||
if (message?.parts) {
|
||||
const sourceParts = message.parts.filter(
|
||||
(part): part is SourceUIPart => part.type === 'source',
|
||||
);
|
||||
if (sourceParts.length > 0) {
|
||||
setIsSourceOpen(messageId);
|
||||
}
|
||||
}
|
||||
};
|
||||
|
||||
// Calculer la hauteur pour le message de streaming
|
||||
const calculateStreamingHeight = useCallback(() => {
|
||||
@@ -633,26 +642,317 @@ export const Chat = ({
|
||||
>
|
||||
{messages.length > 0 && (
|
||||
<Box>
|
||||
{messages.map((message, index) => (
|
||||
<MessageItem
|
||||
key={message.id}
|
||||
message={message}
|
||||
isLastMessage={index === messages.length - 1}
|
||||
isLastAssistantMessage={
|
||||
message.role === 'assistant' &&
|
||||
index === lastAssistantMessageIndex
|
||||
}
|
||||
isFirstConversationMessage={isFirstConversationMessage}
|
||||
streamingMessageHeight={streamingMessageHeight}
|
||||
status={status}
|
||||
conversationId={conversationId}
|
||||
isSourceOpen={isSourceOpen}
|
||||
isMobile={isMobile}
|
||||
onCopyToClipboard={copyToClipboard}
|
||||
onOpenSources={openSources}
|
||||
getMetadata={getMetadata}
|
||||
/>
|
||||
))}
|
||||
{messages.map((message, index) => {
|
||||
const isLastMessage = index === messages.length - 1;
|
||||
const isLastAssistantMessageInConversation =
|
||||
message.role === 'assistant' &&
|
||||
index ===
|
||||
messages.findLastIndex((msg) => msg.role === 'assistant');
|
||||
const isFirstConversationMessage = messages.length <= 2;
|
||||
const shouldApplyStreamingHeight =
|
||||
isLastAssistantMessageInConversation &&
|
||||
isLastMessage &&
|
||||
streamingMessageHeight &&
|
||||
!isFirstConversationMessage;
|
||||
const isCurrentlyStreaming =
|
||||
isLastAssistantMessageInConversation &&
|
||||
(status === 'streaming' || status === 'submitted');
|
||||
|
||||
return (
|
||||
<Box
|
||||
key={message.id}
|
||||
data-message-id={message.id}
|
||||
$css={`
|
||||
display: flex;
|
||||
width: 100%;
|
||||
margin: auto;
|
||||
margin-bottom: ${isLastAssistantMessageInConversation ? '30px' : '0px'};
|
||||
color: var(--c--theme--colors--greyscale-850);
|
||||
padding-left: 12px;
|
||||
padding-right: 12px;
|
||||
max-width: 750px;
|
||||
text-align: left;
|
||||
overflow-wrap: anywhere;
|
||||
flex-direction: ${message.role === 'user' ? 'row-reverse' : 'row'};
|
||||
`}
|
||||
>
|
||||
<Box
|
||||
$display="block"
|
||||
$width={`${message.role === 'user' ? 'auto' : '100%'}`}
|
||||
>
|
||||
{message.experimental_attachments &&
|
||||
message.experimental_attachments.length > 0 && (
|
||||
<Box>
|
||||
<AttachmentList
|
||||
attachments={message.experimental_attachments}
|
||||
isReadOnly={true}
|
||||
/>
|
||||
</Box>
|
||||
)}
|
||||
<Box
|
||||
className={`chatMessage ${message.role === 'user' ? 'chatMessage--user' : 'chatMessage--assistant'}`}
|
||||
style={
|
||||
shouldApplyStreamingHeight
|
||||
? { minHeight: `${streamingMessageHeight}px` }
|
||||
: undefined
|
||||
}
|
||||
>
|
||||
{/* Message content */}
|
||||
{message.content && (
|
||||
<Box
|
||||
className="mainContent-chat"
|
||||
data-testid={
|
||||
message.role === 'assistant'
|
||||
? 'assistant-message-content'
|
||||
: undefined
|
||||
}
|
||||
$padding={{ all: 'xxs' }}
|
||||
>
|
||||
<p className="sr-only">
|
||||
{message.role === 'user'
|
||||
? t('You said: ')
|
||||
: t('Assistant IA replied: ')}
|
||||
</p>
|
||||
{message.role === 'user' ? (
|
||||
<Text
|
||||
as="p"
|
||||
$css="white-space: pre-wrap; display: block;"
|
||||
$theme="greyscale"
|
||||
$variation="850"
|
||||
>
|
||||
{message.content}
|
||||
</Text>
|
||||
) : (
|
||||
<MarkdownHooks
|
||||
remarkPlugins={[remarkGfm, remarkMath]}
|
||||
rehypePlugins={[
|
||||
[
|
||||
rehypePrettyCode,
|
||||
{
|
||||
theme: 'github-dark-dimmed',
|
||||
},
|
||||
],
|
||||
rehypeKatex,
|
||||
]}
|
||||
components={{
|
||||
// Custom components for Markdown rendering
|
||||
// eslint-disable-next-line @typescript-eslint/no-unused-vars
|
||||
p: ({ node, ...props }) => (
|
||||
<Text
|
||||
as="p"
|
||||
$css="display: block"
|
||||
$theme="greyscale"
|
||||
$variation="850"
|
||||
{...props}
|
||||
/>
|
||||
),
|
||||
a: ({ children, ...props }) => (
|
||||
<a target="_blank" {...props}>
|
||||
{children}
|
||||
</a>
|
||||
),
|
||||
// eslint-disable-next-line @typescript-eslint/no-unused-vars
|
||||
pre: ({ node, children, ...props }) => (
|
||||
<CodeBlock {...props}>{children}</CodeBlock>
|
||||
),
|
||||
}}
|
||||
>
|
||||
{message.content}
|
||||
</MarkdownHooks>
|
||||
)}
|
||||
</Box>
|
||||
)}
|
||||
|
||||
<Box $direction="column" $gap="2">
|
||||
{isCurrentlyStreaming &&
|
||||
isLastAssistantMessageInConversation &&
|
||||
status === 'streaming' &&
|
||||
message.parts?.some(
|
||||
(part) =>
|
||||
part.type === 'tool-invocation' &&
|
||||
part.toolInvocation.toolName !==
|
||||
'document_parsing',
|
||||
) && (
|
||||
<Box
|
||||
$direction="row"
|
||||
$align="center"
|
||||
$gap="6px"
|
||||
$width="100%"
|
||||
$maxWidth="750px"
|
||||
$margin={{
|
||||
all: 'auto',
|
||||
top: 'base',
|
||||
bottom: 'md',
|
||||
}}
|
||||
>
|
||||
<Loader />
|
||||
<Text $variation="600" $size="md">
|
||||
{(() => {
|
||||
const toolInvocation = message.parts?.find(
|
||||
(part) =>
|
||||
part.type === 'tool-invocation' &&
|
||||
part.toolInvocation.toolName !==
|
||||
'document_parsing',
|
||||
);
|
||||
if (
|
||||
toolInvocation?.type ===
|
||||
'tool-invocation' &&
|
||||
toolInvocation.toolInvocation.toolName ===
|
||||
'summarize'
|
||||
) {
|
||||
return t('Summarizing...');
|
||||
}
|
||||
return t('Search...');
|
||||
})()}
|
||||
</Text>
|
||||
</Box>
|
||||
)}
|
||||
{message.parts
|
||||
?.filter((part) => part.type === 'tool-invocation')
|
||||
.map(
|
||||
(part: ToolInvocationUIPart, partIndex: number) =>
|
||||
part.type === 'tool-invocation' &&
|
||||
isCurrentlyStreaming &&
|
||||
isLastAssistantMessageInConversation ? (
|
||||
<ToolInvocationItem
|
||||
key={`tool-invocation-${partIndex}`}
|
||||
toolInvocation={part.toolInvocation}
|
||||
status={status}
|
||||
hideSearchLoader={true}
|
||||
/>
|
||||
) : null,
|
||||
)}
|
||||
</Box>
|
||||
{message.role === 'assistant' &&
|
||||
!(
|
||||
isLastAssistantMessageInConversation &&
|
||||
status === 'streaming'
|
||||
) && (
|
||||
<Box
|
||||
$css="font-size: 12px;"
|
||||
$direction="row"
|
||||
$align="center"
|
||||
className="clr-content-semantic-neutral-secondary"
|
||||
$justify="space-between"
|
||||
$gap="6px"
|
||||
$margin={{ top: 'base' }}
|
||||
>
|
||||
<Box $direction="row" $gap="4px">
|
||||
<Box
|
||||
$theme="neutral"
|
||||
$variation="secondary"
|
||||
$direction="row"
|
||||
$align="center"
|
||||
$gap="4px"
|
||||
className="c__button c__button--brand c__button--brand--tertiary c__button--nano clr-content-semantic-neutral-secondary"
|
||||
onClick={() => copyToClipboard(message.content)}
|
||||
onKeyDown={(e) => {
|
||||
if (e.key === 'Enter' || e.key === ' ') {
|
||||
e.preventDefault();
|
||||
copyToClipboard(message.content);
|
||||
}
|
||||
}}
|
||||
role="button"
|
||||
tabIndex={0}
|
||||
>
|
||||
<Icon
|
||||
iconName="content_copy"
|
||||
$variation="550"
|
||||
$size="16px"
|
||||
/>
|
||||
{!isMobile && (
|
||||
<Text $theme="neutral" $variation="secondary">
|
||||
{t('Copy')}
|
||||
</Text>
|
||||
)}
|
||||
</Box>
|
||||
{message.parts?.some(
|
||||
(part) => part.type === 'source',
|
||||
) &&
|
||||
(() => {
|
||||
const sourceCount =
|
||||
message.parts?.filter(
|
||||
(part) => part.type === 'source',
|
||||
).length || 0;
|
||||
return (
|
||||
<Box
|
||||
$direction="row"
|
||||
$align="center"
|
||||
$gap="4px"
|
||||
className={`c__button c__button--brand c__button--brand--tertiary c__button--nano ${isSourceOpen === message.id ? 'action-chat-button--open' : ''}`}
|
||||
onClick={() => openSources(message.id)}
|
||||
onKeyDown={(e) => {
|
||||
if (
|
||||
e.key === 'Enter' ||
|
||||
e.key === ' '
|
||||
) {
|
||||
e.preventDefault();
|
||||
openSources(message.id);
|
||||
}
|
||||
}}
|
||||
role="button"
|
||||
tabIndex={0}
|
||||
>
|
||||
<Icon
|
||||
iconName="book"
|
||||
$theme="greyscale"
|
||||
$variation="550"
|
||||
$size="16px"
|
||||
className="action-chat-button-icon"
|
||||
/>
|
||||
<Text
|
||||
$theme="greyscale"
|
||||
$variation="550"
|
||||
$weight="500"
|
||||
$size="12px"
|
||||
>
|
||||
{t('Show')} {sourceCount}{' '}
|
||||
{sourceCount !== 1
|
||||
? t('sources')
|
||||
: t('source')}
|
||||
</Text>
|
||||
</Box>
|
||||
);
|
||||
})()}
|
||||
</Box>
|
||||
<Box $direction="row" $gap="4px">
|
||||
{/* We should display the button, but disabled if no trace linked */}
|
||||
{conversationId &&
|
||||
message.id &&
|
||||
message.id.startsWith('trace-') && (
|
||||
<FeedbackButtons
|
||||
conversationId={conversationId}
|
||||
messageId={message.id}
|
||||
/>
|
||||
)}
|
||||
</Box>
|
||||
</Box>
|
||||
)}
|
||||
{message.parts &&
|
||||
isSourceOpen === message.id &&
|
||||
(() => {
|
||||
const sourceParts = message.parts.filter(
|
||||
(part): part is SourceUIPart =>
|
||||
part.type === 'source',
|
||||
);
|
||||
return (
|
||||
<Box
|
||||
$css={`
|
||||
animation: fade-in 0.2s ease-out;
|
||||
`}
|
||||
>
|
||||
<SourceItemList
|
||||
parts={sourceParts}
|
||||
getMetadata={getMetadata}
|
||||
/>
|
||||
</Box>
|
||||
);
|
||||
})()}
|
||||
</Box>
|
||||
</Box>
|
||||
</Box>
|
||||
);
|
||||
})}
|
||||
</Box>
|
||||
)}
|
||||
{(status !== 'ready' && status !== 'streaming' && status !== 'error') ||
|
||||
|
||||
@@ -71,12 +71,10 @@ export const CodeBlock = ({ children, ...props }: CodeBlockProps) => {
|
||||
|
||||
return (
|
||||
<>
|
||||
<figure data-rehype-pretty-code-figure="">
|
||||
<CopyCodeButton onCopy={handleCopy} />
|
||||
<Box ref={preRef} $position="relative" as="pre" {...props}>
|
||||
{children}
|
||||
</Box>
|
||||
</figure>
|
||||
<CopyCodeButton onCopy={handleCopy} />
|
||||
<Box ref={preRef} $position="relative" as="pre" {...props}>
|
||||
{children}
|
||||
</Box>
|
||||
</>
|
||||
);
|
||||
};
|
||||
|
||||
@@ -213,56 +213,39 @@ export const InputChat = ({
|
||||
}
|
||||
}, [status, input]);
|
||||
|
||||
const validateAndAddFiles = useCallback(
|
||||
(filesToAdd: File[]) => {
|
||||
const acceptedFiles: File[] = [];
|
||||
const rejectedFiles: File[] = [];
|
||||
const handleFilesAccepted = useCallback(
|
||||
(acceptedFiles: File[]) => {
|
||||
setFiles((prev) => {
|
||||
const dt = new DataTransfer();
|
||||
|
||||
filesToAdd.forEach((file) => {
|
||||
if (isFileAccepted(file)) {
|
||||
acceptedFiles.push(file);
|
||||
} else {
|
||||
rejectedFiles.push(file);
|
||||
// Keep existing files
|
||||
if (prev) {
|
||||
Array.from(prev).forEach((f) => dt.items.add(f));
|
||||
}
|
||||
});
|
||||
|
||||
if (rejectedFiles.length > 0) {
|
||||
showToastError();
|
||||
}
|
||||
|
||||
if (acceptedFiles.length > 0) {
|
||||
setFiles((prev) => {
|
||||
const dt = new DataTransfer();
|
||||
|
||||
// Keep existing files
|
||||
if (prev) {
|
||||
Array.from(prev).forEach((f) => dt.items.add(f));
|
||||
// Add new files (avoiding duplicates)
|
||||
acceptedFiles.forEach((f) => {
|
||||
const isDuplicate = Array.from(prev || []).some(
|
||||
(pf) =>
|
||||
pf.name === f.name &&
|
||||
pf.size === f.size &&
|
||||
pf.lastModified === f.lastModified,
|
||||
);
|
||||
if (!isDuplicate) {
|
||||
dt.items.add(f);
|
||||
}
|
||||
|
||||
// Add new files (avoiding duplicates)
|
||||
acceptedFiles.forEach((f) => {
|
||||
const isDuplicate = Array.from(prev || []).some(
|
||||
(pf) =>
|
||||
pf.name === f.name &&
|
||||
pf.size === f.size &&
|
||||
pf.lastModified === f.lastModified,
|
||||
);
|
||||
if (!isDuplicate) {
|
||||
dt.items.add(f);
|
||||
}
|
||||
});
|
||||
|
||||
return dt.files;
|
||||
});
|
||||
}
|
||||
|
||||
return dt.files;
|
||||
});
|
||||
},
|
||||
[isFileAccepted, showToastError, setFiles],
|
||||
[setFiles],
|
||||
);
|
||||
|
||||
const { isDragActive } = useFileDragDrop({
|
||||
enabled: fileUploadEnabled,
|
||||
isFileAccepted,
|
||||
onFilesAccepted: validateAndAddFiles,
|
||||
onFilesAccepted: handleFilesAccepted,
|
||||
onFilesRejected: () => showToastError(),
|
||||
});
|
||||
|
||||
@@ -310,41 +293,6 @@ export const InputChat = ({
|
||||
[],
|
||||
);
|
||||
|
||||
const handlePaste = useCallback(
|
||||
(e: React.ClipboardEvent<HTMLTextAreaElement>) => {
|
||||
if (!fileUploadEnabled) {
|
||||
return;
|
||||
}
|
||||
|
||||
const clipboardData = e.clipboardData;
|
||||
if (!clipboardData) {
|
||||
return;
|
||||
}
|
||||
|
||||
// Due to browser limitations, only one file can be pasted at a time
|
||||
// Check files first (for files from file system)
|
||||
let file: File | null = null;
|
||||
|
||||
if (clipboardData.files && clipboardData.files.length > 0) {
|
||||
file = clipboardData.files[0];
|
||||
} else if (clipboardData.items) {
|
||||
for (let i = 0; i < clipboardData.items.length; i++) {
|
||||
const item = clipboardData.items[i];
|
||||
if (item.kind === 'file') {
|
||||
file = item.getAsFile();
|
||||
break;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
if (file) {
|
||||
e.preventDefault();
|
||||
validateAndAddFiles([file]);
|
||||
}
|
||||
},
|
||||
[fileUploadEnabled, validateAndAddFiles],
|
||||
);
|
||||
|
||||
const handleAttachClick = useCallback(() => {
|
||||
fileInputRef.current?.click();
|
||||
}, []);
|
||||
@@ -361,10 +309,46 @@ export const InputChat = ({
|
||||
return;
|
||||
}
|
||||
|
||||
validateAndAddFiles(Array.from(fileList));
|
||||
const acceptedFiles: File[] = [];
|
||||
const rejectedFiles: string[] = [];
|
||||
|
||||
Array.from(fileList).forEach((file) => {
|
||||
if (isFileAccepted(file)) {
|
||||
acceptedFiles.push(file);
|
||||
} else {
|
||||
rejectedFiles.push(file.name);
|
||||
}
|
||||
});
|
||||
|
||||
if (rejectedFiles.length > 0) {
|
||||
showToastError();
|
||||
}
|
||||
|
||||
if (acceptedFiles.length > 0) {
|
||||
setFiles((prev) => {
|
||||
const dt = new DataTransfer();
|
||||
if (prev) {
|
||||
Array.from(prev).forEach((f) => dt.items.add(f));
|
||||
}
|
||||
acceptedFiles.forEach((f) => {
|
||||
if (
|
||||
!Array.from(prev || []).some(
|
||||
(pf) =>
|
||||
pf.name === f.name &&
|
||||
pf.size === f.size &&
|
||||
pf.lastModified === f.lastModified,
|
||||
)
|
||||
) {
|
||||
dt.items.add(f);
|
||||
}
|
||||
});
|
||||
return dt.files;
|
||||
});
|
||||
}
|
||||
|
||||
e.target.value = '';
|
||||
},
|
||||
[validateAndAddFiles],
|
||||
[isFileAccepted, showToastError, setFiles],
|
||||
);
|
||||
|
||||
const handleAttachmentRemove = useCallback(
|
||||
@@ -459,7 +443,6 @@ export const InputChat = ({
|
||||
name="inputchat-textarea"
|
||||
onChange={handleTextareaChange}
|
||||
onKeyDown={handleTextareaKeyDown}
|
||||
onPaste={handlePaste}
|
||||
disabled={isInputDisabled}
|
||||
rows={1}
|
||||
style={textareaStyle}
|
||||
|
||||
@@ -1,89 +0,0 @@
|
||||
// Memoized components for a single completed markdown blocks - only re-renders when content changes
|
||||
import rehypeShikiFromHighlighter from '@shikijs/rehype/core';
|
||||
import React, { use } from 'react';
|
||||
import { Components, MarkdownHooks } from 'react-markdown';
|
||||
import rehypeKatex from 'rehype-katex';
|
||||
import remarkGfm from 'remark-gfm';
|
||||
import remarkMath from 'remark-math';
|
||||
|
||||
import { Text } from '@/components';
|
||||
import { CodeBlock } from '@/features/chat/components/CodeBlock';
|
||||
|
||||
// Memoized markdown plugins - created once at module level
|
||||
// eslint-disable-next-line @typescript-eslint/no-explicit-any
|
||||
const REMARK_PLUGINS: any[] = [remarkGfm, remarkMath];
|
||||
// // eslint-disable-next-line @typescript-eslint/no-explicit-any
|
||||
|
||||
import { getHighlighter } from '../utils/shiki';
|
||||
|
||||
const highlighterPromise = getHighlighter();
|
||||
|
||||
// eslint-disable-next-line @typescript-eslint/no-explicit-any
|
||||
const rehypePluginsPromise: Promise<any[]> = highlighterPromise.then(
|
||||
(highlighter) => [
|
||||
rehypeKatex,
|
||||
[
|
||||
rehypeShikiFromHighlighter,
|
||||
highlighter,
|
||||
{
|
||||
theme: 'github-dark-dimmed',
|
||||
fallbackLanguage: 'plaintext',
|
||||
},
|
||||
],
|
||||
],
|
||||
);
|
||||
|
||||
// Memoized markdown components - created once at module level
|
||||
const MARKDOWN_COMPONENTS: Components = {
|
||||
// eslint-disable-next-line @typescript-eslint/no-unused-vars
|
||||
p: ({ node, ...props }) => (
|
||||
<Text
|
||||
as="p"
|
||||
$css="display: block"
|
||||
$theme="greyscale"
|
||||
$variation="850"
|
||||
{...props}
|
||||
/>
|
||||
),
|
||||
a: ({ children, ...props }) => (
|
||||
<a target="_blank" {...props}>
|
||||
{children}
|
||||
</a>
|
||||
),
|
||||
|
||||
pre: ({
|
||||
// eslint-disable-next-line @typescript-eslint/no-unused-vars
|
||||
node,
|
||||
children,
|
||||
...props
|
||||
}) => <CodeBlock {...props}>{children}</CodeBlock>,
|
||||
};
|
||||
|
||||
export const CompletedMarkdownBlock = React.memo(
|
||||
({ content }: { content: string }) => {
|
||||
const rehypePlugins = use(rehypePluginsPromise);
|
||||
return (
|
||||
<MarkdownHooks
|
||||
remarkPlugins={REMARK_PLUGINS}
|
||||
rehypePlugins={rehypePlugins}
|
||||
components={MARKDOWN_COMPONENTS}
|
||||
>
|
||||
{content}
|
||||
</MarkdownHooks>
|
||||
);
|
||||
},
|
||||
(prev, next) => prev.content === next.content,
|
||||
);
|
||||
|
||||
CompletedMarkdownBlock.displayName = 'CompletedMarkdownBlock';
|
||||
|
||||
export const RawTextBlock = ({ content }: { content: string }) => (
|
||||
<Text
|
||||
as="div"
|
||||
$css="white-space: pre-wrap; display: block;"
|
||||
$theme="greyscale"
|
||||
$variation="850"
|
||||
>
|
||||
{content}
|
||||
</Text>
|
||||
);
|
||||
@@ -1,554 +0,0 @@
|
||||
import { Message, SourceUIPart, ToolInvocationUIPart } from '@ai-sdk/ui-utils';
|
||||
import React from 'react';
|
||||
import { useTranslation } from 'react-i18next';
|
||||
|
||||
import { Box, Icon, Loader, Text } from '@/components';
|
||||
import { AttachmentList } from '@/features/chat/components/AttachmentList';
|
||||
import { FeedbackButtons } from '@/features/chat/components/FeedbackButtons';
|
||||
import {
|
||||
CompletedMarkdownBlock,
|
||||
RawTextBlock,
|
||||
} from '@/features/chat/components/MessageBlock';
|
||||
import { SourceItemList } from '@/features/chat/components/SourceItemList';
|
||||
import { ToolInvocationItem } from '@/features/chat/components/ToolInvocationItem';
|
||||
|
||||
// Memoized blocks list to prevent parent re-renders from causing block remounts
|
||||
const BlocksList = React.memo(
|
||||
({ blocks, pending }: { blocks: string[]; pending: string }) => (
|
||||
<div>
|
||||
{/* key={index} is safe here: blocks are append-only during streaming
|
||||
and a completed block's content never changes once finalized. */}
|
||||
{blocks.map((block, index) => (
|
||||
<CompletedMarkdownBlock key={index} content={block} />
|
||||
))}
|
||||
{pending && <RawTextBlock content={pending} />}
|
||||
</div>
|
||||
),
|
||||
(prev, next) => {
|
||||
const lengthChanged = prev.blocks.length !== next.blocks.length;
|
||||
const pendingChanged = prev.pending !== next.pending;
|
||||
|
||||
let blocksChanged = false;
|
||||
for (let i = 0; i < Math.min(prev.blocks.length, next.blocks.length); i++) {
|
||||
if (prev.blocks[i] !== next.blocks[i]) {
|
||||
blocksChanged = true;
|
||||
}
|
||||
}
|
||||
|
||||
if (lengthChanged || pendingChanged || blocksChanged) {
|
||||
return false; // needs re-render
|
||||
}
|
||||
return true;
|
||||
},
|
||||
);
|
||||
BlocksList.displayName = 'BlocksList';
|
||||
|
||||
export interface StreamingContent {
|
||||
completedBlocks: string[];
|
||||
pending: string;
|
||||
}
|
||||
|
||||
/**
|
||||
* Splits content into blocks by double newlines, respecting code fences.
|
||||
* Code fences may contain double newlines, so we merge blocks until fences are balanced.
|
||||
*/
|
||||
export const splitIntoBlocks = (content: string): string[] => {
|
||||
if (!content) {
|
||||
return [];
|
||||
}
|
||||
|
||||
const rawBlocks = content.split('\n\n');
|
||||
const blocks: string[] = [];
|
||||
let currentBlock = '';
|
||||
let fenceCount = 0;
|
||||
|
||||
for (const rawBlock of rawBlocks) {
|
||||
const fences = (rawBlock.match(/```/g) || []).length;
|
||||
|
||||
currentBlock = currentBlock ? currentBlock + '\n\n' + rawBlock : rawBlock;
|
||||
fenceCount += fences;
|
||||
|
||||
// Balanced fences = complete block
|
||||
if (fenceCount % 2 === 0) {
|
||||
if (currentBlock.trim()) {
|
||||
blocks.push(currentBlock);
|
||||
}
|
||||
currentBlock = '';
|
||||
fenceCount = 0;
|
||||
}
|
||||
}
|
||||
|
||||
if (currentBlock.trim()) {
|
||||
blocks.push(currentBlock);
|
||||
}
|
||||
|
||||
return blocks;
|
||||
};
|
||||
|
||||
/**
|
||||
* Splits streaming content into completed blocks (safe and ready to render as markdown)
|
||||
* + a pending content (still being streamed, rendered as raw text).
|
||||
*
|
||||
* A block is considered completed when followed by a double newline.
|
||||
* Each block is returned separately to enable independent memoization.
|
||||
* NB: it respects code fences (``` ... ```) that may contain double newlines.
|
||||
*/
|
||||
export const splitStreamingContent = (content: string): StreamingContent => {
|
||||
if (!content) {
|
||||
return { completedBlocks: [], pending: '' };
|
||||
}
|
||||
|
||||
// Find all code fence positions
|
||||
// Note: this counts all ``` occurrences including those inside inline code spans.
|
||||
// In practice this is unlikely to cause issues since inline code rarely contains ```.
|
||||
const fenceRegex = /```/g;
|
||||
const fences: number[] = [];
|
||||
let match;
|
||||
while ((match = fenceRegex.exec(content)) !== null) {
|
||||
fences.push(match.index);
|
||||
}
|
||||
|
||||
// Check if we're inside an unclosed code fence
|
||||
const isInsideCodeFence = fences.length % 2 === 1;
|
||||
|
||||
let completedContent: string;
|
||||
let pendingContent: string;
|
||||
|
||||
if (isInsideCodeFence) {
|
||||
// Find the last opening fence
|
||||
const lastFenceStart = fences[fences.length - 1];
|
||||
// Everything before the unclosed fence is potentially complete
|
||||
const beforeFence = content.slice(0, lastFenceStart);
|
||||
const fenceAndAfter = content.slice(lastFenceStart);
|
||||
|
||||
// Find the last complete block boundary before the fence
|
||||
const lastDoubleNewline = beforeFence.lastIndexOf('\n\n');
|
||||
if (lastDoubleNewline !== -1) {
|
||||
completedContent = beforeFence.slice(0, lastDoubleNewline);
|
||||
pendingContent = beforeFence.slice(lastDoubleNewline) + fenceAndAfter;
|
||||
} else {
|
||||
// No complete blocks before fence
|
||||
return { completedBlocks: [], pending: content };
|
||||
}
|
||||
} else {
|
||||
// Not inside a code fence - find the last double newline as block boundary
|
||||
const lastDoubleNewline = content.lastIndexOf('\n\n');
|
||||
if (lastDoubleNewline === -1) {
|
||||
// No double newline yet - everything is pending
|
||||
return { completedBlocks: [], pending: content };
|
||||
}
|
||||
|
||||
// Content up to the last \n\n is complete
|
||||
completedContent = content.slice(0, lastDoubleNewline);
|
||||
// Content after the last \n\n is pending (may be empty if content ends with \n\n)
|
||||
pendingContent = content.slice(lastDoubleNewline + 2);
|
||||
}
|
||||
|
||||
const completedBlocks = splitIntoBlocks(completedContent);
|
||||
return { completedBlocks, pending: pendingContent };
|
||||
};
|
||||
|
||||
interface SourceMetadata {
|
||||
title: string | null;
|
||||
favicon: string | null;
|
||||
loading: boolean;
|
||||
error: boolean;
|
||||
}
|
||||
|
||||
export interface MessageItemProps {
|
||||
message: Message;
|
||||
isLastMessage: boolean;
|
||||
isLastAssistantMessage: boolean;
|
||||
isFirstConversationMessage: boolean;
|
||||
streamingMessageHeight: number | null;
|
||||
status: 'submitted' | 'streaming' | 'ready' | 'error';
|
||||
conversationId: string | undefined;
|
||||
isSourceOpen: string | null;
|
||||
isMobile: boolean;
|
||||
onCopyToClipboard: (content: string) => void;
|
||||
onOpenSources: (messageId: string) => void;
|
||||
getMetadata: (url: string) => SourceMetadata | undefined;
|
||||
}
|
||||
|
||||
const MessageItemComponent: React.FC<MessageItemProps> = ({
|
||||
message,
|
||||
isLastMessage,
|
||||
isLastAssistantMessage,
|
||||
isFirstConversationMessage,
|
||||
streamingMessageHeight,
|
||||
status,
|
||||
conversationId,
|
||||
isSourceOpen,
|
||||
isMobile,
|
||||
onCopyToClipboard,
|
||||
onOpenSources,
|
||||
getMetadata,
|
||||
}) => {
|
||||
const { t } = useTranslation();
|
||||
|
||||
const shouldApplyStreamingHeight =
|
||||
isLastAssistantMessage &&
|
||||
isLastMessage &&
|
||||
streamingMessageHeight &&
|
||||
!isFirstConversationMessage;
|
||||
|
||||
const isCurrentlyStreaming =
|
||||
isLastAssistantMessage &&
|
||||
(status === 'streaming' || status === 'submitted');
|
||||
|
||||
const sourceParts = React.useMemo(() => {
|
||||
if (!message.parts) {
|
||||
return [];
|
||||
}
|
||||
return message.parts.filter(
|
||||
(part): part is SourceUIPart => part.type === 'source',
|
||||
);
|
||||
}, [message.parts]);
|
||||
|
||||
const toolInvocationParts = React.useMemo(() => {
|
||||
if (!message.parts) {
|
||||
return [];
|
||||
}
|
||||
return message.parts.filter(
|
||||
(part): part is ToolInvocationUIPart => part.type === 'tool-invocation',
|
||||
);
|
||||
}, [message.parts]);
|
||||
|
||||
const hasNonDocumentParsingTool = React.useMemo(() => {
|
||||
return toolInvocationParts.some(
|
||||
(part) => part.toolInvocation.toolName !== 'document_parsing',
|
||||
);
|
||||
}, [toolInvocationParts]);
|
||||
|
||||
const activeToolInvocation = React.useMemo(() => {
|
||||
const tool = toolInvocationParts.find(
|
||||
(part) => part.toolInvocation.toolName !== 'document_parsing',
|
||||
);
|
||||
return tool?.toolInvocation;
|
||||
}, [toolInvocationParts]);
|
||||
|
||||
const activeToolInvocationDisplayName = React.useMemo(() => {
|
||||
if (!activeToolInvocation) {
|
||||
return '';
|
||||
}
|
||||
|
||||
if (activeToolInvocation.toolName === 'summarize') {
|
||||
return t('Summarizing...');
|
||||
}
|
||||
if (activeToolInvocation.toolName === 'translate') {
|
||||
return t('Translation in progress...');
|
||||
}
|
||||
|
||||
return t('Search...');
|
||||
}, [activeToolInvocation, t]);
|
||||
|
||||
// Memoize the streaming content split to avoid recreating components in JSX
|
||||
const { completedBlocks, pending } = React.useMemo(() => {
|
||||
// When not streaming, everything is completed as a single block array
|
||||
if (!isCurrentlyStreaming) {
|
||||
return {
|
||||
completedBlocks: splitIntoBlocks(message.content),
|
||||
pending: '',
|
||||
};
|
||||
}
|
||||
return splitStreamingContent(message.content);
|
||||
}, [isCurrentlyStreaming, message.content]);
|
||||
|
||||
const handleCopy = React.useCallback(() => {
|
||||
onCopyToClipboard(message.content);
|
||||
}, [onCopyToClipboard, message.content]);
|
||||
|
||||
const handleCopyKeyDown = React.useCallback(
|
||||
(e: React.KeyboardEvent) => {
|
||||
if (e.key === 'Enter' || e.key === ' ') {
|
||||
e.preventDefault();
|
||||
onCopyToClipboard(message.content);
|
||||
}
|
||||
},
|
||||
[onCopyToClipboard, message.content],
|
||||
);
|
||||
|
||||
const handleOpenSources = React.useCallback(() => {
|
||||
onOpenSources(message.id);
|
||||
}, [onOpenSources, message.id]);
|
||||
|
||||
const handleOpenSourcesKeyDown = React.useCallback(
|
||||
(e: React.KeyboardEvent) => {
|
||||
if (e.key === 'Enter' || e.key === ' ') {
|
||||
e.preventDefault();
|
||||
onOpenSources(message.id);
|
||||
}
|
||||
},
|
||||
[onOpenSources, message.id],
|
||||
);
|
||||
|
||||
return (
|
||||
<Box
|
||||
data-message-id={message.id}
|
||||
data-testid={message.id}
|
||||
$css={`
|
||||
display: flex;
|
||||
width: 100%;
|
||||
margin: auto;
|
||||
margin-bottom: ${isLastAssistantMessage ? '30px' : '0px'};
|
||||
color: var(--c--theme--colors--greyscale-850);
|
||||
padding-left: 12px;
|
||||
padding-right: 12px;
|
||||
max-width: 750px;
|
||||
text-align: left;
|
||||
overflow-wrap: anywhere;
|
||||
flex-direction: ${message.role === 'user' ? 'row-reverse' : 'row'};
|
||||
`}
|
||||
>
|
||||
<Box
|
||||
$display="block"
|
||||
$width={`${message.role === 'user' ? 'auto' : '100%'}`}
|
||||
>
|
||||
{message.experimental_attachments &&
|
||||
message.experimental_attachments.length > 0 && (
|
||||
<Box>
|
||||
<AttachmentList
|
||||
attachments={message.experimental_attachments}
|
||||
isReadOnly={true}
|
||||
/>
|
||||
</Box>
|
||||
)}
|
||||
<Box
|
||||
$radius="8px"
|
||||
$width={`${message.role === 'user' ? 'auto' : '100%'}`}
|
||||
$maxWidth="100%"
|
||||
$padding={`${message.role === 'user' ? '12px' : '0'}`}
|
||||
$margin={{ vertical: 'base' }}
|
||||
$background={`${message.role === 'user' ? '#EEF1F4' : 'white'}`}
|
||||
$css={`
|
||||
display: inline-block;
|
||||
float: right;
|
||||
${shouldApplyStreamingHeight ? `min-height: ${streamingMessageHeight}px;` : ''}`}
|
||||
>
|
||||
{/* Message content */}
|
||||
{message.content && (
|
||||
<Box
|
||||
className="mainContent-chat"
|
||||
data-testid={
|
||||
message.role === 'assistant'
|
||||
? 'assistant-message-content'
|
||||
: undefined
|
||||
}
|
||||
$padding={{ all: 'xxs' }}
|
||||
>
|
||||
<p className="sr-only">
|
||||
{message.role === 'user'
|
||||
? t('You said: ')
|
||||
: t('Assistant IA replied: ')}
|
||||
</p>
|
||||
{message.role === 'user' ? (
|
||||
<Text
|
||||
as="p"
|
||||
$css="white-space: pre-wrap; display: block;"
|
||||
$theme="greyscale"
|
||||
$variation="850"
|
||||
>
|
||||
{message.content}
|
||||
</Text>
|
||||
) : (
|
||||
// Render completed blocks as markdown, pending block as plain text
|
||||
<BlocksList blocks={completedBlocks} pending={pending} />
|
||||
)}
|
||||
</Box>
|
||||
)}
|
||||
|
||||
<Box $direction="column" $gap="2">
|
||||
{isCurrentlyStreaming &&
|
||||
isLastAssistantMessage &&
|
||||
status === 'streaming' &&
|
||||
hasNonDocumentParsingTool && (
|
||||
<Box
|
||||
$direction="row"
|
||||
$align="center"
|
||||
$gap="6px"
|
||||
$width="100%"
|
||||
$maxWidth="750px"
|
||||
$margin={{
|
||||
all: 'auto',
|
||||
top: 'base',
|
||||
bottom: 'md',
|
||||
}}
|
||||
>
|
||||
<Loader />
|
||||
<Text $variation="600" $size="md">
|
||||
{activeToolInvocationDisplayName}
|
||||
</Text>
|
||||
</Box>
|
||||
)}
|
||||
{toolInvocationParts.map((part, partIndex) =>
|
||||
isCurrentlyStreaming && isLastAssistantMessage ? (
|
||||
<ToolInvocationItem
|
||||
key={`tool-invocation-${partIndex}`}
|
||||
toolInvocation={part.toolInvocation}
|
||||
status={status}
|
||||
hideSearchLoader={true}
|
||||
/>
|
||||
) : null,
|
||||
)}
|
||||
</Box>
|
||||
|
||||
{message.role === 'assistant' &&
|
||||
!(isLastAssistantMessage && status === 'streaming') && (
|
||||
<Box
|
||||
$css="color: #222631; font-size: 12px;"
|
||||
$direction="row"
|
||||
$align="center"
|
||||
$justify="space-between"
|
||||
$gap="6px"
|
||||
$margin={{ top: 'base' }}
|
||||
>
|
||||
<Box $direction="row" $gap="4px">
|
||||
<Box
|
||||
$direction="row"
|
||||
$align="center"
|
||||
$gap="4px"
|
||||
className="c__button--neutral action-chat-button"
|
||||
onClick={handleCopy}
|
||||
onKeyDown={handleCopyKeyDown}
|
||||
role="button"
|
||||
tabIndex={0}
|
||||
>
|
||||
<Icon
|
||||
iconName="content_copy"
|
||||
$theme="greyscale"
|
||||
$variation="550"
|
||||
$size="16px"
|
||||
className="action-chat-button-icon"
|
||||
/>
|
||||
{!isMobile && (
|
||||
<Text $theme="greyscale" $variation="550">
|
||||
{t('Copy')}
|
||||
</Text>
|
||||
)}
|
||||
</Box>
|
||||
{sourceParts.length > 0 && (
|
||||
<Box
|
||||
$direction="row"
|
||||
$align="center"
|
||||
$gap="4px"
|
||||
className={`c__button--neutral action-chat-button ${isSourceOpen === message.id ? 'action-chat-button--open' : ''}`}
|
||||
onClick={handleOpenSources}
|
||||
onKeyDown={handleOpenSourcesKeyDown}
|
||||
role="button"
|
||||
tabIndex={0}
|
||||
>
|
||||
<Icon
|
||||
iconName="book"
|
||||
$theme="greyscale"
|
||||
$variation="550"
|
||||
$size="16px"
|
||||
className="action-chat-button-icon"
|
||||
/>
|
||||
<Text
|
||||
$theme="greyscale"
|
||||
$variation="550"
|
||||
$weight="500"
|
||||
$size="12px"
|
||||
>
|
||||
{t('Show')} {sourceParts.length}{' '}
|
||||
{sourceParts.length !== 1 ? t('sources') : t('source')}
|
||||
</Text>
|
||||
</Box>
|
||||
)}
|
||||
</Box>
|
||||
<Box $direction="row" $gap="4px">
|
||||
{conversationId &&
|
||||
message.id &&
|
||||
message.id.startsWith('trace-') && (
|
||||
<FeedbackButtons
|
||||
conversationId={conversationId}
|
||||
messageId={message.id}
|
||||
/>
|
||||
)}
|
||||
</Box>
|
||||
</Box>
|
||||
)}
|
||||
|
||||
{isSourceOpen === message.id && sourceParts.length > 0 && (
|
||||
<Box
|
||||
$css={`
|
||||
animation: fade-in 0.2s ease-out;
|
||||
`}
|
||||
>
|
||||
<SourceItemList parts={sourceParts} getMetadata={getMetadata} />
|
||||
</Box>
|
||||
)}
|
||||
</Box>
|
||||
</Box>
|
||||
</Box>
|
||||
);
|
||||
};
|
||||
|
||||
MessageItemComponent.displayName = 'MessageItem';
|
||||
|
||||
// Custom comparison function for React.memo
|
||||
// Only re-render when props that affect rendering change
|
||||
const arePropsEqual = (
|
||||
prevProps: MessageItemProps,
|
||||
nextProps: MessageItemProps,
|
||||
): boolean => {
|
||||
// Always re-render if message content changed
|
||||
if (prevProps.message.id !== nextProps.message.id) {
|
||||
return false;
|
||||
}
|
||||
if (prevProps.message.content !== nextProps.message.content) {
|
||||
return false;
|
||||
}
|
||||
if (prevProps.message.role !== nextProps.message.role) {
|
||||
return false;
|
||||
}
|
||||
|
||||
// Check parts changes (for streaming tool invocations and sources)
|
||||
const prevPartsLength = prevProps.message.parts?.length ?? 0;
|
||||
const nextPartsLength = nextProps.message.parts?.length ?? 0;
|
||||
if (prevPartsLength !== nextPartsLength) {
|
||||
return false;
|
||||
}
|
||||
|
||||
// Check attachments
|
||||
const prevAttachmentsLength =
|
||||
prevProps.message.experimental_attachments?.length ?? 0;
|
||||
const nextAttachmentsLength =
|
||||
nextProps.message.experimental_attachments?.length ?? 0;
|
||||
if (prevAttachmentsLength !== nextAttachmentsLength) {
|
||||
return false;
|
||||
}
|
||||
|
||||
// Check rendering flags
|
||||
if (prevProps.isLastMessage !== nextProps.isLastMessage) {
|
||||
return false;
|
||||
}
|
||||
if (prevProps.isLastAssistantMessage !== nextProps.isLastAssistantMessage) {
|
||||
return false;
|
||||
}
|
||||
if (
|
||||
prevProps.isFirstConversationMessage !==
|
||||
nextProps.isFirstConversationMessage
|
||||
) {
|
||||
return false;
|
||||
}
|
||||
if (prevProps.streamingMessageHeight !== nextProps.streamingMessageHeight) {
|
||||
return false;
|
||||
}
|
||||
if (prevProps.status !== nextProps.status) {
|
||||
return false;
|
||||
}
|
||||
if (prevProps.isSourceOpen !== nextProps.isSourceOpen) {
|
||||
return false;
|
||||
}
|
||||
if (prevProps.isMobile !== nextProps.isMobile) {
|
||||
return false;
|
||||
}
|
||||
if (prevProps.conversationId !== nextProps.conversationId) {
|
||||
return false;
|
||||
}
|
||||
|
||||
return true;
|
||||
};
|
||||
|
||||
export const MessageItem = React.memo(MessageItemComponent, arePropsEqual);
|
||||
@@ -23,6 +23,7 @@ const SourceItemListComponent: React.FC<SourceItemListProps> = ({
|
||||
if (parts.length === 0) {
|
||||
return null;
|
||||
}
|
||||
|
||||
return (
|
||||
<Box
|
||||
$direction="column"
|
||||
|
||||
+8
-10
@@ -3,7 +3,13 @@ import { useTranslation } from 'react-i18next';
|
||||
|
||||
import { Box } from '@/components';
|
||||
|
||||
const SUGGESTIONS_COUNT = 4;
|
||||
const SUGGESTION_KEYS = [
|
||||
'Ask a question',
|
||||
'Turn this list into bullet points',
|
||||
'Write a short product description',
|
||||
'Find recent news about...',
|
||||
] as const;
|
||||
const SUGGESTIONS_COUNT = SUGGESTION_KEYS.length;
|
||||
|
||||
const WRAPPER_CSS = `position: absolute;
|
||||
top: 1rem;
|
||||
@@ -36,15 +42,7 @@ export const SuggestionCarousel = ({
|
||||
const [currentSuggestionIndex, setCurrentSuggestionIndex] = useState(0);
|
||||
const [isResetting, setIsResetting] = useState(false);
|
||||
|
||||
const suggestions = useMemo(
|
||||
() => [
|
||||
t('Ask a question'),
|
||||
t('Turn this list into bullet points'),
|
||||
t('Write a short product description'),
|
||||
t('Find recent news about...'),
|
||||
],
|
||||
[t],
|
||||
);
|
||||
const suggestions = useMemo(() => SUGGESTION_KEYS.map((key) => t(key)), [t]);
|
||||
const carouselSuggestions = useMemo(
|
||||
() => [...suggestions, suggestions[0]],
|
||||
[suggestions],
|
||||
|
||||
+12
-7
@@ -29,15 +29,13 @@ export const ToolInvocationItem: React.FC<ToolInvocationItemProps> = ({
|
||||
?.documents;
|
||||
const documentIdentifiers: string[] =
|
||||
Array.isArray(documents) &&
|
||||
documents.every(
|
||||
(doc): doc is { identifier: string } =>
|
||||
typeof doc === 'object' && doc !== null && 'identifier' in doc,
|
||||
)
|
||||
documents.every(
|
||||
(doc): doc is { identifier: string } =>
|
||||
typeof doc === 'object' && doc !== null && 'identifier' in doc,
|
||||
)
|
||||
? documents.map((doc) => doc.identifier)
|
||||
: [];
|
||||
|
||||
const label = documentIdentifiers.length > 1 ? 'Extracting documents...' : 'Extracting document...';
|
||||
|
||||
return (
|
||||
<Box
|
||||
$direction="row"
|
||||
@@ -47,10 +45,17 @@ export const ToolInvocationItem: React.FC<ToolInvocationItemProps> = ({
|
||||
$width="100%"
|
||||
$maxWidth="750px"
|
||||
$margin={{ all: 'auto', top: 'base', bottom: 'md' }}
|
||||
$background="var(--c--contextuals--background--surface--tertiary)"
|
||||
$color="var(--c--contextuals--content--semantic--neutral--secondary)"
|
||||
$padding={{ all: 'sm' }}
|
||||
$radius="8px"
|
||||
$css="font-size: 0.9em; width: 100%; white-space: pre-wrap; word-wrap: break-word;"
|
||||
>
|
||||
<Loader />
|
||||
<Text $variation="600" $size="md">
|
||||
{t(label, { documents: documentIdentifiers.join(', ') })}
|
||||
{t('Extracting documents: {{documents}} ...', {
|
||||
documents: documentIdentifiers.join(', '),
|
||||
})}
|
||||
</Text>
|
||||
</Box>
|
||||
);
|
||||
|
||||
-171
@@ -1,171 +0,0 @@
|
||||
/* eslint-disable testing-library/no-unnecessary-act, @typescript-eslint/require-await */
|
||||
import { CunninghamProvider } from '@openfun/cunningham-react';
|
||||
import { act, render, screen } from '@testing-library/react';
|
||||
import { Suspense } from 'react';
|
||||
|
||||
import { CompletedMarkdownBlock, RawTextBlock } from '../MessageBlock';
|
||||
|
||||
// Mock react-markdown (ESM module not compatible with Jest)
|
||||
jest.mock('react-markdown', () => ({
|
||||
MarkdownHooks: ({ children }: { children: string }) => {
|
||||
// Simple mock that renders markdown-like content
|
||||
// This tests the component integration, not the markdown parsing itself
|
||||
return <div data-testid="markdown-content">{children}</div>;
|
||||
},
|
||||
}));
|
||||
|
||||
// Mock rehype/remark plugins
|
||||
jest.mock('@shikijs/rehype/core', () => () => {});
|
||||
jest.mock('../../utils/shiki', () => ({
|
||||
getHighlighter: () => Promise.resolve({}),
|
||||
}));
|
||||
jest.mock('rehype-katex', () => () => {});
|
||||
jest.mock('remark-gfm', () => () => {});
|
||||
jest.mock('remark-math', () => () => {});
|
||||
|
||||
jest.mock('react-i18next', () => ({
|
||||
useTranslation: () => ({
|
||||
t: (key: string) => key,
|
||||
}),
|
||||
}));
|
||||
|
||||
const renderWithProviders = (ui: React.ReactNode) => {
|
||||
return render(
|
||||
<CunninghamProvider>
|
||||
<Suspense fallback={null}>{ui}</Suspense>
|
||||
</CunninghamProvider>,
|
||||
);
|
||||
};
|
||||
|
||||
describe('CompletedMarkdownBlock', () => {
|
||||
it('renders content through MarkdownHooks', async () => {
|
||||
await act(async () => {
|
||||
renderWithProviders(<CompletedMarkdownBlock content="Hello world" />);
|
||||
});
|
||||
|
||||
expect(screen.getByText('Hello world')).toBeInTheDocument();
|
||||
});
|
||||
|
||||
it('passes content to markdown renderer', async () => {
|
||||
const content = '# Header Some **bold** text';
|
||||
await act(async () => {
|
||||
renderWithProviders(<CompletedMarkdownBlock content={content} />);
|
||||
});
|
||||
|
||||
expect(screen.getByTestId('markdown-content')).toHaveTextContent(content);
|
||||
});
|
||||
|
||||
it('does not re-render when content is the same (memoization)', async () => {
|
||||
let rerender: ReturnType<typeof render>['rerender'];
|
||||
await act(async () => {
|
||||
({ rerender } = renderWithProviders(
|
||||
<CompletedMarkdownBlock content="Same content" />,
|
||||
));
|
||||
});
|
||||
|
||||
const firstRender = screen.getByTestId('markdown-content');
|
||||
|
||||
rerender!(
|
||||
<CunninghamProvider>
|
||||
<Suspense fallback={null}>
|
||||
<CompletedMarkdownBlock content="Same content" />
|
||||
</Suspense>
|
||||
</CunninghamProvider>,
|
||||
);
|
||||
|
||||
const secondRender = screen.getByTestId('markdown-content');
|
||||
|
||||
// The DOM element should be the same instance (not recreated)
|
||||
expect(firstRender).toBe(secondRender);
|
||||
});
|
||||
|
||||
it('re-renders when content changes', async () => {
|
||||
let rerender: ReturnType<typeof render>['rerender'];
|
||||
await act(async () => {
|
||||
({ rerender } = renderWithProviders(
|
||||
<CompletedMarkdownBlock content="Original content" />,
|
||||
));
|
||||
});
|
||||
|
||||
expect(screen.getByText('Original content')).toBeInTheDocument();
|
||||
|
||||
rerender!(
|
||||
<CunninghamProvider>
|
||||
<Suspense fallback={null}>
|
||||
<CompletedMarkdownBlock content="New content" />
|
||||
</Suspense>
|
||||
</CunninghamProvider>,
|
||||
);
|
||||
|
||||
expect(screen.queryByText('Original content')).not.toBeInTheDocument();
|
||||
expect(screen.getByText('New content')).toBeInTheDocument();
|
||||
});
|
||||
|
||||
it('handles empty content', async () => {
|
||||
let container: HTMLElement;
|
||||
await act(async () => {
|
||||
({ container } = renderWithProviders(
|
||||
<CompletedMarkdownBlock content="" />,
|
||||
));
|
||||
});
|
||||
|
||||
expect(container!).toBeInTheDocument();
|
||||
expect(screen.getByTestId('markdown-content')).toBeInTheDocument();
|
||||
});
|
||||
|
||||
it('handles content with special characters', async () => {
|
||||
await act(async () => {
|
||||
renderWithProviders(
|
||||
<CompletedMarkdownBlock content={`Special chars: < > & " '`} />,
|
||||
);
|
||||
});
|
||||
|
||||
expect(screen.getByText(/Special chars:/)).toBeInTheDocument();
|
||||
});
|
||||
});
|
||||
|
||||
describe('RawTextBlock', () => {
|
||||
it('renders plain text content', () => {
|
||||
renderWithProviders(<RawTextBlock content="Raw text content" />);
|
||||
|
||||
expect(screen.getByText('Raw text content')).toBeInTheDocument();
|
||||
});
|
||||
|
||||
it('preserves whitespace and newlines', () => {
|
||||
renderWithProviders(
|
||||
<RawTextBlock content="Line 1\n Indented line\nLine 3" />,
|
||||
);
|
||||
|
||||
const textElement = screen.getByText(/Line 1/);
|
||||
expect(textElement).toHaveStyle('white-space: pre-wrap');
|
||||
});
|
||||
|
||||
it('renders as a div element', () => {
|
||||
renderWithProviders(<RawTextBlock content="Test content" />);
|
||||
|
||||
const element = screen.getByText('Test content');
|
||||
// Text component renders with as="div", check it's in the DOM
|
||||
expect(element).toBeInTheDocument();
|
||||
});
|
||||
|
||||
it('does not parse markdown syntax', () => {
|
||||
renderWithProviders(<RawTextBlock content="**not bold** *not italic*" />);
|
||||
|
||||
// Should render the raw markdown syntax, not parsed
|
||||
expect(screen.getByText('**not bold** *not italic*')).toBeInTheDocument();
|
||||
});
|
||||
|
||||
it('handles empty content', () => {
|
||||
const { container } = renderWithProviders(<RawTextBlock content="" />);
|
||||
|
||||
expect(container).toBeInTheDocument();
|
||||
});
|
||||
|
||||
it('handles content with code fence markers', () => {
|
||||
renderWithProviders(
|
||||
<RawTextBlock content="```python\npsquares = [x**2 for x in range(10)]" />,
|
||||
);
|
||||
|
||||
expect(screen.getByText(/```python/)).toBeInTheDocument();
|
||||
});
|
||||
});
|
||||
-536
@@ -1,536 +0,0 @@
|
||||
/* eslint-disable testing-library/no-unnecessary-act, @typescript-eslint/require-await */
|
||||
import { CunninghamProvider } from '@openfun/cunningham-react';
|
||||
import { act, render, screen } from '@testing-library/react';
|
||||
import userEvent from '@testing-library/user-event';
|
||||
import { Suspense } from 'react';
|
||||
|
||||
import {
|
||||
MessageItem,
|
||||
splitIntoBlocks,
|
||||
splitStreamingContent,
|
||||
} from '../MessageItem';
|
||||
|
||||
// Mock react-markdown (ESM module)
|
||||
jest.mock('react-markdown', () => ({
|
||||
MarkdownHooks: ({ children }: { children: string }) => (
|
||||
<div data-testid="markdown-content">{children}</div>
|
||||
),
|
||||
}));
|
||||
|
||||
jest.mock('@shikijs/rehype/core', () => () => {});
|
||||
jest.mock('../../utils/shiki', () => ({
|
||||
getHighlighter: () => Promise.resolve({}),
|
||||
}));
|
||||
jest.mock('rehype-katex', () => () => {});
|
||||
jest.mock('remark-gfm', () => () => {});
|
||||
jest.mock('remark-math', () => () => {});
|
||||
|
||||
jest.mock('react-i18next', () => ({
|
||||
useTranslation: () => ({
|
||||
t: (key: string) => key,
|
||||
}),
|
||||
}));
|
||||
|
||||
// Mock child components
|
||||
jest.mock('../AttachmentList', () => ({
|
||||
AttachmentList: () => <div data-testid="attachment-list" />,
|
||||
}));
|
||||
|
||||
jest.mock('../FeedbackButtons', () => ({
|
||||
FeedbackButtons: () => <div data-testid="feedback-buttons" />,
|
||||
}));
|
||||
|
||||
jest.mock('../SourceItemList', () => ({
|
||||
SourceItemList: () => <div data-testid="source-item-list" />,
|
||||
}));
|
||||
|
||||
jest.mock('../ToolInvocationItem', () => ({
|
||||
ToolInvocationItem: () => <div data-testid="tool-invocation-item" />,
|
||||
}));
|
||||
|
||||
describe('splitIntoBlocks', () => {
|
||||
describe('basic splitting', () => {
|
||||
it('returns empty array for empty content', () => {
|
||||
expect(splitIntoBlocks('')).toEqual([]);
|
||||
});
|
||||
|
||||
it('returns empty array for null/undefined content', () => {
|
||||
expect(splitIntoBlocks(null as unknown as string)).toEqual([]);
|
||||
expect(splitIntoBlocks(undefined as unknown as string)).toEqual([]);
|
||||
});
|
||||
|
||||
it('returns single block for content without double newlines', () => {
|
||||
expect(splitIntoBlocks('Hello world')).toEqual(['Hello world']);
|
||||
});
|
||||
|
||||
it('splits content by double newlines', () => {
|
||||
expect(splitIntoBlocks('Block 1\n\nBlock 2')).toEqual([
|
||||
'Block 1',
|
||||
'Block 2',
|
||||
]);
|
||||
});
|
||||
|
||||
it('splits multiple blocks', () => {
|
||||
expect(splitIntoBlocks('Block 1\n\nBlock 2\n\nBlock 3')).toEqual([
|
||||
'Block 1',
|
||||
'Block 2',
|
||||
'Block 3',
|
||||
]);
|
||||
});
|
||||
|
||||
it('ignores single newlines', () => {
|
||||
expect(splitIntoBlocks('Line 1\nLine 2\n\nBlock 2')).toEqual([
|
||||
'Line 1\nLine 2',
|
||||
'Block 2',
|
||||
]);
|
||||
});
|
||||
|
||||
it('filters out empty blocks', () => {
|
||||
expect(splitIntoBlocks('Block 1\n\n\n\nBlock 2')).toEqual([
|
||||
'Block 1',
|
||||
'Block 2',
|
||||
]);
|
||||
});
|
||||
|
||||
it('filters out whitespace-only blocks', () => {
|
||||
expect(splitIntoBlocks('Block 1\n\n \n\nBlock 2')).toEqual([
|
||||
'Block 1',
|
||||
'Block 2',
|
||||
]);
|
||||
});
|
||||
});
|
||||
|
||||
describe('code fence handling', () => {
|
||||
it('keeps code block with internal double newlines as single block', () => {
|
||||
const content = '```python\nline1\n\nline2\n```';
|
||||
expect(splitIntoBlocks(content)).toEqual([content]);
|
||||
});
|
||||
|
||||
it('keeps code block intact when followed by other content', () => {
|
||||
const content = '```python\ncode\n```\n\nText after';
|
||||
expect(splitIntoBlocks(content)).toEqual([
|
||||
'```python\ncode\n```',
|
||||
'Text after',
|
||||
]);
|
||||
});
|
||||
|
||||
it('keeps code block intact when preceded by other content', () => {
|
||||
const content = 'Text before\n\n```python\ncode\n```';
|
||||
expect(splitIntoBlocks(content)).toEqual([
|
||||
'Text before',
|
||||
'```python\ncode\n```',
|
||||
]);
|
||||
});
|
||||
|
||||
it('handles multiple code blocks', () => {
|
||||
const content = '```js\ncode1\n```\n\nText\n\n```python\ncode2\n```';
|
||||
expect(splitIntoBlocks(content)).toEqual([
|
||||
'```js\ncode1\n```',
|
||||
'Text',
|
||||
'```python\ncode2\n```',
|
||||
]);
|
||||
});
|
||||
|
||||
it('handles code block with multiple double newlines inside', () => {
|
||||
const content = '```\nline1\n\nline2\n\nline3\n```';
|
||||
expect(splitIntoBlocks(content)).toEqual([content]);
|
||||
});
|
||||
|
||||
it('handles nested backticks inside code block', () => {
|
||||
const content = '```markdown\nSome `inline` code\n\nMore text\n```';
|
||||
expect(splitIntoBlocks(content)).toEqual([content]);
|
||||
});
|
||||
|
||||
it('handles unclosed code fence', () => {
|
||||
const content = 'Text\n\n```python\ncode without closing';
|
||||
const result = splitIntoBlocks(content);
|
||||
// The unclosed fence should be kept with the text before it
|
||||
expect(result).toEqual(['Text', '```python\ncode without closing']);
|
||||
});
|
||||
});
|
||||
|
||||
describe('edge cases', () => {
|
||||
it('handles content ending with double newline', () => {
|
||||
expect(splitIntoBlocks('Block 1\n\nBlock 2\n\n')).toEqual([
|
||||
'Block 1',
|
||||
'Block 2',
|
||||
]);
|
||||
});
|
||||
|
||||
it('handles content starting with double newline', () => {
|
||||
expect(splitIntoBlocks('\n\nBlock 1\n\nBlock 2')).toEqual([
|
||||
'Block 1',
|
||||
'Block 2',
|
||||
]);
|
||||
});
|
||||
|
||||
it('handles markdown headers', () => {
|
||||
expect(splitIntoBlocks('# Header\n\nParagraph')).toEqual([
|
||||
'# Header',
|
||||
'Paragraph',
|
||||
]);
|
||||
});
|
||||
|
||||
it('handles markdown lists', () => {
|
||||
const content = '- Item 1\n- Item 2\n\nParagraph';
|
||||
expect(splitIntoBlocks(content)).toEqual([
|
||||
'- Item 1\n- Item 2',
|
||||
'Paragraph',
|
||||
]);
|
||||
});
|
||||
});
|
||||
});
|
||||
|
||||
describe('splitStreamingContent', () => {
|
||||
describe('basic splitting', () => {
|
||||
it('returns empty blocks and empty pending for empty content', () => {
|
||||
expect(splitStreamingContent('')).toEqual({
|
||||
completedBlocks: [],
|
||||
pending: '',
|
||||
});
|
||||
});
|
||||
|
||||
it('returns all content as pending when no double newline', () => {
|
||||
expect(splitStreamingContent('Partial content')).toEqual({
|
||||
completedBlocks: [],
|
||||
pending: 'Partial content',
|
||||
});
|
||||
});
|
||||
|
||||
it('splits completed and pending content', () => {
|
||||
expect(splitStreamingContent('Block 1\n\nPending')).toEqual({
|
||||
completedBlocks: ['Block 1'],
|
||||
pending: 'Pending',
|
||||
});
|
||||
});
|
||||
|
||||
it('handles multiple completed blocks with pending', () => {
|
||||
expect(splitStreamingContent('Block 1\n\nBlock 2\n\nPending')).toEqual({
|
||||
completedBlocks: ['Block 1', 'Block 2'],
|
||||
pending: 'Pending',
|
||||
});
|
||||
});
|
||||
});
|
||||
|
||||
describe('content ending with double newline (bug fix)', () => {
|
||||
it('keeps blocks when content ends with double newline', () => {
|
||||
// This was the bug: content ending with \n\n would return empty blocks
|
||||
const result = splitStreamingContent('Block 1\n\nBlock 2\n\n');
|
||||
expect(result.completedBlocks).toEqual(['Block 1', 'Block 2']);
|
||||
expect(result.pending).toBe('');
|
||||
});
|
||||
|
||||
it('keeps single block when content ends with double newline', () => {
|
||||
const result = splitStreamingContent('Block 1\n\n');
|
||||
expect(result.completedBlocks).toEqual(['Block 1']);
|
||||
expect(result.pending).toBe('');
|
||||
});
|
||||
|
||||
it('handles multiple trailing double newlines', () => {
|
||||
// 'Block 1\n\n\n\n' - lastIndexOf('\n\n') finds the last pair
|
||||
// completedContent = 'Block 1\n\n', pending = ''
|
||||
const result = splitStreamingContent('Block 1\n\n\n\n');
|
||||
expect(result.completedBlocks).toEqual(['Block 1']);
|
||||
expect(result.pending).toBe('');
|
||||
});
|
||||
});
|
||||
|
||||
describe('code fence handling', () => {
|
||||
it('treats unclosed code fence as pending', () => {
|
||||
const result = splitStreamingContent('Text\n\n```python\ncode');
|
||||
expect(result.completedBlocks).toEqual(['Text']);
|
||||
expect(result.pending).toBe('\n\n```python\ncode');
|
||||
});
|
||||
|
||||
it('handles closed code fence as completed', () => {
|
||||
const result = splitStreamingContent('```python\ncode\n```\n\nPending');
|
||||
expect(result.completedBlocks).toEqual(['```python\ncode\n```']);
|
||||
expect(result.pending).toBe('Pending');
|
||||
});
|
||||
|
||||
it('handles unclosed fence with no content before', () => {
|
||||
const result = splitStreamingContent('```python\ncode');
|
||||
expect(result.completedBlocks).toEqual([]);
|
||||
expect(result.pending).toBe('```python\ncode');
|
||||
});
|
||||
|
||||
it('handles unclosed fence with double newline inside', () => {
|
||||
const result = splitStreamingContent('Text\n\n```python\nline1\n\nline2');
|
||||
expect(result.completedBlocks).toEqual(['Text']);
|
||||
expect(result.pending).toContain('```python');
|
||||
});
|
||||
|
||||
it('handles multiple code blocks', () => {
|
||||
const result = splitStreamingContent(
|
||||
'```js\ncode1\n```\n\n```python\ncode2\n```\n\nPending',
|
||||
);
|
||||
expect(result.completedBlocks).toEqual([
|
||||
'```js\ncode1\n```',
|
||||
'```python\ncode2\n```',
|
||||
]);
|
||||
expect(result.pending).toBe('Pending');
|
||||
});
|
||||
});
|
||||
|
||||
describe('streaming simulation', () => {
|
||||
it('maintains block stability as content grows', () => {
|
||||
// Simulate streaming: content grows over time
|
||||
const stream1 = 'Hello';
|
||||
const stream2 = 'Hello world';
|
||||
const stream3 = 'Hello world\n\n';
|
||||
const stream4 = 'Hello world\n\nSecond';
|
||||
const stream5 = 'Hello world\n\nSecond block\n\n';
|
||||
const stream6 = 'Hello world\n\nSecond block\n\nThird';
|
||||
|
||||
// Initially all pending
|
||||
expect(splitStreamingContent(stream1).completedBlocks).toEqual([]);
|
||||
expect(splitStreamingContent(stream2).completedBlocks).toEqual([]);
|
||||
|
||||
// After first \n\n, first block is complete
|
||||
const result3 = splitStreamingContent(stream3);
|
||||
expect(result3.completedBlocks).toEqual(['Hello world']);
|
||||
expect(result3.pending).toBe('');
|
||||
|
||||
// New content arrives
|
||||
const result4 = splitStreamingContent(stream4);
|
||||
expect(result4.completedBlocks).toEqual(['Hello world']);
|
||||
expect(result4.pending).toBe('Second');
|
||||
|
||||
// Second block completes
|
||||
const result5 = splitStreamingContent(stream5);
|
||||
expect(result5.completedBlocks).toEqual(['Hello world', 'Second block']);
|
||||
expect(result5.pending).toBe('');
|
||||
|
||||
// More content
|
||||
const result6 = splitStreamingContent(stream6);
|
||||
expect(result6.completedBlocks).toEqual(['Hello world', 'Second block']);
|
||||
expect(result6.pending).toBe('Third');
|
||||
});
|
||||
|
||||
it('block content remains stable during streaming', () => {
|
||||
// The key test: first block content should not change as more content arrives
|
||||
const stream1 = 'First block\n\nSecond';
|
||||
const stream2 = 'First block\n\nSecond block\n\nThird';
|
||||
|
||||
const result1 = splitStreamingContent(stream1);
|
||||
const result2 = splitStreamingContent(stream2);
|
||||
|
||||
// First block should be identical
|
||||
expect(result1.completedBlocks[0]).toBe(result2.completedBlocks[0]);
|
||||
expect(result1.completedBlocks[0]).toBe('First block');
|
||||
});
|
||||
});
|
||||
|
||||
describe('edge cases', () => {
|
||||
it('handles only whitespace', () => {
|
||||
expect(splitStreamingContent(' ')).toEqual({
|
||||
completedBlocks: [],
|
||||
pending: ' ',
|
||||
});
|
||||
});
|
||||
|
||||
it('handles only newlines', () => {
|
||||
expect(splitStreamingContent('\n\n')).toEqual({
|
||||
completedBlocks: [],
|
||||
pending: '',
|
||||
});
|
||||
});
|
||||
|
||||
it('handles special characters', () => {
|
||||
const result = splitStreamingContent('Special: < > & "\n\nMore');
|
||||
expect(result.completedBlocks).toEqual(['Special: < > & "']);
|
||||
expect(result.pending).toBe('More');
|
||||
});
|
||||
});
|
||||
});
|
||||
|
||||
describe('MessageItem', () => {
|
||||
const defaultProps = {
|
||||
message: {
|
||||
id: 'msg-1',
|
||||
role: 'assistant' as const,
|
||||
content: 'Hello world',
|
||||
},
|
||||
isLastMessage: false,
|
||||
isLastAssistantMessage: false,
|
||||
isFirstConversationMessage: false,
|
||||
streamingMessageHeight: null,
|
||||
status: 'ready' as const,
|
||||
conversationId: 'conv-1',
|
||||
isSourceOpen: null,
|
||||
isMobile: false,
|
||||
onCopyToClipboard: jest.fn(),
|
||||
onOpenSources: jest.fn(),
|
||||
getMetadata: jest.fn(),
|
||||
};
|
||||
|
||||
const renderWithProviders = (ui: React.ReactNode) => {
|
||||
return render(
|
||||
<CunninghamProvider>
|
||||
<Suspense fallback={null}>{ui}</Suspense>
|
||||
</CunninghamProvider>,
|
||||
);
|
||||
};
|
||||
|
||||
beforeEach(() => {
|
||||
jest.clearAllMocks();
|
||||
});
|
||||
|
||||
describe('rendering', () => {
|
||||
it('renders assistant message content', async () => {
|
||||
await act(async () => {
|
||||
renderWithProviders(<MessageItem {...defaultProps} />);
|
||||
});
|
||||
|
||||
expect(
|
||||
screen.getByTestId('assistant-message-content'),
|
||||
).toBeInTheDocument();
|
||||
});
|
||||
|
||||
it('renders user message content', async () => {
|
||||
await act(async () => {
|
||||
renderWithProviders(
|
||||
<MessageItem
|
||||
{...defaultProps}
|
||||
message={{ ...defaultProps.message, role: 'user' }}
|
||||
/>,
|
||||
);
|
||||
});
|
||||
|
||||
expect(screen.getByText('Hello world')).toBeInTheDocument();
|
||||
});
|
||||
|
||||
it('renders message with data-message-id attribute', async () => {
|
||||
await act(async () => {
|
||||
renderWithProviders(<MessageItem {...defaultProps} />);
|
||||
});
|
||||
|
||||
expect(screen.getByTestId('msg-1')).toBeInTheDocument();
|
||||
});
|
||||
|
||||
it('renders copy button for non-streaming assistant messages', async () => {
|
||||
await act(async () => {
|
||||
renderWithProviders(<MessageItem {...defaultProps} />);
|
||||
});
|
||||
|
||||
expect(screen.getByText('Copy')).toBeInTheDocument();
|
||||
});
|
||||
|
||||
it('does not render copy button while streaming', async () => {
|
||||
await act(async () => {
|
||||
renderWithProviders(
|
||||
<MessageItem
|
||||
{...defaultProps}
|
||||
status="streaming"
|
||||
isLastAssistantMessage={true}
|
||||
/>,
|
||||
);
|
||||
});
|
||||
|
||||
expect(screen.queryByText('Copy')).not.toBeInTheDocument();
|
||||
});
|
||||
|
||||
it('hides copy text on mobile', async () => {
|
||||
await act(async () => {
|
||||
renderWithProviders(<MessageItem {...defaultProps} isMobile={true} />);
|
||||
});
|
||||
|
||||
expect(screen.queryByText('Copy')).not.toBeInTheDocument();
|
||||
});
|
||||
});
|
||||
|
||||
describe('interactions', () => {
|
||||
it('calls onCopyToClipboard when copy button is clicked', async () => {
|
||||
const user = userEvent.setup();
|
||||
const onCopyToClipboard = jest.fn();
|
||||
|
||||
await act(async () => {
|
||||
renderWithProviders(
|
||||
<MessageItem
|
||||
{...defaultProps}
|
||||
onCopyToClipboard={onCopyToClipboard}
|
||||
/>,
|
||||
);
|
||||
});
|
||||
|
||||
await user.click(screen.getByText('Copy'));
|
||||
|
||||
expect(onCopyToClipboard).toHaveBeenCalledWith('Hello world');
|
||||
});
|
||||
});
|
||||
|
||||
describe('streaming state', () => {
|
||||
it('uses splitStreamingContent when streaming', async () => {
|
||||
// When streaming, content should be split into blocks + pending
|
||||
await act(async () => {
|
||||
renderWithProviders(
|
||||
<MessageItem
|
||||
{...defaultProps}
|
||||
message={{
|
||||
...defaultProps.message,
|
||||
content: 'Block 1\n\nPending content',
|
||||
}}
|
||||
status="streaming"
|
||||
isLastAssistantMessage={true}
|
||||
/>,
|
||||
);
|
||||
});
|
||||
|
||||
// The markdown content should contain "Block 1" but not necessarily "Pending"
|
||||
// since pending is rendered as raw text
|
||||
expect(
|
||||
screen.getByTestId('assistant-message-content'),
|
||||
).toBeInTheDocument();
|
||||
});
|
||||
});
|
||||
|
||||
describe('attachments', () => {
|
||||
it('renders AttachmentList when message has attachments', async () => {
|
||||
const messageWithAttachments = {
|
||||
...defaultProps.message,
|
||||
experimental_attachments: [
|
||||
{ url: 'https://example.com/file.pdf', name: 'file.pdf' },
|
||||
],
|
||||
};
|
||||
|
||||
await act(async () => {
|
||||
renderWithProviders(
|
||||
<MessageItem {...defaultProps} message={messageWithAttachments} />,
|
||||
);
|
||||
});
|
||||
|
||||
expect(screen.getByTestId('attachment-list')).toBeInTheDocument();
|
||||
});
|
||||
|
||||
it('does not render AttachmentList when no attachments', async () => {
|
||||
await act(async () => {
|
||||
renderWithProviders(<MessageItem {...defaultProps} />);
|
||||
});
|
||||
|
||||
expect(screen.queryByTestId('attachment-list')).not.toBeInTheDocument();
|
||||
});
|
||||
});
|
||||
|
||||
describe('feedback buttons', () => {
|
||||
it('renders FeedbackButtons for trace messages', async () => {
|
||||
await act(async () => {
|
||||
renderWithProviders(
|
||||
<MessageItem
|
||||
{...defaultProps}
|
||||
message={{ ...defaultProps.message, id: 'trace-123' }}
|
||||
/>,
|
||||
);
|
||||
});
|
||||
|
||||
expect(screen.getByTestId('feedback-buttons')).toBeInTheDocument();
|
||||
});
|
||||
|
||||
it('does not render FeedbackButtons for non-trace messages', async () => {
|
||||
await act(async () => {
|
||||
renderWithProviders(<MessageItem {...defaultProps} />);
|
||||
});
|
||||
|
||||
expect(screen.queryByTestId('feedback-buttons')).not.toBeInTheDocument();
|
||||
});
|
||||
});
|
||||
});
|
||||
+1
-20
@@ -1,5 +1,4 @@
|
||||
import { render, screen } from '@testing-library/react';
|
||||
import i18next from 'i18next';
|
||||
|
||||
import '@/i18n/initI18n';
|
||||
|
||||
@@ -10,26 +9,8 @@ describe('SuggestionCarousel', () => {
|
||||
jest.useFakeTimers();
|
||||
});
|
||||
|
||||
afterEach(async () => {
|
||||
afterEach(() => {
|
||||
jest.useRealTimers();
|
||||
await i18next.changeLanguage('en');
|
||||
});
|
||||
|
||||
it('should render all suggestions in french', async () => {
|
||||
await i18next.changeLanguage('fr');
|
||||
|
||||
render(<SuggestionCarousel messagesLength={0} />);
|
||||
|
||||
expect(screen.getAllByText('Poser une question')).toHaveLength(2);
|
||||
expect(
|
||||
screen.getByText('Transformer cette liste en liste à puces...'),
|
||||
).toBeInTheDocument();
|
||||
expect(
|
||||
screen.getByText('Écrire une description courte du produit...'),
|
||||
).toBeInTheDocument();
|
||||
expect(
|
||||
screen.getByText('Trouver les dernières actualités concernant...'),
|
||||
).toBeInTheDocument();
|
||||
});
|
||||
|
||||
it('should render all suggestions', () => {
|
||||
|
||||
@@ -4,10 +4,8 @@ import { persist } from 'zustand/middleware';
|
||||
interface ChatPreferencesState {
|
||||
selectedModelHrid: string | null;
|
||||
forceWebSearch: boolean;
|
||||
isDarkModePreference: boolean;
|
||||
isPanelOpen: boolean;
|
||||
setSelectedModelHrid: (hrid: string | null) => void;
|
||||
toggleDarkModePreferences: () => void;
|
||||
toggleForceWebSearch: () => void;
|
||||
setPanelOpen: (isOpen: boolean) => void;
|
||||
togglePanel: () => void;
|
||||
@@ -18,11 +16,8 @@ export const useChatPreferencesStore = create<ChatPreferencesState>()(
|
||||
(set) => ({
|
||||
selectedModelHrid: null,
|
||||
forceWebSearch: false,
|
||||
isDarkModePreference: false,
|
||||
isPanelOpen: false,
|
||||
setSelectedModelHrid: (hrid) => set({ selectedModelHrid: hrid }),
|
||||
toggleDarkModePreferences: () =>
|
||||
set((state) => ({ isDarkModePreference: !state.isDarkModePreference })),
|
||||
toggleForceWebSearch: () =>
|
||||
set((state) => ({ forceWebSearch: !state.forceWebSearch })),
|
||||
setPanelOpen: (isOpen) => set({ isPanelOpen: isOpen }),
|
||||
|
||||
@@ -1,32 +0,0 @@
|
||||
import { createHighlighterCore } from 'shiki/core';
|
||||
import { createOnigurumaEngine } from 'shiki/engine/oniguruma';
|
||||
import langBash from 'shiki/langs/bash.mjs';
|
||||
import langCss from 'shiki/langs/css.mjs';
|
||||
import langHtml from 'shiki/langs/html.mjs';
|
||||
import langJavascript from 'shiki/langs/javascript.mjs';
|
||||
import langJson from 'shiki/langs/json.mjs';
|
||||
import langMarkdown from 'shiki/langs/markdown.mjs';
|
||||
import langPython from 'shiki/langs/python.mjs';
|
||||
import langSql from 'shiki/langs/sql.mjs';
|
||||
import langTypescript from 'shiki/langs/typescript.mjs';
|
||||
import langYaml from 'shiki/langs/yaml.mjs';
|
||||
import themeDimmed from 'shiki/themes/github-dark-dimmed.mjs';
|
||||
|
||||
export const getHighlighter = () =>
|
||||
createHighlighterCore({
|
||||
themes: [themeDimmed],
|
||||
langs: [
|
||||
langJavascript,
|
||||
langTypescript,
|
||||
langPython,
|
||||
langBash,
|
||||
langJson,
|
||||
langHtml,
|
||||
langCss,
|
||||
langSql,
|
||||
langYaml,
|
||||
langMarkdown,
|
||||
],
|
||||
|
||||
engine: createOnigurumaEngine(import('shiki/wasm')),
|
||||
});
|
||||
@@ -173,8 +173,25 @@ export const InfoIcon = () => {
|
||||
>
|
||||
<path
|
||||
d="M12 15.5C12.2833 15.5 12.5208 15.4042 12.7125 15.2125C12.9042 15.0208 13 14.7833 13 14.5C13 14.2167 12.9042 13.9792 12.7125 13.7875C12.5208 13.5958 12.2833 13.5 12 13.5C11.7167 13.5 11.4792 13.5958 11.2875 13.7875C11.0958 13.9792 11 14.2167 11 14.5C11 14.7833 11.0958 15.0208 11.2875 15.2125C11.4792 15.4042 11.7167 15.5 12 15.5ZM11 11.5H13V5.5H11V11.5ZM2 22.5V4.5C2 3.95 2.19583 3.47917 2.5875 3.0875C2.97917 2.69583 3.45 2.5 4 2.5H20C20.55 2.5 21.0208 2.69583 21.4125 3.0875C21.8042 3.47917 22 3.95 22 4.5V16.5C22 17.05 21.8042 17.5208 21.4125 17.9125C21.0208 18.3042 20.55 18.5 20 18.5H6L2 22.5ZM5.15 16.5H20V4.5H4V17.625L5.15 16.5Z"
|
||||
fill="currentColor"
|
||||
fill="#265eaa"
|
||||
/>
|
||||
</svg>
|
||||
);
|
||||
};
|
||||
|
||||
// export const VisioIcon = () => {
|
||||
// return (
|
||||
// <svg
|
||||
// width="42"
|
||||
// height="43"
|
||||
// viewBox="0 0 42 43"
|
||||
// fill="none"
|
||||
// xmlns="http://www.w3.org/2000/svg"
|
||||
// >
|
||||
// <path
|
||||
// d="M14.1288 27.1205C13.8568 27.1205 13.6502 27.0399 13.5092 26.8787C13.3783 26.7074 13.3128 26.4908 13.3128 26.2289C13.3128 25.8562 13.4588 25.3676 13.751 24.7631C14.0431 24.1486 14.4814 23.5341 15.0656 22.9196C15.66 22.3051 16.4105 21.7913 17.3172 21.3783C18.2239 20.9552 19.2867 20.7436 20.5056 20.7436C21.7346 20.7436 22.7975 20.9552 23.694 21.3783C24.6007 21.7913 25.3512 22.3051 25.9456 22.9196C26.5399 23.5341 26.9832 24.1486 27.2754 24.7631C27.5675 25.3676 27.7136 25.8562 27.7136 26.2289C27.7136 26.4908 27.6431 26.7074 27.502 26.8787C27.3711 27.0399 27.1645 27.1205 26.8825 27.1205H14.1288ZM20.5056 19.6103C19.8407 19.6103 19.2363 19.439 18.6923 19.0965C18.1584 18.754 17.7302 18.2906 17.4079 17.7063C17.0855 17.1119 16.9243 16.442 16.9243 15.6965C16.9243 15.0014 17.0855 14.3617 17.4079 13.7774C17.7302 13.1931 18.1584 12.7297 18.6923 12.3872C19.2363 12.0346 19.8407 11.8583 20.5056 11.8583C21.1705 11.8583 21.7699 12.0346 22.3038 12.3872C22.8478 12.7297 23.281 13.1931 23.6034 13.7774C23.9257 14.3617 24.0869 15.0014 24.0869 15.6965C24.0869 16.442 23.9257 17.1119 23.6034 17.7063C23.281 18.2906 22.8478 18.754 22.3038 19.0965C21.7699 19.439 21.1705 19.6103 20.5056 19.6103ZM13.1465 38.1968C12.6227 38.1968 12.2147 38.0205 11.9226 37.6679C11.6405 37.3254 11.4994 36.862 11.4994 36.2777V32.3489H10.7741C9.27309 32.3489 8.0088 32.0819 6.98125 31.548C5.9537 31.004 5.17297 30.2182 4.63904 29.1907C4.1152 28.1631 3.85327 26.9089 3.85327 25.428V13.853C3.85327 12.3721 4.1152 11.1179 4.63904 10.0903C5.17297 9.06278 5.9537 8.28205 6.98125 7.74812C8.0088 7.20413 9.27309 6.93213 10.7741 6.93213H30.2371C31.7381 6.93213 33.0024 7.20413 34.03 7.74812C35.0575 8.28205 35.8332 9.06278 36.3571 10.0903C36.891 11.1179 37.158 12.3721 37.158 13.853V25.428C37.158 26.9089 36.891 28.1631 36.3571 29.1907C35.8332 30.2182 35.0575 31.004 34.03 31.548C33.0024 32.0819 31.7381 32.3489 30.2371 32.3489H20.5358L15.3225 36.9879C14.8692 37.3909 14.4864 37.6931 14.1741 37.8946C13.8618 38.0961 13.5193 38.1968 13.1465 38.1968ZM13.7661 35.4315L18.6016 30.6262C18.8837 30.3341 19.1557 30.1427 19.4176 30.052C19.6795 29.9613 20.0221 29.916 20.4452 29.916H30.2371C31.7583 29.916 32.8866 29.5382 33.622 28.7827C34.3574 28.017 34.7251 26.8938 34.7251 25.4129V13.853C34.7251 12.3822 34.3574 11.269 33.622 10.5134C32.8866 9.74782 31.7583 9.365 30.2371 9.365H10.7741C9.24287 9.365 8.10954 9.74782 7.37414 10.5134C6.64881 11.269 6.28615 12.3822 6.28615 13.853V25.4129C6.28615 26.8938 6.64881 28.017 7.37414 28.7827C8.10954 29.5382 9.24287 29.916 10.7741 29.916H12.6328C13.0458 29.916 13.338 30.0016 13.5092 30.1729C13.6805 30.3441 13.7661 30.6363 13.7661 31.0493V35.4315Z"
|
||||
// fill="currentColor"
|
||||
// />
|
||||
// </svg>
|
||||
// );
|
||||
// };
|
||||
|
||||
@@ -16,6 +16,7 @@ const BlueStripe = styled.div`
|
||||
position: absolute;
|
||||
height: 2px;
|
||||
width: 100%;
|
||||
background: var(--c--theme--colors--primary-600);
|
||||
top: 0;
|
||||
`;
|
||||
|
||||
@@ -128,15 +129,12 @@ export const Footer = () => {
|
||||
gap:0.2rem;
|
||||
transition: box-shadow 0.3s;
|
||||
&:hover {
|
||||
box-shadow: 0px 2px 0 0 var(--c--contextuals--content--semantic--neutral--tertiary);
|
||||
box-shadow: 0px 2px 0 0 var(--c--theme--colors--greyscale-text);
|
||||
}
|
||||
`}
|
||||
>
|
||||
<Text $weight="bold">{label}</Text>
|
||||
<IconLink
|
||||
width={18}
|
||||
color="var(--c--contextuals--content--semantic--neutral--primary)"
|
||||
/>
|
||||
<IconLink width={18} />
|
||||
</StyledLink>
|
||||
))}
|
||||
</Box>
|
||||
@@ -174,9 +172,7 @@ export const Footer = () => {
|
||||
$css={css`
|
||||
&:hover {
|
||||
box-shadow: 0px 2px 0 0
|
||||
var(
|
||||
--c--contextuals--content--semantic--neutral--tertiary
|
||||
);
|
||||
var(--c--theme--colors--greyscale-text);
|
||||
}
|
||||
`}
|
||||
>
|
||||
@@ -203,17 +199,14 @@ export const Footer = () => {
|
||||
$css={css`
|
||||
display: inline-flex;
|
||||
box-shadow: 0px 1px 0 0
|
||||
var(--c--contextuals--content--semantic--neutral--tertiary);
|
||||
var(--c--theme--colors--greyscale-text);
|
||||
gap: 0.2rem;
|
||||
`}
|
||||
>
|
||||
<Text $variation="tertiary" $theme="neutral">
|
||||
{bottomInformation.link.label}
|
||||
</Text>
|
||||
<IconLink
|
||||
width={14}
|
||||
color="var(--c--contextuals--content--semantic--neutral--primary)"
|
||||
/>
|
||||
<IconLink width={14} />
|
||||
</StyledLink>
|
||||
)}
|
||||
</Text>
|
||||
|
||||
@@ -1,6 +1,5 @@
|
||||
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24">
|
||||
<path
|
||||
fill="currentColor"
|
||||
d="M10 6v2H5v11h11v-5h2v6a1 1 0 0 1-1 1H4a1 1 0 0 1-1-1V7a1 1 0 0 1 1-1h6Zm11-3v8h-2V6.413l-7.793 7.794-1.414-1.414L17.585 5H13V3h8Z"
|
||||
/>
|
||||
</svg>
|
||||
|
||||
|
Before Width: | Height: | Size: 243 B After Width: | Height: | Size: 219 B |
@@ -24,10 +24,7 @@ import { LaGaufre } from './LaGaufre';
|
||||
|
||||
export const Header = () => {
|
||||
const { t } = useTranslation();
|
||||
const { spacingsTokens, colorsTokens, componentTokens } =
|
||||
useCunninghamTheme();
|
||||
const showLaGaufre =
|
||||
(componentTokens as Record<string, unknown>)['la-gaufre'] === true;
|
||||
const { spacingsTokens, colorsTokens } = useCunninghamTheme();
|
||||
const { isDesktop } = useResponsiveStore();
|
||||
const { setPanelOpen } = useChatPreferencesStore();
|
||||
const { isAtTop } = useChatScroll();
|
||||
@@ -98,7 +95,7 @@ export const Header = () => {
|
||||
>
|
||||
<ButtonLogin />
|
||||
<LanguagePicker />
|
||||
{showLaGaufre && <LaGaufre />}
|
||||
<LaGaufre />
|
||||
</Box>
|
||||
)}
|
||||
</Box>
|
||||
|
||||
@@ -1,210 +0,0 @@
|
||||
<svg width="386" height="384" viewBox="0 0 1025 1024" fill="none" xmlns="http://www.w3.org/2000/svg">
|
||||
<g filter="url(#filter0_n_386_10828)">
|
||||
<path d="M892.092 587C899.824 587 906.092 593.268 906.092 601V667.955C907.978 679.026 913.901 689.799 927.744 693.844C929.9 694.474 929.765 697.546 927.52 697.508C918.813 697.358 908.404 697.081 905.37 696.589C902.117 696.061 899.152 695.182 896.475 693.979C895.096 694.433 893.623 694.68 892.092 694.68H334C326.268 694.68 320 688.412 320 680.68V601C320 593.268 326.268 587 334 587H892.092Z" fill="#626A80"/>
|
||||
<path d="M892.092 587C899.824 587 906.092 593.268 906.092 601V667.955C907.978 679.026 913.901 689.799 927.744 693.844C929.9 694.474 929.765 697.546 927.52 697.508C918.813 697.358 908.404 697.081 905.37 696.589C902.117 696.061 899.152 695.182 896.475 693.979C895.096 694.433 893.623 694.68 892.092 694.68H334C326.268 694.68 320 688.412 320 680.68V601C320 593.268 326.268 587 334 587H892.092Z" fill="#181B24" fill-opacity="0.35"/>
|
||||
<path d="M892.092 587L892.092 585.5H892.092V587ZM906.092 667.955H904.592V668.082L904.613 668.207L906.092 667.955ZM927.744 693.844L928.165 692.404L928.165 692.404L927.744 693.844ZM927.52 697.508L927.494 699.008L927.494 699.008L927.52 697.508ZM905.37 696.589L905.13 698.069L905.13 698.07L905.37 696.589ZM896.475 693.979L897.089 692.61L896.558 692.372L896.005 692.554L896.475 693.979ZM892.092 694.68V696.18H892.092L892.092 694.68ZM334 694.68L334 696.18H334V694.68ZM320 680.68H318.5V680.68L320 680.68ZM334 587V585.5H334L334 587ZM892.092 587L892.092 588.5C898.995 588.5 904.592 594.097 904.592 601H906.092H907.592C907.592 592.44 900.652 585.5 892.092 585.5L892.092 587ZM906.092 601H904.592V667.955H906.092H907.592V601H906.092ZM906.092 667.955L904.613 668.207C906.561 679.638 912.755 691.026 927.323 695.284L927.744 693.844L928.165 692.404C915.047 688.571 909.395 678.413 907.57 667.703L906.092 667.955ZM927.744 693.844L927.323 695.283C927.528 695.343 927.634 695.443 927.693 695.53C927.761 695.63 927.79 695.747 927.784 695.846C927.782 695.894 927.772 695.928 927.763 695.949C927.759 695.96 927.755 695.966 927.753 695.97C927.75 695.973 927.749 695.975 927.748 695.975C927.748 695.975 927.748 695.976 927.746 695.977C927.745 695.978 927.739 695.981 927.729 695.985C927.709 695.993 927.653 696.01 927.545 696.008L927.52 697.508L927.494 699.008C928.419 699.023 929.252 698.71 929.862 698.105C930.454 697.516 930.741 696.749 930.78 696.006C930.859 694.52 929.959 692.928 928.165 692.404L927.744 693.844ZM927.52 697.508L927.545 696.008C923.196 695.933 918.428 695.827 914.372 695.678C910.273 695.527 907.016 695.336 905.61 695.108L905.37 696.589L905.13 698.07C906.758 698.334 910.222 698.527 914.262 698.676C918.346 698.826 923.136 698.933 927.494 699.008L927.52 697.508ZM905.37 696.589L905.61 695.108C902.475 694.599 899.637 693.755 897.089 692.61L896.475 693.979L895.86 695.347C898.666 696.608 901.758 697.522 905.13 698.069L905.37 696.589ZM896.475 693.979L896.005 692.554C894.775 692.959 893.46 693.18 892.092 693.18L892.092 694.68L892.092 696.18C893.785 696.18 895.416 695.906 896.944 695.403L896.475 693.979ZM892.092 694.68V693.18H334V694.68V696.18H892.092V694.68ZM334 694.68L334 693.18C327.096 693.18 321.5 687.583 321.5 680.68L320 680.68L318.5 680.68C318.5 689.24 325.44 696.18 334 696.18L334 694.68ZM320 680.68H321.5V601H320H318.5V680.68H320ZM320 601H321.5C321.5 594.096 327.096 588.5 334 588.5L334 587L334 585.5C325.44 585.5 318.5 592.44 318.5 601H320ZM334 587V588.5H892.092V587V585.5H334V587Z" fill="#626A80"/>
|
||||
<path d="M892.092 587L892.092 585.5H892.092V587ZM906.092 667.955H904.592V668.082L904.613 668.207L906.092 667.955ZM927.744 693.844L928.165 692.404L928.165 692.404L927.744 693.844ZM927.52 697.508L927.494 699.008L927.494 699.008L927.52 697.508ZM905.37 696.589L905.13 698.069L905.13 698.07L905.37 696.589ZM896.475 693.979L897.089 692.61L896.558 692.372L896.005 692.554L896.475 693.979ZM892.092 694.68V696.18H892.092L892.092 694.68ZM334 694.68L334 696.18H334V694.68ZM320 680.68H318.5V680.68L320 680.68ZM334 587V585.5H334L334 587ZM892.092 587L892.092 588.5C898.995 588.5 904.592 594.097 904.592 601H906.092H907.592C907.592 592.44 900.652 585.5 892.092 585.5L892.092 587ZM906.092 601H904.592V667.955H906.092H907.592V601H906.092ZM906.092 667.955L904.613 668.207C906.561 679.638 912.755 691.026 927.323 695.284L927.744 693.844L928.165 692.404C915.047 688.571 909.395 678.413 907.57 667.703L906.092 667.955ZM927.744 693.844L927.323 695.283C927.528 695.343 927.634 695.443 927.693 695.53C927.761 695.63 927.79 695.747 927.784 695.846C927.782 695.894 927.772 695.928 927.763 695.949C927.759 695.96 927.755 695.966 927.753 695.97C927.75 695.973 927.749 695.975 927.748 695.975C927.748 695.975 927.748 695.976 927.746 695.977C927.745 695.978 927.739 695.981 927.729 695.985C927.709 695.993 927.653 696.01 927.545 696.008L927.52 697.508L927.494 699.008C928.419 699.023 929.252 698.71 929.862 698.105C930.454 697.516 930.741 696.749 930.78 696.006C930.859 694.52 929.959 692.928 928.165 692.404L927.744 693.844ZM927.52 697.508L927.545 696.008C923.196 695.933 918.428 695.827 914.372 695.678C910.273 695.527 907.016 695.336 905.61 695.108L905.37 696.589L905.13 698.07C906.758 698.334 910.222 698.527 914.262 698.676C918.346 698.826 923.136 698.933 927.494 699.008L927.52 697.508ZM905.37 696.589L905.61 695.108C902.475 694.599 899.637 693.755 897.089 692.61L896.475 693.979L895.86 695.347C898.666 696.608 901.758 697.522 905.13 698.069L905.37 696.589ZM896.475 693.979L896.005 692.554C894.775 692.959 893.46 693.18 892.092 693.18L892.092 694.68L892.092 696.18C893.785 696.18 895.416 695.906 896.944 695.403L896.475 693.979ZM892.092 694.68V693.18H334V694.68V696.18H892.092V694.68ZM334 694.68L334 693.18C327.096 693.18 321.5 687.583 321.5 680.68L320 680.68L318.5 680.68C318.5 689.24 325.44 696.18 334 696.18L334 694.68ZM320 680.68H321.5V601H320H318.5V680.68H320ZM320 601H321.5C321.5 594.096 327.096 588.5 334 588.5L334 587L334 585.5C325.44 585.5 318.5 592.44 318.5 601H320ZM334 587V588.5H892.092V587V585.5H334V587Z" fill="#181B24" fill-opacity="0.35"/>
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<feFlood flood-opacity="0" result="BackgroundImageFix"/>
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<feBlend mode="normal" in="SourceGraphic" in2="BackgroundImageFix" result="shape"/>
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<feTurbulence type="fractalNoise" baseFrequency="1 1" stitchTiles="stitch" numOctaves="3" result="noise" seed="1493" />
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<feColorMatrix in="noise" type="luminanceToAlpha" result="alphaNoise" />
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<feComponentTransfer in="alphaNoise" result="coloredNoise1">
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</feComponentTransfer>
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<feComposite operator="in" in2="shape" in="coloredNoise1" result="noise1Clipped" />
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<feFlood flood-color="rgba(131, 131, 131, 0.27)" result="color1Flood" />
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<feComposite operator="in" in2="noise1Clipped" in="color1Flood" result="color1" />
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<feMerge result="effect1_noise_386_10828">
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<feMergeNode in="shape" />
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<feMergeNode in="color1" />
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</feMerge>
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<feColorMatrix in="SourceAlpha" type="matrix" values="0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 127 0" result="hardAlpha"/>
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<feOffset dx="3" dy="4"/>
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<feComposite in2="hardAlpha" operator="out"/>
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<feColorMatrix type="matrix" values="0 0 0 0 0.0941176 0 0 0 0 0.105882 0 0 0 0 0.141176 0 0 0 0.25 0"/>
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<feBlend mode="normal" in2="BackgroundImageFix" result="effect1_dropShadow_386_10828"/>
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<feBlend mode="normal" in="SourceGraphic" in2="effect1_dropShadow_386_10828" result="shape"/>
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</filter>
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<clipPath id="clip0_386_10828">
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<rect x="788.178" y="232.646" width="84.6173" height="112.823" rx="12.5359" transform="rotate(-9.63619 788.178 232.646)" fill="white"/>
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</clipPath>
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<clipPath id="clip1_386_10828">
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<rect x="481.391" y="654.445" width="84.2274" height="112.303" rx="12.4781" transform="rotate(-9.63619 481.391 654.445)" fill="white"/>
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</clipPath>
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<clipPath id="clip2_386_10828">
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<rect x="305.475" y="80.6992" width="85.801" height="114.401" rx="12.7113" transform="rotate(11.9505 305.475 80.6992)" fill="white"/>
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</clipPath>
|
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</defs>
|
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</svg>
|
||||
|
Before Width: | Height: | Size: 95 KiB |
@@ -12,14 +12,13 @@ import { gotoLogin } from '@/features/auth';
|
||||
// import { ProConnectButton } from '@/features/auth';
|
||||
import { useResponsiveStore } from '@/stores';
|
||||
|
||||
import BannerDarkMode from '../assets/banner-dark.svg';
|
||||
import Banner from '../assets/banner.svg';
|
||||
|
||||
import { getHeaderHeight } from './HomeHeader';
|
||||
|
||||
export default function HomeBanner() {
|
||||
const { t } = useTranslation();
|
||||
const { spacingsTokens, colorsTokens, componentTokens, isDarkMode } =
|
||||
const { spacingsTokens, colorsTokens, componentTokens } =
|
||||
useCunninghamTheme();
|
||||
const { isMobile, isSmallMobile } = useResponsiveStore();
|
||||
const withProConnect = Boolean(
|
||||
@@ -108,7 +107,7 @@ export default function HomeBanner() {
|
||||
</Button>
|
||||
</Box>
|
||||
</Box>
|
||||
{!isMobile && (isDarkMode ? <BannerDarkMode /> : <Banner />)}
|
||||
{!isMobile && <Banner />}
|
||||
</Box>
|
||||
</Box>
|
||||
);
|
||||
|
||||
@@ -26,8 +26,6 @@ export const HomeHeader = () => {
|
||||
const logo = (componentTokens as Record<string, unknown>).logo as
|
||||
| { src: string; alt: string; widthHeader: string; widthFooter: string }
|
||||
| undefined;
|
||||
const showLaGaufre =
|
||||
(componentTokens as Record<string, unknown>)['la-gaufre'] === true;
|
||||
|
||||
return (
|
||||
<Box
|
||||
@@ -81,7 +79,7 @@ export const HomeHeader = () => {
|
||||
<Box $direction="row" $gap="1rem" $align="center">
|
||||
<ButtonLogin />
|
||||
<LanguagePicker />
|
||||
{showLaGaufre && <LaGaufre />}
|
||||
<LaGaufre />
|
||||
</Box>
|
||||
)}
|
||||
</Box>
|
||||
|
||||
+42
-32
@@ -2,6 +2,7 @@ import { Modal, ModalSize } from '@openfun/cunningham-react';
|
||||
import { useTranslation } from 'react-i18next';
|
||||
|
||||
import { Box, StyledLink, Text, ToggleSwitch, useToast } from '@/components';
|
||||
import { HorizontalSeparator } from '@/components/separators/HorizontalSeparator';
|
||||
import { useUserUpdate } from '@/core/api/useUserUpdate';
|
||||
import { useCunninghamTheme } from '@/cunningham';
|
||||
import { useAuthQuery } from '@/features/auth/api';
|
||||
@@ -55,7 +56,7 @@ export const SettingsModal = ({ onClose, isOpen }: SettingsModalProps) => {
|
||||
title={t('Assistant settings')}
|
||||
>
|
||||
<Box aria-label={t('Assistant settings')}>
|
||||
<Box $justify="space-between">
|
||||
<Box $align="center" $justify="space-between">
|
||||
<Box $gap="2xs">
|
||||
<Text
|
||||
$size="xs"
|
||||
@@ -65,10 +66,49 @@ export const SettingsModal = ({ onClose, isOpen }: SettingsModalProps) => {
|
||||
$padding={{ top: 'sm', bottom: 'sm' }}
|
||||
>
|
||||
{t(
|
||||
'The Assistant is a sovereign AI for public servants. It helps with daily tasks (rephrasing, summarising, translating, information search). Your data stays in France on secure, state-compliant infrastructure and is never used for commercial purposes.',
|
||||
'The Assistant is a sovereign conversational AI designed for public servants. It helps you save time on daily tasks like rephrasing, summarising, translating, or searching information. Your data never leaves France and is stored on secure, state-compliant infrastructures. It is never used for commercial purposes.',
|
||||
)}
|
||||
</Text>
|
||||
|
||||
<Box $gap="2xs" $padding={{ top: 'md' }}>
|
||||
<Text
|
||||
$size="md"
|
||||
$weight="500"
|
||||
$theme="greyscale"
|
||||
$variation="850"
|
||||
>
|
||||
{t('Dark mode')}
|
||||
</Text>
|
||||
<Box
|
||||
$direction="row"
|
||||
$justify="space-between"
|
||||
$align="flex-start"
|
||||
>
|
||||
<Box $css="max-width: 70%;">
|
||||
<Text
|
||||
$css={`
|
||||
display: inline-block;
|
||||
`}
|
||||
$size="xs"
|
||||
$theme="greyscale"
|
||||
$variation="600"
|
||||
$weight="400"
|
||||
>
|
||||
{t(
|
||||
'Enable dark mode to reduce eye strain in low-light environments.',
|
||||
)}
|
||||
</Text>
|
||||
</Box>
|
||||
<ToggleSwitch
|
||||
checked={isDarkMode}
|
||||
onChange={() => toggleDarkMode()}
|
||||
aria-label={t('Dark mode')}
|
||||
/>
|
||||
</Box>
|
||||
</Box>
|
||||
|
||||
<HorizontalSeparator />
|
||||
|
||||
<Text
|
||||
$size="md"
|
||||
$weight="500"
|
||||
@@ -121,36 +161,6 @@ export const SettingsModal = ({ onClose, isOpen }: SettingsModalProps) => {
|
||||
aria-label={t('Allow conversation analysis')}
|
||||
/>
|
||||
</Box>
|
||||
<Box
|
||||
$display="block"
|
||||
$justify="space-between"
|
||||
$align="flex-end"
|
||||
$gap="2xs"
|
||||
$padding={{ top: 'md' }}
|
||||
$css="min-width: 100%;"
|
||||
>
|
||||
<Box
|
||||
$direction="row"
|
||||
$justify="space-between"
|
||||
$css="min-width: 70%;"
|
||||
>
|
||||
<Box $css="min-width: 70%;">
|
||||
<Text
|
||||
$size="md"
|
||||
$weight="500"
|
||||
$theme="greyscale"
|
||||
$variation="850"
|
||||
>
|
||||
{t('Dark mode')}
|
||||
</Text>
|
||||
</Box>
|
||||
<ToggleSwitch
|
||||
checked={isDarkMode}
|
||||
onChange={() => toggleDarkMode()}
|
||||
aria-label={t('Dark mode')}
|
||||
/>
|
||||
</Box>
|
||||
</Box>
|
||||
</Box>
|
||||
</Box>
|
||||
</Modal>
|
||||
|
||||
@@ -1,15 +1,6 @@
|
||||
{
|
||||
"de": {
|
||||
"translation": {
|
||||
"ABC-1234-XY": "ABC-1234-XY"
|
||||
}
|
||||
},
|
||||
"en": {
|
||||
"translation": {
|
||||
"Login": "Login",
|
||||
"Logout": "Logout"
|
||||
}
|
||||
},
|
||||
"de": { "translation": { "ABC-1234-XY": "ABC-1234-XY" } },
|
||||
"en": { "translation": { "Login": "Login", "Logout": "Logout" } },
|
||||
"fr": {
|
||||
"translation": {
|
||||
"30 sec to tell us what you think or report a bug": "Prenez 30 secondes pour partager votre avis ou signaler un bug",
|
||||
@@ -25,13 +16,13 @@
|
||||
"An error occurred while renaming the conversation": "Une erreur est survenue lors du renommage de la conversation",
|
||||
"An error occurred. Please try again.": "Une erreur s'est produite. Veuillez réessayer.",
|
||||
"Are you sure you want to delete this conversation ?": "Êtes-vous sûr de vouloir supprimer cette conversation ?",
|
||||
"Ask a question": "Poser une question",
|
||||
"Assistant IA replied: ": "Assistant IA a répondu : ",
|
||||
"Assistant is already available, log in to use it now.": "L'Assistant est déjà disponible, connectez-vous pour l'utiliser maintenant.",
|
||||
"Assistant is in development: your feedback matters! Choose how to share your ideas:": "L'assistant est en cours de développement : vos commentaires sont importants ! Choisissez comment partager vos avis :",
|
||||
"Assistant settings": "Paramètres de l'Assistant",
|
||||
"Attach file": "Joindre un fichier",
|
||||
"Attachment summary not supported": "Résumé des pièces jointes non pris en charge",
|
||||
"Available soon": "Disponible prochainement",
|
||||
"Cancel": "Annuler",
|
||||
"Clear search": "Effacer la recherche",
|
||||
"Close model selector": "Fermer le sélecteur de modèle",
|
||||
@@ -46,7 +37,6 @@
|
||||
"Copied": "Copié",
|
||||
"Copy": "Copier",
|
||||
"Copy code": "Copier le code",
|
||||
"Dark mode": "Mode sombre",
|
||||
"Default": "Par défaut",
|
||||
"Delete": "Supprimer",
|
||||
"Delete a conversation": "Supprimer une conversation",
|
||||
@@ -54,8 +44,6 @@
|
||||
"Direct exchange with our team": "Échange direct avec notre équipe",
|
||||
"Enter your message or a question": "Entrez votre message ou une question",
|
||||
"Explore other LaSuite apps": "Explorer les autres applications de LaSuite",
|
||||
"Extracting document: {{documents}} ...": "Extraction du document : {{documents}}...",
|
||||
"Extracting documents: {{documents}} ...": "Extraction des documents : {{documents}}...",
|
||||
"Failed to activate account. Please try again.": "Échec de l'activation du compte. Veuillez réessayer.",
|
||||
"Failed to copy": "Échec de la copie",
|
||||
"Failed to register for notifications. Please try again.": "Échec de l'inscription aux notifications. Veuillez réessayer.",
|
||||
@@ -66,7 +54,6 @@
|
||||
"Feedback Négatif": "Retour négatif",
|
||||
"Feedback positif": "Retour positif",
|
||||
"File type not supported": "Type de fichier non pris en charge",
|
||||
"Find recent news about...": "Trouver les dernières actualités concernant...",
|
||||
"Get notified about the Public Beta.": "Soyez informé de la Bêta publique.",
|
||||
"Get notified for the public beta": "Être notifié pour la bêta publique",
|
||||
"Give a quick opinion": "Donner un avis rapide",
|
||||
@@ -74,11 +61,13 @@
|
||||
"History": "Historique",
|
||||
"Home": "Accueil",
|
||||
"If enabled, this allows us to analyse your exchanges to improve the Assistant. If disabled, all conversations remain confidential and are not used in any way. ": "Si cette option est activée, cela nous permet d'analyser vos conversations afin d'améliorer l'Assistant. Si elle est désactivée, toutes les conversations restent confidentielles et ne sont utilisées d'aucune manière. ",
|
||||
"Illustration": "Image",
|
||||
"Image 401": "Image 401",
|
||||
"Image 403": "Image 403",
|
||||
"Invalid activation code. Please check and try again.": "Code d'activation invalide. Veuillez le vérifier et réessayer.",
|
||||
"It seems that the page you are looking for does not exist or cannot be displayed correctly.": "Il semble que la page que vous cherchez n'existe pas ou ne puisse pas être affichée correctement.",
|
||||
"Know more": "En savoir plus",
|
||||
"Language": "Langue",
|
||||
"Learn more about data usage.": "En savoir plus sur l’usage des données.",
|
||||
"Load more": "Afficher plus",
|
||||
"Log in to access this page.": "Connectez-vous pour accéder à cette page.",
|
||||
@@ -108,7 +97,6 @@
|
||||
"Search results": "Résultats de la recherche",
|
||||
"Search...": "Recherche...",
|
||||
"Select": "Sélectionner",
|
||||
"Select language": "Sélectionnez une langue",
|
||||
"Select model": "Sélectionner un modèle",
|
||||
"Send": "Envoyer",
|
||||
"Settings": "Réglages",
|
||||
@@ -120,15 +108,13 @@
|
||||
"Start conversation": "Entamer la conversation",
|
||||
"Stop": "Stop",
|
||||
"Summarizing...": "Résumé en cours...",
|
||||
"Translation in progress...": "Traduction en cours...",
|
||||
"The Assistant is a sovereign AI for public servants. It helps with daily tasks (rephrasing, summarising, translating, information search). Your data stays in France on secure, state-compliant infrastructure and is never used for commercial purposes.": "L'Assistant est une IA souveraine destinée aux fonctionnaires. Il les aide dans leurs tâches quotidiennes (reformulation, résumé, traduction, recherche d'informations). Vos données restent en France, sur une infrastructure sécurisée et conforme aux normes nationales, et ne sont jamais utilisées à des fins commerciales.",
|
||||
"The Assistant is a sovereign conversational AI designed for public servants. It helps you save time on daily tasks like rephrasing, summarising, translating, or searching information. Your data never leaves France and is stored on secure, state-compliant infrastructures. It is never used for commercial purposes.": "L'Assistant est une IA souveraine conçue pour les fonctionnaires. Il vous permet de gagner du temps sur des tâches quotidiennes telles que la reformulation, le résumé, la traduction ou la recherche d'informations. Vos données ne quittent jamais la France et sont stockées sur des infrastructures sûres et conformes à l'état et ne sont jamais utilisées à des fins commerciales.",
|
||||
"The Assistant is in Beta": "L'Assistant est en Bêta",
|
||||
"The conversation has been deleted.": "La conversation a été supprimée.",
|
||||
"The conversation has been renamed.": "La conversation a été renommée.",
|
||||
"The summary feature is not supported yet.": "La fonctionnalité de résumé n'est pas encore prise en charge.",
|
||||
"Thinking...": "Réflexion...",
|
||||
"To add a file to the conversation, drop it here.": "Pour ajouter un fichier à la conversation, déposez-le ici.",
|
||||
"Turn this list into bullet points": "Transformer cette liste en liste à puces...",
|
||||
"Unlock access": "Déverrouiller l'accès",
|
||||
"Unlocking...": "Déverrouillage en cours...",
|
||||
"Untitled conversation": "Conversation sans titre",
|
||||
@@ -138,7 +124,6 @@
|
||||
"We'll email you when the public beta opens.": "Nous vous enverrons un email quand la bêta publique sera ouverte.",
|
||||
"Web": "Web",
|
||||
"What is on your mind?": "Qu’avez-vous en tête ?",
|
||||
"Write a short product description": "Écrire une description courte du produit...",
|
||||
"Write on Tchap": "Écrire sur Tchap",
|
||||
"You are on the list": "Vous êtes dans la liste",
|
||||
"You do not have permission to view this page.": "Vous n’avez pas la permission de voir cette page.",
|
||||
@@ -166,13 +151,13 @@
|
||||
"An error occurred while renaming the conversation": "Er is een fout opgetreden bij het hernoemen van het gesprek",
|
||||
"An error occurred. Please try again.": "Er is een fout opgetreden. Probeer het opnieuw.",
|
||||
"Are you sure you want to delete this conversation ?": "Weet u zeker dat u dit gesprek wilt verwijderen?",
|
||||
"Ask a question": "Stel een vraag",
|
||||
"Assistant IA replied: ": "AI Assistent antwoordde: ",
|
||||
"Assistant is already available, log in to use it now.": "Assistent is al beschikbaar, log in om het nu te gebruiken.",
|
||||
"Assistant is in development: your feedback matters! Choose how to share your ideas:": "Assistent is in ontwikkeling: uw feedback telt! Kies hoe u uw ideeën wilt delen:",
|
||||
"Assistant settings": "Assistentinstellingen",
|
||||
"Attach file": "Bestand bijvoegen",
|
||||
"Attachment summary not supported": "Bijlageoverzicht niet ondersteund",
|
||||
"Available soon": "Binnenkort beschikbaar",
|
||||
"Cancel": "Annuleren",
|
||||
"Clear search": "Zoekopdracht wissen",
|
||||
"Close model selector": "Sluit modelselector",
|
||||
@@ -187,7 +172,6 @@
|
||||
"Copied": "Gekopieerd",
|
||||
"Copy": "Kopiëren",
|
||||
"Copy code": "Kopieer code",
|
||||
"Dark mode": "Donkere modus",
|
||||
"Default": "Standaard",
|
||||
"Delete": "Verwijderen",
|
||||
"Delete a conversation": "Een gesprek verwijderen",
|
||||
@@ -195,8 +179,6 @@
|
||||
"Direct exchange with our team": "Directe uitwisseling met ons team",
|
||||
"Enter your message or a question": "Voer uw bericht of een vraag in",
|
||||
"Explore other LaSuite apps": "Ontdek andere LaSuite-apps",
|
||||
"Extracting document: {{documents}} ...": "Document uitpakken: {{documents}}...",
|
||||
"Extracting documents: {{documents}} ...": "Documenten uitpakken: {{documents}}...",
|
||||
"Failed to activate account. Please try again.": "Account activeren mislukt. Probeer het opnieuw.",
|
||||
"Failed to copy": "Kopiëren mislukt",
|
||||
"Failed to register for notifications. Please try again.": "Registratie voor meldingen mislukt. Probeer het opnieuw.",
|
||||
@@ -207,7 +189,6 @@
|
||||
"Feedback Négatif": "Negatieve feedback",
|
||||
"Feedback positif": "Positieve feedback",
|
||||
"File type not supported": "Bestandstype niet ondersteund",
|
||||
"Find recent news about...": "Vind het laatste nieuws over...",
|
||||
"Get notified about the Public Beta.": "Ontvang een melding over de openbare bèta.",
|
||||
"Get notified for the public beta": "Ontvang een melding voor de openbare bètaversie",
|
||||
"Give a quick opinion": "Geef snel een mening",
|
||||
@@ -215,11 +196,13 @@
|
||||
"History": "Geschiedenis",
|
||||
"Home": "Thuis",
|
||||
"If enabled, this allows us to analyse your exchanges to improve the Assistant. If disabled, all conversations remain confidential and are not used in any way. ": "Indien ingeschakeld, kunnen we uw gesprekken analyseren om de Assistent te verbeteren. Indien uitgeschakeld, blijven alle gesprekken vertrouwelijk en worden ze op geen enkele manier gebruikt. ",
|
||||
"Illustration": "Illustratie",
|
||||
"Image 401": "Afbeelding 401",
|
||||
"Image 403": "Afbeelding 403",
|
||||
"Invalid activation code. Please check and try again.": "Ongeldige activeringscode. Controleer en probeer het opnieuw.",
|
||||
"It seems that the page you are looking for does not exist or cannot be displayed correctly.": "Het lijkt erop dat de pagina die u zoekt niet bestaat of niet correct kan worden weergegeven.",
|
||||
"Know more": "Meer weten",
|
||||
"Language": "Taal",
|
||||
"Learn more about data usage.": "Meer informatie over datagebruik.",
|
||||
"Load more": "Laad Meer",
|
||||
"Log in to access this page.": "Meld u aan om deze pagina te zien.",
|
||||
@@ -249,7 +232,6 @@
|
||||
"Search results": "Zoekresultaten",
|
||||
"Search...": "Zoek...",
|
||||
"Select": "Selecteer",
|
||||
"Select language": "Selecteer taal",
|
||||
"Select model": "Selecteer model",
|
||||
"Send": "Verstuur",
|
||||
"Settings": "Instellingen",
|
||||
@@ -261,15 +243,13 @@
|
||||
"Start conversation": "Begin een gesprek",
|
||||
"Stop": "Stop",
|
||||
"Summarizing...": "Samenvatten...",
|
||||
"Translation in progress...": "Vertaling bezig...",
|
||||
"The Assistant is a sovereign AI for public servants. It helps with daily tasks (rephrasing, summarising, translating, information search). Your data stays in France on secure, state-compliant infrastructure and is never used for commercial purposes.": "De assistent is een soevereine AI voor overheidsambtenaren. Het helpt met dagelijkse taken (herformuleren, samenvatten, vertalen, informatiezoeken). Je gegevens blijven in Nederland op een veilige, door de staat compatibele infrastructuur en worden nooit voor commerciële doeleinden gebruikt.",
|
||||
"The Assistant is a sovereign conversational AI designed for public servants. It helps you save time on daily tasks like rephrasing, summarising, translating, or searching information. Your data never leaves France and is stored on secure, state-compliant infrastructures. It is never used for commercial purposes.": "De Assistent is een soevereine conversationele AI, ontworpen voor ambtenaren. Het helpt je tijd te besparen bij dagelijkse taken zoals het herformuleren, samenvatten, vertalen of zoeken van informatie. Je gegevens verlaten het land nooit en worden opgeslagen op beveiligde, door de overheid goedgekeurde infrastructuren. Ze worden nooit gebruikt voor commerciële doeleinden.",
|
||||
"The Assistant is in Beta": "De Assistent is in bèta",
|
||||
"The conversation has been deleted.": "Het gesprek is verwijderd.",
|
||||
"The conversation has been renamed.": "Het gesprek is verwijderd.",
|
||||
"The summary feature is not supported yet.": "De samenvattingsfunctie wordt nog niet ondersteund.",
|
||||
"Thinking...": "Denken...",
|
||||
"To add a file to the conversation, drop it here.": "Als u een bestand aan het gesprek wilt toevoegen, sleept u het hierheen.",
|
||||
"Turn this list into bullet points": "Zet deze lijst om in opsommingstekens",
|
||||
"Unlock access": "Toegang ontgrendelen",
|
||||
"Unlocking...": "Ontgrendelen...",
|
||||
"Untitled conversation": "Ongetiteld gesprek",
|
||||
@@ -279,7 +259,6 @@
|
||||
"We'll email you when the public beta opens.": "We sturen u een e-mail zodra de openbare bètaversie beschikbaar is.",
|
||||
"Web": "Internet",
|
||||
"What is on your mind?": "Waar denk je aan?",
|
||||
"Write a short product description": "Schrijf een korte productbeschrijving",
|
||||
"Write on Tchap": "Schrijf op Tchap",
|
||||
"You are on the list": "Je staat op de lijst",
|
||||
"You do not have permission to view this page.": "U heeft geen toestemming om deze pagina te bekijken.",
|
||||
@@ -307,13 +286,13 @@
|
||||
"An error occurred while renaming the conversation": "Ошибка при переименовании беседы",
|
||||
"An error occurred. Please try again.": "Произошла ошибка. Пожалуйста, повторите попытку.",
|
||||
"Are you sure you want to delete this conversation ?": "Вы действительно хотите удалить эту беседу?",
|
||||
"Ask a question": "Задать вопрос",
|
||||
"Assistant IA replied: ": "Помощник ИИ ответил: ",
|
||||
"Assistant is already available, log in to use it now.": "Помощник уже доступен, просто войдите в систему.",
|
||||
"Assistant is in development: your feedback matters! Choose how to share your ideas:": "Помощник находится в разработке: ваши отзывы важны! Выберите, как поделиться своими идеями:",
|
||||
"Assistant settings": "Настройки помощника",
|
||||
"Attach file": "Прикрепить файл",
|
||||
"Attachment summary not supported": "Сводка о вложениях не поддерживается",
|
||||
"Available soon": "Скоро будет доступно",
|
||||
"Cancel": "Отмена",
|
||||
"Clear search": "Очистить поиск",
|
||||
"Close model selector": "Закрыть выбор модели",
|
||||
@@ -328,7 +307,6 @@
|
||||
"Copied": "Скопировано",
|
||||
"Copy": "Копировать",
|
||||
"Copy code": "Скопировать код",
|
||||
"Dark mode": "Тёмный режим",
|
||||
"Default": "По-умолчанию",
|
||||
"Delete": "Удалить",
|
||||
"Delete a conversation": "Удалить беседу",
|
||||
@@ -336,8 +314,6 @@
|
||||
"Direct exchange with our team": "Прямое общение с нашей командой",
|
||||
"Enter your message or a question": "Введите сообщение или вопрос",
|
||||
"Explore other LaSuite apps": "Посмотреть другие приложения LaSuite",
|
||||
"Extracting document: {{documents}} ...": "Извлечение документа: {{documents}}...",
|
||||
"Extracting documents: {{documents}} ...": "Извлечение документов: {{documents}}...",
|
||||
"Failed to activate account. Please try again.": "Не удалось активировать учётную запись. Пожалуйста, попробуйте снова.",
|
||||
"Failed to copy": "Не удалось скопировать",
|
||||
"Failed to register for notifications. Please try again.": "Не удалось зарегистрироваться для получения уведомлений. Пожалуйста, попробуйте ещё раз.",
|
||||
@@ -348,7 +324,6 @@
|
||||
"Feedback Négatif": "Отрицательный отзыв",
|
||||
"Feedback positif": "Положительный отзыв",
|
||||
"File type not supported": "Тип файла не поддерживается",
|
||||
"Find recent news about...": "Найти последние новости...",
|
||||
"Get notified about the Public Beta.": "Получать уведомления о публичной бета-версии.",
|
||||
"Get notified for the public beta": "Получать уведомления о публичной бета-версии",
|
||||
"Give a quick opinion": "Оставить быстрый отзыв",
|
||||
@@ -356,11 +331,13 @@
|
||||
"History": "История",
|
||||
"Home": "Главная",
|
||||
"If enabled, this allows us to analyse your exchanges to improve the Assistant. If disabled, all conversations remain confidential and are not used in any way. ": "Если этот параметр включён, мы можем анализировать ваши беседы для улучшения интеллекта помощника. Если отключён, то все разговоры остаются конфиденциальными и никак не используются. ",
|
||||
"Illustration": "Иллюстрация",
|
||||
"Image 401": "Изображение 401",
|
||||
"Image 403": "Изображение 403",
|
||||
"Invalid activation code. Please check and try again.": "Неверный код активации. Пожалуйста, проверьте его и повторите попытку.",
|
||||
"It seems that the page you are looking for does not exist or cannot be displayed correctly.": "Похоже, страница, которую вы ищете, не существует или не может быть правильно отображена.",
|
||||
"Know more": "Подробнее",
|
||||
"Language": "Язык",
|
||||
"Learn more about data usage.": "Узнайте больше об использовании данных.",
|
||||
"Load more": "Загрузить ещё",
|
||||
"Log in to access this page.": "Войдите, чтобы получить доступ к этой странице.",
|
||||
@@ -390,7 +367,6 @@
|
||||
"Search results": "Результаты поиска",
|
||||
"Search...": "Поиск...",
|
||||
"Select": "Выбрать",
|
||||
"Select language": "Выберите язык",
|
||||
"Select model": "Выберите модель",
|
||||
"Send": "Отправить",
|
||||
"Settings": "Настройки",
|
||||
@@ -402,15 +378,13 @@
|
||||
"Start conversation": "Начать беседу",
|
||||
"Stop": "Остановить",
|
||||
"Summarizing...": "Обобщение...",
|
||||
"Translation in progress...": "Перевод выполняется...",
|
||||
"The Assistant is a sovereign AI for public servants. It helps with daily tasks (rephrasing, summarising, translating, information search). Your data stays in France on secure, state-compliant infrastructure and is never used for commercial purposes.": "Помощник — независимый ИИ для государственных служащих. Он помогает в выполнении повседневных задач (перефразирование, резюмирование, перевод, поиск информации). Ваши данные хранятся во Франции на безопасной инфраструктуре, соответствующей государственным требованиям, и никогда не используются в коммерческих целях.",
|
||||
"The Assistant is a sovereign conversational AI designed for public servants. It helps you save time on daily tasks like rephrasing, summarising, translating, or searching information. Your data never leaves France and is stored on secure, state-compliant infrastructures. It is never used for commercial purposes.": "Помощник - собеседник на основе ИИ для государственных служащих. Он поможет вам сэкономить время на ежедневных задачах, таких как перефразирование, обобщение, перевод или поиск информации. Ваши данные никогда не покидают Францию и хранятся в охраняемой государственной инфраструктуре, которая никогда не используется в коммерческих целях.",
|
||||
"The Assistant is in Beta": "Помощник находится на этапе Бета-версии",
|
||||
"The conversation has been deleted.": "Беседа была удалена.",
|
||||
"The conversation has been renamed.": "Беседа была переименована.",
|
||||
"The summary feature is not supported yet.": "Функция сводки пока не поддерживается.",
|
||||
"Thinking...": "Размышление...",
|
||||
"To add a file to the conversation, drop it here.": "Чтобы добавить файл в беседу, поместите его сюда.",
|
||||
"Turn this list into bullet points": "Преобразовать этот список в маркированный",
|
||||
"Unlock access": "Разблокировать",
|
||||
"Unlocking...": "Разблокировка...",
|
||||
"Untitled conversation": "Беседа без названия",
|
||||
@@ -420,7 +394,6 @@
|
||||
"We'll email you when the public beta opens.": "Мы отправим вам письмо, когда станет доступна публичная бета-версия.",
|
||||
"Web": "Интернет",
|
||||
"What is on your mind?": "О чём вы думаете?",
|
||||
"Write a short product description": "Введите краткое описание продукта",
|
||||
"Write on Tchap": "Написать в Tchap",
|
||||
"You are on the list": "Вы в списке",
|
||||
"You do not have permission to view this page.": "У вас недостаточно прав для просмотра этой страницы.",
|
||||
@@ -448,13 +421,13 @@
|
||||
"An error occurred while renaming the conversation": "Сталася помилка під час перейменування розмови",
|
||||
"An error occurred. Please try again.": "Сталась помилка. Спробуйте ще раз.",
|
||||
"Are you sure you want to delete this conversation ?": "Ви дійсно бажаєте видалити цю розмову?",
|
||||
"Ask a question": "Задати питання",
|
||||
"Assistant IA replied: ": "Відповідь помічника ШІ: ",
|
||||
"Assistant is already available, log in to use it now.": "Помічник вже доступний, увійдіть щоб почати використання.",
|
||||
"Assistant is in development: your feedback matters! Choose how to share your ideas:": "Помічник в розробці: ваші відгуки мають значення! Оберіть, як поділитися своїми ідеями:",
|
||||
"Assistant settings": "Налаштування помічника",
|
||||
"Attach file": "Додати файл",
|
||||
"Attachment summary not supported": "Узагальнення вкладень не підтримується",
|
||||
"Available soon": "Незабаром буде доступно",
|
||||
"Cancel": "Скасувати",
|
||||
"Clear search": "Очистити вікно пошуку",
|
||||
"Close model selector": "Закрити вікно вибору моделі",
|
||||
@@ -469,7 +442,6 @@
|
||||
"Copied": "Скопійовано",
|
||||
"Copy": "Копіювати",
|
||||
"Copy code": "Скопіювати код",
|
||||
"Dark mode": "Темний режим",
|
||||
"Default": "За замовчуванням",
|
||||
"Delete": "Видалити",
|
||||
"Delete a conversation": "Видалити розмову",
|
||||
@@ -477,8 +449,6 @@
|
||||
"Direct exchange with our team": "Пряме спілкування з нашою командою",
|
||||
"Enter your message or a question": "Введіть ваше повідомлення або питання",
|
||||
"Explore other LaSuite apps": "Ознайомтесь з іншими застосунками LaSuite",
|
||||
"Extracting document: {{documents}} ...": "Видобування документа: {{documents}}...",
|
||||
"Extracting documents: {{documents}} ...": "Видобування документів: {{documents}}...",
|
||||
"Failed to activate account. Please try again.": "Не вдалося активувати обліковий запис. Спробуйте ще раз.",
|
||||
"Failed to copy": "Не вдалось скопіювати",
|
||||
"Failed to register for notifications. Please try again.": "Не вдалося виконати реєстрацію для повідомлень. Будь ласка, спробуйте ще раз.",
|
||||
@@ -489,7 +459,6 @@
|
||||
"Feedback Négatif": "Негативний відгук",
|
||||
"Feedback positif": "Позитивний відгук",
|
||||
"File type not supported": "Тип файлу не підтримується",
|
||||
"Find recent news about...": "Знайти останні новини про...",
|
||||
"Get notified about the Public Beta.": "Отримувати повідомлення про публічну бета-версію.",
|
||||
"Get notified for the public beta": "Отримувати повідомлення про публічну бета-версію",
|
||||
"Give a quick opinion": "Дати швидкий відгук",
|
||||
@@ -497,11 +466,13 @@
|
||||
"History": "Історія",
|
||||
"Home": "Головна",
|
||||
"If enabled, this allows us to analyse your exchanges to improve the Assistant. If disabled, all conversations remain confidential and are not used in any way. ": "Якщо увімкнуто, це дозволить нам аналізувати ваші розмови для покращення помічника. Якщо вимкнено, всі розмови залишаються конфіденційними та не використовуються жодним чином. ",
|
||||
"Illustration": "Ілюстрація",
|
||||
"Image 401": "Зображення 401",
|
||||
"Image 403": "Зображення 403",
|
||||
"Invalid activation code. Please check and try again.": "Невірний код активації. Будь ласка, перевірте та повторіть спробу.",
|
||||
"It seems that the page you are looking for does not exist or cannot be displayed correctly.": "Схоже, що сторінка, яку ви шукаєте, не існує або не може бути показаною правильно.",
|
||||
"Know more": "Докладніше",
|
||||
"Language": "Мова",
|
||||
"Learn more about data usage.": "Дізнатися більше про використання даних.",
|
||||
"Load more": "Завантажити ще",
|
||||
"Log in to access this page.": "Увійдіть, щоб отримати доступ до цієї сторінки.",
|
||||
@@ -531,7 +502,6 @@
|
||||
"Search results": "Результати пошуку",
|
||||
"Search...": "Пошук...",
|
||||
"Select": "Вибрати",
|
||||
"Select language": "Оберіть мову",
|
||||
"Select model": "Виберіть модель",
|
||||
"Send": "Відправити",
|
||||
"Settings": "Налаштування",
|
||||
@@ -543,15 +513,13 @@
|
||||
"Start conversation": "Почати розмову",
|
||||
"Stop": "Зупинити",
|
||||
"Summarizing...": "Узагальнення...",
|
||||
"Translation in progress...": "Переклад виконується...",
|
||||
"The Assistant is a sovereign AI for public servants. It helps with daily tasks (rephrasing, summarising, translating, information search). Your data stays in France on secure, state-compliant infrastructure and is never used for commercial purposes.": "Помічник — це незалежний штучний інтелект для державних службовців. Він допомагає у виконанні щоденних завдань (перефразування, узагальнення, переклад, пошук інформації). Ваші дані зберігаються у Франції на безпечній інфраструктурі, що відповідає державним вимогам, і ніколи не використовуються в комерційних цілях.",
|
||||
"The Assistant is a sovereign conversational AI designed for public servants. It helps you save time on daily tasks like rephrasing, summarising, translating, or searching information. Your data never leaves France and is stored on secure, state-compliant infrastructures. It is never used for commercial purposes.": "Помічник - це розмовний ШІ, призначений для державних службовців. Він допоможе вам зберегти час в таких щоденних завданнях, як рефразування, узагальнення, переклад або пошукова інформація. Ваші дані ніколи не покидають Францію та зберігаються на захищеній державній інфраструктурі. Вони ніколи не використовуються для комерційних цілей.",
|
||||
"The Assistant is in Beta": "Помічник у бета-версії",
|
||||
"The conversation has been deleted.": "Розмова була видалена.",
|
||||
"The conversation has been renamed.": "Розмова була перейменована.",
|
||||
"The summary feature is not supported yet.": "Функція узагальнення ще не підтримується.",
|
||||
"Thinking...": "Мислення...",
|
||||
"To add a file to the conversation, drop it here.": "Щоб додати файл до розмови, покладіть його сюди.",
|
||||
"Turn this list into bullet points": "Перетворити цей список на маркований",
|
||||
"Unlock access": "Розблокувати доступ",
|
||||
"Unlocking...": "Розблоковування...",
|
||||
"Untitled conversation": "Розмова без назви",
|
||||
|
||||
@@ -1,7 +1,6 @@
|
||||
import { useRouter } from 'next/router';
|
||||
import { type ReactElement, Suspense } from 'react';
|
||||
import type { ReactElement } from 'react';
|
||||
|
||||
import { Loader } from '@/components';
|
||||
import { Chat } from '@/features/chat/components/Chat';
|
||||
import { MainLayout } from '@/layouts';
|
||||
import { NextPageWithLayout } from '@/types/next';
|
||||
@@ -10,11 +9,7 @@ const Page: NextPageWithLayout = () => {
|
||||
const router = useRouter();
|
||||
const { id } = router.query;
|
||||
|
||||
return (
|
||||
<Suspense fallback={<Loader />}>
|
||||
<Chat initialConversationId={id as string} />
|
||||
</Suspense>
|
||||
);
|
||||
return <Chat initialConversationId={id as string} />;
|
||||
};
|
||||
|
||||
Page.getLayout = function getLayout(page: ReactElement) {
|
||||
|
||||
@@ -1,16 +1,11 @@
|
||||
import { type ReactElement, Suspense } from 'react';
|
||||
import type { ReactElement } from 'react';
|
||||
|
||||
import { Loader } from '@/components';
|
||||
import { Chat } from '@/features/chat/components/Chat';
|
||||
import { MainLayout } from '@/layouts';
|
||||
import { NextPageWithLayout } from '@/types/next';
|
||||
|
||||
const Page: NextPageWithLayout = () => {
|
||||
return (
|
||||
<Suspense fallback={<Loader />}>
|
||||
<Chat initialConversationId={undefined} />
|
||||
</Suspense>
|
||||
);
|
||||
return <Chat initialConversationId={undefined} />;
|
||||
};
|
||||
|
||||
Page.getLayout = function getLayout(page: ReactElement) {
|
||||
|
||||
@@ -30,7 +30,7 @@ main ::-webkit-scrollbar-track,
|
||||
|
||||
main ::-webkit-scrollbar-thumb,
|
||||
.ReactModalPortal ::-webkit-scrollbar-thumb {
|
||||
background-color: var(--c--contextuals--background--surface--tertiary);
|
||||
background-color: #d6dee1;
|
||||
border-radius: 20px;
|
||||
border: 6px solid transparent;
|
||||
background-clip: content-box;
|
||||
@@ -38,7 +38,7 @@ main ::-webkit-scrollbar-thumb,
|
||||
|
||||
main ::-webkit-scrollbar-thumb:hover,
|
||||
.ReactModalPortal ::-webkit-scrollbar-thumb:hover {
|
||||
background-color: var(--c--contextuals--background--surface--primary);
|
||||
background-color: #a8bbbf;
|
||||
}
|
||||
|
||||
.btn-unstyled {
|
||||
@@ -234,6 +234,21 @@ ul a:hover {
|
||||
box-shadow: none !important;
|
||||
}
|
||||
|
||||
.c__button--info {
|
||||
background-color: #cfe5ff !important;
|
||||
color: #265eaa !important;
|
||||
font-weight: 500 !important;
|
||||
}
|
||||
|
||||
.c__button--info:hover,
|
||||
.c__button--info:active,
|
||||
.c__button--info:focus {
|
||||
outline: none !important;
|
||||
background-color: #b7d7ff !important;
|
||||
color: #265eaa !important;
|
||||
border-color: #b7d7ff !important;
|
||||
}
|
||||
|
||||
.research-web-button:focus:not(:focus-visible) {
|
||||
box-shadow: none !important;
|
||||
}
|
||||
@@ -301,40 +316,6 @@ figure[data-rehype-pretty-code-figure] > pre > code {
|
||||
display: block;
|
||||
}
|
||||
|
||||
.mainContent-chat table {
|
||||
display: block;
|
||||
width: 100%;
|
||||
margin-top: 32px;
|
||||
overflow-x: scroll;
|
||||
font-size: 0.875rem;
|
||||
}
|
||||
|
||||
.mainContent-chat table th {
|
||||
color: var(--c--contextuals--content--semantic--neutral--secondary);
|
||||
font-weight: 500;
|
||||
font-size: 0.75rem;
|
||||
}
|
||||
|
||||
.mainContent-chat table tr,
|
||||
.mainContent-chat table th {
|
||||
display: flex;
|
||||
border-bottom: 1px solid var(--c--contextuals--border--surface--primary);
|
||||
}
|
||||
|
||||
.mainContent-chat tbody tr,
|
||||
.mainContent-chat thead th {
|
||||
padding: 8px;
|
||||
}
|
||||
|
||||
.mainContent-chat table tr:last-child {
|
||||
border-bottom: none;
|
||||
}
|
||||
|
||||
.mainContent-chat table td,
|
||||
.mainContent-chat table th {
|
||||
min-width: 200px;
|
||||
}
|
||||
|
||||
.sr-only {
|
||||
position: absolute;
|
||||
width: 1px;
|
||||
|
||||
@@ -63,7 +63,7 @@ export function PostHogProvider({
|
||||
},
|
||||
capture_pageview: false,
|
||||
capture_pageleave: true,
|
||||
__add_tracing_headers: false,
|
||||
__add_tracing_headers: true,
|
||||
});
|
||||
|
||||
const handleRouteChange = () => posthog?.capture('$pageview');
|
||||
|
||||
@@ -1,7 +1,5 @@
|
||||
import { expect, test } from '@playwright/test';
|
||||
|
||||
import { overrideConfig } from './common';
|
||||
|
||||
test.beforeEach(async ({ page }) => {
|
||||
await page.goto('/home/');
|
||||
});
|
||||
@@ -71,71 +69,4 @@ test.describe('Chat page', () => {
|
||||
await chatHistoryLink.click();
|
||||
await expect(messageContent).toBeVisible();
|
||||
});
|
||||
|
||||
test('the user can paste a document into the chat input', async ({ page }) => {
|
||||
await overrideConfig(page, {
|
||||
FEATURE_FLAGS: {
|
||||
'document-upload': 'enabled',
|
||||
'web-search': 'enabled',
|
||||
},
|
||||
});
|
||||
|
||||
await page.goto('/');
|
||||
|
||||
const chatInput = page.getByRole('textbox', {
|
||||
name: 'Enter your message or a',
|
||||
});
|
||||
await expect(chatInput).toBeVisible();
|
||||
await chatInput.click();
|
||||
|
||||
// Create a test file content
|
||||
const fileContent = 'Test document content for paste';
|
||||
const fileName = 'test-document.txt';
|
||||
const fileType = 'text/plain';
|
||||
|
||||
// Simulate paste event with file
|
||||
await page.evaluate(
|
||||
({ content, name, type }) => {
|
||||
const textarea = document.querySelector(
|
||||
'textarea[name="inputchat-textarea"]',
|
||||
) as HTMLTextAreaElement;
|
||||
if (!textarea) return;
|
||||
|
||||
// Create a File object
|
||||
const file = new File([content], name, { type });
|
||||
|
||||
// Create a DataTransfer object to simulate clipboard
|
||||
const dataTransfer = new DataTransfer();
|
||||
dataTransfer.items.add(file);
|
||||
|
||||
// Create a paste event - ClipboardEvent constructor doesn't accept clipboardData
|
||||
// so we create a regular Event and add clipboardData property
|
||||
const pasteEvent = new Event('paste', {
|
||||
bubbles: true,
|
||||
cancelable: true,
|
||||
}) as unknown as ClipboardEvent;
|
||||
|
||||
// Define clipboardData property to make it accessible
|
||||
Object.defineProperty(pasteEvent, 'clipboardData', {
|
||||
value: {
|
||||
files: dataTransfer.files,
|
||||
items: dataTransfer.items,
|
||||
types: Array.from(dataTransfer.types),
|
||||
getData: () => '',
|
||||
setData: () => {},
|
||||
},
|
||||
writable: false,
|
||||
configurable: true,
|
||||
});
|
||||
|
||||
textarea.dispatchEvent(pasteEvent);
|
||||
},
|
||||
{ content: fileContent, name: fileName, type: fileType },
|
||||
);
|
||||
|
||||
// Wait for the file to be processed and appear in the attachment list
|
||||
// The attachment should be visible with the file name
|
||||
const attachment = page.getByText(fileName, { exact: false }).first();
|
||||
await expect(attachment).toBeVisible({ timeout: 5000 });
|
||||
});
|
||||
});
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
{
|
||||
"name": "app-e2e",
|
||||
"version": "0.0.13",
|
||||
"version": "0.0.12",
|
||||
"private": true,
|
||||
"scripts": {
|
||||
"lint": "eslint . --ext .ts",
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
{
|
||||
"name": "conversations",
|
||||
"version": "0.0.13",
|
||||
"version": "0.0.12",
|
||||
"private": true,
|
||||
"workspaces": {
|
||||
"packages": [
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
{
|
||||
"name": "eslint-config-conversations",
|
||||
"version": "0.0.13",
|
||||
"version": "0.0.12",
|
||||
"license": "MIT",
|
||||
"scripts": {
|
||||
"lint": "eslint --ext .js ."
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
{
|
||||
"name": "packages-i18n",
|
||||
"version": "0.0.13",
|
||||
"version": "0.0.12",
|
||||
"private": true,
|
||||
"scripts": {
|
||||
"extract-translation": "yarn extract-translation:conversations",
|
||||
|
||||
+635
-109
File diff suppressed because it is too large
Load Diff
@@ -1,5 +1,5 @@
|
||||
apiVersion: v2
|
||||
type: application
|
||||
name: conversations
|
||||
version: 0.0.5
|
||||
version: 0.0.4
|
||||
appVersion: latest
|
||||
|
||||
@@ -72,11 +72,6 @@ spec:
|
||||
subPath: {{ .subPath | default "" }}
|
||||
readOnly: {{ .readOnly }}
|
||||
{{- end }}
|
||||
{{- if .Values.backend.llmConfiguration.enabled }}
|
||||
- name: llm-configuration
|
||||
mountPath: {{ .Values.backend.llmConfiguration.mount_path }}
|
||||
readOnly: true
|
||||
{{- end }}
|
||||
{{- with .Values.backend.nodeSelector }}
|
||||
nodeSelector:
|
||||
{{- toYaml . | nindent 8 }}
|
||||
@@ -126,9 +121,4 @@ spec:
|
||||
emptyDir: {}
|
||||
{{- end }}
|
||||
{{- end }}
|
||||
{{- if .Values.backend.llmConfiguration.enabled }}
|
||||
- name: llm-configuration
|
||||
configMap:
|
||||
name: conversations-llm-configuration
|
||||
{{- end }}
|
||||
{{- end }}
|
||||
|
||||
@@ -73,11 +73,6 @@ spec:
|
||||
subPath: {{ .subPath | default "" }}
|
||||
readOnly: {{ .readOnly }}
|
||||
{{- end }}
|
||||
{{- if .Values.backend.llmConfiguration.enabled }}
|
||||
- name: llm-configuration
|
||||
mountPath: {{ .Values.backend.llmConfiguration.mount_path }}
|
||||
readOnly: true
|
||||
{{- end }}
|
||||
{{- with .Values.backend.nodeSelector }}
|
||||
nodeSelector:
|
||||
{{- toYaml . | nindent 8 }}
|
||||
@@ -127,8 +122,3 @@ spec:
|
||||
emptyDir: {}
|
||||
{{- end }}
|
||||
{{- end }}
|
||||
{{- if .Values.backend.llmConfiguration.enabled }}
|
||||
- name: llm-configuration
|
||||
configMap:
|
||||
name: conversations-llm-configuration
|
||||
{{- end }}
|
||||
|
||||
@@ -73,11 +73,6 @@ spec:
|
||||
subPath: {{ .subPath | default "" }}
|
||||
readOnly: {{ .readOnly }}
|
||||
{{- end }}
|
||||
{{- if .Values.backend.llmConfiguration.enabled }}
|
||||
- name: llm-configuration
|
||||
mountPath: {{ .Values.backend.llmConfiguration.mount_path }}
|
||||
readOnly: true
|
||||
{{- end }}
|
||||
{{- with .Values.backend.nodeSelector }}
|
||||
nodeSelector:
|
||||
{{- toYaml . | nindent 8 }}
|
||||
@@ -127,8 +122,3 @@ spec:
|
||||
emptyDir: {}
|
||||
{{- end }}
|
||||
{{- end }}
|
||||
{{- if .Values.backend.llmConfiguration.enabled }}
|
||||
- name: llm-configuration
|
||||
configMap:
|
||||
name: conversations-llm-configuration
|
||||
{{- end }}
|
||||
|
||||
@@ -234,10 +234,10 @@ backend:
|
||||
## @param backend.probes.readiness.initialDelaySeconds [nullable] Configure timeout for backend readiness probe
|
||||
probes:
|
||||
liveness:
|
||||
path: /__lbheartbeat__
|
||||
path: /__heartbeat__
|
||||
initialDelaySeconds: 10
|
||||
readiness:
|
||||
path: /__heartbeat__
|
||||
path: /__lbheartbeat__
|
||||
initialDelaySeconds: 10
|
||||
|
||||
## @param backend.resources Resource requirements for the backend container
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
{
|
||||
"name": "mail_mjml",
|
||||
"version": "0.0.13",
|
||||
"version": "0.0.12",
|
||||
"description": "An util to generate html and text django's templates from mjml templates",
|
||||
"type": "module",
|
||||
"dependencies": {
|
||||
|
||||
+1
-1
@@ -399,7 +399,7 @@ glob-parent@~5.1.2:
|
||||
dependencies:
|
||||
is-glob "^4.0.1"
|
||||
|
||||
glob@^10.3.10, glob@^10.3.3:
|
||||
glob@^10.5.0:
|
||||
version "10.5.0"
|
||||
resolved "https://registry.yarnpkg.com/glob/-/glob-10.5.0.tgz#8ec0355919cd3338c28428a23d4f24ecc5fe738c"
|
||||
integrity sha512-DfXN8DfhJ7NH3Oe7cFmu3NCu1wKbkReJ8TorzSAFbSKrlNaQSKfIzqYqVY8zlbs2NLBbWpRiU52GX2PbaBVNkg==
|
||||
|
||||
Reference in New Issue
Block a user