🚨(backend) fix tests

I am removing hard coded datetime.

.gitignore

@@ -44,6 +44,9 @@ env.d/development/*
 !env.d/development/*.dist
 env.d/terraform
 
+# Configuration
+**/conversations/configuration/llm/dev.json
+
 # npm
 node_modules
 

CHANGELOG.md

@@ -8,17 +8,27 @@ and this project adheres to
 
 ## [Unreleased]
 
+### Added
+
+- ✨(backend) add FindRagBackend
+
+### Removed
+
+- 🔥(chat) consider PDF documents as other kind of documents #234
+
 ## [0.0.11] - 2026-01-16
 
 ### Changed
 
 - 📦️(front) update react
+- ✨(chat) Generate and edit conversation title
 
 ### Fixed
 
 - 🐛(e2e) fix test-e2e-chromium
 - 🐛(back) fix system prompt compatibility with self-hosted models #200
 - ⚰️(back) remove dead code and unused files
+- 🐛(back) prevent tool call timeouts
 
 ### Removed
 

Dockerfile

@@ -4,7 +4,7 @@
 FROM python:3.13.3-alpine AS base
 
 # Upgrade pip to its latest release to speed up dependencies installation
-RUN python -m pip install --upgrade pip setuptools
+RUN python -m pip install --upgrade pip
 
 # Upgrade system packages to install security updates
 RUN apk update && \

compose.yml

@@ -71,6 +71,9 @@ services:
       - "host.docker.internal:host-gateway"
     ports:
       - "8071:8000"
+    networks:
+      - default
+      - lasuite
     volumes:
       - ./src/backend:/app
       - ./data/static:/data/static
@@ -89,6 +92,9 @@ services:
     image: nginx:1.25
     ports:
       - "8083:8083"
+    networks:
+      - default
+      - lasuite
     volumes:
       - ./docker/files/etc/nginx/conf.d:/etc/nginx/conf.d:ro
     depends_on:
@@ -177,3 +183,8 @@ services:
       kc_postgresql:
         condition: service_healthy
         restart: true
+
+networks:
+  lasuite:
+    name: lasuite-network
+    driver: bridge

docs/env.md

@@ -95,6 +95,9 @@ These are the environment variables you can set for the `conversations-backend`
 | CACHES_KEY_PREFIX                               | The prefix used to every cache keys.                                                                                              | conversations                                           |
 | THEME_CUSTOMIZATION_FILE_PATH                   | full path to the file customizing the theme. An example is provided in src/backend/conversations/configuration/theme/default.json | BASE_DIR/conversations/configuration/theme/default.json |
 | THEME_CUSTOMIZATION_CACHE_TIMEOUT               | Cache duration for the customization settings                                                                                     | 86400                                                   |
+| FIND_API_KEY                                    | API key of Find                                                                                                                   |                                                         |
+| FIND_API_URL                                    | URL of Find                                                                                                                       | `https://app-find/api`                                  |
+| FIND_API_TIMEOUT                                | Find API timeout                                                                                                                  | 30                                                      |
 
 
 ## conversations-frontend image

docs/llm-configuration.md

@@ -244,9 +244,9 @@ For Mistral AI models using the Etalab platform:
 {
   "models": [
     {
-      "hrid": "mistral-large",
-      "model_name": "mistral-large-latest",
-      "human_readable_name": "Mistral Large (Etalab)",
+      "hrid": "mistral-medium",
+      "model_name": "mistral-medium-2508",
+      "human_readable_name": "Mistral Medium (Etalab)",
       "provider_name": "mistral-etalab",
       "profile": null,
       "settings": {

docs/tools/web_search_brave.md

@@ -357,6 +357,7 @@ The RAG backend performs semantic search to find the most relevant content:
 rag_results = document_store.search(
     query,
     results_count=settings.BRAVE_RAG_WEB_SEARCH_CHUNK_NUMBER,
+    **kwargs, # Additional search parameters like session with access_token
 )
 ```
 

env.d/development/common.e2e.dist

@@ -8,3 +8,5 @@ LLM_CONFIGURATION_FILE_PATH = /app/conversations/configuration/llm/default.e2e.j
 # Features
 FEATURE_FLAG_WEB_SEARCH=ENABLED
 FEATURE_FLAG_DOCUMENT_UPLOAD=ENABLED
+
+AUTO_TITLE_AFTER_USER_MESSAGES=3

src/backend/chat/agent_rag/document_converter/parser.py

@@ -0,0 +1,66 @@
+"""Document parsers for RAG backends."""
+
+import logging
+from io import BytesIO
+from urllib.parse import urljoin
+
+from django.conf import settings
+
+import requests
+
+from chat.agent_rag.document_converter.markitdown import DocumentConverter
+
+logger = logging.getLogger(__name__)
+
+
+class BaseParser:
+    """Base class for document parsers."""
+
+    def parse_document(self, name: str, content_type: str, content: BytesIO) -> str:
+        """
+        Parse the document and prepare it for the search operation.
+        This method should handle the logic to convert the document
+        into a format suitable for storage.
+
+        Args:
+            name (str): The name of the document.
+            content_type (str): The MIME type of the document (e.g., "application/pdf").
+            content (BytesIO): The content of the document as a BytesIO stream.
+
+        Returns:
+            str: The document content in Markdown format.
+        """
+        raise NotImplementedError("Must be implemented in subclass.")
+
+
+class AlbertParser(BaseParser):
+    """Document parser using Albert API for PDFs and DocumentConverter for other formats."""
+
+    endpoint = urljoin(settings.ALBERT_API_URL, "/v1/parse-beta")
+
+    def parse_pdf_document(self, name: str, content_type: str, content: bytes) -> str:
+        """Parse PDF document using Albert API."""
+        response = requests.post(
+            self.endpoint,
+            headers={
+                "Authorization": f"Bearer {settings.ALBERT_API_KEY}",
+            },
+            files={
+                "file": (name, content, content_type),
+                "output_format": (None, "markdown"),
+            },
+            timeout=settings.ALBERT_API_PARSE_TIMEOUT,
+        )
+        response.raise_for_status()
+
+        return "\n\n".join(
+            document_page["content"] for document_page in response.json().get("data", [])
+        )
+
+    def parse_document(self, name: str, content_type: str, content: bytes) -> str:
+        """Parse document 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
+        )

src/backend/chat/agent_rag/document_rag_backends/albert_rag_backend.py

@@ -13,7 +13,7 @@ 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.markitdown import DocumentConverter
+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__)
@@ -26,9 +26,6 @@ class AlbertRagBackend(BaseRagBackend):  # pylint: disable=too-many-instance-att
 
     It provides methods to:
     - Create a collection for the search operation.
-    - Parse documents and convert them to Markdown format:
-       + Handle PDF parsing using the Albert API.
-       + Use the DocumentConverter (markitdown) for other formats.
     - Store parsed documents in the Albert collection.
     - Perform a search operation using the Albert API.
     """
@@ -46,10 +43,9 @@ class AlbertRagBackend(BaseRagBackend):  # pylint: disable=too-many-instance-att
         }
         self._collections_endpoint = urljoin(self._base_url, "/v1/collections")
         self._documents_endpoint = urljoin(self._base_url, "/v1/documents")
-        self._pdf_parser_endpoint = urljoin(self._base_url, "/v1/parse-beta")
         self._search_endpoint = urljoin(self._base_url, "/v1/search")
-
         self._default_collection_description = "Temporary collection for RAG document search"
+        self.parser = AlbertParser()
 
     def create_collection(self, name: str, description: Optional[str] = None) -> str:
         """
@@ -91,7 +87,7 @@ class AlbertRagBackend(BaseRagBackend):  # pylint: disable=too-many-instance-att
         self.collection_id = str(response.json()["id"])
         return self.collection_id
 
-    def delete_collection(self) -> None:
+    def delete_collection(self, **kwargs) -> None:
         """
         Delete the current collection
         """
@@ -102,7 +98,7 @@ class AlbertRagBackend(BaseRagBackend):  # pylint: disable=too-many-instance-att
         )
         response.raise_for_status()
 
-    async def adelete_collection(self) -> None:
+    async def adelete_collection(self, **kwargs) -> None:
         """
         Asynchronously delete the current collection
         """
@@ -114,59 +110,7 @@ class AlbertRagBackend(BaseRagBackend):  # pylint: disable=too-many-instance-att
             )
             response.raise_for_status()
 
-    def parse_pdf_document(self, name: str, content_type: str, content: BytesIO) -> str:
-        """
-        Parse the PDF document content and return the text content.
-        This method should handle the logic to convert the PDF into
-        a format suitable for the Albert API.
-        """
-        response = requests.post(
-            self._pdf_parser_endpoint,
-            headers=self._headers,
-            files={
-                "file": (
-                    name,
-                    content,
-                    content_type,
-                ),  # Use the name as the filename in the request
-                "output_format": (None, "markdown"),  # Specify the output format as Markdown,
-            },
-            timeout=settings.ALBERT_API_PARSE_TIMEOUT,
-        )
-        response.raise_for_status()
-
-        return "\n\n".join(
-            document_page["content"] for document_page in response.json().get("data", [])
-        )
-
-    def parse_document(self, name: str, content_type: str, content: BytesIO):
-        """
-        Parse the document and prepare it for the search operation.
-        This method should handle the logic to convert the document
-        into a format suitable for the Albert API.
-
-        Args:
-            name (str): The name of the document.
-            content_type (str): The MIME type of the document (e.g., "application/pdf").
-            content (BytesIO): The content of the document as a BytesIO stream.
-
-        Returns:
-            str: The document content in Markdown format.
-        """
-        # Implement the parsing logic here
-        if content_type == "application/pdf":
-            # Handle PDF parsing
-            markdown_content = self.parse_pdf_document(
-                name=name, content_type=content_type, content=content
-            )
-        else:
-            markdown_content = DocumentConverter().convert_raw(
-                name=name, content_type=content_type, content=content
-            )
-
-        return markdown_content
-
-    def store_document(self, name: str, content: str) -> None:
+    def store_document(self, name: str, content: str, **kwargs) -> None:
         """
         Store the document content in the Albert collection.
         This method should handle the logic to send the document content to the Albert API.
@@ -174,6 +118,7 @@ class AlbertRagBackend(BaseRagBackend):  # pylint: disable=too-many-instance-att
         Args:
             name (str): The name of the document.
             content (str): The content of the document in Markdown format.
+            **kwargs: Additional arguments.
         """
         response = requests.post(
             urljoin(self._base_url, self._documents_endpoint),
@@ -188,7 +133,7 @@ class AlbertRagBackend(BaseRagBackend):  # pylint: disable=too-many-instance-att
         logger.debug(response.json())
         response.raise_for_status()
 
-    async def astore_document(self, name: str, content: str) -> None:
+    async def astore_document(self, name: str, content: str, **kwargs) -> None:
         """
         Store the document content in the Albert collection.
         This method should handle the logic to send the document content to the Albert API.
@@ -196,6 +141,7 @@ class AlbertRagBackend(BaseRagBackend):  # pylint: disable=too-many-instance-att
         Args:
             name (str): The name of the document.
             content (str): The content of the document in Markdown format.
+            **kwargs: Additional arguments.
         """
         async with httpx.AsyncClient(timeout=settings.ALBERT_API_TIMEOUT) as client:
             response = await client.post(
@@ -213,13 +159,14 @@ class AlbertRagBackend(BaseRagBackend):  # pylint: disable=too-many-instance-att
             logger.debug(response.json())
             response.raise_for_status()
 
-    def search(self, query, results_count: int = 4) -> RAGWebResults:
+    def search(self, query: str, results_count: int = 4, **kwargs) -> RAGWebResults:
         """
         Perform a search using the Albert API based on the provided query.
 
         Args:
             query (str): The search query.
             results_count (int): The number of results to return.
+            **kwargs: Additional arguments.
 
         Returns:
             RAGWebResults: The search results.
@@ -256,13 +203,14 @@ class AlbertRagBackend(BaseRagBackend):  # pylint: disable=too-many-instance-att
             ),
         )
 
-    async def asearch(self, query, results_count: int = 4) -> RAGWebResults:
+    async def asearch(self, query, results_count: int = 4, **kwargs) -> RAGWebResults:
         """
         Perform an asynchronous search using the Albert API based on the provided query.
 
         Args:
             query (str): The search query.
             results_count (int): The number of results to return.
+            **kwargs: Additional arguments.
 
         Returns:
             RAGWebResults: The search results.

src/backend/chat/agent_rag/document_rag_backends/base_rag_backend.py

@@ -1,6 +1,7 @@
 """Implementation of the Albert API for RAG document search."""
 
 import logging
+from abc import ABC, abstractmethod
 from contextlib import asynccontextmanager, contextmanager
 from io import BytesIO
 from typing import List, Optional
@@ -8,11 +9,12 @@ from typing import List, Optional
 from asgiref.sync import sync_to_async
 
 from chat.agent_rag.constants import RAGWebResults
+from chat.agent_rag.document_converter.parser import BaseParser
 
 logger = logging.getLogger(__name__)
 
 
-class BaseRagBackend:
+class BaseRagBackend(ABC):
     """Base class for RAG backends."""
 
     def __init__(
@@ -38,6 +40,7 @@ class BaseRagBackend:
         self.collection_id = collection_id
         self.read_only_collection_id = read_only_collection_id or []
         self._default_collection_description = "Temporary collection for RAG document search"
+        self.parser: BaseParser = BaseParser()
 
     def get_all_collection_ids(self) -> List[str]:
         """
@@ -53,13 +56,14 @@ class BaseRagBackend:
 
         collection_ids = []
         if self.collection_id:
-            collection_ids.append(int(self.collection_id))
+            collection_ids.append(self.collection_id)
         if self.read_only_collection_id:
             collection_ids.extend(
                 [int(collection_id) for collection_id in self.read_only_collection_id]
             )
         return collection_ids
 
+    @abstractmethod
     def create_collection(self, name: str, description: Optional[str] = None) -> str:
         """
         Create a temporary collection for the search operation.
@@ -88,9 +92,10 @@ class BaseRagBackend:
         Returns:
             str: The document content in Markdown format.
         """
-        raise NotImplementedError("Must be implemented in subclass.")
+        return self.parser.parse_document(name, content_type, content)
 
-    def store_document(self, name: str, content: str) -> None:
+    @abstractmethod
+    def store_document(self, name: str, content: str, **kwargs) -> None:
         """
         Store the document content in the collection.
         This method should handle the logic to send the document content to the API.
@@ -98,10 +103,11 @@ class BaseRagBackend:
         Args:
             name (str): The name of the document.
             content (str): The content of the document in Markdown format.
+            **kwargs: Additional arguments. ex: "user_sub" for access control.
         """
         raise NotImplementedError("Must be implemented in subclass.")
 
-    async def astore_document(self, name: str, content: str) -> None:
+    async def astore_document(self, name: str, content: str, **kwargs) -> None:
         """
         Store the document content in the collection.
         This method should handle the logic to send the document content to the API.
@@ -109,10 +115,13 @@ class BaseRagBackend:
         Args:
             name (str): The name of the document.
             content (str): The content of the document in Markdown format.
+            **kwargs: Additional arguments. ex: "user_sub" for access control.
         """
-        return await sync_to_async(self.store_document)(name=name, content=content)
+        return await sync_to_async(self.store_document)(name=name, content=content, **kwargs)
 
-    def parse_and_store_document(self, name: str, content_type: str, content: BytesIO) -> str:
+    def parse_and_store_document(
+        self, name: str, content_type: str, content: BytesIO, **kwargs
+    ) -> str:
         """
         Parse the document and store it in the Albert collection.
 
@@ -120,39 +129,52 @@ class BaseRagBackend:
             name (str): The name of the document.
             content_type (str): The MIME type of the document (e.g., "application/pdf").
             content (BytesIO): The content of the document as a BytesIO stream.
+            **kwargs: Additional arguments. ex: "user_sub" for access control.
         """
         if not self.collection_id:
             raise RuntimeError("The RAG backend requires collection_id")
 
         document_content = self.parse_document(name, content_type, content)
-        self.store_document(name, document_content)
+        self.store_document(name, document_content, **kwargs)
         return document_content
 
-    def delete_collection(self) -> None:
+    @abstractmethod
+    def delete_collection(self, **kwargs) -> None:
         """
         Delete the collection.
         This method should handle the logic to delete the collection from the backend.
         """
         raise NotImplementedError("Must be implemented in subclass.")
 
-    async def adelete_collection(self) -> None:
+    async def adelete_collection(self, **kwargs) -> None:
         """
         Delete the collection.
         This method should handle the logic to delete the collection from the backend.
         """
-        return await sync_to_async(self.delete_collection)()
+        return await sync_to_async(self.delete_collection)(**kwargs)
 
-    def search(self, query, results_count: int = 4) -> RAGWebResults:
+    @abstractmethod
+    def search(self, query: str, results_count: int = 4, **kwargs) -> RAGWebResults:
         """
         Search the collection for the given query.
+
+        Args:
+            query: The search query string.
+            results_count: Number of results to return.
+            **kwargs: Additional arguments. ex: 'session' for OIDC authentication.
         """
         raise NotImplementedError("Must be implemented in subclass.")
 
-    async def asearch(self, query, results_count: int = 4) -> RAGWebResults:
+    async def asearch(self, query: str, results_count: int = 4, **kwargs) -> RAGWebResults:
         """
-        Search the collection for the given query.
+        Search the collection for the given query asynchronously.
+
+        Args:
+            query: The search query string.
+            results_count: Number of results to return.
+            **kwargs: Additional arguments. ex: 'session' for OIDC authentication.
         """
-        return await sync_to_async(self.search)(query=query, results_count=results_count)
+        return await sync_to_async(self.search)(query=query, results_count=results_count, **kwargs)
 
     @classmethod
     @contextmanager
@@ -168,7 +190,9 @@ class BaseRagBackend:
 
     @classmethod
     @asynccontextmanager
-    async def temporary_collection_async(cls, name: str, description: Optional[str] = None):
+    async def temporary_collection_async(
+        cls, name: str, description: Optional[str] = None, **kwargs
+    ):
         """Context manager for RAG backend with temporary collections."""
         backend = cls()
 
@@ -176,4 +200,4 @@ class BaseRagBackend:
         try:
             yield backend
         finally:
-            await backend.adelete_collection()
+            await backend.adelete_collection(**kwargs)

src/backend/chat/agent_rag/document_rag_backends/find_rag_backend.py

@@ -0,0 +1,163 @@
+"""Implementation of the Find API for RAG document search."""
+
+import logging
+import uuid
+from typing import List, Optional
+from urllib.parse import urljoin
+from uuid import uuid4
+
+from django.conf import settings
+from django.utils import timezone
+
+import requests
+
+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
+from utils.oidc import with_fresh_access_token
+
+logger = logging.getLogger(__name__)
+
+
+SUPPORTED_LANGUAGE_CODES = ["en", "fr", "de", "nl"]
+
+
+class FindRagBackend(BaseRagBackend):
+    """
+    This class is a placeholder for the Find API implementation.
+    It is designed to be used with the RAG (Retrieval-Augmented Generation) document search system.
+
+    It provides methods to:
+    - Store parsed documents in the Find index.
+    - Perform a search operation using the Find API.
+    """
+
+    def __init__(
+        self,
+        collection_id: Optional[str] = None,
+        read_only_collection_id: Optional[List[str]] = None,
+    ):
+        # Initialize any necessary parameters or configurations here
+        super().__init__(collection_id, read_only_collection_id)
+        self.api_key = settings.FIND_API_KEY
+        self.search_endpoint = "api/v1.0/documents/search/"
+        self.indexing_endpoint = "api/v1.0/documents/index/"
+        self.deleting_endpoint = "api/v1.0/documents/delete/"
+        self.parser = AlbertParser()  # Find Rag relies on Albert parser
+
+    def create_collection(self, name: str, description: Optional[str] = None) -> str:
+        """
+        init collection_id
+        """
+        self.collection_id = self.collection_id or str(uuid.uuid4())
+        return self.collection_id
+
+    @with_fresh_access_token
+    def delete_collection(self, **kwargs) -> None:
+        """
+        Delete the current collection
+        """
+        response = requests.post(
+            urljoin(settings.FIND_API_URL, self.deleting_endpoint),
+            headers={"Authorization": f"Bearer {kwargs['session'].get('oidc_access_token')}"},
+            json={
+                "tags": [f"collection-{self.collection_id}"],
+                # "service": "conversations"
+            },
+            timeout=settings.FIND_API_TIMEOUT,
+        )
+        response.raise_for_status()
+
+    def store_document(self, name: str, content: str, **kwargs) -> None:
+        """
+        index document in Find
+
+        Args:
+            name (str): The name of the document.
+            content (str): The content of the document in Markdown format.
+            user_sub (str): The user subject identifier for access control.
+        """
+        logger.debug("index document '%s' in Find", name)
+
+        user_sub = kwargs.get("user_sub")
+        if not user_sub:
+            raise ValueError("user_sub is required to store document in FindRagBackend")
+
+        response = requests.post(
+            urljoin(settings.FIND_API_URL, self.indexing_endpoint),
+            headers={"Authorization": f"Bearer {self.api_key}"},
+            json={
+                "id": str(uuid4()),
+                "title": str(name) or "",
+                "depth": 0,
+                "path": str(name) or "",
+                "numchild": 0,
+                "content": content or "",
+                "created_at": timezone.now().isoformat(),
+                "updated_at": timezone.now().isoformat(),
+                "tags": [f"collection-{self.collection_id}"],
+                "size": len(content.encode("utf-8")),
+                "users": [user_sub],
+                "groups": [],
+                "reach": "authenticated",
+                "is_active": True,
+            },
+            timeout=settings.FIND_API_TIMEOUT,
+        )
+        response.raise_for_status()
+
+    @with_fresh_access_token
+    def search(self, query: str, results_count: int = 4, **kwargs) -> RAGWebResults:
+        """
+        Perform a search using the Find API.
+        Uses the user's OIDC token from the request session.
+
+        Args:
+            query: The search query.
+            results_count: Number of results to return.
+            **kwargs: Additional arguments. Expected: 'session' containing OIDC tokens,
+
+        Returns:
+            RAGWebResults: The search results.
+        """
+        logger.debug("search documents in Find with query '%s'", query)
+        response = requests.post(
+            urljoin(settings.FIND_API_URL, self.search_endpoint),
+            headers={"Authorization": f"Bearer {kwargs['session'].get('oidc_access_token')}"},
+            json={
+                "q": query or "*",
+                "tags": [
+                    f"collection-{collection_id}" for collection_id in self.get_all_collection_ids()
+                ],
+                "k": results_count,
+            },
+            timeout=settings.FIND_API_TIMEOUT,
+        )
+        response.raise_for_status()
+
+        return RAGWebResults(
+            data=[
+                RAGWebResult(
+                    url=get_language_value(result["_source"], "title"),
+                    content=get_language_value(result["_source"], "content"),
+                    score=result["_score"],
+                )
+                for result in response.json()
+            ],
+            usage=RAGWebUsage(
+                prompt_tokens=0,
+                completion_tokens=0,
+            ),
+        )
+
+
+def get_language_value(source, language_field):
+    """
+    extract the value of the language field with the correct language_code extension.
+    "title" and "content" have extensions like "title.en" or "title.fr".
+    get_language_value will return the value regardless of the extension.
+    """
+    for language_code in SUPPORTED_LANGUAGE_CODES:
+        if f"{language_field}.{language_code}" in source:
+            return source[f"{language_field}.{language_code}"]
+    raise ValueError(f"No '{language_field}' field with any supported language code in object")

src/backend/chat/agents/base.py

@@ -10,7 +10,6 @@ import httpx
 from pydantic_ai import Agent
 from pydantic_ai.models import get_user_agent
 from pydantic_ai.profiles import ModelProfile
-from pydantic_ai.toolsets import FunctionToolset
 
 from chat.tools import get_pydantic_tools_by_name
 
@@ -174,20 +173,18 @@ class BaseAgent(Agent):
             # and pydantic_ai.models.infer_model()
             _model_instance = self.configuration.model_name
 
-        _system_prompt = self.configuration.system_prompt
-        _base_toolset = (
-            [
-                FunctionToolset(
-                    tools=[
-                        get_pydantic_tools_by_name(tool_name)
-                        for tool_name in self.configuration.tools
-                    ]
-                )
-            ]
-            if self.configuration.tools
-            else None
-        )
+        _system_prompt = self.get_system_prompt()
 
-        _tools = [get_pydantic_tools_by_name(tool_name) for tool_name in self.configuration.tools]
+        _tools = self.get_tools()
 
         super().__init__(model=_model_instance, instructions=_system_prompt, tools=_tools, **kwargs)
+
+    def get_system_prompt(self) -> str | None:
+        """Override this method to customize the system prompt."""
+        return self.configuration.system_prompt
+
+    def get_tools(self) -> list | None:
+        """Override this method to customize tools."""
+        if not self.configuration.tools:
+            return []
+        return [get_pydantic_tools_by_name(tool_name) for tool_name in self.configuration.tools]

src/backend/chat/agents/conversation.py

@@ -131,3 +131,25 @@ class ConversationAgent(BaseAgent):
                 if tool.name.startswith("web_search_"):
                     return tool.name
         return None
+
+
+@dataclasses.dataclass(init=False)
+class TitleGenerationAgent(BaseAgent):
+    """Agent that generates concise, descriptive titles for conversations."""
+
+    def __init__(self, **kwargs):
+        super().__init__(
+            model_hrid=settings.LLM_DEFAULT_MODEL_HRID,
+            output_type=str,
+            **kwargs,
+        )
+
+    def get_tools(self):
+        return []
+
+    def get_system_prompt(self):
+        return (
+            "You are a title generator. Your task is to create concise, descriptive titles "
+            "that accurately summarize conversation content and help the user quickly identify the "
+            "conversation.\n\n"
+        )

src/backend/chat/clients/pydantic_ai.py

@@ -52,10 +52,9 @@ from pydantic_ai.messages import (
 )
 
 from core.feature_flags.helpers import is_feature_enabled
-from core.file_upload.utils import generate_retrieve_policy
 
 from chat import models
-from chat.agents.conversation import ConversationAgent
+from chat.agents.conversation import ConversationAgent, TitleGenerationAgent
 from chat.agents.local_media_url_processors import (
     update_history_local_urls,
     update_local_urls,
@@ -76,7 +75,7 @@ from chat.tools.document_generic_search_rag import add_document_rag_search_tool_
 from chat.tools.document_search_rag import add_document_rag_search_tool
 from chat.tools.document_summarize import document_summarize
 from chat.vercel_ai_sdk.core import events_v4, events_v5
-from chat.vercel_ai_sdk.encoder import EventEncoder
+from chat.vercel_ai_sdk.encoder import CURRENT_EVENT_ENCODER_VERSION, EventEncoder
 
 # Keep at the top of the file to avoid mocking issues
 document_store_backend = import_string(settings.RAG_DOCUMENT_SEARCH_BACKEND)
@@ -92,6 +91,7 @@ class ContextDeps:
 
     conversation: models.ChatConversation
     user: User
+    session: Optional[Dict] = None
     web_search_enabled: bool = False
 
 
@@ -106,7 +106,14 @@ def get_model_configuration(model_hrid: str):
 class AIAgentService:  # pylint: disable=too-many-instance-attributes
     """Service class for AI-related operations (Pydantic-AI edition)."""
 
-    def __init__(self, conversation: models.ChatConversation, user, model_hrid=None, language=None):
+    def __init__(  # pylint: disable=too-many-arguments,too-many-positional-arguments
+        self,
+        conversation: models.ChatConversation,
+        user,
+        session=None,
+        model_hrid=None,
+        language=None,
+    ):
         """
         Initialize the AI agent service.
 
@@ -122,7 +129,7 @@ class AIAgentService:  # pylint: disable=too-many-instance-attributes
 
         self._langfuse_available = settings.LANGFUSE_ENABLED
         self._store_analytics = self._langfuse_available and user.allow_conversation_analytics
-        self.event_encoder = EventEncoder("v4")  # Always use v4 for now
+        self.event_encoder = EventEncoder(CURRENT_EVENT_ENCODER_VERSION)  # We use v4 for now
 
         self._support_streaming = True
         if (streaming := get_model_configuration(self.model_hrid).supports_streaming) is not None:
@@ -136,6 +143,7 @@ class AIAgentService:  # pylint: disable=too-many-instance-attributes
         self._context_deps = ContextDeps(
             conversation=conversation,
             user=user,
+            session=session,
             web_search_enabled=self._is_web_search_enabled,
         )
 
@@ -278,6 +286,7 @@ class AIAgentService:  # pylint: disable=too-many-instance-attributes
                         name=document.identifier,
                         content_type=document.media_type,
                         content=document_data,
+                        user_sub=self.user.sub,
                     )
                 else:
                     # Remote URL
@@ -287,6 +296,7 @@ class AIAgentService:  # pylint: disable=too-many-instance-attributes
                     name=document.identifier,
                     content_type=document.media_type,
                     content=document.data,
+                    user_sub=self.user.sub,
                 )
 
             if not document.media_type.startswith("text/"):
@@ -471,27 +481,19 @@ class AIAgentService:  # pylint: disable=too-many-instance-attributes
         _tool_is_streaming = False
         _model_response_message_id = None
 
-        # Check for existing non-PDF documents in the conversation:
-        # - if no document at all: do nothing
-        # - if only PDFs: prepare document URLs for the agent
-        # - if other document types: add the RAG search tool
-        #   to allow searching in all kinds of documents
-        has_not_pdf_docs = await (
+        # Check for existing documents (any non-image attachment for this conversation)
+        has_documents = await (
             models.ChatConversationAttachment.objects.filter(
                 Q(conversion_from__isnull=True) | Q(conversion_from=""),
                 conversation=self.conversation,
             )
-            .exclude(
-                Q(content_type__startswith="image/") | Q(content_type="application/pdf"),
-            )
+            .exclude(content_type__startswith="image/")
             .aexists()
         )
 
-        document_urls = []
-        if not conversation_has_documents and not has_not_pdf_docs:
-            # No documents to process
-            pass
-        elif has_not_pdf_docs:
+        should_enable_rag = conversation_has_documents or has_documents
+
+        if should_enable_rag:
             add_document_rag_search_tool(self.conversation_agent)
 
             @self.conversation_agent.instructions
@@ -521,30 +523,6 @@ class AIAgentService:  # pylint: disable=too-many-instance-attributes
             async def summarize(ctx: RunContext, *args, **kwargs) -> ToolReturn:
                 """Wrap the document_summarize tool to provide context and add the tool."""
                 return await document_summarize(ctx, *args, **kwargs)
-        else:
-            conversation_documents = [
-                cd
-                async for cd in models.ChatConversationAttachment.objects.filter(
-                    Q(conversion_from__isnull=True) | Q(conversion_from=""),
-                    conversation=self.conversation,
-                )
-                .exclude(
-                    content_type__startswith="image/",
-                )
-                .values_list("key", "content_type")
-            ]
-
-            for doc_key, doc_content_type in conversation_documents:
-                if doc_content_type == "application/pdf":
-                    _presigned_url = generate_retrieve_policy(doc_key)
-                    document_urls.append(
-                        DocumentUrl(
-                            url=_presigned_url,
-                            identifier=doc_key.split("/")[-1],
-                            media_type="application/pdf",
-                        )
-                    )
-                    image_key_mapping[_presigned_url] = f"/media-key/{doc_key}"
 
         async with AsyncExitStack() as stack:
             # MCP servers (if any) can be initialized here
@@ -559,7 +537,7 @@ class AIAgentService:  # pylint: disable=too-many-instance-attributes
                     history.append(ModelResponse(parts=[TextPart(content="ok")], kind="response"))
 
             async with self.conversation_agent.iter(
-                [user_prompt] + input_images + document_urls,
+                [user_prompt] + input_images,
                 message_history=history,  # history will pass through agent's history_processors
                 deps=self._context_deps,
                 toolsets=mcp_servers,
@@ -720,8 +698,8 @@ class AIAgentService:  # pylint: disable=too-many-instance-attributes
 
         await self._agent_stop_streaming(force_cache_check=True)
 
-        # Persist conversation
-        await sync_to_async(self._update_conversation)(
+        # Prepare conversation update (save deferred until after potential title generation)
+        await sync_to_async(self._prepare_update_conversation)(
             final_output=run.result.new_messages(),
             usage=usage,
             final_output_from_tool=_final_output_from_tool,
@@ -730,6 +708,35 @@ class AIAgentService:  # pylint: disable=too-many-instance-attributes
             image_key_mapping=image_key_mapping or None,
         )
 
+        generated_title = None
+
+        # Auto-generate title after N user messages if not manually set
+        user_messages_count = sum(1 for msg in self.conversation.messages if msg.role == "user")
+
+        should_generate_title = (
+            user_messages_count == settings.AUTO_TITLE_AFTER_USER_MESSAGES
+            and not self.conversation.title_set_by_user_at
+        )
+
+        if should_generate_title:
+            if generated_title := await self._generate_title():
+                self.conversation.title = generated_title
+
+        # Persist conversation (including any generated title)
+        await sync_to_async(self.conversation.save)()
+
+        # Notify frontend about the title update
+        if generated_title:
+            yield events_v4.DataPart(
+                data=[
+                    {
+                        "type": "conversation_metadata",
+                        "conversationId": str(self.conversation.pk),
+                        "title": generated_title,
+                    }
+                ]
+            )
+
         if self._langfuse_available:
             langfuse.update_current_trace(
                 output=run.result.output if self._store_analytics else "REDACTED"
@@ -743,7 +750,7 @@ class AIAgentService:  # pylint: disable=too-many-instance-attributes
             ),
         )
 
-    def _update_conversation(  # noqa: PLR0913
+    def _prepare_update_conversation(  # noqa: PLR0913
         self,
         *,
         final_output: List[ModelRequest | ModelMessage],
@@ -810,4 +817,39 @@ class AIAgentService:  # pylint: disable=too-many-instance-attributes
             ModelMessagesTypeAdapter.dump_json(final_output).decode("utf-8")
         )
 
-        self.conversation.save()
+    async def _generate_title(self) -> str | None:
+        """Generate a title for the conversation using LLM based on first messages."""
+
+        # Build context from messages
+        # Note: We intentionally use only msg.content for title generation.
+        # Parts containing tool invocations or reasoning are excluded as they
+        # don't contribute to a meaningful context here
+        context = "\n".join(
+            f"{msg.role}: {(msg.content or '')[:300]}"  # Limit content length per message
+            for msg in self.conversation.messages
+            if msg.content
+        )
+
+        language = self.language or settings.LANGUAGE_CODE
+        prompt = (
+            "Generate a concise title (3-5 words, max 100 characters) for this conversation.\n\n"
+            "Requirements:\n"
+            "- Capture the main topic or user intent\n"
+            "- The title must be a simple string, no markdown\n"
+            "- Help the user quickly identify the conversation\n"
+            f"- Match the language of the user messages (default: {language})\n"
+            "- Avoid the word 'summary' unless explicitly requested\n\n"
+            "Output: Title text only, no quotes, labels, or explanation.\n\n"
+            f"Conversation:\n{context}"
+        )
+        try:
+            agent = TitleGenerationAgent()
+            result = await agent.run(prompt)
+            title = (result.output or "").strip()[:100]  # Enforce max length (conversation.title)
+            logger.info("Generated title for conversation %s: %s", self.conversation.pk, title)
+            return title if title else None
+        except Exception as exc:  # pylint: disable=broad-except #noqa: BLE001
+            logger.warning(
+                "Failed to generate title for conversation %s: %s", self.conversation.pk, exc
+            )
+            return None

src/backend/chat/keepalive.py

@@ -0,0 +1,171 @@
+"""Helpers to prevent proxy timeouts during long-running stream operations.
+
+This module provides utilities to wrap synchronous and asynchronous iterators
+with keepalive messages. When a stream pauses for longer than the specified
+interval, keepalive messages are injected to prevent proxy/gateway
+timeouts while waiting for the stream data.
+"""
+
+import asyncio
+import logging
+import queue
+import threading
+import time
+from typing import AsyncIterator, Iterator
+
+from django.conf import settings
+
+from .vercel_ai_sdk.core.events_v4 import DataPart as V4DataPart
+from .vercel_ai_sdk.core.events_v5 import DataPart as V5DataPart
+from .vercel_ai_sdk.encoder import (
+    CURRENT_EVENT_ENCODER_VERSION,
+    EventEncoder,
+    EventEncoderVersion,
+)
+
+logger = logging.getLogger(__name__)
+
+
+def get_keepalive_message() -> str:
+    """Generate a keepalive message based on encoder/SDK version."""
+    if CURRENT_EVENT_ENCODER_VERSION == EventEncoderVersion.V4:
+        event = V4DataPart(data=[{"status": "WAITING"}])
+    else:
+        event = V5DataPart(data={"status": "WAITING"})
+    encoder = EventEncoder(CURRENT_EVENT_ENCODER_VERSION)
+    return encoder.encode(event)
+
+
+async def stream_with_keepalive_async(
+    stream: AsyncIterator[str],
+) -> AsyncIterator[str]:
+    """Wrap an async iterator to emit keepalive during long pauses.
+
+    Args:
+        stream: The async iterator to wrap
+    Yields:
+        Items from the original stream, plus keepalive messages during pauses
+    Raises:
+        Any exception raised by the original stream
+    """
+    q: asyncio.Queue = asyncio.Queue()
+    finished = asyncio.Event()
+    keepalive_message = get_keepalive_message()
+
+    async def producer():
+        """Background task that consumes the original stream into a queue."""
+
+        try:
+            async for stream_item in stream:
+                await q.put(stream_item)
+        except Exception as exc:  # pylint: disable=broad-except #noqa: BLE001
+            # Pass exceptions through the queue so the consumer can re-raise them.
+            # This ensures errors aren't silently swallowed.
+            await q.put(exc)
+        finally:
+            finished.set()
+            await q.put(None)  # Sentinel to signal completion
+
+    producer_task = asyncio.create_task(producer())
+
+    try:
+        while True:
+            try:
+                item = await asyncio.wait_for(q.get(), timeout=settings.KEEPALIVE_INTERVAL)
+                if item is None:
+                    break
+                if isinstance(item, Exception):
+                    raise item
+                yield item
+            except asyncio.TimeoutError:
+                # No data received within interval
+                if finished.is_set():
+                    # Producer is done, queue is empty (else we would not have timed out)
+                    break
+
+                logger.debug("Send keepalive")
+                yield keepalive_message
+    finally:
+        # Cleanup
+        producer_task.cancel()
+        try:
+            await producer_task
+        except asyncio.CancelledError:
+            pass
+
+
+def get_current_time() -> float:
+    """Get current monotonic time, avoiding freezegun interferences.
+
+    Returns time.monotonic() which:
+    - Is NOT affected by freezegun's @freeze_time decorator (unlike time.time())
+    - Prevents issues where frozen time in main thread differs from real time in
+      spawned threads, causing incorrect keepalive interval computation
+    - Is the best clock for measuring time intervals
+
+    Wrapped in a function to ease mocking in tests.
+
+    Returns:
+        float: Monotonic time in seconds since an arbitrary reference point
+    """
+    return time.monotonic()
+
+
+def stream_with_keepalive_sync(stream: Iterator[str]) -> Iterator[str]:
+    """Wraps a synchronous stream with keepalive messages."""
+
+    q: queue.Queue = queue.Queue()
+    stream_done = threading.Event()
+    keepalive_message = get_keepalive_message()
+    # Mutable container so threads can read/write shared timestamp
+    last_yield_time = [get_current_time()]
+
+    def consume_stream():
+        """Read from source stream and forward chunks to queue."""
+        try:
+            for chunk in stream:
+                if stream_done.is_set():
+                    return  # early exit
+                q.put(chunk, timeout=1)  # Arbitrary timeout prevents blocking forever
+        # pylint: disable=broad-exception-caught
+        except Exception as e:
+            logger.exception("Error in stream consumption")
+            q.put(e)
+        finally:
+            stream_done.set()
+
+    def send_keepalives():
+        """Inject keepalive messages when idle too long.
+
+        Uses get_current_time() (time.monotonic) instead of time.time()
+        to avoid issues with freezegun in tests.
+        """
+        while not stream_done.is_set():
+            # Sleep before checking to give main loop time to process and update timestamp
+            time.sleep(0.5)  # let main loop process first, empiric value
+            if get_current_time() - last_yield_time[0] >= settings.KEEPALIVE_INTERVAL:
+                try:
+                    q.put(keepalive_message, timeout=0.1)
+                except queue.Full:
+                    pass
+
+    for target in (consume_stream, send_keepalives):
+        threading.Thread(target=target, daemon=True).start()
+
+    try:
+        # Continue while stream is active or queue has still items
+        while not stream_done.is_set() or not q.empty():
+            try:
+                item = q.get(timeout=1)  # short timeout, avoid blocking and stay responsive
+            except queue.Empty:
+                continue
+
+            # Re-raise from consume_stream
+            if isinstance(item, Exception):
+                raise item
+
+            yield item
+            last_yield_time[0] = get_current_time()
+    finally:
+        # Signal threads to stop
+        stream_done.set()

src/backend/chat/migrations/0005_chatconversation_title_set_by_user_at.py

@@ -0,0 +1,21 @@
+# Generated by Django 5.2.9 on 2025-12-30 09:44
+
+from django.db import migrations, models
+
+
+class Migration(migrations.Migration):
+    dependencies = [
+        ("chat", "0004_chatconversationattachment_and_more"),
+    ]
+
+    operations = [
+        migrations.AddField(
+            model_name="chatconversation",
+            name="title_set_by_user_at",
+            field=models.DateTimeField(
+                blank=True,
+                help_text="Timestamp when the user manually set the title. If set, prevent automatic title generation.",
+                null=True,
+            ),
+        ),
+    ]

src/backend/chat/models.py

@@ -44,7 +44,12 @@ class ChatConversation(BaseModel):
         null=True,
         help_text="Title of the chat conversation",
     )
-
+    title_set_by_user_at = models.DateTimeField(
+        blank=True,
+        null=True,
+        help_text="Timestamp when the user manually set the title. If set, prevent automatic "
+        "title generation.",
+    )
     ui_messages = models.JSONField(
         default=list,
         blank=True,

src/backend/chat/serializers.py

@@ -4,6 +4,7 @@ from typing import Optional
 from urllib.parse import quote
 
 from django.conf import settings
+from django.utils import timezone
 
 from django_pydantic_field.rest_framework import SchemaField  # pylint: disable=no-name-in-module
 from drf_spectacular.utils import extend_schema_field
@@ -27,6 +28,12 @@ class ChatConversationSerializer(serializers.ModelSerializer):
         fields = ["id", "title", "created_at", "updated_at", "messages", "owner"]
         read_only_fields = ["id", "created_at", "updated_at", "messages"]
 
+    def update(self, instance, validated_data):
+        # If title is being changed, mark it as user-set
+        if "title" in validated_data and validated_data["title"] != instance.title:
+            instance.title_set_by_user_at = timezone.now()
+        return super().update(instance, validated_data)
+
 
 class ChatConversationInputSerializer(serializers.Serializer):
     """

src/backend/chat/tests/agents/test_title_generation_agent.py

@@ -0,0 +1,66 @@
+"""Test cases for the TitleGenerationAgent class."""
+
+# pylint: disable=protected-access
+
+import pytest
+from pydantic_ai.models.openai import OpenAIChatModel
+
+from chat.agents.conversation import TitleGenerationAgent
+
+
+@pytest.fixture(autouse=True)
+def base_settings(settings):
+    """Set up base settings for the tests."""
+    settings.AI_BASE_URL = "https://api.llm.com/v1/"
+    settings.AI_API_KEY = "test-key"
+    settings.AI_MODEL = "model-XYZ"
+    settings.AI_AGENT_INSTRUCTIONS = "You are a helpful assistant"
+    settings.AI_AGENT_TOOLS = []
+    settings.LLM_DEFAULT_MODEL_HRID = "default-model"
+
+
+def test_title_generation_agent_uses_default_model_hrid(settings):
+    """Test that TitleGenerationAgent uses LLM_DEFAULT_MODEL_HRID from settings."""
+    settings.AI_MODEL = "custom-llm-model"
+    settings.AI_BASE_URL = "https://custom.api.com/v1/"
+    settings.AI_API_KEY = "custom-key"
+    settings.LLM_DEFAULT_MODEL_HRID = "default-model"
+
+    agent = TitleGenerationAgent()
+
+    assert isinstance(agent._model, OpenAIChatModel)
+    assert settings.LLM_CONFIGURATIONS["default-model"].model_name == "custom-llm-model"
+    assert agent._model.model_name == "custom-llm-model"
+
+
+def test_title_generation_agent_model_configuration():
+    """Test that the agent model is properly configured."""
+    agent = TitleGenerationAgent()
+
+    assert isinstance(agent._model, OpenAIChatModel)
+    assert agent._model.model_name == "model-XYZ"
+    assert str(agent._model.client.base_url) == "https://api.llm.com/v1/"
+    assert agent._model.client.api_key == "test-key"
+
+
+def test_title_generation_agent_has_no_tools():
+    """Test that TitleGenerationAgent has no tools configured."""
+    agent = TitleGenerationAgent()
+
+    assert agent._function_toolset.tools == {}
+    assert not agent.get_tools()
+
+
+def test_title_generation_agent_instructions():
+    """Test that the agent instructions contain the system prompt."""
+    agent = TitleGenerationAgent()
+
+    # The agent should have the title generation system prompt as instructions
+    instructions = agent._instructions
+    assert len(instructions) == 1
+    expected = (
+        "You are a title generator. Your task is to create concise, descriptive titles "
+        "that accurately summarize conversation content and help the user quickly identify the "
+        "conversation.\n\n"
+    )
+    assert instructions[0] == expected

src/backend/chat/tests/tools/test_web_search_brave.py

@@ -38,9 +38,6 @@ def brave_settings(settings):
     settings.BRAVE_SEARCH_EXTRA_SNIPPETS = True
     settings.BRAVE_SUMMARIZATION_ENABLED = False
     settings.BRAVE_CACHE_TTL = 3600
-    settings.RAG_DOCUMENT_SEARCH_BACKEND = (
-        "chat.agent_rag.document_rag_backends.albert_rag_backend.AlbertRagBackend"
-    )
     settings.BRAVE_RAG_WEB_SEARCH_CHUNK_NUMBER = 5
 
 

src/backend/chat/tests/views/chat/conftest.py

@@ -0,0 +1,17 @@
+"""Common test fixtures for chat views tests."""
+
+from unittest import mock
+
+import pytest
+
+
+@pytest.fixture(autouse=True)
+def mock_process_request():
+    """
+    Mock process_request to bypass OIDC authentication in tests.
+    """
+    with mock.patch(
+        "lasuite.oidc_login.decorators.RefreshOIDCAccessToken.process_request"
+    ) as mocked_process_request:
+        mocked_process_request.return_value = None
+        yield mocked_process_request

src/backend/chat/tests/views/chat/conversations/conftest.py

@@ -1,5 +1,6 @@
 """Common test fixtures for chat conversation endpoint tests."""
 
+import asyncio
 import json
 
 from django.utils import timezone
@@ -10,15 +11,9 @@ import respx
 from freezegun import freeze_time
 
 
-@pytest.fixture(name="mock_openai_stream")
-@freeze_time("2025-07-25T10:36:35.297675Z")
-def fixture_mock_openai_stream():
-    """
-    Fixture to mock the OpenAI stream response.
-
-    See https://platform.openai.com/docs/api-reference/chat-streaming/streaming
-    """
-    openai_stream = (
+def _create_openai_stream_data():
+    """Helper to create OpenAI stream data."""
+    return (
         "data: "
         + json.dumps(
             {
@@ -59,12 +54,111 @@ def fixture_mock_openai_stream():
         "data: [DONE]\n\n"
     )
 
+
+def _create_mock_openai_route(with_delays: bool = False, delay_seconds: float = 1.0):
+    """Create a mock OpenAI stream route with optional delays."""
+    openai_stream = _create_openai_stream_data()
+
     async def mock_stream():
-        for line in openai_stream.splitlines(keepends=True):
+        lines = openai_stream.splitlines(keepends=True)
+        for i, line in enumerate(lines):
             yield line.encode()
+            if with_delays and i == 1:
+                # Delay after second line to trigger keepalive during streaming
+                await asyncio.sleep(delay_seconds)
+
+    return respx.post("https://www.external-ai-service.com/chat/completions").mock(
+        return_value=httpx.Response(200, stream=mock_stream())
+    )
+
+
+@pytest.fixture(name="mock_openai_stream")
+@freeze_time("2025-07-25T10:36:35.297675Z")
+def fixture_mock_openai_stream():
+    """
+    Fixture to mock the OpenAI stream response (no delays).
+
+    See https://platform.openai.com/docs/api-reference/chat-streaming/streaming
+    """
+    return _create_mock_openai_route(with_delays=False)
+
+
+@pytest.fixture(name="mock_openai_stream_slow")
+def fixture_mock_openai_stream_slow():
+    """
+    Fixture to mock the OpenAI stream response with delays to trigger keepalives.
+
+    No @freeze_time decorator because asyncio.sleep() needs real time to work properly.
+    """
+    return _create_mock_openai_route(with_delays=True, delay_seconds=1.0)
+
+
+@pytest.fixture(name="mock_openai_stream_with_title_generation")
+@freeze_time("2025-07-25T10:36:35.297675Z")
+def fixture_mock_openai_stream_with_title_generation():
+    """
+    Fixture to mock the OpenAI stream response.
+
+
+    This fixture handles two different types of API calls made during a single request:
+
+    1. **Conversation (streaming)**: The main chat uses `stream=True` to get real-time
+       token-by-token responses. The API returns chunked data like:
+       `data: {"choices": [{"delta": {"content": "Hello"}}]}`
+
+    2. **Title generation (non-streaming)**: After the conversation, the backend calls
+       the API again with `stream=False` to generate a title. This returns a standard
+       JSON response with the complete message.
+
+    The `handle_request` function inspects each incoming request's body to determine
+    which type of response to return:
+    - `{"stream": true, ...}`  → SSE streaming response
+    - `{"stream": false, ...}` → JSON response with generated title
+    Each call gets a new generator instance (avoiding generator exhaustion)
+    """
+
+    def create_stream_response():
+        """Create a fresh streaming response for each call."""
+        openai_stream = _create_openai_stream_data()
+
+        async def mock_stream():
+            for line in openai_stream.splitlines(keepends=True):
+                yield line.encode()
+
+        return httpx.Response(200, stream=mock_stream())
+
+    def create_non_stream_response():
+        """Create a non-streaming response for title generation."""
+        return httpx.Response(
+            200,
+            json={
+                "id": "chatcmpl-title",
+                "object": "chat.completion",
+                "created": int(timezone.make_naive(timezone.now()).timestamp()),
+                "model": "test-model",
+                "choices": [
+                    {
+                        "index": 0,
+                        "message": {
+                            "role": "assistant",
+                            "content": "GENERATED TITLE",
+                        },
+                        "finish_reason": "stop",
+                    }
+                ],
+                "usage": {"prompt_tokens": 50, "completion_tokens": 5, "total_tokens": 55},
+            },
+        )
+
+    def handle_request(request):
+        """Route to streaming or non-streaming response based on request."""
+        body = json.loads(request.content)
+        if body.get("stream", False):
+            return create_stream_response()
+        return create_non_stream_response()
 
     route = respx.post("https://www.external-ai-service.com/chat/completions").mock(
-        return_value=httpx.Response(200, stream=mock_stream())
+        side_effect=handle_request
     )
 
     return route

src/backend/chat/tests/views/chat/conversations/test_conversation.py

@@ -3,6 +3,7 @@
 
 import json
 import logging
+from unittest.mock import ANY, patch
 
 from django.utils import timezone
 
@@ -221,6 +222,133 @@ def test_post_conversation_data_protocol(api_client, mock_openai_stream):
     ]
 
 
+@freeze_time("2025-07-25T10:36:35.297675Z")
+@respx.mock
+@patch("chat.keepalive.get_current_time")
+def test_post_conversation_data_protocol_triggers_keepalives(
+    mock_time, api_client, mock_openai_stream
+):
+    """Test streaming response contains keepalive messages"""
+    chat_conversation = ChatConversationFactory(owner__language="en-us")
+    mock_time.side_effect = [float(i * 60) for i in range(10)]
+    url = f"/api/v1.0/chats/{chat_conversation.pk}/conversation/?protocol=data"
+    data = {
+        "messages": [
+            {
+                "id": "yuPoOuBkKA4FnKvk",
+                "role": "user",
+                "parts": [{"text": "Hello", "type": "text"}],
+                "content": "Hello",
+                "createdAt": "2025-07-03T15:22:17.105Z",
+            }
+        ]
+    }
+    api_client.force_login(chat_conversation.owner)
+
+    response = api_client.post(url, data, format="json")
+
+    assert response.status_code == status.HTTP_200_OK
+    assert response.get("Content-Type") == "text/event-stream"
+    assert response.get("x-vercel-ai-data-stream") == "v1"
+    assert response.streaming
+
+    # Wait for the streaming content to be fully received
+    response_content = b"".join(response.streaming_content).decode("utf-8")
+
+    # Replace UUIDs with placeholders for assertion
+    response_content = replace_uuids_with_placeholder(response_content)
+
+    assert response_content == (
+        '0:"Hello"\n'
+        '0:" there"\n'
+        'f:{"messageId":"<mocked_uuid>"}\n'
+        'd:{"finishReason":"stop","usage":{"promptTokens":0,"completionTokens":0}}\n'
+        '2:[{"status": "WAITING"}]\n'
+    )
+
+    assert mock_openai_stream.called
+
+    chat_conversation.refresh_from_db()
+    assert chat_conversation.ui_messages == [
+        {
+            "content": "Hello",
+            "createdAt": "2025-07-03T15:22:17.105Z",
+            "id": "yuPoOuBkKA4FnKvk",
+            "parts": [{"text": "Hello", "type": "text"}],
+            "role": "user",
+        }
+    ]
+
+    assert len(chat_conversation.messages) == 2
+
+    assert chat_conversation.messages[0].id == IsUUID(4)
+    assert chat_conversation.messages[0] == UIMessage(
+        id=chat_conversation.messages[0].id,  # don't test the message ID here
+        createdAt=timezone.now(),  # Mocked timestamp
+        content="Hello",
+        reasoning=None,
+        experimental_attachments=None,
+        role="user",
+        annotations=None,
+        toolInvocations=None,
+        parts=[TextUIPart(type="text", text="Hello")],
+    )
+
+    assert chat_conversation.messages[1].id == IsUUID(4)
+    assert chat_conversation.messages[1] == UIMessage(
+        id=chat_conversation.messages[1].id,  # don't test the message ID here
+        createdAt=timezone.now(),  # Mocked timestamp
+        content="Hello there",
+        reasoning=None,
+        experimental_attachments=None,
+        role="assistant",
+        annotations=None,
+        toolInvocations=None,
+        parts=[TextUIPart(type="text", text="Hello there")],
+    )
+
+    _run_id = chat_conversation.pydantic_messages[0]["run_id"]
+    assert chat_conversation.pydantic_messages == [
+        {
+            "instructions": (
+                "You are a helpful test assistant :)\n\n"
+                "Today is Friday 25/07/2025.\n\n"
+                "Answer in english."
+            ),
+            "kind": "request",
+            "parts": [
+                {
+                    "content": ["Hello"],
+                    "part_kind": "user-prompt",
+                    "timestamp": "2025-07-25T10:36:35.297675Z",
+                },
+            ],
+            "run_id": _run_id,
+        },
+        {
+            "finish_reason": "stop",
+            "kind": "response",
+            "model_name": "test-model",
+            "parts": [{"content": "Hello there", "id": None, "part_kind": "text"}],
+            "provider_details": {"finish_reason": "stop"},
+            "provider_name": "openai",
+            "provider_response_id": "chatcmpl-1234567890",
+            "timestamp": "2025-07-25T10:36:35.297675Z",
+            "usage": {
+                "cache_audio_read_tokens": 0,
+                "cache_read_tokens": 0,
+                "cache_write_tokens": 0,
+                "details": {},
+                "input_audio_tokens": 0,
+                "input_tokens": 0,
+                "output_audio_tokens": 0,
+                "output_tokens": 0,
+            },
+            "run_id": _run_id,
+        },
+    ]
+
+
 @freeze_time("2025-07-25T10:36:35.297675Z")
 @respx.mock
 def test_post_conversation_text_protocol(api_client, mock_openai_stream):
@@ -1344,3 +1472,143 @@ async def test_post_conversation_async(api_client, mock_openai_stream, monkeypat
             "run_id": _run_id,
         },
     ]
+
+
+@freeze_time("2025-07-25T10:36:35.297675Z", tick=True)
+@respx.mock
+@pytest.mark.asyncio
+async def test_post_conversation_async_triggers_keepalive(
+    api_client, mock_openai_stream_slow, monkeypatch, caplog, settings
+):
+    """Test posting messages to a conversation using the 'data' protocol."""
+    monkeypatch.setenv("PYTHON_SERVER_MODE", "async")
+
+    settings.KEEPALIVE_INTERVAL = 1  # s
+
+    chat_conversation = await sync_to_async(ChatConversationFactory)(owner__language="en-us")
+
+    url = f"/api/v1.0/chats/{chat_conversation.pk}/conversation/?protocol=data"
+    data = {
+        "messages": [
+            {
+                "id": "yuPoOuBkKA4FnKvk",
+                "role": "user",
+                "parts": [{"text": "Hello", "type": "text"}],
+                "content": "Hello",
+                "createdAt": "2025-07-03T15:22:17.105Z",
+            }
+        ]
+    }
+    await api_client.aforce_login(chat_conversation.owner)
+
+    caplog.clear()
+    caplog.set_level(level=logging.DEBUG, logger="chat.views")
+
+    response = await sync_to_async(api_client.post)(url, data, format="json")  # client is sync
+
+    assert response.status_code == status.HTTP_200_OK
+    assert response.get("Content-Type") == "text/event-stream"
+    assert response.get("x-vercel-ai-data-stream") == "v1"
+    assert response.streaming
+
+    assert "Using ASYNC streaming for chat conversation" in caplog.text
+
+    # Wait for the streaming content to be fully received => async iterator -> list
+    # This fails it the streaming is not an async generator
+    response_content = b"".join([content async for content in response.streaming_content]).decode(
+        "utf-8"
+    )
+
+    # Replace UUIDs with placeholders for assertion
+    response_content = replace_uuids_with_placeholder(response_content)
+
+    assert response_content == (
+        '0:"Hello"\n'
+        '2:[{"status": "WAITING"}]\n'
+        '0:" there"\n'
+        'f:{"messageId":"<mocked_uuid>"}\n'
+        'd:{"finishReason":"stop","usage":{"promptTokens":0,"completionTokens":0}}\n'
+    )
+
+    assert mock_openai_stream_slow.called
+
+    await chat_conversation.arefresh_from_db()
+    assert chat_conversation.ui_messages == [
+        {
+            "content": "Hello",
+            "createdAt": "2025-07-03T15:22:17.105Z",
+            "id": "yuPoOuBkKA4FnKvk",
+            "parts": [{"text": "Hello", "type": "text"}],
+            "role": "user",
+        }
+    ]
+
+    assert len(chat_conversation.messages) == 2
+
+    assert chat_conversation.messages[0].id == IsUUID(4)
+    assert chat_conversation.messages[0] == UIMessage(
+        id=chat_conversation.messages[0].id,  # don't test the message ID here
+        createdAt=chat_conversation.messages[0].createdAt,  # Mocked timestamp
+        content="Hello",
+        reasoning=None,
+        experimental_attachments=None,
+        role="user",
+        annotations=None,
+        toolInvocations=None,
+        parts=[TextUIPart(type="text", text="Hello")],
+    )
+
+    assert chat_conversation.messages[1].id == IsUUID(4)
+    assert chat_conversation.messages[1] == UIMessage(
+        id=chat_conversation.messages[1].id,  # don't test the message ID here
+        createdAt=chat_conversation.messages[1].createdAt,  # Mocked timestamp
+        content="Hello there",
+        reasoning=None,
+        experimental_attachments=None,
+        role="assistant",
+        annotations=None,
+        toolInvocations=None,
+        parts=[TextUIPart(type="text", text="Hello there")],
+    )
+
+    _run_id = chat_conversation.pydantic_messages[0]["run_id"]
+
+    # using ANY because time is not frozen in this api mock
+    assert chat_conversation.pydantic_messages == [
+        {
+            "instructions": (
+                "You are a helpful test assistant :)\n\n"
+                "Today is Friday 25/07/2025.\n\nAnswer in english."
+            ),
+            "kind": "request",
+            "parts": [
+                {
+                    "content": ["Hello"],
+                    "part_kind": "user-prompt",
+                    "timestamp": ANY,
+                },
+            ],
+            "run_id": _run_id,
+        },
+        {
+            "finish_reason": "stop",
+            "kind": "response",
+            "model_name": "test-model",
+            "parts": [{"content": "Hello there", "id": None, "part_kind": "text"}],
+            "provider_details": {"finish_reason": "stop"},
+            "provider_name": "openai",
+            "provider_response_id": "chatcmpl-1234567890",
+            "timestamp": ANY,
+            "usage": {
+                "cache_audio_read_tokens": 0,
+                "cache_read_tokens": 0,
+                "cache_write_tokens": 0,
+                "details": {},
+                "input_audio_tokens": 0,
+                "input_tokens": 0,
+                "output_audio_tokens": 0,
+                "output_tokens": 0,
+            },
+            "run_id": _run_id,
+        },
+    ]

src/backend/chat/tests/views/chat/conversations/test_conversation_with_document_upload.py

@@ -8,6 +8,7 @@ import logging
 from io import BytesIO
 from unittest import mock
 
+from django.contrib.sessions.backends.cache import SessionStore
 from django.utils import formats, timezone
 
 import httpx
@@ -41,28 +42,49 @@ from chat.tests.utils import replace_uuids_with_placeholder
 pytestmark = pytest.mark.django_db(transaction=True)
 
 
-@pytest.fixture(autouse=True)
-def ai_settings(settings):
+@pytest.fixture(
+    autouse=True,
+    params=[
+        "chat.agent_rag.document_rag_backends.find_rag_backend.FindRagBackend",
+        "chat.agent_rag.document_rag_backends.albert_rag_backend.AlbertRagBackend",
+    ],
+)
+def ai_settings(request, settings):
     """Fixture to set AI service URLs for testing."""
-    settings.AI_BASE_URL = "https://www.external-ai-service.com/"
-    settings.AI_API_KEY = "test-api-key"
-    settings.AI_MODEL = "test-model"
-    settings.AI_AGENT_INSTRUCTIONS = "You are a helpful test assistant :)"
 
-    # Enable Albert API for document search
-    settings.RAG_DOCUMENT_SEARCH_BACKEND = (
-        "chat.agent_rag.document_rag_backends.albert_rag_backend.AlbertRagBackend"
-    )
-    settings.ALBERT_API_URL = "https://albert.api.etalab.gouv.fr"
-    settings.ALBERT_API_KEY = "albert-api-key"
+    # enable on rag document search tool
+    settings.RAG_DOCUMENT_SEARCH_BACKEND = request.param
     settings.RAG_WEB_SEARCH_PROMPT_UPDATE = (
         "Based on the following document contents:\n\n{search_results}\n\n"
         "Please answer the user's question: {user_prompt}"
     )
 
+    settings.AI_BASE_URL = "https://www.external-ai-service.com/"
+    settings.AI_API_KEY = "test-api-key"
+    settings.AI_MODEL = "test-model"
+    settings.AI_AGENT_INSTRUCTIONS = "You are a helpful test assistant :)"
+
+    # Albert API settings
+    settings.ALBERT_API_URL = "https://albert.api.etalab.gouv.fr"
+    settings.ALBERT_API_KEY = "albert-api-key"
+
+    # Find API settings
+    settings.FIND_API_URL = "https://find.api.example.com"
+    settings.FIND_API_KEY = "find-api-key"
+
     return settings
 
 
+@pytest.fixture(autouse=True)
+def mock_refresh_access_token():
+    """Mock refresh_access_token to bypass token refresh in tests."""
+    with mock.patch("utils.oidc.refresh_access_token") as mocked_refresh_access_token:
+        session = SessionStore()
+        session["oidc_access_token"] = "mocked-access-token"
+        mocked_refresh_access_token.return_value = session
+        yield mocked_refresh_access_token
+
+
 @pytest.fixture(name="sample_pdf_content")
 def fixture_sample_pdf_content():
     """Create a dummy PDF content as BytesIO."""
@@ -81,10 +103,18 @@ def fixture_sample_pdf_content():
     return BytesIO(pdf_data)
 
 
-@pytest.fixture(name="mock_albert_api")
-def fixture_mock_albert_api():
+@pytest.fixture(name="mock_document_api")
+def fixture_mock_document_api():
     """Fixture to mock the Albert API endpoints."""
     # Mock collection creation
+
+    document_name = "sample.pdf"
+    document_content = "This is the content of the PDF."
+    prompt_tokens = 10
+    completion_tokens = 20
+    search_method = "semantic"
+    search_score = 0.9
+
     responses.post(
         "https://albert.api.etalab.gouv.fr/v1/collections",
         json={"id": "123", "name": "test-collection"},
@@ -101,7 +131,7 @@ def fixture_mock_albert_api():
                     "metadata": {"document_name": "sample.pdf"},
                 }
             ],
-            "usage": {"prompt_tokens": 10, "completion_tokens": 20},
+            "usage": {"prompt_tokens": prompt_tokens, "completion_tokens": completion_tokens},
         },
         status=status.HTTP_200_OK,
     )
@@ -119,20 +149,42 @@ def fixture_mock_albert_api():
         json={
             "data": [
                 {
-                    "method": "semantic",
+                    "method": search_method,
                     "chunk": {
                         "id": 123,
-                        "content": "This is the content of the PDF.",
-                        "metadata": {"document_name": "sample.pdf"},
+                        "content": document_content,
+                        "metadata": {"document_name": document_name},
                     },
-                    "score": 0.9,
+                    "score": search_score,
                 }
             ],
-            "usage": {"prompt_tokens": 10, "completion_tokens": 20},
+            "usage": {"prompt_tokens": prompt_tokens, "completion_tokens": completion_tokens},
         },
         status=status.HTTP_200_OK,
     )
 
+    # Mock document indexing (Find API)
+    responses.post(
+        "https://find.api.example.com/api/v1.0/documents/index/",
+        json={"id": "456", "status": "indexed"},
+        status=status.HTTP_200_OK,
+    )
+
+    # Mock document search (Find API)
+    responses.post(
+        "https://find.api.example.com/api/v1.0/documents/search/",
+        json=[
+            {
+                "_source": {
+                    "title.fr": document_name,
+                    "content.fr": document_content,
+                },
+                "_score": search_score,
+            }
+        ],
+        status=status.HTTP_200_OK,
+    )
+
 
 @pytest.fixture(name="mock_summarization_agent")
 def fixture_mock_summarization_agent():
@@ -219,7 +271,7 @@ def fixture_mock_openai_stream():
 def test_post_conversation_with_document_upload(
     # pylint: disable=too-many-arguments,too-many-positional-arguments
     api_client,
-    mock_albert_api,  # pylint: disable=unused-argument
+    mock_document_api,  # pylint: disable=unused-argument
     sample_pdf_content,
     today_promt_date,
     mock_ai_agent_service,
@@ -548,7 +600,7 @@ def test_post_conversation_with_document_upload_feature_disabled(
 @freeze_time()
 def test_post_conversation_with_document_upload_summarize(  # pylint: disable=too-many-arguments,too-many-positional-arguments  # noqa: PLR0913
     api_client,
-    mock_albert_api,  # pylint: disable=unused-argument
+    mock_document_api,  # pylint: disable=unused-argument
     sample_pdf_content,
     today_promt_date,
     mock_ai_agent_service,

src/backend/chat/tests/views/chat/conversations/test_conversation_with_document_url.py

@@ -37,11 +37,19 @@ from chat.tests.utils import replace_uuids_with_placeholder
 pytestmark = pytest.mark.django_db(transaction=True)
 
 
-@pytest.fixture(autouse=True)
-def ai_settings(settings):
+@pytest.fixture(
+    autouse=True,
+    params=[
+        "chat.agent_rag.document_rag_backends.find_rag_backend.FindRagBackend",
+        "chat.agent_rag.document_rag_backends.albert_rag_backend.AlbertRagBackend",
+    ],
+)
+def ai_settings(request, settings):
     """Fixture to set AI service URLs for testing."""
+    settings.RAG_DOCUMENT_SEARCH_BACKEND = request.param
     settings.AI_BASE_URL = "https://www.external-ai-service.com/"
     settings.AI_API_KEY = "test-api-key"
+    settings.FIND_API_KEY = "find-api-key"
     settings.AI_MODEL = "test-model"
     settings.AI_AGENT_INSTRUCTIONS = "You are a helpful test assistant :)"
     return settings
@@ -85,6 +93,10 @@ def test_post_conversation_with_local_pdf_document_url(
         json={"id": "document_id", "object": "document"},
         status=200,
     )
+    responses.post(
+        "https://app-find/api/v1.0/documents/index/",
+        status=200,
+    )
 
     chat_conversation = ChatConversationFactory(owner__language="en-us")
     api_client.force_authenticate(user=chat_conversation.owner)
@@ -120,29 +132,28 @@ def test_post_conversation_with_local_pdf_document_url(
     )
 
     async def agent_model(messages: list[ModelMessage], _info: AgentInfo):
-        presigned_url = messages[0].parts[0].content[1].url
-        assert presigned_url.startswith("http://localhost:9000/conversations-media-storage/")
-        assert presigned_url.find("X-Amz-Signature=") != -1
-        assert presigned_url.find("X-Amz-Date=") != -1
-        assert presigned_url.find("X-Amz-Expires=") != -1
-
         assert messages == [
             ModelRequest(
                 parts=[
-                    UserPromptPart(
-                        content=[
-                            "What is in this document?",
-                            DocumentUrl(
-                                url=presigned_url,  # presigned URL for this conversation
-                                media_type="application/pdf",
-                                identifier="sample.pdf",
-                            ),
-                        ],
-                        timestamp=timezone.now(),
-                    ),
+                    UserPromptPart(content=["What is in this document?"], timestamp=timezone.now())
                 ],
-                instructions=f"You are a helpful test assistant :)\n\n{today_promt_date}"
-                "\n\nAnswer in english.",
+                instructions=(
+                    "You are a helpful test assistant :)\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 "
+                    "tool instead.\n\nWhen you receive a result from the summarization tool, "
+                    "you MUST return it directly to the user without any modification, "
+                    "paraphrasing, or additional summarization.The tool already produces "
+                    "optimized summaries that should be presented verbatim.You may translate "
+                    "the summary if required, but you MUST preserve all the information from "
+                    "the original summary.You may add a follow-up question after the summary "
+                    "if needed.\n\n"
+                    "[Internal context] User documents are attached to this conversation. "
+                    "Do not request re-upload of documents; consider them already available "
+                    "via the internal store."
+                ),
                 run_id=messages[0].run_id,
             )
         ]
@@ -186,9 +197,7 @@ def test_post_conversation_with_local_pdf_document_url(
         createdAt=timezone.now(),
         content="What is in this document?",
         reasoning=None,
-        experimental_attachments=[
-            Attachment(name="sample.pdf", contentType="application/pdf", url=document_url)
-        ],
+        experimental_attachments=None,  # We should fix this, but for now document appears in source
         role="user",
         annotations=None,
         toolInvocations=None,
@@ -220,20 +229,29 @@ def test_post_conversation_with_local_pdf_document_url(
         {
             "instructions": "You are a helpful test assistant :)\n\n"
             f"{today_promt_date}\n\n"
-            "Answer in english.",
+            "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 tool instead.\n"
+            "\n"
+            "When you receive a result from the summarization tool, you "
+            "MUST return it directly to the user without any "
+            "modification, paraphrasing, or additional summarization.The "
+            "tool already produces optimized summaries that should be "
+            "presented verbatim.You may translate the summary if "
+            "required, but you MUST preserve all the information from "
+            "the original summary.You may add a follow-up question after "
+            "the summary if needed.\n"
+            "\n"
+            "[Internal context] User documents are attached to this "
+            "conversation. Do not request re-upload of documents; "
+            "consider them already available via the internal store.",
             "kind": "request",
             "parts": [
                 {
                     "content": [
                         "What is in this document?",
-                        {
-                            "force_download": False,
-                            "identifier": "sample.pdf",
-                            "kind": "document-url",
-                            "media_type": "application/pdf",
-                            "url": document_url,
-                            "vendor_metadata": None,
-                        },
                     ],
                     "part_kind": "user-prompt",
                     "timestamp": timestamp,
@@ -795,6 +813,10 @@ def test_post_conversation_with_local_not_pdf_document_url(
         json={"id": "document_id", "object": "document"},
         status=200,
     )
+    responses.post(
+        "https://app-find/api/v1.0/documents/index/",
+        status=200,
+    )
 
     chat_conversation = ChatConversationFactory(owner__language="en-us")
     api_client.force_authenticate(user=chat_conversation.owner)

src/backend/chat/tests/views/chat/conversations/test_conversation_with_history.py

@@ -2,6 +2,7 @@
 # pylint: disable=too-many-lines
 
 import json
+from unittest.mock import patch
 
 from django.utils import timezone
 
@@ -11,6 +12,7 @@ from dirty_equals import IsUUID
 from freezegun import freeze_time
 from rest_framework import status
 
+from chat.agents.conversation import TitleGenerationAgent
 from chat.ai_sdk_types import (
     Attachment,
     TextUIPart,
@@ -35,6 +37,7 @@ def ai_settings(settings):
     settings.AI_MODEL = "test-model"
     settings.AI_AGENT_INSTRUCTIONS = "You are a helpful test assistant :)"
 
+    settings.AUTO_TITLE_AFTER_USER_MESSAGES = None  # disable auto title generation
     return settings
 
 
@@ -1573,3 +1576,307 @@ def test_post_conversation_add_image_to_conversation_with_tool_history(
         toolInvocations=None,
         parts=[TextUIPart(type="text", text="I see a cat in the picture.")],
     )
+
+
+@freeze_time("2025-07-25T10:36:35.297675Z")
+@respx.mock
+@patch("chat.clients.pydantic_ai.TitleGenerationAgent", wraps=TitleGenerationAgent)
+def test_post_conversation_triggers_automatic_title_generation_after_first_message(
+    mock_title_agent, api_client, mock_openai_stream_with_title_generation, settings
+):
+    """
+    Test that posting the first user message triggers automatic title generation.
+
+    AUTO_TITLE_AFTER_USER_MESSAGES = 1
+
+    The conversation is a new one. Posting the first message
+    should trigger title generation via the TitleGenerationAgent.
+    """
+    # Configure the title generation threshold
+    settings.AUTO_TITLE_AFTER_USER_MESSAGES = 1
+    conversation = ChatConversationFactory()
+    url = f"/api/v1.0/chats/{conversation.pk}/conversation/?protocol=data"
+    data = {
+        "messages": [
+            {
+                "id": "third-user-msg",
+                "role": "user",
+                "parts": [{"text": "Can you explain backpropagation?", "type": "text"}],
+                "content": "Can you explain backpropagation?",
+                "createdAt": "2025-07-25T10:36:00.000Z",
+            }
+        ]
+    }
+    api_client.force_login(conversation.owner)
+
+    conversation.title = "initial title"
+    conversation.save()
+
+    assert not conversation.title_set_by_user_at
+
+    response = api_client.post(url, data, format="json")
+
+    assert response.status_code == status.HTTP_200_OK
+    assert response.get("Content-Type") == "text/event-stream"
+    assert response.streaming
+
+    # Wait for the streaming content to be fully received
+    response_content = b"".join(response.streaming_content).decode("utf-8")
+
+    # Verify the conversation_metadata event is in the stream
+
+    assert '"type": "conversation_metadata"' in response_content
+
+    # Refresh and verify title was updated
+    conversation.refresh_from_db()
+
+    assert conversation.title == "GENERATED TITLE"
+    # title_set_by_user_at should remain None since it was auto-generated
+    assert not conversation.title_set_by_user_at
+
+    assert mock_openai_stream_with_title_generation.called
+    assert mock_openai_stream_with_title_generation.call_count == 2
+
+    # Verify TitleGenerationAgent was called
+    mock_title_agent.assert_called_once()
+
+
+@freeze_time("2025-07-25T10:36:35.297675Z")
+@respx.mock
+def test_post_conversation_triggers_automatic_title_generation_at_threshold(
+    api_client, mock_openai_stream_with_title_generation, settings, history_conversation
+):
+    """
+    Test that posting the 3rd user message triggers automatic title generation.
+
+    AUTO_TITLE_AFTER_USER_MESSAGES = 3
+
+
+    The history_conversation fixture has 2 user messages. Posting a 3rd message
+    should trigger title generation via the TitleGenerationAgent.
+    """
+    # Configure the title generation threshold
+    settings.AUTO_TITLE_AFTER_USER_MESSAGES = 3
+
+    url = f"/api/v1.0/chats/{history_conversation.pk}/conversation/?protocol=data"
+    data = {
+        "messages": [
+            {
+                "id": "third-user-msg",
+                "role": "user",
+                "parts": [{"text": "Can you explain backpropagation?", "type": "text"}],
+                "content": "Can you explain backpropagation?",
+                "createdAt": "2025-07-25T10:36:00.000Z",
+            }
+        ]
+    }
+    api_client.force_login(history_conversation.owner)
+
+    history_conversation.title = "initial title"
+    history_conversation.save()
+
+    assert not history_conversation.title_set_by_user_at
+
+    response = api_client.post(url, data, format="json")
+
+    assert response.status_code == status.HTTP_200_OK
+    assert response.get("Content-Type") == "text/event-stream"
+    assert response.streaming
+
+    # Wait for the streaming content to be fully received
+    response_content = b"".join(response.streaming_content).decode("utf-8")
+
+    # Verify the conversation_metadata event is in the stream
+
+    assert '"type": "conversation_metadata"' in response_content
+
+    # Refresh and verify title was updated
+    history_conversation.refresh_from_db()
+
+    assert history_conversation.title == "GENERATED TITLE"
+    # title_set_by_user_at should remain None since it was auto-generated
+    assert not history_conversation.title_set_by_user_at
+
+    assert mock_openai_stream_with_title_generation.called
+    assert mock_openai_stream_with_title_generation.call_count == 2
+
+
+@freeze_time("2025-07-25T10:36:35.297675Z")
+@respx.mock
+def test_post_conversation_does_not_regenerate_title_when_user_set(
+    api_client, mock_openai_stream_with_title_generation, settings, history_conversation
+):
+    """
+    Test that title is NOT regenerated if the user has manually set a title.
+    """
+    settings.AUTO_TITLE_AFTER_USER_MESSAGES = 3
+
+    # Simulate user having set a custom title
+    history_conversation.title = "My Custom Title"
+    history_conversation.title_set_by_user_at = timezone.now()
+    history_conversation.save()
+
+    url = f"/api/v1.0/chats/{history_conversation.pk}/conversation/?protocol=data"
+    data = {
+        "messages": [
+            {
+                "id": "third-user-msg",
+                "role": "user",
+                "parts": [{"text": "Can you explain backpropagation?", "type": "text"}],
+                "content": "Can you explain backpropagation?",
+                "createdAt": "2025-07-25T10:36:00.000Z",
+            }
+        ]
+    }
+    api_client.force_login(history_conversation.owner)
+
+    response = api_client.post(url, data, format="json")
+
+    assert response.status_code == status.HTTP_200_OK
+
+    # Consume the stream
+    response_content = b"".join(response.streaming_content).decode("utf-8")
+
+    # conversation_metadata should NOT be in the stream since title wasn't generated
+    assert "conversation_metadata" not in response_content
+
+    # Refresh and verify title was NOT changed
+    history_conversation.refresh_from_db()
+
+    assert history_conversation.title == "My Custom Title"
+    assert history_conversation.title_set_by_user_at
+
+    assert mock_openai_stream_with_title_generation.called
+    assert mock_openai_stream_with_title_generation.call_count == 1
+
+
+@freeze_time("2025-07-25T10:36:35.297675Z")
+@respx.mock
+def test_post_conversation_does_not_generate_title_before_threshold(
+    api_client, mock_openai_stream_with_title_generation, settings
+):
+    """
+    Test that title is NOT generated before reaching the message threshold.
+    """
+    settings.AUTO_TITLE_AFTER_USER_MESSAGES = 3
+
+    # Create a conversation with only 1 user message
+    history_timestamp = timezone.now().replace(year=2025, month=6, day=15, hour=10, minute=30)
+    conversation = ChatConversationFactory(title="initial title")
+
+    conversation.messages = [
+        UIMessage(
+            id="prev-user-msg-1",
+            createdAt=history_timestamp,
+            content="Hello!",
+            reasoning=None,
+            experimental_attachments=None,
+            role="user",
+            annotations=None,
+            toolInvocations=None,
+            parts=[TextUIPart(type="text", text="Hello!")],
+        ),
+        UIMessage(
+            id="prev-assistant-msg-1",
+            createdAt=history_timestamp.replace(minute=31),
+            content="Hi there! How can I help you?",
+            reasoning=None,
+            experimental_attachments=None,
+            role="assistant",
+            annotations=None,
+            toolInvocations=None,
+            parts=[TextUIPart(type="text", text="Hi there! How can I help you?")],
+        ),
+    ]
+    conversation.save()
+
+    url = f"/api/v1.0/chats/{conversation.pk}/conversation/?protocol=data"
+    data = {
+        "messages": [
+            {
+                "id": "second-user-msg",
+                "role": "user",
+                "parts": [{"text": "What's machine learning?", "type": "text"}],
+                "content": "What's machine learning?",
+                "createdAt": "2025-07-25T10:36:00.000Z",
+            }
+        ]
+    }
+    api_client.force_login(conversation.owner)
+
+    response = api_client.post(url, data, format="json")
+
+    assert response.status_code == status.HTTP_200_OK
+
+    # Consume the stream
+    response_content = b"".join(response.streaming_content).decode("utf-8")
+
+    # conversation_metadata should NOT be in the stream (only 2 user messages)
+    assert "conversation_metadata" not in response_content
+
+    # Refresh and verify title was not updated
+    conversation.refresh_from_db()
+
+    assert conversation.title == "initial title"
+    assert not conversation.title_set_by_user_at
+
+    assert mock_openai_stream_with_title_generation.call_count == 1
+
+
+@freeze_time("2025-07-25T10:36:35.297675Z")
+@respx.mock
+def test_post_conversation_does_not_generate_title_after_threshold(
+    api_client, mock_openai_stream_with_title_generation, settings, history_conversation
+):
+    """
+    Test that posting the 3rd user message does not trigger automatic title generation.
+
+    AUTO_TITLE_AFTER_USER_MESSAGES = 2
+
+    The history_conversation fixture has 2 user messages. Posting a 3rd message
+    should not trigger title generation.
+    """
+    # Configure the title generation threshold
+    settings.AUTO_TITLE_AFTER_USER_MESSAGES = 2
+
+    url = f"/api/v1.0/chats/{history_conversation.pk}/conversation/?protocol=data"
+    data = {
+        "messages": [
+            {
+                "id": "third-user-msg",
+                "role": "user",
+                "parts": [{"text": "Can you explain backpropagation?", "type": "text"}],
+                "content": "Can you explain backpropagation?",
+                "createdAt": "2025-07-25T10:36:00.000Z",
+            }
+        ]
+    }
+    api_client.force_login(history_conversation.owner)
+
+    history_conversation.title = "initial title"
+    history_conversation.save()
+
+    assert not history_conversation.title_set_by_user_at
+
+    response = api_client.post(url, data, format="json")
+
+    assert response.status_code == status.HTTP_200_OK
+    assert response.get("Content-Type") == "text/event-stream"
+    assert response.streaming
+
+    # Wait for the streaming content to be fully received
+    response_content = b"".join(response.streaming_content).decode("utf-8")
+
+    # Verify the conversation_metadata event is not in the stream
+
+    assert "conversation_metadata" not in response_content
+
+    # Refresh and verify title was NOT updated (past threshold)
+    history_conversation.refresh_from_db()
+
+    # title not updated
+    assert history_conversation.title == "initial title"
+    # title_set_by_user_at should remain None since it was auto-generated
+    assert not history_conversation.title_set_by_user_at
+
+    assert mock_openai_stream_with_title_generation.call_count == 1

src/backend/chat/tests/views/chat/test_create.py

@@ -28,6 +28,7 @@ def test_create_conversation(api_client):
     conversation = ChatConversation.objects.get(id=response.data["id"])
     assert conversation.owner == user
     assert conversation.title == "New Conversation"
+    assert not conversation.title_set_by_user_at
 
 
 def test_create_conversation_other_owner(api_client):

src/backend/chat/tests/views/chat/test_update.py

@@ -2,6 +2,7 @@
 
 import pytest
 from rest_framework import status
+from rest_framework.exceptions import ErrorDetail
 
 from core.factories import UserFactory
 
@@ -26,6 +27,34 @@ def test_update_conversation(api_client):
     # Verify in database
     conversation = ChatConversation.objects.get(id=chat_conversation.pk)
     assert conversation.title == "Updated Title"
+    assert conversation.title_set_by_user_at
+
+
+def test_update_conversation_limit_title_length(api_client):
+    """Test that updating a conversation with a title exceeding 100 characters fails validation."""
+    chat_conversation = ChatConversationFactory(title="Initial title")
+
+    url = f"/api/v1.0/chats/{chat_conversation.pk}/"
+    # Create a 101-character title to exceed the 100-character maximum limit
+    new_title = "X" * 101
+    data = {"title": new_title}
+    api_client.force_login(chat_conversation.owner)
+    response = api_client.put(url, data, format="json")
+
+    assert response.status_code == status.HTTP_400_BAD_REQUEST
+
+    assert response.data == {
+        "title": [
+            ErrorDetail(
+                string="Ensure this field has no more than 100 characters.", code="max_length"
+            )
+        ]
+    }
+
+    # Verify in database (title should remain unchanged)
+    conversation = ChatConversation.objects.get(id=chat_conversation.pk)
+    assert conversation.title == "Initial title"
+    assert not conversation.title_set_by_user_at
 
 
 def test_update_conversation_anonymous(api_client):

src/backend/chat/tools/document_search_rag.py

@@ -26,7 +26,7 @@ def add_document_rag_search_tool(agent: Agent) -> None:
 
         document_store = document_store_backend(ctx.deps.conversation.collection_id)
 
-        rag_results = document_store.search(query)
+        rag_results = document_store.search(query, session=ctx.deps.session)
 
         ctx.usage += RunUsage(
             input_tokens=rag_results.usage.prompt_tokens,

src/backend/chat/tools/web_search_brave.py

@@ -127,7 +127,7 @@ async def _extract_and_summarize_snippets_async(query: str, url: str) -> List[st
         return []
 
 
-async def _fetch_and_store_async(url: str, document_store) -> None:
+async def _fetch_and_store_async(url: str, document_store, **kwargs) -> None:
     """Fetch, extract and store text content from the URL in the document store."""
 
     try:
@@ -136,7 +136,7 @@ async def _fetch_and_store_async(url: str, document_store) -> None:
         logger.debug("Fetched document: %s", document)
 
         if document:
-            await document_store.astore_document(url, document)
+            await document_store.astore_document(url, document, **kwargs)
     except DocumentFetchError as e:
         logger.warning("Failed to fetch and store %s: %s", url, e)
         # Continue with other documents
@@ -307,19 +307,26 @@ async def web_search_brave_with_document_backend(ctx: RunContext, query: str) ->
         temp_collection_name = f"tmp-{uuid.uuid4()}"
         try:
             async with document_store_backend.temporary_collection_async(
-                temp_collection_name
+                temp_collection_name, session=ctx.deps.session
             ) as document_store:
                 # Fetch and store all documents concurrently
                 tasks = [
-                    _fetch_and_store_async(result["url"], document_store)
+                    _fetch_and_store_async(
+                        result["url"],
+                        document_store,
+                        user_sub=ctx.deps.user.sub,
+                        session=ctx.deps.session,
+                    )
                     for result in raw_search_results
                 ]
                 await asyncio.gather(*tasks, return_exceptions=True)
 
                 # Perform RAG search
                 rag_results = await document_store.asearch(
-                    query,
+                    query=query,
                     results_count=settings.BRAVE_RAG_WEB_SEARCH_CHUNK_NUMBER,
+                    session=ctx.deps.session,
+                    user_sub=ctx.deps.user.sub,
                 )
                 logger.info("RAG search returned:  %s", rag_results)
 

src/backend/chat/vercel_ai_sdk/encoder/__init__.py

@@ -2,6 +2,6 @@
 This module contains the EventEncoder class.
 """
 
-from .encoder import EventEncoder
+from .encoder import CURRENT_EVENT_ENCODER_VERSION, EventEncoder, EventEncoderVersion
 
-__all__ = ["EventEncoder"]
+__all__ = ["EventEncoder", "CURRENT_EVENT_ENCODER_VERSION", "EventEncoderVersion"]

src/backend/chat/vercel_ai_sdk/encoder/encoder.py

@@ -1,6 +1,7 @@
 """Event Encoder for Vercel AI SDK"""
 
-from typing import Literal, Union
+from enum import Enum
+from typing import Union
 
 from ..core.events_v4 import BaseEvent as V4BaseEvent
 from ..core.events_v4 import TextPart
@@ -8,16 +9,26 @@ from ..core.events_v5 import BaseEvent as V5BaseEvent
 from ..core.events_v5 import TextDeltaEvent
 
 
+class EventEncoderVersion(str, Enum):
+    """Enumeration of supported event encoder versions."""
+
+    V4 = "v4"
+    V5 = "v5"
+
+
+CURRENT_EVENT_ENCODER_VERSION = EventEncoderVersion.V4  # used encoder version
+
+
 class EventEncoder:
     """
     Encodes events for the Vercel AI SDK based on the specified version.
     """
 
-    def __init__(self, version: Literal["v4", "v5"] = None):
+    def __init__(self, version: EventEncoderVersion):
         """
         Initializes the EventEncoder with the specified version.
         """
-        if version not in ["v4", "v5"]:
+        if version not in [EventEncoderVersion.V4, EventEncoderVersion.V5]:
             raise ValueError("Unsupported version. Supported versions are 'v4' and 'v5'.")
 
         self.version = version
@@ -28,7 +39,7 @@ class EventEncoder:
         """
         return "text/event-stream"
 
-    def encode(self, event: Union[V5BaseEvent, V5BaseEvent]) -> str | None:
+    def encode(self, event: Union[V4BaseEvent, V5BaseEvent]) -> str | None:
         """
         Encodes an event based on the version.
 
@@ -38,15 +49,15 @@ class EventEncoder:
             str | None: The encoded event as a string,
             or None if the event type is not adapted to the SDK version.
         """
-        if self.version == "v4" and isinstance(event, V4BaseEvent):
+        if self.version == EventEncoderVersion.V4 and isinstance(event, V4BaseEvent):
             return self._encode_v4_streaming(event)
 
-        if self.version == "v5" and isinstance(event, V5BaseEvent):
+        if self.version == EventEncoderVersion.V5 and isinstance(event, V5BaseEvent):
             return self._encode_sse(event)
 
         return None
 
-    def encode_text(self, event: Union[V5BaseEvent, V5BaseEvent]) -> str | None:
+    def encode_text(self, event: Union[V4BaseEvent, V5BaseEvent]) -> str | None:
         """
         Encodes an event based on the version.
 
@@ -56,10 +67,10 @@ class EventEncoder:
             str | None: The encoded event as a string,
             or None if the event type is not adapted to the SDK version.
         """
-        if self.version == "v4" and isinstance(event, TextPart):
+        if self.version == EventEncoderVersion.V4 and isinstance(event, TextPart):
             return event.text
 
-        if self.version == "v5" and isinstance(event, TextDeltaEvent):
+        if self.version == EventEncoderVersion.V5 and isinstance(event, TextDeltaEvent):
             return event.delta
 
         return None
@@ -70,7 +81,7 @@ class EventEncoder:
         """
         return f"{event.type}:{event.model_dump_json(by_alias=True, exclude={'type'})}\n"
 
-    def _encode_sse(self, event: Union[V5BaseEvent, V5BaseEvent]) -> str:
+    def _encode_sse(self, event: Union[V4BaseEvent, V5BaseEvent]) -> str:
         """
         Encodes an event into an SSE string.
         """

src/backend/chat/views.py

@@ -7,11 +7,13 @@ from uuid import uuid4
 from django.conf import settings
 from django.core.files.storage import default_storage
 from django.http import Http404, StreamingHttpResponse
+from django.utils.decorators import method_decorator
 
 import langfuse
 import magic
 import posthog
 from lasuite.malware_detection import malware_detection
+from lasuite.oidc_login.decorators import refresh_oidc_access_token
 from rest_framework import decorators, filters, mixins, permissions, status, viewsets
 from rest_framework.exceptions import MethodNotAllowed, PermissionDenied, ValidationError
 from rest_framework.response import Response
@@ -26,6 +28,7 @@ from core.filters import remove_accents
 from activation_codes.permissions import IsActivatedUser
 from chat import models, serializers
 from chat.clients.pydantic_ai import AIAgentService
+from chat.keepalive import stream_with_keepalive_async, stream_with_keepalive_sync
 from chat.serializers import ChatConversationRequestSerializer
 
 logger = logging.getLogger(__name__)
@@ -122,6 +125,7 @@ class ChatViewSet(  # pylint: disable=too-many-ancestors, abstract-method
             self.permission_classes = []
         return super().get_permissions()
 
+    @method_decorator(refresh_oidc_access_token)
     @decorators.action(
         methods=["post"],
         detail=True,
@@ -173,6 +177,7 @@ class ChatViewSet(  # pylint: disable=too-many-ancestors, abstract-method
         ai_service = AIAgentService(
             conversation=conversation,
             user=self.request.user,
+            session=request.session,
             model_hrid=model_hrid,
             language=(
                 self.request.user.language
@@ -188,29 +193,28 @@ class ChatViewSet(  # pylint: disable=too-many-ancestors, abstract-method
         if is_async_mode:
             logger.debug("Using ASYNC streaming for chat conversation.")
             if protocol == "data":
-                streaming_content = ai_service.stream_data_async(
+                base_stream = ai_service.stream_data_async(
                     messages, force_web_search=force_web_search
                 )
             else:  # Default to 'text' protocol
-                streaming_content = ai_service.stream_text_async(
+                base_stream = ai_service.stream_text_async(
                     messages, force_web_search=force_web_search
                 )
+            streaming_content = stream_with_keepalive_async(base_stream)
         else:
             logger.debug("Using SYNC streaming for chat conversation.")
             if protocol == "data":
-                streaming_content = ai_service.stream_data(
-                    messages, force_web_search=force_web_search
-                )
+                base_stream = ai_service.stream_data(messages, force_web_search=force_web_search)
             else:  # Default to 'text' protocol
-                streaming_content = ai_service.stream_text(
-                    messages, force_web_search=force_web_search
-                )
+                base_stream = ai_service.stream_text(messages, force_web_search=force_web_search)
 
+            streaming_content = stream_with_keepalive_sync(base_stream)
         response = StreamingHttpResponse(
             streaming_content,
             content_type="text/event-stream",
             headers={
                 "x-vercel-ai-data-stream": "v1",  # This header is used for Vercel AI streaming,
+                "X-Accel-Buffering": "no",  # Prevent nginx buffering
             },
         )
         return response
@@ -371,7 +375,6 @@ class ChatConversationAttachmentViewSet(
             owner=self.request.user,
         ).exists():
             raise Http404
-
         file_name = serializer.validated_data["file_name"]
         extension = file_name.rpartition(".")[-1] if "." in file_name else None
 

src/backend/conftest.py

@@ -22,7 +22,7 @@ def no_http_requests(monkeypatch):
     Credits: https://blog.jerrycodes.com/no-http-requests/
     """
 
-    allowed_hosts = {"localhost", "minio", "minio:9000"}
+    allowed_hosts = {"localhost", "127.0.0.1", "minio", "minio:9000"}
     original_urlopen = HTTPConnectionPool.urlopen
 
     def urlopen_mock(self, method, url, *args, **kwargs):

src/backend/conversations/settings.py

@@ -841,6 +841,23 @@ USER QUESTION:
         environ_prefix=None,
     )
 
+    # Find
+    FIND_API_KEY = values.Value(
+        None,
+        environ_name="FIND_API_KEY",
+        environ_prefix=None,
+    )
+    FIND_API_URL = values.Value(
+        "https://app-find/api",
+        environ_name="FIND_API_URL",
+        environ_prefix=None,
+    )
+    FIND_API_TIMEOUT = values.PositiveIntegerValue(
+        default=30,  # seconds
+        environ_name="FIND_API_TIMEOUT",
+        environ_prefix=None,
+    )
+
     # Logging
     # We want to make it easy to log to console but by default we log production
     # to Sentry and don't want to log to console.
@@ -911,7 +928,9 @@ USER QUESTION:
     LANGFUSE_MEDIA_UPLOAD_ENABLED = values.BooleanValue(
         default=False, environ_name="LANGFUSE_MEDIA_UPLOAD_ENABLED", environ_prefix=None
     )
-
+    AUTO_TITLE_AFTER_USER_MESSAGES = values.PositiveIntegerValue(
+        default=None, environ_name="AUTO_TITLE_AFTER_USER_MESSAGES", environ_prefix=None
+    )
     # WARNING: Testing purpose only. Do not use in production.
     WARNING_MOCK_CONVERSATION_AGENT = values.BooleanValue(
         default=False,
@@ -919,6 +938,12 @@ USER QUESTION:
         environ_prefix=None,
     )
 
+    # Default keepalive interval: 55s (safely below typical 60s proxy timeouts)
+    # Prevents connection drops during long stream pauses while providing 5s safety margin.
+    KEEPALIVE_INTERVAL = values.PositiveIntegerValue(
+        default=55, environ_name="KEEPALIVE_INTERVAL", environ_prefix=None
+    )
+
     # pylint: disable=invalid-name
     @property
     def ENVIRONMENT(self):
@@ -1131,6 +1156,8 @@ class Test(Base):
 
     POSTHOG_KEY = None
 
+    AUTO_TITLE_AFTER_USER_MESSAGES = None
+
     def __init__(self):
         # pylint: disable=invalid-name
         self.INSTALLED_APPS += ["drf_spectacular_sidecar"]

src/backend/pyproject.toml

@@ -46,6 +46,7 @@ dependencies = [
     "easy_thumbnails==2.10.1",
     "factory_boy==3.3.3",
     "gunicorn==23.0.0",
+    "jaraco.context>=6.1.0",
     "jsonschema==4.25.1",
     "langfuse==3.10.0",
     "lxml==5.4.0",

src/backend/utils/oidc.py

@@ -0,0 +1,54 @@
+"""Utility functions for OIDC token management."""
+
+from functools import wraps
+
+from django.conf import settings
+
+import requests
+from lasuite.oidc_login.backends import get_oidc_refresh_token, store_tokens
+from rest_framework.exceptions import AuthenticationFailed
+
+
+def refresh_access_token(session):
+    """Refresh the OIDC access token using the refresh token."""
+    refresh_token = get_oidc_refresh_token(session)
+    if not refresh_token:
+        raise AuthenticationFailed({"error": "Refresh token is missing from session"})
+
+    response = requests.post(
+        settings.OIDC_OP_TOKEN_ENDPOINT,
+        data={
+            "grant_type": "refresh_token",
+            "client_id": settings.OIDC_RP_CLIENT_ID,
+            "client_secret": settings.OIDC_RP_CLIENT_SECRET,
+            "refresh_token": refresh_token,
+        },
+        timeout=5,
+    )
+    response.raise_for_status()
+    token_info = response.json()
+
+    store_tokens(
+        session,
+        access_token=token_info.get("access_token"),
+        id_token=None,
+        refresh_token=token_info.get("refresh_token"),
+    )
+    return session
+
+
+def with_fresh_access_token(func):
+    """
+    Decorator to handle OIDC token refresh and extraction.
+    Expects 'session' in kwargs and update it with the fresh token.
+    """
+
+    @wraps(func)
+    def wrapper(*args, **kwargs):
+        session = kwargs.pop("session", None)
+        if session is None:
+            raise AuthenticationFailed({"error": "Session is required but not provided"})
+        refreshed_session = refresh_access_token(session)
+        return func(*args, session=refreshed_session, **kwargs)
+
+    return wrapper

src/frontend/apps/conversations/package.json

@@ -9,6 +9,7 @@
     "build-theme": "cunningham -g css,ts -o src/cunningham --utility-classes && yarn prettier && yarn stylelint --fix",
     "start": "npx -y serve@latest out",
     "lint": "tsc --noEmit && next lint",
+    "lint:fix": "tsc --noEmit && next lint --fix",
     "prettier": "prettier --write .",
     "stylelint": "stylelint \"**/*.css\"",
     "test": "jest",

src/frontend/apps/conversations/src/features/chat/api/useChat.tsx

@@ -1,6 +1,9 @@
 import { UseChatOptions, useChat as useAiSdkChat } from '@ai-sdk/react';
+import { useQueryClient } from '@tanstack/react-query';
+import { useEffect } from 'react';
 
 import { fetchAPI } from '@/api';
+import { KEY_LIST_CONVERSATION } from '@/features/chat/api/useConversations';
 import { useChatPreferencesStore } from '@/features/chat/stores/useChatPreferencesStore';
 
 const fetchAPIAdapter = (input: RequestInfo | URL, init?: RequestInit) => {
@@ -36,10 +39,46 @@ const fetchAPIAdapter = (input: RequestInfo | URL, init?: RequestInit) => {
   return fetchAPI(url, init);
 };
 
+interface ConversationMetadataEvent {
+  type: 'conversation_metadata';
+  conversationId: string;
+  title: string;
+}
+// Type guard to check if an item is a ConversationMetadataEvent
+function isConversationMetadataEvent(
+  item: unknown,
+): item is ConversationMetadataEvent {
+  return (
+    typeof item === 'object' &&
+    item !== null &&
+    'type' in item &&
+    item.type === 'conversation_metadata' &&
+    'conversationId' in item &&
+    typeof item.conversationId === 'string' &&
+    'title' in item &&
+    typeof item.title === 'string'
+  );
+}
+
 export function useChat(options: Omit<UseChatOptions, 'fetch'>) {
-  return useAiSdkChat({
+  const queryClient = useQueryClient();
+
+  const result = useAiSdkChat({
     ...options,
     maxSteps: 3,
     fetch: fetchAPIAdapter,
   });
+
+  useEffect(() => {
+    if (result.data && Array.isArray(result.data)) {
+      for (const item of result.data) {
+        if (isConversationMetadataEvent(item)) {
+          void queryClient.invalidateQueries({
+            queryKey: [KEY_LIST_CONVERSATION],
+          });
+        }
+      }
+    }
+  }, [result.data, queryClient]);
+  return result;
 }

src/frontend/apps/conversations/src/features/chat/api/useRenameConversation.tsx

@@ -0,0 +1,62 @@
+import {
+  UseMutationOptions,
+  useMutation,
+  useQueryClient,
+} from '@tanstack/react-query';
+
+import { APIError, errorCauses, fetchAPI } from '@/api';
+
+import { KEY_LIST_CONVERSATION } from './useConversations';
+
+interface RenameConversationProps {
+  conversationId: string;
+  title: string;
+}
+
+export const renameConversation = async ({
+  conversationId,
+  title,
+}: RenameConversationProps): Promise<void> => {
+  const response = await fetchAPI(`chats/${conversationId}/`, {
+    method: 'PUT',
+    body: JSON.stringify({
+      title,
+    }),
+  });
+
+  if (!response.ok) {
+    throw new APIError(
+      'Failed to rename the conversation',
+      await errorCauses(response),
+    );
+  }
+};
+
+type UseRenameConversationOptions = UseMutationOptions<
+  void,
+  APIError,
+  RenameConversationProps
+>;
+
+export const useRenameConversation = (
+  options?: UseRenameConversationOptions,
+) => {
+  const queryClient = useQueryClient();
+  return useMutation<void, APIError, RenameConversationProps>({
+    mutationFn: renameConversation,
+    ...options,
+    onSuccess: (data, variables, context) => {
+      void queryClient.invalidateQueries({
+        queryKey: [KEY_LIST_CONVERSATION],
+      });
+      if (options?.onSuccess) {
+        void options.onSuccess(data, variables, context);
+      }
+    },
+    onError: (error, variables, context) => {
+      if (options?.onError) {
+        void options.onError(error, variables, context);
+      }
+    },
+  });
+};

src/frontend/apps/conversations/src/features/left-panel/components/ConversationItemActions.tsx

@@ -1,4 +1,4 @@
-import { Button as _Button, useModal } from '@openfun/cunningham-react';
+import { useModal } from '@openfun/cunningham-react';
 import { useTranslation } from 'react-i18next';
 import { css } from 'styled-components';
 
@@ -6,6 +6,7 @@ import { DropdownMenu, DropdownMenuOption, Icon } from '@/components';
 import { ChatConversation } from '@/features/chat/types';
 
 import { ModalRemoveConversation } from './ModalRemoveConversation';
+import { ModalRenameConversation } from './ModalRenameConversation';
 
 interface ConversationItemActionsProps {
   conversation: ChatConversation;
@@ -17,8 +18,16 @@ export const ConversationItemActions = ({
   const { t } = useTranslation();
 
   const deleteModal = useModal();
+  const renameModal = useModal();
 
   const options: DropdownMenuOption[] = [
+    {
+      label: t('Rename chat'),
+      icon: 'edit',
+      callback: () => renameModal.open(),
+      disabled: false,
+      testId: `conversation-item-actions-rename-${conversation.id}`,
+    },
     {
       label: t('Delete chat'),
       icon: 'delete',
@@ -71,6 +80,12 @@ export const ConversationItemActions = ({
           conversation={conversation}
         />
       )}
+      {renameModal.isOpen && (
+        <ModalRenameConversation
+          onClose={renameModal.onClose}
+          conversation={conversation}
+        />
+      )}
     </>
   );
 };

src/frontend/apps/conversations/src/features/left-panel/components/ModalRemoveConversation.tsx

@@ -46,7 +46,7 @@ export const ModalRemoveConversation = ({
         <>
           <Button
             aria-label={t('Close the modal')}
-            color="secondary"
+            color="tertiary"
             fullWidth
             onClick={() => onClose()}
           >
@@ -79,7 +79,10 @@ export const ModalRemoveConversation = ({
         </Text>
       }
     >
-      <Box className="--converstions--modal-remove-chat">
+      <Box
+        className="--conversations--modal-remove-chat"
+        data-testid="delete-chat-confirm"
+      >
         <Text $size="sm" $variation="600">
           {t('Are you sure you want to delete this conversation ?')}
         </Text>

src/frontend/apps/conversations/src/features/left-panel/components/ModalRenameConversation.tsx

@@ -0,0 +1,108 @@
+import { Button, Input, Modal, ModalSize } from '@openfun/cunningham-react';
+import { useState } from 'react';
+import { useTranslation } from 'react-i18next';
+
+import { Box, Text, useToast } from '@/components';
+import { useRenameConversation } from '@/features/chat/api/useRenameConversation';
+import { ChatConversation } from '@/features/chat/types';
+
+interface ModalRenameConversationProps {
+  onClose: () => void;
+  conversation: ChatConversation;
+}
+
+export const ModalRenameConversation = ({
+  onClose,
+  conversation,
+}: ModalRenameConversationProps) => {
+  const { showToast } = useToast();
+  const { t } = useTranslation();
+  const { mutate: renameConversation } = useRenameConversation({
+    onSuccess: () => {
+      showToast(
+        'success',
+        t('The conversation has been renamed.'),
+        undefined,
+        4000,
+      );
+      onClose();
+    },
+    onError: (error) => {
+      const errorMessage =
+        error.cause?.[0] ||
+        error.message ||
+        t('An error occurred while renaming the conversation');
+      showToast('error', errorMessage, undefined, 4000);
+    },
+  });
+
+  const [newName, setNewName] = useState(conversation.title ?? '');
+  const handleSubmit = (e: React.FormEvent) => {
+    e.preventDefault();
+    const trimmedNewName = newName.trim();
+    if (trimmedNewName) {
+      renameConversation({
+        conversationId: conversation.id,
+        title: trimmedNewName,
+      });
+    }
+  };
+  return (
+    <Modal
+      isOpen
+      closeOnClickOutside
+      onClose={() => onClose()}
+      aria-label={t('Content modal to rename a conversation')}
+      rightActions={
+        <>
+          <Button
+            aria-label={t('Close the modal')}
+            color="tertiary"
+            onClick={() => onClose()}
+          >
+            {t('Cancel')}
+          </Button>
+          <Button
+            aria-label={t('Rename chat')}
+            color="primary"
+            type="submit"
+            form="rename-chat-form"
+          >
+            {t('Rename')}
+          </Button>
+        </>
+      }
+      size={ModalSize.SMALL}
+      title={
+        <Text
+          $size="h6"
+          as="h6"
+          $margin={{ all: '0' }}
+          $align="flex-start"
+          $variation="1000"
+        >
+          {t('Rename chat')}
+        </Text>
+      }
+    >
+      <Box className="--conversations--modal-rename-chat">
+        <form
+          onSubmit={handleSubmit}
+          id="rename-chat-form"
+          data-testid="rename-chat-form"
+          className="mt-s"
+        >
+          <Input
+            type="text"
+            label={t('New name')}
+            maxLength={100}
+            value={newName}
+            onChange={(e: React.ChangeEvent<HTMLInputElement>) => {
+              setNewName(e.target.value);
+            }}
+          />
+        </form>
+      </Box>
+    </Modal>
+  );
+};

src/frontend/apps/conversations/src/features/left-panel/components/__tests__/ConversationItemActions.test.tsx

@@ -0,0 +1,255 @@
+import { CunninghamProvider } from '@openfun/cunningham-react';
+import { render, screen, waitFor } from '@testing-library/react';
+import userEvent from '@testing-library/user-event';
+
+import { ToastProvider } from '@/components';
+import { ChatConversation } from '@/features/chat/types';
+
+import { ConversationItemActions } from '../ConversationItemActions';
+
+const mockPush = jest.fn();
+let mockPathname = '/';
+
+jest.mock('next/router', () => ({
+  useRouter: () => ({
+    push: mockPush,
+    pathname: mockPathname,
+    route: '/',
+    query: {},
+    asPath: '/',
+  }),
+}));
+
+jest.mock('next/navigation', () => ({
+  usePathname: () => mockPathname,
+}));
+
+jest.mock('react-i18next', () => ({
+  useTranslation: () => ({
+    t: (key: string, options?: Record<string, string>) => {
+      if (options) {
+        return Object.entries(options).reduce(
+          (acc, [k, v]) => acc.replace(`{{${k}}}`, v),
+          key,
+        );
+      }
+      return key;
+    },
+  }),
+}));
+
+jest.mock('i18next', () => ({
+  t: (key: string) => key,
+}));
+
+jest.mock('@/features/chat/api/useRenameConversation', () => ({
+  useRenameConversation: () => ({
+    mutate: jest.fn(),
+  }),
+}));
+
+jest.mock('@/features/chat/api/useRemoveConversation', () => ({
+  useRemoveConversation: () => ({
+    mutate: jest.fn(),
+  }),
+}));
+
+const renderWithProviders = (ui: React.ReactNode) => {
+  return render(
+    <CunninghamProvider>
+      <ToastProvider>{ui}</ToastProvider>
+    </CunninghamProvider>,
+  );
+};
+
+describe('ConversationItemActions', () => {
+  const mockConversation: ChatConversation = {
+    id: 'conv-123',
+    title: 'Original Title',
+    messages: [],
+    created_at: new Date().toISOString(),
+    updated_at: new Date().toISOString(),
+  };
+  beforeEach(() => {
+    jest.clearAllMocks();
+    mockPathname = '/';
+  });
+
+  const renderComponent = (conversation = mockConversation) => {
+    return renderWithProviders(
+      <ConversationItemActions conversation={conversation} />,
+    );
+  };
+
+  it('renders the actions button', () => {
+    renderComponent();
+
+    expect(
+      screen.getByTestId(
+        `conversation-item-actions-button-${mockConversation.id}`,
+      ),
+    ).toBeInTheDocument();
+  });
+
+  it('renders dropdown menu with correct aria-label', () => {
+    renderComponent();
+
+    expect(
+      screen.getByLabelText(
+        `Actions list for conversation ${mockConversation.title}`,
+      ),
+    ).toBeInTheDocument();
+  });
+
+  it('renders dropdown menu with fallback title when conversation has no title', () => {
+    const untitledConversation = { ...mockConversation, title: '' };
+    renderComponent(untitledConversation);
+
+    expect(
+      screen.getByLabelText(
+        `Actions list for conversation Untitled conversation`,
+      ),
+    ).toBeInTheDocument();
+  });
+
+  it('opens dropdown menu when clicking the actions button', async () => {
+    const user = userEvent.setup();
+    renderComponent();
+
+    const actionsButton = screen.getByLabelText(
+      `Actions list for conversation ${mockConversation.title}`,
+    );
+    await user.click(actionsButton);
+
+    expect(
+      screen.getByTestId(
+        `conversation-item-actions-rename-${mockConversation.id}`,
+      ),
+    ).toBeInTheDocument();
+    expect(
+      screen.getByTestId(
+        `conversation-item-actions-remove-${mockConversation.id}`,
+      ),
+    ).toBeInTheDocument();
+  });
+
+  it('displays rename and delete options in the dropdown', async () => {
+    const user = userEvent.setup();
+    renderComponent();
+
+    const actionsButton = screen.getByLabelText(
+      `Actions list for conversation ${mockConversation.title}`,
+    );
+    await user.click(actionsButton);
+
+    expect(screen.getByText('Rename chat')).toBeInTheDocument();
+    expect(screen.getByText('Delete chat')).toBeInTheDocument();
+  });
+
+  it('opens rename modal when clicking rename option', async () => {
+    const user = userEvent.setup();
+    renderComponent();
+
+    const actionsButton = screen.getByLabelText(
+      `Actions list for conversation ${mockConversation.title}`,
+    );
+    await user.click(actionsButton);
+
+    const renameOption = screen.getByTestId(
+      `conversation-item-actions-rename-${mockConversation.id}`,
+    );
+    await user.click(renameOption);
+    // Modal should be open
+    await waitFor(() => {
+      expect(screen.getByRole('dialog')).toBeInTheDocument();
+    });
+
+    expect(screen.getByRole('textbox')).toHaveValue(mockConversation.title);
+
+    expect(screen.getByTestId('rename-chat-form')).toBeInTheDocument();
+  });
+
+  it('opens delete modal when clicking delete option', async () => {
+    const user = userEvent.setup();
+    renderComponent();
+
+    const actionsButton = screen.getByLabelText(
+      `Actions list for conversation ${mockConversation.title}`,
+    );
+    await user.click(actionsButton);
+
+    const deleteOption = screen.getByTestId(
+      `conversation-item-actions-remove-${mockConversation.id}`,
+    );
+    await user.click(deleteOption);
+
+    await waitFor(() => {
+      expect(screen.getByRole('dialog')).toBeInTheDocument();
+    });
+    expect(screen.getByTestId('delete-chat-confirm')).toBeInTheDocument();
+  });
+
+  it('does not render modals initially', () => {
+    renderComponent();
+
+    expect(screen.queryByRole('dialog')).not.toBeInTheDocument();
+    expect(screen.queryByTestId('delete-chat-confirm')).not.toBeInTheDocument();
+    expect(screen.queryByTestId('rename-chat-form')).not.toBeInTheDocument();
+  });
+
+  it('closes rename modal when onClose is called', async () => {
+    const user = userEvent.setup();
+    renderComponent();
+
+    // Open dropdown and click rename
+    const actionsButton = screen.getByLabelText(
+      `Actions list for conversation ${mockConversation.title}`,
+    );
+    await user.click(actionsButton);
+    await user.click(
+      screen.getByTestId(
+        `conversation-item-actions-rename-${mockConversation.id}`,
+      ),
+    );
+
+    // Modal should be open
+    await waitFor(() => {
+      expect(screen.getByRole('dialog')).toBeInTheDocument();
+    });
+
+    // Close the modal
+    await user.click(screen.getByText('Cancel'));
+
+    await waitFor(() => {
+      expect(screen.queryByRole('dialog')).not.toBeInTheDocument();
+    });
+  });
+
+  it('closes delete modal when onClose is called', async () => {
+    const user = userEvent.setup();
+    renderComponent();
+
+    // Open dropdown and click delete
+    const actionsButton = screen.getByLabelText(
+      `Actions list for conversation ${mockConversation.title}`,
+    );
+    await user.click(actionsButton);
+    await user.click(
+      screen.getByTestId(
+        `conversation-item-actions-remove-${mockConversation.id}`,
+      ),
+    );
+
+    // Modal should be open
+    await waitFor(() => {
+      expect(screen.getByRole('dialog')).toBeInTheDocument();
+    });
+
+    // Close the modal
+    await user.click(screen.getByText('Cancel'));
+
+    await waitFor(() => {
+      expect(screen.queryByRole('dialog')).not.toBeInTheDocument();
+    });
+  });
+});

src/frontend/apps/conversations/src/features/left-panel/components/__tests__/ModalRenameConversation.test.tsx

@@ -0,0 +1,280 @@
+import { CunninghamProvider } from '@openfun/cunningham-react';
+import { render, screen, waitFor } from '@testing-library/react';
+import userEvent from '@testing-library/user-event';
+
+import { useToast } from '@/components';
+import { useRenameConversation } from '@/features/chat/api/useRenameConversation';
+import { ChatConversation } from '@/features/chat/types';
+
+import { ModalRenameConversation } from '../ModalRenameConversation';
+
+jest.mock('@/components', () => ({
+  ...jest.requireActual('@/components'),
+  useToast: jest.fn(),
+}));
+
+jest.mock('@/features/chat/api/useRenameConversation');
+
+jest.mock('react-i18next', () => ({
+  useTranslation: () => ({
+    t: (key: string, options?: Record<string, string>) => {
+      if (options) {
+        return Object.entries(options).reduce(
+          (acc, [k, v]) => acc.replace(`{{${k}}}`, v),
+          key,
+        );
+      }
+      return key;
+    },
+  }),
+}));
+jest.mock('i18next', () => ({
+  t: (key: string) => key,
+}));
+const renderWithProviders = (component: React.ReactNode) => {
+  return render(<CunninghamProvider>{component}</CunninghamProvider>);
+};
+
+describe('ModalRenameConversation', () => {
+  const mockOnClose = jest.fn();
+  const mockShowToast = jest.fn();
+  const mockRenameConversation = jest.fn();
+
+  const mockConversation: ChatConversation = {
+    id: 'conv-123',
+    title: 'Original Title',
+    messages: [],
+    created_at: new Date().toISOString(),
+    updated_at: new Date().toISOString(),
+  } as ChatConversation;
+
+  beforeEach(() => {
+    jest.clearAllMocks();
+    (useToast as jest.Mock).mockReturnValue({
+      showToast: mockShowToast,
+    });
+    (useRenameConversation as jest.Mock).mockReturnValue({
+      mutate: mockRenameConversation,
+    });
+  });
+
+  it('renders the modal with correct title and initial value', () => {
+    renderWithProviders(
+      <ModalRenameConversation
+        onClose={mockOnClose}
+        conversation={mockConversation}
+      />,
+    );
+
+    expect(screen.getByText('Rename chat')).toBeInTheDocument();
+    expect(screen.getByRole('textbox')).toHaveValue('Original Title');
+    expect(screen.getByText('Cancel')).toBeInTheDocument();
+    expect(screen.getByText('Rename')).toBeInTheDocument();
+  });
+
+  it('updates input value when user types', async () => {
+    const user = userEvent.setup();
+    renderWithProviders(
+      <ModalRenameConversation
+        onClose={mockOnClose}
+        conversation={mockConversation}
+      />,
+    );
+
+    const input = screen.getByRole('textbox');
+
+    await user.clear(input);
+    await user.type(input, 'New Title');
+
+    expect(input).toHaveValue('New Title');
+  });
+
+  it('closes modal when Cancel button is clicked', async () => {
+    const user = userEvent.setup();
+    renderWithProviders(
+      <ModalRenameConversation
+        onClose={mockOnClose}
+        conversation={mockConversation}
+      />,
+    );
+
+    await user.click(screen.getByText('Cancel'));
+
+    expect(mockOnClose).toHaveBeenCalledTimes(1);
+  });
+
+  it('submits form with new name and shows success toast', async () => {
+    const user = userEvent.setup();
+    let onSuccessCallback: (() => void) | undefined;
+
+    (useRenameConversation as jest.Mock).mockImplementation(({ onSuccess }) => {
+      onSuccessCallback = onSuccess;
+      return { mutate: mockRenameConversation };
+    });
+
+    renderWithProviders(
+      <ModalRenameConversation
+        onClose={mockOnClose}
+        conversation={mockConversation}
+      />,
+    );
+
+    const input = screen.getByRole('textbox');
+    await user.clear(input);
+    await user.type(input, 'Updated Title');
+    await user.click(screen.getByText('Rename'));
+
+    expect(mockRenameConversation).toHaveBeenCalledWith({
+      conversationId: 'conv-123',
+      title: 'Updated Title',
+    });
+
+    onSuccessCallback?.();
+
+    await waitFor(() => {
+      expect(mockShowToast).toHaveBeenCalledWith(
+        'success',
+        'The conversation has been renamed.',
+        undefined,
+        4000,
+      );
+    });
+    expect(mockOnClose).toHaveBeenCalled();
+  });
+
+  it('does not submit form when new name is empty or whitespace', async () => {
+    const user = userEvent.setup();
+    renderWithProviders(
+      <ModalRenameConversation
+        onClose={mockOnClose}
+        conversation={mockConversation}
+      />,
+    );
+
+    const input = screen.getByRole('textbox');
+    await user.clear(input);
+    await user.type(input, '   ');
+    await user.click(screen.getByText('Rename'));
+
+    expect(mockRenameConversation).not.toHaveBeenCalled();
+  });
+
+  it('shows error toast when rename fails with cause', async () => {
+    const user = userEvent.setup();
+    let onErrorCallback: ((error: any) => void) | undefined;
+
+    (useRenameConversation as jest.Mock).mockImplementation(({ onError }) => {
+      onErrorCallback = onError;
+      return { mutate: mockRenameConversation };
+    });
+
+    renderWithProviders(
+      <ModalRenameConversation
+        onClose={mockOnClose}
+        conversation={mockConversation}
+      />,
+    );
+
+    const input = screen.getByRole('textbox');
+    await user.clear(input);
+    await user.type(input, 'New Title');
+    await user.click(screen.getByText('Rename'));
+
+    const error = {
+      cause: ['Specific error from API'],
+      message: 'Generic error',
+    };
+    onErrorCallback?.(error);
+
+    await waitFor(() => {
+      expect(mockShowToast).toHaveBeenCalledWith(
+        'error',
+        'Specific error from API',
+        undefined,
+        4000,
+      );
+    });
+  });
+
+  it('shows error toast with message when no cause is provided', async () => {
+    const user = userEvent.setup();
+    let onErrorCallback: ((error: any) => void) | undefined;
+
+    (useRenameConversation as jest.Mock).mockImplementation(({ onError }) => {
+      onErrorCallback = onError;
+      return { mutate: mockRenameConversation };
+    });
+
+    renderWithProviders(
+      <ModalRenameConversation
+        onClose={mockOnClose}
+        conversation={mockConversation}
+      />,
+    );
+
+    const input = screen.getByRole('textbox');
+    await user.clear(input);
+    await user.type(input, 'New Title');
+    await user.click(screen.getByText('Rename'));
+
+    const error = {
+      message: 'Network error',
+    };
+    onErrorCallback?.(error);
+
+    await waitFor(() => {
+      expect(mockShowToast).toHaveBeenCalledWith(
+        'error',
+        'Network error',
+        undefined,
+        4000,
+      );
+    });
+  });
+
+  it('shows default error message when error has no cause or message', async () => {
+    const user = userEvent.setup();
+    let onErrorCallback: ((error: any) => void) | undefined;
+
+    (useRenameConversation as jest.Mock).mockImplementation(({ onError }) => {
+      onErrorCallback = onError;
+      return { mutate: mockRenameConversation };
+    });
+
+    renderWithProviders(
+      <ModalRenameConversation
+        onClose={mockOnClose}
+        conversation={mockConversation}
+      />,
+    );
+
+    const input = screen.getByRole('textbox');
+    await user.clear(input);
+    await user.type(input, 'New Title');
+    await user.click(screen.getByText('Rename'));
+
+    const error = {};
+    onErrorCallback?.(error);
+
+    await waitFor(() => {
+      expect(mockShowToast).toHaveBeenCalledWith(
+        'error',
+        'An error occurred while renaming the conversation',
+        undefined,
+        4000,
+      );
+    });
+  });
+
+  it('enforces maxLength of 100 characters on input', () => {
+    renderWithProviders(
+      <ModalRenameConversation
+        onClose={mockOnClose}
+        conversation={mockConversation}
+      />,
+    );
+
+    const input = screen.getByRole('textbox');
+    expect(input).toHaveAttribute('maxLength', '100');
+  });
+});

src/frontend/yarn.lock

@@ -11355,9 +11355,9 @@ posthog-js@1.249.3:
     web-vitals "^4.2.4"
 
 preact@^10.19.3:
-  version "10.26.6"
-  resolved "https://registry.npmjs.org/preact/-/preact-10.26.6.tgz"
-  integrity sha512-5SRRBinwpwkaD+OqlBDeITlRgvd8I8QlxHJw9AxSdMNV6O+LodN9nUyYGpSF7sadHjs6RzeFShMexC6DbtWr9g==
+  version "10.24.0"
+  resolved "https://registry.npmjs.org/preact/-/preact-10.24.0.tgz"
+  integrity sha512-aK8Cf+jkfyuZ0ZZRG9FbYqwmEiGQ4y/PUO4SuTWoyWL244nZZh7bd5h2APd4rSNDYTBNghg1L+5iJN3Skxtbsw==
 
 prelude-ls@^1.2.1:
   version "1.2.1"

src/mail/yarn.lock

@@ -399,10 +399,10 @@ glob-parent@~5.1.2:
   dependencies:
     is-glob "^4.0.1"
 
-glob@^10.3.10, glob@^10.3.3:
-  version "10.4.5"
-  resolved "https://registry.yarnpkg.com/glob/-/glob-10.4.5.tgz#f4d9f0b90ffdbab09c9d77f5f29b4262517b0956"
-  integrity sha512-7Bv8RF0k6xjo7d4A/PxYLbUCfb6c+Vpd2/mB2yRDlew7Jb5hEXiCD9ibfO7wpk8i4sevK6DFny9h7EYbM3/sHg==
+glob@^10.5.0:
+  version "10.5.0"
+  resolved "https://registry.yarnpkg.com/glob/-/glob-10.5.0.tgz#8ec0355919cd3338c28428a23d4f24ecc5fe738c"
+  integrity sha512-DfXN8DfhJ7NH3Oe7cFmu3NCu1wKbkReJ8TorzSAFbSKrlNaQSKfIzqYqVY8zlbs2NLBbWpRiU52GX2PbaBVNkg==
   dependencies:
     foreground-child "^3.1.0"
     jackspeak "^3.1.2"