AndyMik90
80 lines
2.3 KiB
Python
80 lines
2.3 KiB
Python
"""
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Conflict Context
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================
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Minimal context needed to resolve a conflict.
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This module provides the ConflictContext class that encapsulates
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all the information needed to send to the AI for conflict resolution,
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optimized for minimal token usage.
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"""
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from __future__ import annotations
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from dataclasses import dataclass
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from typing import TYPE_CHECKING
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if TYPE_CHECKING:
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from ..types import SemanticChange
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@dataclass
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class ConflictContext:
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"""
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Minimal context needed to resolve a conflict.
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This is what gets sent to the AI - optimized for minimal tokens.
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"""
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file_path: str
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location: str
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baseline_code: str # The code before any task modified it
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task_changes: list[
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tuple[str, str, list[SemanticChange]]
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] # (task_id, intent, changes)
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conflict_description: str
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language: str = "unknown"
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def to_prompt_context(self) -> str:
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"""Format as context for the AI prompt."""
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lines = [
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f"File: {self.file_path}",
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f"Location: {self.location}",
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f"Language: {self.language}",
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"",
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"--- BASELINE CODE (before any changes) ---",
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self.baseline_code,
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"--- END BASELINE ---",
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"",
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"CHANGES FROM EACH TASK:",
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]
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for task_id, intent, changes in self.task_changes:
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lines.append(f"\n[Task: {task_id}]")
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lines.append(f"Intent: {intent}")
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lines.append("Changes:")
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for change in changes:
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lines.append(f" - {change.change_type.value}: {change.target}")
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if change.content_after:
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# Truncate long content
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content = change.content_after
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if len(content) > 500:
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content = content[:500] + "... (truncated)"
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lines.append(f" Code: {content}")
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lines.extend(
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[
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"",
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f"CONFLICT: {self.conflict_description}",
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]
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)
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return "\n".join(lines)
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@property
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def estimated_tokens(self) -> int:
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"""Rough estimate of tokens in this context."""
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text = self.to_prompt_context()
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# Rough estimate: 4 chars per token for code
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return len(text) // 4
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