Fix conversation history duplication and optimize file embedding
This major refactoring addresses critical bugs in conversation history management and significantly improves token efficiency through intelligent file embedding: **Key Improvements:** • Fixed conversation history duplication bug by centralizing reconstruction in server.py • Added intelligent file filtering to prevent re-embedding files already in conversation history • Centralized file processing logic in BaseTool._prepare_file_content_for_prompt() • Enhanced log monitoring with better categorization and file embedding visibility • Updated comprehensive test suite to verify new architecture and edge cases **Architecture Changes:** • Removed duplicate conversation history reconstruction from tools/base.py • Conversation history now handled exclusively by server.py:reconstruct_thread_context • All tools now use centralized file processing with automatic deduplication • Improved token efficiency by embedding unique files only once per conversation **Performance Benefits:** • Reduced token usage through smart file filtering • Eliminated redundant file embeddings in continued conversations • Better observability with detailed debug logging for file operations 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
This commit is contained in:
Fahad
@@ -46,6 +46,7 @@ USAGE EXAMPLE:
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This enables true AI-to-AI collaboration across the entire tool ecosystem.
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"""
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import logging
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import os
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import uuid
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from datetime import datetime, timezone
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@@ -53,6 +54,8 @@ from typing import Any, Optional
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from pydantic import BaseModel
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logger = logging.getLogger(__name__)
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# Configuration constants
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MAX_CONVERSATION_TURNS = 10 # Maximum turns allowed per conversation thread
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@@ -278,45 +281,174 @@ def add_turn(
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return False
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def build_conversation_history(context: ThreadContext) -> str:
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def get_conversation_file_list(context: ThreadContext) -> list[str]:
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"""
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Build formatted conversation history for tool prompts
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Get all unique files referenced across all turns in a conversation.
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Creates a formatted string representation of the conversation history
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that can be included in tool prompts to provide context. This is the
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critical function that enables cross-tool continuation by reconstructing
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the full conversation context.
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This function extracts and deduplicates file references from all conversation
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turns to enable efficient file embedding - files are read once and shared
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across all turns rather than being embedded multiple times.
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Args:
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context: ThreadContext containing the complete conversation
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Returns:
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str: Formatted conversation history ready for inclusion in prompts
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list[str]: Deduplicated list of file paths referenced in the conversation
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"""
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if not context.turns:
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return []
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# Collect all unique files from all turns, preserving order of first appearance
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seen_files = set()
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unique_files = []
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for turn in context.turns:
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if turn.files:
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for file_path in turn.files:
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if file_path not in seen_files:
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seen_files.add(file_path)
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unique_files.append(file_path)
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return unique_files
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def build_conversation_history(context: ThreadContext, read_files_func=None) -> str:
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"""
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Build formatted conversation history for tool prompts with embedded file contents.
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Creates a formatted string representation of the conversation history that includes
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full file contents from all referenced files. Files are embedded only ONCE at the
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start, even if referenced in multiple turns, to prevent duplication and optimize
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token usage.
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Args:
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context: ThreadContext containing the complete conversation
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Returns:
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str: Formatted conversation history with embedded files ready for inclusion in prompts
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Empty string if no conversation turns exist
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Format:
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- Header with thread metadata and turn count
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- Each turn shows: role, tool used, files referenced, content
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- Files from previous turns are explicitly listed
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- All referenced files embedded once with full contents
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- Each turn shows: role, tool used, which files were used, content
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- Clear delimiters for AI parsing
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- Continuation instruction at end
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Note:
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This formatted history allows tools to "see" files and context
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from previous tools, enabling true cross-tool collaboration.
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This formatted history allows tools to "see" both conversation context AND
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file contents from previous tools, enabling true cross-tool collaboration
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while preventing duplicate file embeddings.
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"""
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if not context.turns:
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return ""
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# Get all unique files referenced in this conversation
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all_files = get_conversation_file_list(context)
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history_parts = [
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"=== CONVERSATION HISTORY ===",
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f"Thread: {context.thread_id}",
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f"Tool: {context.tool_name}", # Original tool that started the conversation
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f"Turn {len(context.turns)}/{MAX_CONVERSATION_TURNS}",
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"",
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"Previous exchanges:",
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]
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# Embed all files referenced in this conversation once at the start
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if all_files:
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history_parts.extend(
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[
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"=== FILES REFERENCED IN THIS CONVERSATION ===",
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"The following files have been shared and analyzed during our conversation.",
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"Refer to these when analyzing the context and requests below:",
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"",
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]
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)
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# Import required functions
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from config import MAX_CONTEXT_TOKENS
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if read_files_func is None:
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from utils.file_utils import read_file_content
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# Optimized: read files incrementally with token tracking
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file_contents = []
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total_tokens = 0
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files_included = 0
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files_truncated = 0
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for file_path in all_files:
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try:
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# Correctly unpack the tuple returned by read_file_content
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formatted_content, content_tokens = read_file_content(file_path)
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if formatted_content:
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# read_file_content already returns formatted content, use it directly
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# Check if adding this file would exceed the limit
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if total_tokens + content_tokens <= MAX_CONTEXT_TOKENS:
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file_contents.append(formatted_content)
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total_tokens += content_tokens
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files_included += 1
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logger.debug(
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f"📄 File embedded in conversation history: {file_path} ({content_tokens:,} tokens)"
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)
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else:
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files_truncated += 1
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logger.debug(
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f"📄 File truncated due to token limit: {file_path} ({content_tokens:,} tokens, would exceed {MAX_CONTEXT_TOKENS:,} limit)"
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)
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# Stop processing more files
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break
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else:
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logger.debug(f"📄 File skipped (empty content): {file_path}")
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except Exception as e:
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# Skip files that can't be read but log the failure
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logger.warning(
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f"📄 Failed to embed file in conversation history: {file_path} - {type(e).__name__}: {e}"
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)
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continue
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if file_contents:
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files_content = "".join(file_contents)
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if files_truncated > 0:
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files_content += (
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f"\n[NOTE: {files_truncated} additional file(s) were truncated due to token limit]\n"
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)
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history_parts.append(files_content)
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logger.debug(
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f"📄 Conversation history file embedding complete: {files_included} files embedded, {files_truncated} truncated, {total_tokens:,} total tokens"
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)
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else:
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history_parts.append("(No accessible files found)")
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logger.debug(
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f"📄 Conversation history file embedding: no accessible files found from {len(all_files)} requested"
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)
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else:
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# Fallback to original read_files function for backward compatibility
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files_content = read_files_func(all_files)
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if files_content:
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# Add token validation for the combined file content
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from utils.token_utils import check_token_limit
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within_limit, estimated_tokens = check_token_limit(files_content)
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if within_limit:
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history_parts.append(files_content)
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else:
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# Handle token limit exceeded for conversation files
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error_message = f"ERROR: The total size of files referenced in this conversation has exceeded the context limit and cannot be displayed.\nEstimated tokens: {estimated_tokens}, but limit is {MAX_CONTEXT_TOKENS}."
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history_parts.append(error_message)
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else:
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history_parts.append("(No accessible files found)")
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history_parts.extend(
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[
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"",
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"=== END REFERENCED FILES ===",
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"",
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]
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)
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history_parts.append("Previous conversation turns:")
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for i, turn in enumerate(context.turns, 1):
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role_label = "Claude" if turn.role == "user" else "Gemini"
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@@ -327,9 +459,10 @@ def build_conversation_history(context: ThreadContext) -> str:
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turn_header += ") ---"
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history_parts.append(turn_header)
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# Add files context if present - critical for cross-tool file access
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# Add files context if present - but just reference which files were used
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# (the actual contents are already embedded above)
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if turn.files:
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history_parts.append(f"📁 Files referenced: {', '.join(turn.files)}")
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history_parts.append(f"📁 Files used in this turn: {', '.join(turn.files)}")
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history_parts.append("") # Empty line for readability
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# Add the actual content
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@@ -340,7 +473,7 @@ def build_conversation_history(context: ThreadContext) -> str:
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history_parts.append(f"\n[Gemini's Follow-up: {turn.follow_up_question}]")
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history_parts.extend(
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["", "=== END HISTORY ===", "", "Continue this conversation by building on the previous context."]
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["", "=== END CONVERSATION HISTORY ===", "", "Continue this conversation by building on the previous context."]
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)
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return "\n".join(history_parts)
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