Add DocGen tool with comprehensive documentation generation capabilities (#109)
* WIP: new workflow architecture * WIP: further improvements and cleanup * WIP: cleanup and docks, replace old tool with new * WIP: cleanup and docks, replace old tool with new * WIP: new planner implementation using workflow * WIP: precommit tool working as a workflow instead of a basic tool Support for passing False to use_assistant_model to skip external models completely and use Claude only * WIP: precommit workflow version swapped with old * WIP: codereview * WIP: replaced codereview * WIP: replaced codereview * WIP: replaced refactor * WIP: workflow for thinkdeep * WIP: ensure files get embedded correctly * WIP: thinkdeep replaced with workflow version * WIP: improved messaging when an external model's response is received * WIP: analyze tool swapped * WIP: updated tests * Extract only the content when building history * Use "relevant_files" for workflow tools only * WIP: updated tests * Extract only the content when building history * Use "relevant_files" for workflow tools only * WIP: fixed get_completion_next_steps_message missing param * Fixed tests Request for files consistently * Fixed tests Request for files consistently * Fixed tests * New testgen workflow tool Updated docs * Swap testgen workflow * Fix CI test failures by excluding API-dependent tests - Update GitHub Actions workflow to exclude simulation tests that require API keys - Fix collaboration tests to properly mock workflow tool expert analysis calls - Update test assertions to handle new workflow tool response format - Ensure unit tests run without external API dependencies in CI 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com> * WIP - Update tests to match new tools * WIP - Update tests to match new tools * WIP - Update tests to match new tools * Should help with https://github.com/BeehiveInnovations/zen-mcp-server/issues/97 Clear python cache when running script: https://github.com/BeehiveInnovations/zen-mcp-server/issues/96 Improved retry error logging Cleanup * WIP - chat tool using new architecture and improved code sharing * Removed todo * Removed todo * Cleanup old name * Tweak wordings * Tweak wordings Migrate old tests * Support for Flash 2.0 and Flash Lite 2.0 * Support for Flash 2.0 and Flash Lite 2.0 * Support for Flash 2.0 and Flash Lite 2.0 Fixed test * Improved consensus to use the workflow base class * Improved consensus to use the workflow base class * Allow images * Allow images * Replaced old consensus tool * Cleanup tests * Tests for prompt size * New tool: docgen Tests for prompt size Fixes: https://github.com/BeehiveInnovations/zen-mcp-server/issues/107 Use available token size limits: https://github.com/BeehiveInnovations/zen-mcp-server/issues/105 * Improved docgen prompt Exclude TestGen from pytest inclusion * Updated errors * Lint * DocGen instructed not to fix bugs, surface them and stick to d * WIP * Stop claude from being lazy and only documenting a small handful * More style rules --------- Co-authored-by: Claude <noreply@anthropic.com>
This commit is contained in:
Beehive Innovations
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commit
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158
tools/chat.py
158
tools/chat.py
@@ -1,5 +1,9 @@
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"""
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Chat tool - General development chat and collaborative thinking
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This tool provides a conversational interface for general development assistance,
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brainstorming, problem-solving, and collaborative thinking. It supports file context,
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images, and conversation continuation for seamless multi-turn interactions.
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"""
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from typing import TYPE_CHECKING, Any, Optional
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@@ -11,10 +15,11 @@ if TYPE_CHECKING:
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from config import TEMPERATURE_BALANCED
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from systemprompts import CHAT_PROMPT
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from tools.shared.base_models import ToolRequest
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from .base import BaseTool, ToolRequest
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from .simple.base import SimpleTool
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# Field descriptions to avoid duplication between Pydantic and JSON schema
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# Field descriptions matching the original Chat tool exactly
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CHAT_FIELD_DESCRIPTIONS = {
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"prompt": (
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"You MUST provide a thorough, expressive question or share an idea with as much context as possible. "
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@@ -32,15 +37,23 @@ CHAT_FIELD_DESCRIPTIONS = {
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class ChatRequest(ToolRequest):
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"""Request model for chat tool"""
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"""Request model for Chat tool"""
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prompt: str = Field(..., description=CHAT_FIELD_DESCRIPTIONS["prompt"])
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files: Optional[list[str]] = Field(default_factory=list, description=CHAT_FIELD_DESCRIPTIONS["files"])
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images: Optional[list[str]] = Field(default_factory=list, description=CHAT_FIELD_DESCRIPTIONS["images"])
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class ChatTool(BaseTool):
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"""General development chat and collaborative thinking tool"""
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class ChatTool(SimpleTool):
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"""
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General development chat and collaborative thinking tool using SimpleTool architecture.
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This tool provides identical functionality to the original Chat tool but uses the new
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SimpleTool architecture for cleaner code organization and better maintainability.
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Migration note: This tool is designed to be a drop-in replacement for the original
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Chat tool with 100% behavioral compatibility.
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"""
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def get_name(self) -> str:
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return "chat"
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@@ -57,7 +70,33 @@ class ChatTool(BaseTool):
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"provide enhanced capabilities."
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)
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def get_system_prompt(self) -> str:
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return CHAT_PROMPT
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def get_default_temperature(self) -> float:
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return TEMPERATURE_BALANCED
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def get_model_category(self) -> "ToolModelCategory":
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"""Chat prioritizes fast responses and cost efficiency"""
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from tools.models import ToolModelCategory
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return ToolModelCategory.FAST_RESPONSE
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def get_request_model(self):
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"""Return the Chat-specific request model"""
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return ChatRequest
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# === Schema Generation ===
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# For maximum compatibility, we override get_input_schema() to match the original Chat tool exactly
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def get_input_schema(self) -> dict[str, Any]:
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"""
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Generate input schema matching the original Chat tool exactly.
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This maintains 100% compatibility with the original Chat tool by using
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the same schema generation approach while still benefiting from SimpleTool
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convenience methods.
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"""
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schema = {
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"type": "object",
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"properties": {
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@@ -115,79 +154,62 @@ class ChatTool(BaseTool):
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return schema
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def get_system_prompt(self) -> str:
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return CHAT_PROMPT
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# === Tool-specific field definitions (alternative approach for reference) ===
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# These aren't used since we override get_input_schema(), but they show how
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# the tool could be implemented using the automatic SimpleTool schema building
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def get_default_temperature(self) -> float:
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return TEMPERATURE_BALANCED
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def get_tool_fields(self) -> dict[str, dict[str, Any]]:
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"""
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Tool-specific field definitions for ChatSimple.
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def get_model_category(self) -> "ToolModelCategory":
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"""Chat prioritizes fast responses and cost efficiency"""
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from tools.models import ToolModelCategory
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Note: This method isn't used since we override get_input_schema() for
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exact compatibility, but it demonstrates how ChatSimple could be
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implemented using automatic schema building.
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"""
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return {
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"prompt": {
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"type": "string",
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"description": CHAT_FIELD_DESCRIPTIONS["prompt"],
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},
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"files": {
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"type": "array",
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"items": {"type": "string"},
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"description": CHAT_FIELD_DESCRIPTIONS["files"],
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},
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"images": {
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"type": "array",
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"items": {"type": "string"},
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"description": CHAT_FIELD_DESCRIPTIONS["images"],
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},
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}
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return ToolModelCategory.FAST_RESPONSE
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def get_required_fields(self) -> list[str]:
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"""Required fields for ChatSimple tool"""
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return ["prompt"]
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def get_request_model(self):
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return ChatRequest
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# === Hook Method Implementations ===
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async def prepare_prompt(self, request: ChatRequest) -> str:
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"""Prepare the chat prompt with optional context files"""
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# Check for prompt.txt in files
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prompt_content, updated_files = self.handle_prompt_file(request.files)
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"""
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Prepare the chat prompt with optional context files.
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# Use prompt.txt content if available, otherwise use the prompt field
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user_content = prompt_content if prompt_content else request.prompt
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# Check user input size at MCP transport boundary (before adding internal content)
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size_check = self.check_prompt_size(user_content)
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if size_check:
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# Need to return error, but prepare_prompt returns str
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# Use exception to handle this cleanly
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from tools.models import ToolOutput
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raise ValueError(f"MCP_SIZE_CHECK:{ToolOutput(**size_check).model_dump_json()}")
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# Update request files list
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if updated_files is not None:
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request.files = updated_files
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# Add context files if provided (using centralized file handling with filtering)
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if request.files:
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file_content, processed_files = self._prepare_file_content_for_prompt(
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request.files, request.continuation_id, "Context files"
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)
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self._actually_processed_files = processed_files
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if file_content:
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user_content = f"{user_content}\n\n=== CONTEXT FILES ===\n{file_content}\n=== END CONTEXT ===="
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# Check token limits
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self._validate_token_limit(user_content, "Content")
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# Add web search instruction if enabled
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websearch_instruction = self.get_websearch_instruction(
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request.use_websearch,
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"""When discussing topics, consider if searches for these would help:
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- Documentation for any technologies or concepts mentioned
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- Current best practices and patterns
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- Recent developments or updates
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- Community discussions and solutions""",
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)
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# Combine system prompt with user content
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full_prompt = f"""{self.get_system_prompt()}{websearch_instruction}
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=== USER REQUEST ===
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{user_content}
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=== END REQUEST ===
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Please provide a thoughtful, comprehensive response:"""
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return full_prompt
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This implementation matches the original Chat tool exactly while using
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SimpleTool convenience methods for cleaner code.
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"""
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# Use SimpleTool's Chat-style prompt preparation
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return self.prepare_chat_style_prompt(request)
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def format_response(self, response: str, request: ChatRequest, model_info: Optional[dict] = None) -> str:
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"""Format the chat response"""
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"""
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Format the chat response to match the original Chat tool exactly.
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"""
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return (
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f"{response}\n\n---\n\n**Claude's Turn:** Evaluate this perspective alongside your analysis to "
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"form a comprehensive solution and continue with the user's request and task at hand."
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)
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def get_websearch_guidance(self) -> str:
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"""
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Return Chat tool-style web search guidance.
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"""
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return self.get_chat_style_websearch_guidance()
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