Tools is broken
This commit is contained in:
eweeman
@@ -1,20 +1,94 @@
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import logging
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from typing import Dict, Any
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import json
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from typing import Dict, Any, List
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from slack_sdk import WebClient
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from slack_sdk.errors import SlackApiError
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logger = logging.getLogger(__name__)
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# Try to import LLM client, but don't fail if it's not available
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# Try to import LLM client
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try:
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from llm.local_llm_client import chat_completion
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LLM_AVAILABLE = True
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except ImportError:
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logger.warning("LLM client not available, using simple echo mode")
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logger.info("LLM client loaded successfully")
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except ImportError as e:
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logger.warning(f"LLM client not available: {e}")
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LLM_AVAILABLE = False
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chat_completion = None
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def format_tools_for_llm(tool_registry: Dict[str, Any]) -> List[Dict]:
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"""
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Convert tool registry to format suitable for LLM.
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"""
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tools = []
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for tool_name, tool_module in tool_registry.items():
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if hasattr(tool_module, 'TOOL_DEFINITION'):
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tools.append(tool_module.TOOL_DEFINITION)
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return tools
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def execute_tool(tool_name: str, tool_args: Dict, tool_registry: Dict) -> str:
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"""
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Execute a tool and return the result as a string.
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"""
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try:
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if tool_name not in tool_registry:
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return f"Error: Tool '{tool_name}' not found"
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tool_module = tool_registry[tool_name]
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if not hasattr(tool_module, 'run'):
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return f"Error: Tool '{tool_name}' has no run function"
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logger.info(f"Executing tool: {tool_name} with args: {tool_args}")
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result = tool_module.run(**tool_args)
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# Convert result to string if needed
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if isinstance(result, dict):
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return json.dumps(result, indent=2)
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return str(result)
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except Exception as e:
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logger.error(f"Error executing tool {tool_name}: {e}", exc_info=True)
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return f"Error executing {tool_name}: {str(e)}"
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def parse_tool_calls_from_text(response_text: str) -> List[Dict]:
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"""
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Parse tool calls from LLM response text.
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Looks for patterns like:
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TOOL_CALL: tool_name(arg1="value1", arg2="value2")
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or JSON format:
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{"tool": "tool_name", "args": {"arg1": "value1"}}
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"""
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tool_calls = []
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# Simple pattern matching for tool calls
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# You can enhance this based on how your LLM formats tool calls
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# Pattern 1: TOOL_CALL: function_name(args)
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if "TOOL_CALL:" in response_text:
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lines = response_text.split('\n')
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for line in lines:
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if line.strip().startswith("TOOL_CALL:"):
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try:
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# Extract tool call
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tool_str = line.split("TOOL_CALL:")[1].strip()
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# Parse it (simplified - you may need better parsing)
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if "(" in tool_str:
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tool_name = tool_str.split("(")[0].strip()
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tool_calls.append({
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"name": tool_name,
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"arguments": {} # You'd need to parse the args
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})
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except:
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pass
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return tool_calls
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def process_mention(
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event_data: dict,
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slack_client: WebClient,
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@@ -29,7 +103,7 @@ def process_mention(
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channel = event.get("channel")
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user = event.get("user")
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text = event.get("text", "")
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ts = event.get("ts") # This is the message timestamp
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ts = event.get("ts")
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logger.info(f"Processing mention from {user} in {channel}")
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@@ -39,50 +113,102 @@ def process_mention(
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# Get bot configuration
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bot_name = getattr(bot_profile, "BOT_IDENTIFIER", "Bot")
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system_prompt = getattr(bot_profile, "SYSTEM_PROMPT", "You are a helpful assistant.")
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system_prompt = getattr(bot_profile, "SYSTEM_PROMPT", "You are a helpful AI assistant.")
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try:
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# Try to get RAG context if enabled
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# Get RAG context if enabled
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rag_enabled = getattr(bot_profile, "ENABLE_RAG_INSERT", False)
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context = ""
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context_messages = []
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if rag_enabled:
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try:
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# Search for similar messages
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similar = vector_store.search_similar(clean_text, limit=3)
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if similar:
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context = "\nRelevant context:\n" + "\n".join(similar)
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except AttributeError:
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logger.warning("RAG retrieval failed: search_similar not implemented")
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context = "\n".join(similar)
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context_messages.append({
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"role": "system",
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"content": f"Relevant context from previous messages:\n{context}"
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})
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logger.info(f"Added RAG context: {len(similar)} similar messages")
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except Exception as e:
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logger.error(f"RAG retrieval error: {e}")
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# Generate response
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# Add tool information to system prompt if tools are available
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if tool_registry:
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tool_descriptions = []
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for tool_name, tool_module in tool_registry.items():
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if hasattr(tool_module, 'TOOL_DEFINITION'):
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tool_def = tool_module.TOOL_DEFINITION
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desc = f"- {tool_name}: {tool_def.get('description', 'No description')}"
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tool_descriptions.append(desc)
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if tool_descriptions:
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tools_info = "\n".join(tool_descriptions)
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enhanced_system_prompt = f"""{system_prompt}
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You have access to these tools:
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{tools_info}
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To use a tool, respond with: USE_TOOL: tool_name
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Then I will execute it and provide the results."""
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else:
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enhanced_system_prompt = system_prompt
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else:
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enhanced_system_prompt = system_prompt
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logger.info("No tools available for this bot")
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# Generate response using LLM if available
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if LLM_AVAILABLE and chat_completion:
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try:
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# Use LLM to generate response
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# Build messages for LLM
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messages = [
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{"role": "system", "content": system_prompt},
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{"role": "system", "content": enhanced_system_prompt},
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*context_messages,
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{"role": "user", "content": clean_text}
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]
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if context:
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messages.insert(1, {"role": "system", "content": f"Context: {context}"})
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logger.info(f"Calling LLM with {len(messages)} messages and {len(tool_registry)} tools available")
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# Call LLM
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llm_response = chat_completion(messages)
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response_text = llm_response.get("content", "Sorry, I couldn't generate a response.")
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logger.info(f"LLM response: {response_text[:200]}...")
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# Check if LLM wants to use a tool
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if "USE_TOOL:" in response_text:
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lines = response_text.split('\n')
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for line in lines:
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if line.strip().startswith("USE_TOOL:"):
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tool_name = line.split("USE_TOOL:")[1].strip()
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if tool_name in tool_registry:
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logger.info(f"LLM requested tool: {tool_name}")
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# Execute the tool
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tool_result = execute_tool(tool_name, {}, tool_registry)
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# Get LLM to process the tool result
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messages.append({"role": "assistant", "content": response_text})
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messages.append({"role": "user", "content": f"Tool result from {tool_name}:\n{tool_result}"})
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llm_response = chat_completion(messages)
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response_text = llm_response.get("content", "Sorry, I couldn't process the tool result.")
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else:
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response_text = f"I tried to use the tool '{tool_name}' but it's not available."
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except Exception as e:
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logger.error(f"LLM error: {e}", exc_info=True)
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response_text = f"You said: {clean_text}"
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logger.error(f"LLM call failed: {e}", exc_info=True)
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response_text = "Sorry, I encountered an error processing your request."
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else:
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# Simple echo response when LLM not available
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# Fallback: simple echo response
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logger.info("Using fallback echo response (LLM not available)")
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response_text = f"You said: {clean_text}"
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if context:
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response_text += f"\n{context}"
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if tool_registry:
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response_text += f"\n\nI have {len(tool_registry)} tools available but LLM is not configured."
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# Send message to channel (NOT as a thread reply)
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# Send message to channel
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slack_client.chat_postMessage(
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channel=channel,
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text=response_text
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