set temperature param on all initialize_llm calls
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d54203b819
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@ -368,6 +368,7 @@ def main():
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_global_memory["config"]["model"] = args.model
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_global_memory["config"]["expert_provider"] = args.expert_provider
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_global_memory["config"]["expert_model"] = args.expert_model
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_global_memory["config"]["temperature"] = args.temperature
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# Create chat agent with appropriate tools
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chat_agent = create_agent(
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@ -437,6 +438,9 @@ def main():
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)
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_global_memory["config"]["research_model"] = args.research_model or args.model
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# Store temperature in global config
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_global_memory["config"]["temperature"] = args.temperature
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# Run research stage
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print_stage_header("Research Stage")
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@ -38,6 +38,7 @@ def request_research(query: str) -> ResearchResult:
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model = initialize_llm(
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config.get("provider", "anthropic"),
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config.get("model", "claude-3-5-sonnet-20241022"),
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temperature=config.get("temperature"),
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)
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# Check recursion depth
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@ -120,6 +121,7 @@ def request_web_research(query: str) -> ResearchResult:
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model = initialize_llm(
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config.get("provider", "anthropic"),
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config.get("model", "claude-3-5-sonnet-20241022"),
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temperature=config.get("temperature"),
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)
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success = True
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@ -188,6 +190,7 @@ def request_research_and_implementation(query: str) -> Dict[str, Any]:
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model = initialize_llm(
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config.get("provider", "anthropic"),
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config.get("model", "claude-3-5-sonnet-20241022"),
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temperature=config.get("temperature"),
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)
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try:
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@ -258,6 +261,7 @@ def request_task_implementation(task_spec: str) -> Dict[str, Any]:
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model = initialize_llm(
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config.get("provider", "anthropic"),
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config.get("model", "claude-3-5-sonnet-20241022"),
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temperature=config.get("temperature"),
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)
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# Get required parameters
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@ -334,6 +338,7 @@ def request_implementation(task_spec: str) -> Dict[str, Any]:
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model = initialize_llm(
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config.get("provider", "anthropic"),
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config.get("model", "claude-3-5-sonnet-20241022"),
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temperature=config.get("temperature"),
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)
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try:
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@ -117,8 +117,6 @@ def run_programming_task(
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# Log the programming task
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log_work_event(f"Executed programming task: {_truncate_for_log(instructions)}")
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print(repr(result))
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# Return structured output
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return {
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