Kackle commited on
Commit
245f5ad
·
verified ·
1 Parent(s): 9d2708b

removed wiki bc timeout

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Files changed (1) hide show
  1. app.py +13 -13
app.py CHANGED
@@ -97,9 +97,9 @@ class SlpMultiAgent:
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  # Create only essential agents with reduced complexity
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  research_agent = CodeAgent(
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- tools=[KnowledgeBaseTool(), WikipediaSearchTool()],
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  model=model,
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- additional_authorized_imports=["re", "datetime", "requests"],
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  max_steps=2, # Reduced steps for cost
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  name="ResearchAgent",
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  verbosity_level=0,
@@ -122,14 +122,14 @@ class SlpMultiAgent:
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  temperature=0.0,
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  max_tokens=500
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  ),
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- tools=[KnowledgeBaseTool(), WikipediaSearchTool()],
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  managed_agents=[research_agent, solver_agent], # Only 2 agents
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  name="ManagerAgent",
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  description="Efficient manager for quick problem solving.",
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- additional_authorized_imports=["re", "math", "requests"],
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  planning_interval=1, # Faster planning
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  verbosity_level=0, # Reduce verbosity
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- max_steps=4, # Drastically reduced steps
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  final_answer_checks=[check_reasoning]
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  )
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@@ -145,16 +145,16 @@ class SlpMultiAgent:
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  lambda: manager_agent.run(f"""
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  Question: {short_question}
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- Available tools:
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- - knowledge_base(topic): Get structured knowledge
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- - wikipedia_search(query): Search Wikipedia
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- - ResearchAgent: For factual research
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  - SolverAgent: For calculations and logic
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- Be efficient and direct. Always end with:
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- <code>final_answer("your answer")</code>
 
 
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- No explanations - just the answer.
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  """)
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  )
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  break # Success, exit retry loop
@@ -180,7 +180,7 @@ class SlpMultiAgent:
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  if result and isinstance(result, str):
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  # Look for final_answer pattern
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  import re
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- final_answer_match = re.search(r'final_answer\(["\']([^"\']*)["\'\])', result)
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  if final_answer_match:
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  clean_answer = final_answer_match.group(1)
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  return clean_answer
 
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  # Create only essential agents with reduced complexity
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  research_agent = CodeAgent(
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+ tools=[KnowledgeBaseTool()], # Remove Wikipedia to avoid timeouts
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  model=model,
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+ additional_authorized_imports=["re", "datetime"],
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  max_steps=2, # Reduced steps for cost
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  name="ResearchAgent",
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  verbosity_level=0,
 
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  temperature=0.0,
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  max_tokens=500
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  ),
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+ tools=[KnowledgeBaseTool()], # Remove Wikipedia to avoid timeouts
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  managed_agents=[research_agent, solver_agent], # Only 2 agents
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  name="ManagerAgent",
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  description="Efficient manager for quick problem solving.",
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+ additional_authorized_imports=["re", "math"],
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  planning_interval=1, # Faster planning
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  verbosity_level=0, # Reduce verbosity
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+ max_steps=3, # Further reduced steps to avoid timeouts
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  final_answer_checks=[check_reasoning]
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  )
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  lambda: manager_agent.run(f"""
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  Question: {short_question}
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+ You have knowledge_base() tool and two agents:
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+ - ResearchAgent: For factual questions
 
 
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  - SolverAgent: For calculations and logic
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+ IMPORTANT: Always end with exactly this format:
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+ <code>
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+ final_answer("your direct answer")
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+ </code>
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+ Be concise and direct.
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  """)
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  )
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  break # Success, exit retry loop
 
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  if result and isinstance(result, str):
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  # Look for final_answer pattern
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  import re
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+ final_answer_match = re.search(r'final_answer\(["\']([^"\']*)["\'\)]', result) # Fixed regex
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  if final_answer_match:
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  clean_answer = final_answer_match.group(1)
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  return clean_answer