more agents added

app.py

@@ -112,25 +112,55 @@ class SlpMultiAgent:
             max_tokens=1000    # Keep higher tokens for complex reasoning
         )
         
-        # Create specialized agents
+        # Create specialized agents for complex problem-solving
         research_agent = CodeAgent(
-            tools=[ReliableSearchTool(), KnowledgeBaseTool()],
+            tools=[KnowledgeBaseTool()],
             model=model,
-            additional_authorized_imports=["pandas", "time", "json", "requests", "urllib", "re", "datetime"],
+            additional_authorized_imports=["pandas", "time", "json", "requests", "re", "datetime"],
             max_steps=4,
             name="ResearchAgent",
             verbosity_level=0,
-            description="Specialized agent for research and fact-finding with knowledge base access."
+            description="Specializes in factual research, historical data, and knowledge retrieval."
+        )
+        
+        math_agent = CodeAgent(
+            tools=[],
+            model=model,
+            additional_authorized_imports=["math", "statistics", "numpy", "pandas", "fractions", "decimal"],
+            max_steps=4,
+            name="MathAgent",
+            verbosity_level=0,
+            description="Specializes in mathematical calculations, statistics, and numerical analysis."
         )
         
-        analysis_agent = CodeAgent(
+        logic_agent = CodeAgent(
             tools=[],
             model=model,
-            additional_authorized_imports=["pandas", "time", "json", "requests", "math", "statistics"],
+            additional_authorized_imports=["itertools", "collections", "re", "string"],
+            max_steps=4,
+            name="LogicAgent",
+            verbosity_level=0,
+            description="Specializes in logical reasoning, pattern recognition, and problem decomposition."
+        )
+        
+        language_agent = CodeAgent(
+            tools=[],
+            model=model,
+            additional_authorized_imports=["re", "string", "collections"],
             max_steps=3,
-            name="AnalysisAgent",
+            name="LanguageAgent",
+            verbosity_level=0,
+            description="Specializes in text analysis, word puzzles, linguistics, and language patterns."
+        )
+        
+        data_agent = CodeAgent(
+            tools=[],
+            model=model,
+            additional_authorized_imports=["pandas", "json", "csv", "collections", "statistics"],
+            max_steps=4,
+            name="DataAgent",
             verbosity_level=0,
-            description="Specialized agent for data analysis, calculations, and logical reasoning."
+            description="Specializes in data processing, sorting, filtering, and structured analysis."
         )
 
         manager_agent = CodeAgent(
@@ -140,7 +170,7 @@ class SlpMultiAgent:
                 max_tokens=1200
             ),
             tools=[KnowledgeBaseTool()],
-            managed_agents=[research_agent, analysis_agent],
+            managed_agents=[research_agent, math_agent, logic_agent, language_agent, data_agent],
             name="ManagerAgent",
             description="A manager agent that coordinates research and analysis agents to solve complex questions.",
             additional_authorized_imports=[
@@ -153,7 +183,7 @@ class SlpMultiAgent:
             ],
             planning_interval=2,
             verbosity_level=1,
-            max_steps=8,
+            max_steps=10,  # More steps for complex coordination
             final_answer_checks=[check_reasoning]
         )
         
@@ -169,19 +199,22 @@ class SlpMultiAgent:
                     lambda: manager_agent.run(f"""
                     Question: {short_question}
                     
-                    You have access to ResearchAgent and AnalysisAgent. Use them strategically:
-                    - ResearchAgent: For finding facts, searching, and knowledge lookup
-                    - AnalysisAgent: For calculations, data processing, and logical reasoning
+                    You have 5 specialized agents available:
+                    - ResearchAgent: Facts, history, knowledge lookup
+                    - MathAgent: Calculations, statistics, numerical problems
+                    - LogicAgent: Logical reasoning, patterns, problem decomposition
+                    - LanguageAgent: Text analysis, word puzzles, linguistics
+                    - DataAgent: Data processing, sorting, structured analysis
                     
-                    Process:
-                    1. Analyze what type of question this is
-                    2. Use knowledge_base() to check for relevant context
-                    3. Delegate to appropriate agents if needed
-                    4. Synthesize information and provide final answer
+                    Strategy:
+                    1. Analyze question type and complexity
+                    2. Use knowledge_base() for context
+                    3. Delegate to most appropriate specialist agent(s)
+                    4. Synthesize results into final answer
                     
-                    CRITICAL: End with <code>final_answer("exact answer only")</code>
+                    CRITICAL: End with <code>final_answer("exact answer")</code>
                     
-                    The final_answer must contain ONLY the specific answer requested - no explanations.
+                    Final answer must be direct and specific - no explanations.
                     """)
                 )
                 break  # Success, exit retry loop