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README.md

@@ -198,6 +198,8 @@ pip install -r requirements.txt
 # Create .env file
 GEMINI_API_KEY=your_gemini_api_key
 TAVILY_API_KEY=your_tavily_api_key
+LANGSMITH_API_KEY=your_langsmith_api_key  # Optional: for tracing and debugging
+LANGSMITH_PROJECT=profile-analyzer         # Optional: project name for LangSmith
 ```
 
 ### Running the System
@@ -231,6 +233,22 @@ result = analyze_profile({
 print(result.model_dump())
 ```
 
+### LangSmith Tracing & Debugging
+The system includes comprehensive tracing for debugging and analysis:
+
+1. **Public Run Viewing**: All agent executions are traced and publicly viewable
+2. **Detailed Progress**: Step-by-step tracking of agent decisions and tool executions
+3. **Performance Metrics**: Monitor execution time, tool usage, and agent collaboration
+4. **Debug Information**: Trace through the entire reasoning process
+
+**To enable tracing:**
+```bash
+export LANGSMITH_API_KEY=your_api_key
+export LANGSMITH_PROJECT=profile-analyzer
+```
+
+**View runs at:** `https://smith.langchain.com/o/default/p/profile-analyzer`
+
 ## System Capabilities
 
 ### Autonomous Decision Making
@@ -242,6 +260,7 @@ print(result.model_dump())
 - **Live Web Search**: Current information from multiple sources
 - **Dynamic Updates**: Real-time progress tracking and status updates
 - **Adaptive Queries**: Search strategies that adapt to available data
+- **LangSmith Tracing**: Public viewing of agent execution traces and reasoning
 
 ### Fault Tolerance
 - **Incomplete Data Handling**: Works with partial profile information

requirements.txt

@@ -3,4 +3,5 @@ langgraph
 langgraph-supervisor
 pydantic
 python-dotenv
-tavily-python 
+tavily-python
+langsmith 

supervisor_agent.py

@@ -662,14 +662,22 @@ def extract_data_with_ai(agent_responses: List[str], profile_input: Dict) -> Pro
     search_results = []
     parsed_current_company = None
     parsed_current_title = None
+    
+    # First priority: Get parsed data from modified profile_input (direct from tool)
+    if 'parsed_current_company' in profile_input:
+        parsed_current_company = profile_input['parsed_current_company']
+    if 'parsed_current_title' in profile_input:
+        parsed_current_title = profile_input['parsed_current_title']
+    
+    # Second priority: Try to extract from agent_responses
     try:
         response_json = json.loads(agent_responses[0]) if isinstance(agent_responses[0], str) else agent_responses[0]
         if isinstance(response_json, dict):
             if 'search_results' in response_json:
                 search_results = response_json['search_results']
-            if response_json.get('parsed_current_company'):
+            if not parsed_current_company and response_json.get('parsed_current_company'):
                 parsed_current_company = response_json['parsed_current_company']
-            if response_json.get('parsed_current_title'):
+            if not parsed_current_title and response_json.get('parsed_current_title'):
                 parsed_current_title = response_json['parsed_current_title']
     except Exception:
         pass
@@ -813,9 +821,38 @@ def analyze_profile(profile_input: Dict[str, Any]) -> ProfileAnalysisResult:
     
     print(f"🔍 Supervisor Synthesis: {supervisor_synthesis}")
     
+    # Extract parsed_current_company and parsed_current_title directly from profile_researcher results
+    parsed_current_company = None
+    parsed_current_title = None
+    
+    if 'profile_researcher' in agent_results:
+        profile_result = agent_results['profile_researcher']
+        if hasattr(profile_result, 'messages') and profile_result.messages:
+            for msg in profile_result.messages:
+                if hasattr(msg, 'tool_calls') and msg.tool_calls:
+                    for tool_call in msg.tool_calls:
+                        if tool_call.get('name') == 'research_person_profile':
+                            try:
+                                tool_output = json.loads(tool_call.get('args', {}))
+                                if 'parsed_current_company' in tool_output:
+                                    parsed_current_company = tool_output['parsed_current_company']
+                                if 'parsed_current_title' in tool_output:
+                                    parsed_current_title = tool_output['parsed_current_title']
+                                print(f"🔍 Direct tool output - Company: {parsed_current_company}, Title: {parsed_current_title}")
+                            except Exception as e:
+                                print(f"❌ Error parsing tool output: {e}")
+    
     # Use AI to extract structured data from the supervisor's synthesis
     agent_responses = [supervisor_synthesis]  # Only use the final synthesis
-    return extract_data_with_ai(agent_responses, profile_input)
+    
+    # Create a modified profile_input with the parsed data
+    modified_profile_input = profile_input.copy()
+    if parsed_current_company:
+        modified_profile_input['parsed_current_company'] = parsed_current_company
+    if parsed_current_title:
+        modified_profile_input['parsed_current_title'] = parsed_current_title
+    
+    return extract_data_with_ai(agent_responses, modified_profile_input)
 
 def analyze_profile_with_progress(profile_input: Dict[str, Any], progress) -> ProfileAnalysisResult:
     """Analyze profile with progress updates for Gradio UI"""