force tool call more logs

subagents/doc_editor.py

@@ -40,7 +40,9 @@ class DocumentEditorAgent:
         self.llm = llm
         # All tools are LangChain tools with @tool decorator
         self.tools = [replace_html, add_html, delete_html, inspect_document, attempt_completion]
-        self.llm_with_tools = self.llm.bind_tools(self.tools)
+        # Force at least one tool call at each iteration using tool_choice="any"
+        self.llm_with_tools = self.llm.bind_tools(self.tools, tool_choice="any")
+        logger.info("🔧 Tool binding configured with tool_choice='any' to force tool calls")
         self.workflow = self._build_workflow()
     
     def _build_workflow(self) -> StateGraph:

subagents/pdf_analyzer.py

@@ -173,6 +173,15 @@ class PDFAnalyzerAgent:
         intermediate_steps.append(response)
         state["actors"] = response.content
         state["intermediate_steps"] = intermediate_steps
+        
+        # Log detailed LLM response
+        logger.info("=" * 80)
+        logger.info("🤖 LLM RESPONSE (extract_actors)")
+        logger.info("=" * 80)
+        logger.info(f"📊 Response length: {len(response.content)} characters")
+        logger.info(f"📄 Content preview (first 300 chars):")
+        logger.info(response.content[:300] + ("..." if len(response.content) > 300 else ""))
+        logger.info("=" * 80)
         logger.info("✅ Actors extracted")
         
         return state
@@ -193,6 +202,15 @@ class PDFAnalyzerAgent:
         intermediate_steps.append(response)
         state["key_details"] = response.content
         state["intermediate_steps"] = intermediate_steps
+        
+        # Log detailed LLM response
+        logger.info("=" * 80)
+        logger.info("🤖 LLM RESPONSE (extract_key_details)")
+        logger.info("=" * 80)
+        logger.info(f"📊 Response length: {len(response.content)} characters")
+        logger.info(f"📄 Content preview (first 300 chars):")
+        logger.info(response.content[:300] + ("..." if len(response.content) > 300 else ""))
+        logger.info("=" * 80)
         logger.info("✅ Key details extracted")
         
         return state
@@ -214,6 +232,15 @@ class PDFAnalyzerAgent:
         state["summary"] = response.content
         state["intermediate_steps"] = intermediate_steps
         state["processing_status"] = "complete"
+        
+        # Log detailed LLM response
+        logger.info("=" * 80)
+        logger.info("🤖 LLM RESPONSE (generate_summary)")
+        logger.info("=" * 80)
+        logger.info(f"📊 Response length: {len(response.content)} characters")
+        logger.info(f"📄 Content preview (first 300 chars):")
+        logger.info(response.content[:300] + ("..." if len(response.content) > 300 else ""))
+        logger.info("=" * 80)
         logger.info("✅ Summary generated")
         
         return state