sync

src/langgraphagenticai/nodes/blog_generation_node.py

@@ -172,8 +172,10 @@ class BlogGenerationNode:
         return {"initial_draft": initial_draft}
 
     def feedback_collector(self, state: State) -> dict:
-        logger.info(f"\n\n----------------:Entered  feedback_collector with state:----------------------\n\n{state}")
-
+        logger.info(f"\n\n----------------:Entered feedback_collector with state:----------------------\n\n{state}")
+        logger.info(f"Message count: {len(state.get('messages', []))}")
+        logger.info(f"Last message type: {type(state['messages'][-1]) if state.get('messages') else 'None'}")
+        
         if state.get("messages") and len(state["messages"]) > 0 and isinstance(state["messages"][-1], HumanMessage):
             try:
                 feedback_data = json.loads(state["messages"][-1].content)
@@ -220,11 +222,12 @@ class BlogGenerationNode:
     # Conditional edge for feedback loop
     def route_feedback(self, state: State):
         """Route based on whether draft is approved."""
-        logger.info(f"route_feedback: draft_approved = {state.get('draft_approved', False)}")
-        logger.info(f"route_feedback: state[\\'draft_approved\\'] = {state['draft_approved']}")
-        if state["draft_approved"]== True:
+        draft_approved = state.get('draft_approved', False)
+        logger.info(f"route_feedback: draft_approved = {draft_approved}")
+        
+        if draft_approved is True:  # Strict comparison
             logger.info("Draft approved; routing to file_generator")
-            state["final_report"] = state.get("initial_draft", "") 
-            return "file_generator" # Routes to file_generator if approved
-        logger.info("Draft not approved; routing back to orchestrator for revision")
-        return "orchestrator" # Routes back to orchestrator if not approved
+            return "file_generator"
+        else:
+            logger.info("Draft not approved; routing back to orchestrator for revision")
+            return "orchestrator"

src/langgraphagenticai/ui/streamlitui/display_result.py

@@ -130,13 +130,35 @@ class DisplayResultStreamlit:
                         logger.info(f"\n{'*'*20}st.session_state[feedback] is {st.session_state["feedback"]}{'*'*20}\n")
                         st.rerun() # Trigger rerun to enter the processing_feedback stage
 
+            # In DisplayResultStreamlit.process_user_input() for the "processing_feedback" stage
             elif st.session_state.current_stage == "processing_feedback":
                 logger.info(f"\n\n{"="*20}: Entered main Display processing_feedback stage:{"="*20}\n\n")
+                
+                # Create a proper feedback message
+                feedback_message = HumanMessage(content=json.dumps({
+                    "approved": False, 
+                    "comments": st.session_state['feedback']
+                }))
+                
+                # Resume the graph with the stored state and new feedback
+                logger.info(f"Resuming graph with feedback: {feedback_message.content}")
+                
+                # Use the stored checkpoint state to resume the graph
+                checkpoint_state = st.session_state.get("graph_state")
+                if checkpoint_state:
+                    input_data = {
+                        "messages": [feedback_message],
+                        "__checkpoint__": checkpoint_state  # Pass the stored checkpoint
+                    }
+                    blog_display.process_graph_events_with_checkpoint(input_data)
+                else:
+                    # Fall back to regular processing if no checkpoint available
+                    blog_display.process_graph_events(feedback_message)
+                
                 st.session_state.current_stage = "processing"
-                logger.info(f"\n{'*'*20}st.session_state[feedback] is {st.session_state["feedback"]}{'*'*20}\n")
-                blog_display.process_graph_events(HumanMessage(content=json.dumps({"approved": False, "comments": st.session_state['feedback']})))
-                st.session_state['feedback_result'] = None # Clear the feedback result
+                st.session_state['feedback_result'] = None  # Clear the feedback result
                 st.rerun()
+                
             elif st.session_state.current_stage == "complete":
                 st.success("✅ Blog generation complete!")
                 if st.session_state.get("blog_content"):

src/langgraphagenticai/ui/streamlitui/display_result_blog.py

@@ -138,85 +138,106 @@ class DisplayBlogResult:
           
 
 
-    def process_feedback(self):
-        print("\n\n----blog_display process_feedback function entered----\n\n")
-        logger.info("---blog_display process_feedback function entered ----\n\n")
-        st.write("Session State in process_feedback:", st.session_state)
-        st.markdown("## Stage 3: Feedback")
-        if st.session_state.get("generated_draft"):
-            st.markdown("### Drafted Blog Content:")
-            st.markdown(st.session_state["generated_draft"])
-        with st.expander("Stage 3: Feedback", expanded=True):
-            feedback_text = st.text_input(
-                "Revision comments:",
-                placeholder="Please explain what changes you would like to see.",
-                key="revision_comments_area",
-                value=st.session_state.get("revision_comments_area", "Add some reference to it ")
-            )
-            st.session_state["feedback"] = feedback_text  # Update session state for graph processing
-
-            col1, col2 = st.columns(2)
-            with col1:
-                st.button("✅ Approve Content", on_click=self._handle_approved_click, key="blog_feedback_approve_button")
-            with col2:
-                st.button("Submit Revision Request", on_click=self._handle_revised_click, key="blog_feedback_revise_button")
-        return st.session_state.get('feedback_result')
-
-
     def process_graph_events(self, input_message=None):
         try:
-            
             input_data = {"messages": [input_message]} if input_message else None
             progress_bar = st.progress(0)
+            
+            # Store the graph state for resuming later
+            checkpoint_state = None
 
             for i, event in enumerate(self.graph.stream(input_data, self.config)):
                 logger.info(f"Graph event received: #{i+1}")
-
+                
                 # Update progress indicator
-                progress_value = min(i * 0.1, 0.9)  # Cap at 90% until complete
+                progress_value = min(i * 0.1, 0.9)
                 progress_bar.progress(progress_value)
+                
+                # Store the latest checkpoint state for resuming after interrupt
+                if "__checkpoint__" in event:
+                    checkpoint_state = event["__checkpoint__"]
+                    st.session_state.graph_state = checkpoint_state
+                    logger.info(f"Checkpoint state stored: {checkpoint_state}")
 
                 # Process event data
                 for node, state in event.items():
-                    logger.info(f"Processing event for node: {node}, state: {state}")
-
-                    # Specifically handle interrupt events
+                    # Handle interrupt after synthesizer
                     if node == "__interrupt__":
                         logger.info("Interrupt event received - transitioning to feedback stage")
                         st.session_state.waiting_for_feedback = True
-                        logger.info("Waiting for feedback from user.")
                         st.session_state.current_stage = "feedback"
-                        logger.info("Feedback stage initiated.")
                         st.rerun()
-                        progress_bar.progress(1.0)
                         return
 
-                    if isinstance(state, dict):
-
-                        if node == "synthesizer" and "initial_draft" in state and not st.session_state.get('synthesizer_output_processed', False):
-                            logger.info("Draft generated by synthesizer, displaying content")
-                            st.markdown("## Generating  Draft")
-                            st.session_state.generated_draft = state["initial_draft"]
-                            st.session_state.content_displayed = True  # Ensure this is set
-                            st.session_state.current_stage = "content"  # Ensure this is set
-                            st.session_state.synthesizer_output_processed = True #Set the flag.
+                    # Process synthesizer output
+                    if node == "synthesizer" and "initial_draft" in state:
+                        logger.info("Draft generated by synthesizer, displaying content")
+                        st.session_state.generated_draft = state["initial_draft"]
+                        st.session_state.content_displayed = True
+                        st.session_state.synthesizer_output_processed = True
+            
+            progress_bar.progress(1.0)
+        except Exception as e:
+            st.error(f"⚠️ Error processing workflow: {e}")
+            logger.exception(f"Error in graph streaming: {e}")
 
-                    # Check if the file_generator node finished 
+    def process_graph_events_with_checkpoint(self, input_data):
+        """Process graph events with a checkpoint to resume from interrupt"""
+        try:
+            progress_bar = st.progress(0)
+            
+            # We're resuming from a stored checkpoint
+            for i, event in enumerate(self.graph.stream(input_data, self.config)):
+                logger.info(f"Graph event received (resuming): #{i+1}")
+                
+                # Update progress indicator
+                progress_value = min(i * 0.1, 0.9)
+                progress_bar.progress(progress_value)
+                
+                # Store the latest checkpoint state for resuming after interrupt
+                if "__checkpoint__" in event:
+                    st.session_state.graph_state = event["__checkpoint__"]
+                
+                # Process event data (similar to process_graph_events)
+                for node, state in event.items():
+                    if node == "feedback_collector":
+                        logger.info(f"Feedback collector processing: {state}")
+                    
                     if node == "file_generator":
                         logger.info("File generator node finished, setting stage to complete.")
                         st.session_state.blog_generation_complete = True
                         st.session_state.current_stage = "complete"
                         st.session_state.processing_complete = True
-                        break  # Stop processing events after completion
-
-      
-
-            # Ensure progress completes
+                        break
+            
             progress_bar.progress(1.0)
-
         except Exception as e:
             st.error(f"⚠️ Error processing workflow: {e}")
             logger.exception(f"Error in graph streaming: {e}")
-            # Add recovery mechanism
-            st.session_state.current_stage = "requirements"
-            st.warning("There was an error. Please try again.")
+
+    def process_feedback(self):
+        """Process user feedback on the generated blog draft."""
+        print("\n\n----blog_display process_feedback function entered----\n\n")
+        logger.info("---blog_display process_feedback function entered ----\n\n")
+        
+        st.markdown("## Stage 3: Feedback")
+        if st.session_state.get("generated_draft"):
+            st.markdown("### Drafted Blog Content:")
+            st.markdown(st.session_state["generated_draft"])
+            
+        with st.expander("Stage 3: Feedback", expanded=True):
+            feedback_text = st.text_input(
+                "Revision comments:",
+                placeholder="Please explain what changes you would like to see.",
+                key="revision_comments_area",
+                value=st.session_state.get("revision_comments_area", "Add some reference to it ")
+            )
+            st.session_state["feedback"] = feedback_text  # Update session state for graph processing
+
+            col1, col2 = st.columns(2)
+            with col1:
+                st.button("✅ Approve Content", on_click=self._handle_approved_click, key="blog_feedback_approve_button")
+            with col2:
+                st.button("Submit Revision Request", on_click=self._handle_revised_click, key="blog_feedback_revise_button")
+        
+        return st.session_state.get('feedback_result')