make new graph execution unique thread_id as local variable => allows PR bot to handle multiple PRs concurrently

app.py

@@ -74,11 +74,6 @@ SQLITE_DB_PATH = tempfile.gettempdir() + '/langgraph_checkpoints.sqlite'
 
 # --- Checkpointer and Graph Compilation ---
 global_memory_saver = None # Initialize to None
-new_thread_id = str(uuid.uuid4())
-
-#----- thread_id is made global until below gradio issue is resolved
-# gradio_issue: https://github.com/gradio-app/gradio/issues/10893
-
 
 try:
     # Attempt to connect to SQLite
@@ -235,8 +230,8 @@ async def github_webhook(
     print(f"pr_repo_name: {pr_repo_name} ")
 
     # each graph invocation will have unique thread_id, it can be used to  RESUME graph post human feedback.
-    #new_thread_id = str(uuid.uuid4())
-    print(f"\n--- Starting New Graph Execution with thread_id: {new_thread_id} ---")
+    graph_thread_id = str(uuid.uuid4())
+    print(f"\n--- Starting New Graph Execution with thread_id: {graph_thread_id} ---")
 
     if not global_graph:
         print("Error: Graph not initialized. Check server logs.")
@@ -269,7 +264,7 @@ async def github_webhook(
     print("Graph is being streamed....")
 
     try:
-        for s in global_graph.stream(initial_state, {"configurable": {"thread_id": new_thread_id}}):
+        for s in global_graph.stream(initial_state, {"configurable": {"thread_id": graph_thread_id}}):
             if "__end__" in s:
                 break
             elif "__interrupt__" in s:
@@ -279,7 +274,7 @@ async def github_webhook(
                 pass 
 
         print("printing state from web_hook since graph is paused at this point")
-        current_state_snapshot = global_graph.get_state({"configurable": {"thread_id": new_thread_id}})
+        current_state_snapshot = global_graph.get_state({"configurable": {"thread_id": graph_thread_id}})
         current_state = current_state_snapshot.values
 
         require_human_approval = current_state['require_human_approval']
@@ -296,10 +291,10 @@ async def github_webhook(
             return
        
 
-        encoded_review_link = quote_plus(review_url)
-        gradio_review_url = f"{GRADIO_SPACE_BASE_URL}?review_id={review_id}&review_link={encoded_review_link}"
+        thread_id = graph_thread_id
+        gradio_review_url = f"{GRADIO_SPACE_BASE_URL}?review_id={review_id}&thread_id={thread_id}"
 
-        print(f"gradio_review_url:{gradio_review_url}\nencoded_review_link:{encoded_review_link}")
+        print(f"gradio_review_url:{gradio_review_url}\nthread_id:{thread_id}")
         comment_body = f"""
             🤖 **Human Review Required!** 🤖
 
@@ -356,6 +351,7 @@ class HumanInputPayload(BaseModel):
     review_id: int
     approval_status: str # "approved" or "rejected"
     feedback_message: Optional[str] = None # Optional feedback
+    thread_id: str
 
 
 @app.post("/resume-review")
@@ -366,15 +362,15 @@ async def resume_review(payload: HumanInputPayload):
     print(f"Received human input for Review ID: {payload.review_id}")
     print(f"Status: {payload.approval_status}")
     print(f"Feedback: {payload.feedback_message}")
-
-    #TODO: get the thread_id_state here from payload
+    print(f"Thread ID: {payload.thread_id}")
 
     if not global_graph or not global_memory_saver:
         print("Error: Graph or checkpointer not initialized. Check server logs.")
         return
 
     try:
-        current_state_snapshot = global_graph.get_state({"configurable": {"thread_id": new_thread_id}})
+        config = {"configurable": {"thread_id": payload.thread_id}}
+        current_state_snapshot = global_graph.get_state(config)
         current_state_values = current_state_snapshot.values
 
         if payload.approval_status.lower() == "rejected":
@@ -384,12 +380,7 @@ async def resume_review(payload: HumanInputPayload):
             
         current_state_values["human_feedback_message"] = payload.feedback_message
 
-
-        # Use put_state() from the SqliteSaver instance
-        #global_memory_saver.put_state(current_state_values, {"configurable": {"thread_id": thread_id_state}})
-
         # Update the state directly
-        config = {"configurable": {"thread_id": new_thread_id}}
         global_graph.update_state(config, current_state_values)
         print("graph state updated successfuly with human feedback")
         
@@ -445,4 +436,4 @@ async def resume_review(payload: HumanInputPayload):
     #         detail=f"Failed to resume workflow: {e}"
     #     )
 
-    return {"message": "Human input received and processed successfully!"}
+    return {"message": "Human input received and processed successfully!"}