fix

app.log

@@ -50797,3 +50797,167 @@ anthropic.BadRequestError: Error code: 400 - {'type': 'error', 'error': {'type':
 2025-06-06 21:18:43:__main__:INFO: Prompt: You are a helpful assistant.
 2025-06-06 21:27:34:__main__:INFO: Prompt: You are a helpful assistant.
 2025-06-06 21:27:48:__main__:INFO: Prompt: You are a helpful assistant.
+2025-06-06 21:39:54:__main__:INFO: Starting the interface
+2025-06-06 21:40:00:__main__:INFO: Greeting added for new user via handle_initial_greeting_load.
+2025-06-06 21:40:04:__main__:INFO: Prompt: You are a helpful assistant.
+2025-06-06 21:40:10:__main__:ERROR: Exception occurred
+Traceback (most recent call last):
+  File "/home/user/app/app.py", line 97, in chat_fn
+    async for stream_mode, chunk in graph.astream(
+  File "/usr/local/lib/python3.10/site-packages/langgraph/pregel/__init__.py", line 2655, in astream
+    async for _ in runner.atick(
+  File "/usr/local/lib/python3.10/site-packages/langgraph/pregel/runner.py", line 400, in atick
+    _panic_or_proceed(
+  File "/usr/local/lib/python3.10/site-packages/langgraph/pregel/runner.py", line 509, in _panic_or_proceed
+    raise exc
+  File "/usr/local/lib/python3.10/site-packages/langgraph/pregel/retry.py", line 136, in arun_with_retry
+    return await task.proc.ainvoke(task.input, config)
+  File "/usr/local/lib/python3.10/site-packages/langgraph/utils/runnable.py", line 676, in ainvoke
+    input = await step.ainvoke(input, config, **kwargs)
+  File "/usr/local/lib/python3.10/site-packages/langgraph/utils/runnable.py", line 440, in ainvoke
+    ret = await self.afunc(*args, **kwargs)
+  File "/home/user/app/graph.py", line 368, in brainstorming_node
+    content = response_message.content.strip()
+AttributeError: 'list' object has no attribute 'strip'
+2025-06-06 22:34:00:__main__:INFO: Starting the interface
+2025-06-06 22:34:11:__main__:INFO: Greeting added for new user via handle_initial_greeting_load.
+2025-06-06 22:34:21:__main__:INFO: Prompt: You are a helpful assistant.
+2025-06-06 22:34:26:__main__:ERROR: Exception occurred
+Traceback (most recent call last):
+  File "/home/user/app/app.py", line 97, in chat_fn
+    async for stream_mode, chunk in graph.astream(
+  File "/usr/local/lib/python3.10/site-packages/langgraph/pregel/__init__.py", line 2655, in astream
+    async for _ in runner.atick(
+  File "/usr/local/lib/python3.10/site-packages/langgraph/pregel/runner.py", line 400, in atick
+    _panic_or_proceed(
+  File "/usr/local/lib/python3.10/site-packages/langgraph/pregel/runner.py", line 509, in _panic_or_proceed
+    raise exc
+  File "/usr/local/lib/python3.10/site-packages/langgraph/pregel/retry.py", line 136, in arun_with_retry
+    return await task.proc.ainvoke(task.input, config)
+  File "/usr/local/lib/python3.10/site-packages/langgraph/utils/runnable.py", line 676, in ainvoke
+    input = await step.ainvoke(input, config, **kwargs)
+  File "/usr/local/lib/python3.10/site-packages/langgraph/utils/runnable.py", line 440, in ainvoke
+    ret = await self.afunc(*args, **kwargs)
+  File "/home/user/app/graph.py", line 368, in brainstorming_node
+    content = response_message.content.strip()
+AttributeError: 'list' object has no attribute 'strip'
+2025-06-06 22:34:41:__main__:INFO: Greeting added for new user via handle_initial_greeting_load.
+2025-06-06 22:40:24:__main__:INFO: Starting the interface
+2025-06-06 22:40:33:__main__:INFO: Greeting added for new user via handle_initial_greeting_load.
+2025-06-06 22:40:41:__main__:INFO: Prompt: You are a helpful assistant.
+2025-06-06 22:47:29:__main__:INFO: Starting the interface
+2025-06-06 22:47:36:__main__:INFO: Greeting added for new user via handle_initial_greeting_load.
+2025-06-06 22:47:51:__main__:INFO: Prompt: You are a helpful assistant.
+2025-06-06 22:48:20:__main__:ERROR: Exception occurred
+Traceback (most recent call last):
+  File "/home/user/app/app.py", line 97, in chat_fn
+    async for stream_mode, chunk in graph.astream(
+  File "/usr/local/lib/python3.10/site-packages/langgraph/pregel/__init__.py", line 2677, in astream
+    raise GraphRecursionError(msg)
+langgraph.errors.GraphRecursionError: Recursion limit of 20 reached without hitting a stop condition. You can increase the limit by setting the `recursion_limit` config key.
+For troubleshooting, visit: https://python.langchain.com/docs/troubleshooting/errors/GRAPH_RECURSION_LIMIT
+2025-06-06 23:09:32:__main__:INFO: Starting the interface
+2025-06-06 23:09:39:__main__:INFO: Greeting added for new user via handle_initial_greeting_load.
+2025-06-06 23:09:44:__main__:INFO: Prompt: You are a helpful assistant.
+2025-06-06 23:10:01:__main__:ERROR: Exception occurred
+Traceback (most recent call last):
+  File "/home/user/app/app.py", line 97, in chat_fn
+    async for stream_mode, chunk in graph.astream(
+  File "/usr/local/lib/python3.10/site-packages/langgraph/pregel/__init__.py", line 2677, in astream
+    raise GraphRecursionError(msg)
+langgraph.errors.GraphRecursionError: Recursion limit of 20 reached without hitting a stop condition. You can increase the limit by setting the `recursion_limit` config key.
+For troubleshooting, visit: https://python.langchain.com/docs/troubleshooting/errors/GRAPH_RECURSION_LIMIT
+2025-06-06 23:10:03:__main__:INFO: Greeting added for new user via handle_initial_greeting_load.
+2025-06-06 23:16:42:__main__:INFO: Starting the interface
+2025-06-06 23:17:03:__main__:INFO: Greeting added for new user via handle_initial_greeting_load.
+2025-06-06 23:17:10:__main__:INFO: Greeting added for new user via handle_initial_greeting_load.
+2025-06-06 23:17:20:__main__:INFO: Prompt: You are a helpful assistant.
+2025-06-06 23:17:52:__main__:ERROR: Exception occurred
+Traceback (most recent call last):
+  File "/home/user/app/app.py", line 97, in chat_fn
+    async for stream_mode, chunk in graph.astream(
+  File "/usr/local/lib/python3.10/site-packages/langgraph/pregel/__init__.py", line 2677, in astream
+    raise GraphRecursionError(msg)
+langgraph.errors.GraphRecursionError: Recursion limit of 20 reached without hitting a stop condition. You can increase the limit by setting the `recursion_limit` config key.
+For troubleshooting, visit: https://python.langchain.com/docs/troubleshooting/errors/GRAPH_RECURSION_LIMIT
+2025-06-06 23:23:37:__main__:INFO: Starting the interface
+2025-06-06 23:23:44:__main__:INFO: Greeting added for new user via handle_initial_greeting_load.
+2025-06-06 23:23:48:__main__:INFO: Prompt: You are a helpful assistant.
+2025-06-06 23:24:56:__main__:ERROR: Exception occurred
+Traceback (most recent call last):
+  File "/home/user/app/app.py", line 97, in chat_fn
+    async for stream_mode, chunk in graph.astream(
+  File "/usr/local/lib/python3.10/site-packages/langgraph/pregel/__init__.py", line 2677, in astream
+    raise GraphRecursionError(msg)
+langgraph.errors.GraphRecursionError: Recursion limit of 20 reached without hitting a stop condition. You can increase the limit by setting the `recursion_limit` config key.
+For troubleshooting, visit: https://python.langchain.com/docs/troubleshooting/errors/GRAPH_RECURSION_LIMIT
+2025-06-06 23:28:59:__main__:INFO: Starting the interface
+2025-06-06 23:29:04:__main__:INFO: Greeting added for new user via handle_initial_greeting_load.
+2025-06-06 23:29:08:__main__:INFO: Prompt: You are a helpful assistant.
+2025-06-06 23:29:57:__main__:ERROR: Exception occurred
+Traceback (most recent call last):
+  File "/home/user/app/app.py", line 97, in chat_fn
+    async for stream_mode, chunk in graph.astream(
+  File "/usr/local/lib/python3.10/site-packages/langgraph/pregel/__init__.py", line 2677, in astream
+    raise GraphRecursionError(msg)
+langgraph.errors.GraphRecursionError: Recursion limit of 20 reached without hitting a stop condition. You can increase the limit by setting the `recursion_limit` config key.
+For troubleshooting, visit: https://python.langchain.com/docs/troubleshooting/errors/GRAPH_RECURSION_LIMIT
+2025-06-06 23:31:00:__main__:INFO: Starting the interface
+2025-06-06 23:31:05:__main__:INFO: Greeting added for new user via handle_initial_greeting_load.
+2025-06-06 23:31:06:__main__:INFO: Greeting added for new user via handle_initial_greeting_load.
+2025-06-06 23:31:14:__main__:INFO: Prompt: You are a helpful assistant.
+2025-06-06 23:32:28:__main__:ERROR: Exception occurred
+Traceback (most recent call last):
+  File "/home/user/app/app.py", line 97, in chat_fn
+    async for stream_mode, chunk in graph.astream(
+  File "/usr/local/lib/python3.10/site-packages/langgraph/pregel/__init__.py", line 2677, in astream
+    raise GraphRecursionError(msg)
+langgraph.errors.GraphRecursionError: Recursion limit of 20 reached without hitting a stop condition. You can increase the limit by setting the `recursion_limit` config key.
+For troubleshooting, visit: https://python.langchain.com/docs/troubleshooting/errors/GRAPH_RECURSION_LIMIT
+2025-06-06 23:33:00:__main__:INFO: Starting the interface
+2025-06-06 23:33:05:__main__:INFO: Greeting added for new user via handle_initial_greeting_load.
+2025-06-06 23:33:13:__main__:INFO: Prompt: You are a helpful assistant.
+2025-06-06 23:33:35:__main__:ERROR: Exception occurred
+Traceback (most recent call last):
+  File "/home/user/app/app.py", line 97, in chat_fn
+    async for stream_mode, chunk in graph.astream(
+  File "/usr/local/lib/python3.10/site-packages/langgraph/pregel/__init__.py", line 2677, in astream
+    raise GraphRecursionError(msg)
+langgraph.errors.GraphRecursionError: Recursion limit of 20 reached without hitting a stop condition. You can increase the limit by setting the `recursion_limit` config key.
+For troubleshooting, visit: https://python.langchain.com/docs/troubleshooting/errors/GRAPH_RECURSION_LIMIT
+2025-06-06 23:38:07:__main__:INFO: Starting the interface
+2025-06-06 23:38:14:__main__:INFO: Greeting added for new user via handle_initial_greeting_load.
+2025-06-06 23:38:29:__main__:INFO: Prompt: You are a helpful assistant.
+2025-06-06 23:41:05:__main__:INFO: Prompt: You are a helpful assistant.
+2025-06-06 23:53:54:__main__:INFO: Starting the interface
+2025-06-06 23:54:01:__main__:INFO: Greeting added for new user via handle_initial_greeting_load.
+2025-06-06 23:54:13:__main__:INFO: Prompt: You are a helpful assistant.
+2025-06-06 23:54:14:__main__:ERROR: Exception occurred
+Traceback (most recent call last):
+  File "/home/user/app/app.py", line 97, in chat_fn
+    async for stream_mode, chunk in graph.astream(
+  File "/usr/local/lib/python3.10/site-packages/langgraph/pregel/__init__.py", line 2677, in astream
+    raise GraphRecursionError(msg)
+langgraph.errors.GraphRecursionError: Recursion limit of 20 reached without hitting a stop condition. You can increase the limit by setting the `recursion_limit` config key.
+For troubleshooting, visit: https://python.langchain.com/docs/troubleshooting/errors/GRAPH_RECURSION_LIMIT
+2025-06-06 23:54:27:__main__:INFO: Greeting added for new user via handle_initial_greeting_load.
+2025-06-06 23:57:18:__main__:INFO: Starting the interface
+2025-06-06 23:57:24:__main__:INFO: Greeting added for new user via handle_initial_greeting_load.
+2025-06-06 23:57:29:__main__:INFO: Prompt: You are a helpful assistant.
+2025-06-06 23:57:30:__main__:ERROR: Exception occurred
+Traceback (most recent call last):
+  File "/home/user/app/app.py", line 97, in chat_fn
+    async for stream_mode, chunk in graph.astream(
+  File "/usr/local/lib/python3.10/site-packages/langgraph/pregel/__init__.py", line 2677, in astream
+    raise GraphRecursionError(msg)
+langgraph.errors.GraphRecursionError: Recursion limit of 20 reached without hitting a stop condition. You can increase the limit by setting the `recursion_limit` config key.
+For troubleshooting, visit: https://python.langchain.com/docs/troubleshooting/errors/GRAPH_RECURSION_LIMIT
+2025-06-06 23:57:38:__main__:INFO: Prompt: You are a helpful assistant.
+2025-06-06 23:57:39:__main__:ERROR: Exception occurred
+Traceback (most recent call last):
+  File "/home/user/app/app.py", line 97, in chat_fn
+    async for stream_mode, chunk in graph.astream(
+  File "/usr/local/lib/python3.10/site-packages/langgraph/pregel/__init__.py", line 2677, in astream
+    raise GraphRecursionError(msg)
+langgraph.errors.GraphRecursionError: Recursion limit of 20 reached without hitting a stop condition. You can increase the limit by setting the `recursion_limit` config key.
+For troubleshooting, visit: https://python.langchain.com/docs/troubleshooting/errors/GRAPH_RECURSION_LIMIT

graph.py

@@ -129,124 +129,35 @@ class GraphProcessingState(BaseModel):
 
 
 
-# async def guidance_node(state: GraphProcessingState, config=None):
-#     print("\n--- Guidance Node (Debug via print) ---")
-
-#     print(f"Prompt: {state.prompt}")
-#     for message in state.messages:
-#         if isinstance(message, HumanMessage):
-#             print(f"Human: {message.content}")
-#         elif isinstance(message, AIMessage):
-#             if message.content:
-#                 if isinstance(message.content, list):
-#                     texts = [item.get('text', '') for item in message.content if isinstance(item, dict) and 'text' in item]
-#                     if texts:
-#                         print(f"AI: {' '.join(texts)}")
-#                 elif isinstance(message.content, str):
-#                     print(f"AI: {message.content}")
-#         elif isinstance(message, SystemMessage):
-#             print(f"System: {message.content}")
-#         elif isinstance(message, ToolMessage):
-#             print(f"Tool: {message.content}")
-
-#     print(f"Tools Enabled: {state.tools_enabled}")
-#     print(f"Search Enabled: {state.search_enabled}")
-#     print(f"Next Stage: {state.next_stage}")
 
 
-#     print(f"Brainstorming Complete: {state.brainstorming_complete}")
-    
-
-#     guidance_node.count = getattr(guidance_node, 'count', 0) + 1
-#     print('\nGuidance Node called count', guidance_node.count)
-#     print("\n--- End Guidance Node Debug ---")
-
-#     stage_order = ["brainstorming", "planning", "drawing", "product_searching", "purchasing"]
-#     completed = [stage for stage in stage_order if getattr(state, f"{stage}_complete", False)]
-#     incomplete = [stage for stage in stage_order if not getattr(state, f"{stage}_complete", False)]
-
-#     if not incomplete:
-#         print("All stages complete!")
-#         # Handle case where all stages are complete
-#         # You might want to return a message and end, or set proposed_next_stage to a special value
-#         ai_all_complete_msg = AIMessage(content="All DIY project stages are complete!")
-#         return {
-#             "messages": current_messages + [ai_all_complete_msg],
-#             "next_stage": "end_project", # Or None, or a final summary node
-#             "pending_approval_stage": None,
-#         }
-#     else:
-#         # THIS LINE DEFINES THE VARIABLE
-#         proposed_next_stage = incomplete[0]
-
-#     print(f"Proposed next stage: {proposed_next_stage}")
-
-#     status_summary = f"Completed stages: {completed}\nIncomplete stages: {incomplete}"
-
-#     guidance_prompt_text = (
-#         "You are the Guiding Assistant for a DIY project. Your primary responsibility is to determine the next logical step "
-#         "and then **obtain the user's explicit approval** before proceeding.\n\n"
-#         f"CURRENT PROJECT STATUS:\n{status_summary}\n\n"
-#         f"Based on the status, the most logical next stage appears to be: **'{proposed_next_stage}'**.\n\n"
-#         "YOUR TASK:\n"
-#         f"1. Formulate a clear and concise question for the user, asking if they agree to proceed to the **'{proposed_next_stage}'** stage. For example: 'It looks like '{proposed_next_stage}' is next. Shall we proceed with that?' or 'Are you ready to move on to {proposed_next_stage}?'\n"
-#         "2. **You MUST use the 'human_assistance' tool to ask this question.** Do not answer directly. Invoke the tool with your question.\n"
-#         "Example of tool usage (though you don't write this, you *call* the tool):\n"
-#         "Tool Call: human_assistance(query='The next stage is planning. Do you want to proceed with planning?')\n\n"
-#         "Consider the user's most recent message if it provides any preference."
-#     )
-
-#     if state.prompt:
-#         final_prompt = "\n".join([guidance_prompt_text, state.prompt, ASSISTANT_SYSTEM_PROMPT_BASE])
-#     else:
-#         final_prompt = "\n".join([guidance_prompt_text, ASSISTANT_SYSTEM_PROMPT_BASE])
-
-#     prompt = ChatPromptTemplate.from_messages(
-#         [
-#             ("system", final_prompt),
-#             MessagesPlaceholder(variable_name="messages"),
-#         ]
-#     )
-
-#     assistant_model = model.bind_tools([human_assistance])
-
-#     chain = prompt | assistant_model
+async def guidance_node(state: GraphProcessingState, config=None):
+    print("\n--- Guidance Node (Debug via print) ---") # Added a newline for clarity
 
-#     try:
-#         response = await chain.ainvoke({"messages": state.messages}, config=config)
 
-#         for msg in response:
-#             if isinstance(msg, HumanMessage):
-#                 print("Human:", msg.content)
-#             elif isinstance(msg, AIMessage):
-#                 if isinstance(msg.content, list):
-#                     ai_texts = [part.get("text", "") for part in msg.content if isinstance(part, dict)]
-#                     print("AI:", " ".join(ai_texts))
-#                 else:
-#                     print("AI:", msg.content)
+    print(f"Prompt: {state.prompt}")
+    for message in state.messages:
+        if isinstance(message, HumanMessage):
+            print(f"Human: {message.content}")
+        elif isinstance(message, AIMessage):
+            # Check if content is non-empty
+            if message.content:
+                # If content is a list (e.g., list of dicts), extract text
+                if isinstance(message.content, list):
+                    texts = [item.get('text', '') for item in message.content if isinstance(item, dict) and 'text' in item]
+                    if texts:
+                        print(f"AI: {' '.join(texts)}")
+                elif isinstance(message.content, str):
+                    print(f"AI: {message.content}")
+        elif isinstance(message, SystemMessage):
+            print(f"System: {message.content}")
+        elif isinstance(message, ToolMessage):
+            print(f"Tool: {message.content}")
 
-#         # Check for tool calls in the response
-#         if hasattr(response, "tool_calls"):
-#             for tool_call in response.tool_calls:
-#                 tool_name = tool_call['name']
-#                 if tool_name == "human_assistance":
-#                     query = tool_call['args']['query']
-#                     print(f"Human input needed: {query}")
-#                     # Handle human assistance tool call
-#                     # You can pause execution and wait for user input here
+    
 
-#         return {
-#             "messages": [response],
-#             "next_stage": incomplete[0] if incomplete else "brainstorming"
-#         }
-#     except Exception as e:
-#         print(f"Error in guidance node: {e}")
-#         return {
-#             "messages": [AIMessage(content="Error in guidance node.")],
-#             "next_stage": "brainstorming"
-#         }
 
-async def guidance_node(state: GraphProcessingState, config=None):
+    # Log boolean completion flags
     # Define the order of stages
     stage_order = ["brainstorming", "planning", "drawing", "product_searching", "purchasing"]
     
@@ -254,6 +165,10 @@ async def guidance_node(state: GraphProcessingState, config=None):
     completed = [stage for stage in stage_order if getattr(state, f"{stage}_complete", False)]
     incomplete = [stage for stage in stage_order if not getattr(state, f"{stage}_complete", False)]
     
+    print(f"Tools Enabled: {state.tools_enabled}")
+    print(f"Search Enabled: {state.search_enabled}")
+    print(f"Next Stage: {state.next_stage}")
+
     # Determine the next stage
     if not incomplete:
         # All stages are complete
@@ -272,7 +187,7 @@ async def guidance_node(state: GraphProcessingState, config=None):
         }
 
 async def brainstorming_node(state: GraphProcessingState, config=None):
-    print("\n--- Guidance Node (Debug via print) ---") # Added a newline for clarity
+    print("\n--- brainstorming Node (Debug via print) ---") # Added a newline for clarity
 
 
     print(f"Prompt: {state.prompt}")
@@ -296,16 +211,12 @@ async def brainstorming_node(state: GraphProcessingState, config=None):
 
     print(f"Tools Enabled: {state.tools_enabled}")
     print(f"Search Enabled: {state.search_enabled}")
-    print(f"Next Stage: {state.next_stage}")
 
+    print(f"Next Stage: {state.next_stage}")
 
     # Log boolean completion flags
-    print(f"Idea Complete: {state.idea_complete}")
-    print(f"Brainstorming Complete: {state.brainstorming_complete}")
-    print(f"Planning Complete: {state.planning_complete}")
-    print(f"Drawing Complete: {state.drawing_complete}")
-    print(f"Product Searching Complete: {state.product_searching_complete}")
-    print(f"Purchasing Complete: {state.purchasing_complete}")
+    print(f"is Brainstorming Complete: {state.brainstorming_complete}")
+
 
     # Check if model is available
     if not model:
@@ -321,78 +232,168 @@ async def brainstorming_node(state: GraphProcessingState, config=None):
     if not filtered_messages:
         filtered_messages.append(AIMessage(content="No valid messages provided."))
 
-    # Define the system prompt guiding the brainstorming assistant
-    brainstorming_system_prompt = ChatPromptTemplate.from_messages(
+    stage_order = ["brainstorming", "planning", "drawing", "product_searching", "purchasing"]
+    completed = [stage for stage in stage_order if getattr(state, f"{stage}_complete", False)]
+    incomplete = [stage for stage in stage_order if not getattr(state, f"{stage}_complete", False)]
+
+    if not incomplete:
+        print("All stages complete!")
+        # Handle case where all stages are complete
+        # You might want to return a message and end, or set proposed_next_stage to a special value
+        ai_all_complete_msg = AIMessage(content="All DIY project stages are complete!")
+        return {
+            "messages": current_messages + [ai_all_complete_msg],
+            "next_stage": "end_project", # Or None, or a final summary node
+            "pending_approval_stage": None,
+        }
+    else:
+        # THIS LINE DEFINES THE VARIABLE
+        proposed_next_stage = incomplete[0]
+
+    print(f"Proposed next stage: {proposed_next_stage}")
+
+    status_summary = f"Completed stages: {completed}\nIncomplete stages: {incomplete}"
+
+    guidance_prompt_text = (
+        "You are the Guiding Assistant for a DIY project. Your primary responsibility is to determine the next logical step "
+        "and then **obtain the user's explicit approval** before proceeding.\n\n"
+        f"CURRENT PROJECT STATUS:\n{status_summary}\n\n"
+        f"Based on the status, the most logical next stage appears to be: **'{proposed_next_stage}'**.\n\n"
+        "YOUR TASK:\n"
+        f"1. Formulate a clear and concise question for the user, asking if they agree to proceed to the **'{proposed_next_stage}'** stage. For example: 'It looks like '{proposed_next_stage}' is next. Shall we proceed with that?' or 'Are you ready to move on to {proposed_next_stage}?'\n"
+        "2. **You MUST use the 'human_assistance' tool to ask this question.** Do not answer directly. Invoke the tool with your question.\n"
+        "Example of tool usage (though you don't write this, you *call* the tool):\n"
+        "Tool Call: human_assistance(query='The next stage is planning. Do you want to proceed with planning?')\n\n"
+        "Consider the user's most recent message if it provides any preference."
+    )
+
+    
+    if state.prompt:
+        final_prompt = "\n".join([guidance_prompt_text, state.prompt, ASSISTANT_SYSTEM_PROMPT_BASE])
+    else:
+        final_prompt = "\n".join([guidance_prompt_text, ASSISTANT_SYSTEM_PROMPT_BASE])
+
+    prompt = ChatPromptTemplate.from_messages(
         [
-            ("system",
-             "You are a brainstorming assistant for DIY projects. Your goal is to help the user finalize a single, specific DIY project idea. "
-             "The project idea MUST satisfy these critical criteria:\n"
-             "1. Buildable by an average person with basic DIY skills.\n"
-             "2. Uses only materials and basic tools commonly available in general hardware stores, craft stores, or supermarkets worldwide. "
-             "(e.g., wood, screws, glue, paint, fabric, cardboard, basic hand tools like screwdrivers, hammers, saws, drills. "
-             "AVOID specialized electronic components, 3D printing, specific brand items not universally available, or complex machinery.)\n"
-             "3. The final product should be a tangible item.\n\n"
-             "Your interaction flow:\n"
-             "- Engage with the user to understand their interests or initial thoughts.\n"
-             "- Propose ideas or refine user's suggestions to meet the criteria.\n"
-             "- If an idea proposed by you or the user clearly meets all criteria and you believe it's a good final choice, respond ONLY with the exact phrase: "
-             "'IDEA FINALIZED: [Name of the Idea]'. Example: 'IDEA FINALIZED: Simple Wooden Spice Rack'. "
-             "Do not add any other text before or after this phrase if you use it.\n"
-             "- If you need more information from the user to refine an idea, or if their current suggestion doesn't meet the criteria, ask clarifying questions. "
-             "Guide them towards simpler, more accessible options.\n"
-             "- If you are stuck, the user's request is too vague for you to make progress towards a suitable idea, or they propose something clearly outside the "
-             "'universally available materials' constraint, and you need their direct input to clarify fundamental aspects, you should use the 'human_assistance' tool. "
-             "Frame your request for the human clearly. For example: 'To ensure the idea is simple enough, could you tell me what kind of tools you are comfortable using?' "
-             "or 'The idea of a custom electronic gadget is interesting, but finding parts globally is hard. Could we think of a non-electronic version, or what's the core function "
-             "you want from it that we could achieve with simpler materials?'"
-             ),
+            ("system", final_prompt),
             MessagesPlaceholder(variable_name="messages"),
         ]
     )
 
+    assistant_model = model.bind_tools([human_assistance])
+
+    # Define the system prompt guiding the brainstorming assistant
+    # brainstorming_system_prompt = ChatPromptTemplate.from_messages(
+    #     [
+    #         ("system",
+            #  "You are a brainstorming assistant for DIY projects. Your goal is to help the user finalize a single, specific DIY project idea. "
+            # "The project idea MUST satisfy these critical criteria:\n"
+            # "1. Buildable by an average person with basic DIY skills.\n"
+            # "2. Uses only materials and basic tools commonly available in general hardware stores, craft stores, or supermarkets worldwide. "
+            # "(e.g., wood, screws, glue, paint, fabric, cardboard, basic hand tools like screwdrivers, hammers, saws, drills. "
+            # "AVOID specialized electronic components, 3D printing, specific brand items not universally available, or complex machinery.)\n"
+            # "3. The final product should be a tangible item.\n\n"
+            # "Your interaction flow:\n"
+            # "- Engage with the user to understand their interests or initial thoughts.\n"
+            # "- Propose ideas or refine user's suggestions to meet the criteria.\n"
+            # "- If an idea proposed by you or the user clearly meets all criteria and you believe it's a good final choice, respond ONLY with the exact phrase: "
+            # "2. **You MUST use the 'human_assistance' tool to ask this question.** Do not answer directly. Invoke the tool with your question.\n"
+            # "Example of tool usage (though you don't write this, you *call* the tool):\n"
+            # "Tool Call: human_assistance(query='The next stage is planning. Do you want to proceed with planning?')\n\n"
+            # "Consider the user's most recent message if it provides any preference."
+            # "'IDEA FINALIZED: [Name of the Idea]'. Example: 'IDEA FINALIZED: Simple Wooden Spice Rack'. "
+            # "Do not add any other text before or after this phrase if you use it.\n"
+    #          ),
+    #         MessagesPlaceholder(variable_name="messages"),
+    #     ]
+    # )
+
     # Tools allowed for brainstorming
     node_tools = [human_assistance]
     if state.search_enabled and tavily_search_tool:  # only add search tool if enabled and initialized
         node_tools.append(tavily_search_tool)
 
     llm_with_tools = model.bind_tools(node_tools)
-    chain = brainstorming_system_prompt | llm_with_tools
+    chain = prompt | llm_with_tools
 
     # Pass filtered messages to the chain
-    response_message = await chain.ainvoke({"messages": filtered_messages}, config=config)
-
-    updates = {"messages": [response_message]}
-    print('response from brainstorm', response_message)
-
-    if isinstance(response_message, AIMessage) and response_message.content:
-        content = response_message.content.strip()
-
-        if content.startswith("IDEA FINALIZED:"):
-            print('final idea')
-            updates["brainstorming_complete"] = True
-            updates["tool_call_required"] = False
-            updates["loop_brainstorming"] = False
-            print(f"✅ Brainstorming complete! Idea: {content}")
-
-        elif getattr(response_message, "tool_calls", None):
-            print('tool call requested')
-            updates["tool_call_required"] = True
-            updates["loop_brainstorming"] = False
-            print(f"🛠️ Brainstorming node initiated tool call(s): {response_message.tool_calls}")
+    try:
+    
+        response = await chain.ainvoke({"messages": filtered_messages}, config=config)
+
+        for msg in response:
+            if isinstance(msg, HumanMessage):
+                print("Human:", msg.content)
+            elif isinstance(msg, AIMessage):
+                if isinstance(msg.content, list):
+                    ai_texts = [part.get("text", "") for part in msg.content if isinstance(part, dict)]
+                    print("AI:", " ".join(ai_texts))
+                else:
+                    print("AI:", msg.content)
+
+        if hasattr(response, "tool_calls"):
+            for tool_call in response.tool_calls:
+                tool_name = tool_call['name']
+                if tool_name == "human_assistance":
+                    query = tool_call['args']['query']
+                    print(f"Human input needed: {query}")
+
+        updates = {"messages": [response]}
+        print('response from brainstorm', response)
+
+        if isinstance(response, AIMessage) and response.content:
+            if isinstance(response.content, str):
+                content = response.content.strip()
+            elif isinstance(response.content, list):
+                texts = [item.get("text", "") for item in response.content if isinstance(item, dict)]
+                content = " ".join(texts).strip()
+            else:
+                content = str(response.content).strip()
+
+            if content.startswith("IDEA FINALIZED:"):
+                print('✅ final idea')
+                updates.update({
+                    "brainstorming_complete": True,
+                    "tool_call_required": False,
+                    "loop_brainstorming": False,
+                })
+
+            else:
+                tool_calls = getattr(response, "tool_calls", None)
+
+                if tool_calls:
+                    print('🛠️ tool call requested')
+                    updates.update({
+                        "tool_call_required": True,
+                        "loop_brainstorming": False,
+                    })
+
+                    for tool_call in tool_calls:
+                        if isinstance(tool_call, dict) and 'name' in tool_call and 'args' in tool_call:
+                            print(f"🔧 Tool Call (Dict): {tool_call.get('name')}, Args: {tool_call.get('args')}")
+                        else:
+                            print(f"🔧 Unknown tool_call format: {tool_call}")
+                else:
+                    print('💬 keep brainstorming')
+                    updates.update({
+                        "tool_call_required": False,
+                        "loop_brainstorming": True,
+                    })
+                    print(f"Brainstorming continues: {content}")
 
         else:
-            print('keep brainstorming')
+            # If no proper response, keep looping brainstorming
             updates["tool_call_required"] = False
             updates["loop_brainstorming"] = True
-            print(f"💬 Brainstorming node continues discussion: {content}")
 
-    else:
-        # If no proper response, keep looping brainstorming
-        updates["tool_call_required"] = False
-        updates["loop_brainstorming"] = True
-
-    print("\n--- End Brainstorming Node Debug ---")
-    return updates
+        print("\n--- End Brainstorming Node Debug ---")
+        return updates
+    except Exception as e:
+        print(f"Error in guidance node: {e}")
+        return {
+            "messages": [AIMessage(content="Error in guidance node.")],
+            "next_stage": "brainstorming"
+        }
 
 def brainstorming_routing(state: GraphProcessingState) -> str:
     print("\n--- brainstorming_routing Edge (Debug via print) ---") # Added a newline for clarity
@@ -422,96 +423,29 @@ def brainstorming_routing(state: GraphProcessingState) -> str:
         return "guidance_node"
 
 
-async def planning_node(state: GraphProcessingState, config=None):
-    # Define the system prompt for planning
-    planning_prompt = "Based on the user's idea, create a detailed step-by-step plan to build the DIY product."
 
-    # Combine the planning prompt with any existing prompts
-    if state.prompt:
-        final_prompt = "\n".join([planning_prompt, state.prompt, ASSISTANT_SYSTEM_PROMPT_BASE])
-    else:
-        final_prompt = "\n".join([planning_prompt, ASSISTANT_SYSTEM_PROMPT_BASE])
-
-    # Create the prompt template
-    prompt = ChatPromptTemplate.from_messages(
-        [
-            ("system", final_prompt),
-            MessagesPlaceholder(variable_name="messages"),
-        ]
-    )
-
-    # Bind tools if necessary
-    assistant_tools = []
-    if state.tools_enabled.get("download_website_text", True):
-        assistant_tools.append(download_website_text)
-    if search_enabled and state.tools_enabled.get("tavily_search_results_json", True):
-        assistant_tools.append(tavily_search_tool)
-    assistant_model = model.bind_tools(assistant_tools)
-
-    # Create the chain and invoke it
-    chain = prompt | assistant_model
-    response = await chain.ainvoke({"messages": state.messages}, config=config)
-
-    return {
-        "messages": response
-    }
-
-def custom_route_after_guidance(state: GraphProcessingState) -> Literal["execute_tools", "proceed_to_next_stage"]:
-    """
-    Checks the last message from the 'guidance_node'.
-    If it's an AIMessage with tool_calls, routes to 'execute_tools'.
-    Otherwise, routes to 'proceed_to_next_stage' (which could be a router itself
-    or directly to the state.next_stage node if it's set).
-    """
-    print("\n--- Custom Route After Guidance Condition ---")
-    messages = state['messages'] if 'messages' in state else []
-    if not messages:
-        print("No messages found in state. Defaulting to proceed_to_next_stage.")
-        return "proceed_to_next_stage" # Or handle as an error/specific state
-
-    last_message = messages[-1]
-    print(f"Last message type: {type(last_message)}")
-
-    if isinstance(last_message, AIMessage):
-        if hasattr(last_message, "tool_calls") and last_message.tool_calls:
-            # Ensure tool_calls is not None and not an empty list
-            print(f"AIMessage has tool_calls: {last_message.tool_calls}")
-            return "execute_tools"
-        else:
-            print("AIMessage, but no tool_calls or tool_calls is empty.")
-            # If next_stage was set by guidance_node (e.g. after approval), we'd use that.
-            # For simplicity here, we just assume a generic "proceed"
-            return "proceed_to_next_stage"
-    else:
-        print(f"Last message is not an AIMessage (type: {type(last_message)}). Proceeding to next stage.")
-        return "proceed_to_next_stage"
-
-    print("--- End Custom Route After Guidance Condition ---")
+# def route_brainstorming(state):
+#     if state.get("tool_call_required"):
+#         return "tools"
+#     else:
+#         return "guidance_node"
 
 def guidance_routing(state: GraphProcessingState) -> str:
 
-    print("\n--- Guidance Routing Edge (Debug via print) ---") # Added a newline for clarity
+    print("\n--- Guidance Routing  (Debug via print) ---") # Added a newline for clarity
     print(f"Prompt: {state.prompt}")
     # print(f"Message: {state.messages}")
     print(f"Tools Enabled: {state.tools_enabled}")
     print(f"Search Enabled: {state.search_enabled}")
     print(f"Next Stage: {state.next_stage}")
 
-
-    # Log boolean completion flags
-    print(f"Idea Complete: {state.idea_complete}")
-    print(f"Brainstorming Complete: {state.brainstorming_complete}")
-    print(f"Planning Complete: {state.planning_complete}")
-    print(f"Drawing Complete: {state.drawing_complete}")
-    print(f"Product Searching Complete: {state.product_searching_complete}")
-    print(f"Purchasing Complete: {state.purchasing_complete}")
-    print("--- End Guidance Node Debug ---") # Added for clarity
     
     next_stage = state.next_stage
     if next_stage == "brainstorming":
         return "brainstorming_node"
 
     elif next_stage == "planning":
+        print('\n may day may day may day may day may day')
     #     return "planning_node"
     # elif next_stage == "drawing":
     #     return "drawing_node"
@@ -531,16 +465,13 @@ def define_workflow() -> CompiledStateGraph:
 
     # Add nodes
     workflow.add_node("tools", DebugToolNode(tools))
-    workflow.add_node("planning_node", planning_node)
+    
     workflow.add_node("guidance_node", guidance_node)
     workflow.add_node("brainstorming_node", brainstorming_node)
+    # workflow.add_node("planning_node", planning_node)
 
     # Edges
-    workflow.add_edge("tools", "guidance_node")
-    # workflow.add_edge("planning_node", "guidance_node")
-    # workflow.add_edge("brainstorming_node", "guidance_node")
-    # workflow.add_edge("brainstorming_node", "tools")
-    workflow.add_edge("tools", "guidance_node")
+
     workflow.add_conditional_edges(
         "guidance_node",
         guidance_routing,
@@ -548,6 +479,15 @@ def define_workflow() -> CompiledStateGraph:
                 "brainstorming_node" : "brainstorming_node",
             }
     )
+
+    workflow.add_conditional_edges(
+        "brainstorming_node",
+        tools_condition,
+    )
+    workflow.add_edge("tools", "guidance_node")
+    workflow.add_edge("brainstorming_node", "guidance_node")
+
+
     # workflow.add_conditional_edges(
     # "guidance_node",  # The source node
     # custom_route_after_guidance,  # Your custom condition function
@@ -666,4 +606,158 @@ graph = define_workflow()
 
 
 
-  # 
+  # 
+
+
+#   async def planning_node(state: GraphProcessingState, config=None):
+#     # Define the system prompt for planning
+#     planning_prompt = "Based on the user's idea, create a detailed step-by-step plan to build the DIY product."
+
+#     # Combine the planning prompt with any existing prompts
+#     if state.prompt:
+#         final_prompt = "\n".join([planning_prompt, state.prompt, ASSISTANT_SYSTEM_PROMPT_BASE])
+#     else:
+#         final_prompt = "\n".join([planning_prompt, ASSISTANT_SYSTEM_PROMPT_BASE])
+
+#     # Create the prompt template
+#     prompt = ChatPromptTemplate.from_messages(
+#         [
+#             ("system", final_prompt),
+#             MessagesPlaceholder(variable_name="messages"),
+#         ]
+#     )
+
+#     # Bind tools if necessary
+#     assistant_tools = []
+#     if state.tools_enabled.get("download_website_text", True):
+#         assistant_tools.append(download_website_text)
+#     if search_enabled and state.tools_enabled.get("tavily_search_results_json", True):
+#         assistant_tools.append(tavily_search_tool)
+#     assistant_model = model.bind_tools(assistant_tools)
+
+#     # Create the chain and invoke it
+#     chain = prompt | assistant_model
+#     response = await chain.ainvoke({"messages": state.messages}, config=config)
+
+#     return {
+#         "messages": response
+#     }
+
+
+
+# async def guidance_node(state: GraphProcessingState, config=None):
+#     print("\n--- Guidance Node (Debug via print) ---")
+
+#     print(f"Prompt: {state.prompt}")
+#     for message in state.messages:
+#         if isinstance(message, HumanMessage):
+#             print(f"Human: {message.content}")
+#         elif isinstance(message, AIMessage):
+#             if message.content:
+#                 if isinstance(message.content, list):
+#                     texts = [item.get('text', '') for item in message.content if isinstance(item, dict) and 'text' in item]
+#                     if texts:
+#                         print(f"AI: {' '.join(texts)}")
+#                 elif isinstance(message.content, str):
+#                     print(f"AI: {message.content}")
+#         elif isinstance(message, SystemMessage):
+#             print(f"System: {message.content}")
+#         elif isinstance(message, ToolMessage):
+#             print(f"Tool: {message.content}")
+
+#     print(f"Tools Enabled: {state.tools_enabled}")
+#     print(f"Search Enabled: {state.search_enabled}")
+#     print(f"Next Stage: {state.next_stage}")
+
+
+#     print(f"Brainstorming Complete: {state.brainstorming_complete}")
+    
+
+#     guidance_node.count = getattr(guidance_node, 'count', 0) + 1
+#     print('\nGuidance Node called count', guidance_node.count)
+#     print("\n--- End Guidance Node Debug ---")
+
+#     stage_order = ["brainstorming", "planning", "drawing", "product_searching", "purchasing"]
+#     completed = [stage for stage in stage_order if getattr(state, f"{stage}_complete", False)]
+#     incomplete = [stage for stage in stage_order if not getattr(state, f"{stage}_complete", False)]
+
+#     if not incomplete:
+#         print("All stages complete!")
+#         # Handle case where all stages are complete
+#         # You might want to return a message and end, or set proposed_next_stage to a special value
+#         ai_all_complete_msg = AIMessage(content="All DIY project stages are complete!")
+#         return {
+#             "messages": current_messages + [ai_all_complete_msg],
+#             "next_stage": "end_project", # Or None, or a final summary node
+#             "pending_approval_stage": None,
+#         }
+#     else:
+#         # THIS LINE DEFINES THE VARIABLE
+#         proposed_next_stage = incomplete[0]
+
+#     print(f"Proposed next stage: {proposed_next_stage}")
+
+#     status_summary = f"Completed stages: {completed}\nIncomplete stages: {incomplete}"
+
+#     guidance_prompt_text = (
+#         "You are the Guiding Assistant for a DIY project. Your primary responsibility is to determine the next logical step "
+#         "and then **obtain the user's explicit approval** before proceeding.\n\n"
+#         f"CURRENT PROJECT STATUS:\n{status_summary}\n\n"
+#         f"Based on the status, the most logical next stage appears to be: **'{proposed_next_stage}'**.\n\n"
+#         "YOUR TASK:\n"
+#         f"1. Formulate a clear and concise question for the user, asking if they agree to proceed to the **'{proposed_next_stage}'** stage. For example: 'It looks like '{proposed_next_stage}' is next. Shall we proceed with that?' or 'Are you ready to move on to {proposed_next_stage}?'\n"
+#         "2. **You MUST use the 'human_assistance' tool to ask this question.** Do not answer directly. Invoke the tool with your question.\n"
+#         "Example of tool usage (though you don't write this, you *call* the tool):\n"
+#         "Tool Call: human_assistance(query='The next stage is planning. Do you want to proceed with planning?')\n\n"
+#         "Consider the user's most recent message if it provides any preference."
+#     )
+
+#     if state.prompt:
+#         final_prompt = "\n".join([guidance_prompt_text, state.prompt, ASSISTANT_SYSTEM_PROMPT_BASE])
+#     else:
+#         final_prompt = "\n".join([guidance_prompt_text, ASSISTANT_SYSTEM_PROMPT_BASE])
+
+#     prompt = ChatPromptTemplate.from_messages(
+#         [
+#             ("system", final_prompt),
+#             MessagesPlaceholder(variable_name="messages"),
+#         ]
+#     )
+
+#     assistant_model = model.bind_tools([human_assistance])
+
+#     chain = prompt | assistant_model
+
+#     try:
+#         response = await chain.ainvoke({"messages": state.messages}, config=config)
+
+#         for msg in response:
+#             if isinstance(msg, HumanMessage):
+#                 print("Human:", msg.content)
+#             elif isinstance(msg, AIMessage):
+#                 if isinstance(msg.content, list):
+#                     ai_texts = [part.get("text", "") for part in msg.content if isinstance(part, dict)]
+#                     print("AI:", " ".join(ai_texts))
+#                 else:
+#                     print("AI:", msg.content)
+
+#         # Check for tool calls in the response
+#         if hasattr(response, "tool_calls"):
+#             for tool_call in response.tool_calls:
+#                 tool_name = tool_call['name']
+#                 if tool_name == "human_assistance":
+#                     query = tool_call['args']['query']
+#                     print(f"Human input needed: {query}")
+#                     # Handle human assistance tool call
+#                     # You can pause execution and wait for user input here
+
+#         return {
+#             "messages": [response],
+#             "next_stage": incomplete[0] if incomplete else "brainstorming"
+#         }
+#     except Exception as e:
+#         print(f"Error in guidance node: {e}")
+#         return {
+#             "messages": [AIMessage(content="Error in guidance node.")],
+#             "next_stage": "brainstorming"
+#         }