toool called debug print

app.log

@@ -49913,3 +49913,72 @@ For troubleshooting, visit: https://python.langchain.com/docs/troubleshooting/er
 2025-06-06 14:43:36:__main__:INFO: Greeting added for new user via handle_initial_greeting_load.
 2025-06-06 15:19:39:__main__:INFO: Starting the interface
 2025-06-06 15:20:37:__main__:INFO: Starting the interface
+2025-06-06 15:32:33:__main__:INFO: Starting the interface
+2025-06-06 15:34:41:__main__:INFO: Starting the interface
+2025-06-06 15:35:07:__main__:INFO: Starting the interface
+2025-06-06 15:35:26:__main__:INFO: Greeting added for new user via handle_initial_greeting_load.
+2025-06-06 15:35:39:__main__:INFO: Prompt: You are a helpful assistant.
+2025-06-06 15:35:41:__main__:ERROR: Exception occurred
+Traceback (most recent call last):
+  File "/home/user/app/app.py", line 85, 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 248, in brainstorming_node
+    chain = brainstorming_system_prompt_template | llm_with_tools
+NameError: name 'brainstorming_system_prompt_template' is not defined. Did you mean: 'brainstorming_system_prompt'?
+2025-06-06 15:35:59:__main__:INFO: Starting the interface
+2025-06-06 15:36:04:__main__:INFO: Greeting added for new user via handle_initial_greeting_load.
+2025-06-06 15:36:10:__main__:INFO: Prompt: You are a helpful assistant.
+2025-06-06 15:36:15:__main__:ERROR: Exception occurred
+Traceback (most recent call last):
+  File "/home/user/app/app.py", line 85, 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 248, in brainstorming_node
+    chain = brainstorming_system_prompt_template | llm_with_tools
+NameError: name 'brainstorming_system_prompt_template' is not defined. Did you mean: 'brainstorming_system_prompt'?
+2025-06-06 15:36:35:__main__:INFO: Greeting added for new user via handle_initial_greeting_load.
+2025-06-06 15:38:34:__main__:INFO: Starting the interface
+2025-06-06 15:38:40:__main__:INFO: Greeting added for new user via handle_initial_greeting_load.
+2025-06-06 15:38:45:__main__:INFO: Prompt: You are a helpful assistant.
+2025-06-06 15:39:40:__main__:ERROR: Exception occurred
+Traceback (most recent call last):
+  File "/home/user/app/app.py", line 85, 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 15:55:25:__main__:INFO: Starting the interface
+2025-06-06 15:55:30:__main__:INFO: Greeting added for new user via handle_initial_greeting_load.
+2025-06-06 15:55:53:__main__:INFO: Prompt: You are a helpful assistant.
+2025-06-06 15:58:00:__main__:ERROR: Exception occurred
+Traceback (most recent call last):
+  File "/home/user/app/app.py", line 85, 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

app.py

@@ -691,10 +691,8 @@ if __name__ == "__main__":
         #     ],
         #     # queue=False # Consider if queueing is needed or affects load order for this
         # )
-        @demo.load(inputs=[browser_state], outputs=[username, password])
-        def load_browser_state(data):
-            return data[0], data[1]
-            
+
+
         @app.load( # Or demo.load
             inputs=[
                 is_new_user_for_greeting,

graph.py

@@ -104,6 +104,9 @@ class GraphProcessingState(BaseModel):
     search_enabled: bool = Field(default=True, description="Whether to enable search tools")
     next_stage: str = Field(default="", description="The next stage to execute, decided by the guidance node.")
 
+    tool_call_required: bool = Field(default=False, description="Whether a tool should be called from brainstorming.")
+    loop_brainstorming: bool = Field(default=False, description="Whether to loop back to brainstorming for further iteration.")
+
     # Completion flags for each stage
     idea_complete: bool = Field(default=False)
     brainstorming_complete: bool = Field(default=False)
@@ -213,66 +216,106 @@ async def guidance_node(state: GraphProcessingState, config=None):
     }
 
 async def brainstorming_node(state: GraphProcessingState, config=None):
-    print("\n--- Brainstorming Node ---")
+    print("\n--- Brainstorming Node (Debug) ---")
+
+    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"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}")
+
     if not model:
         return {"messages": [AIMessage(content="Model not available for brainstorming.")]}
 
-    # Define the system prompt for brainstorming
-    # This prompt guides the LLM on its role, constraints, and how to signal completion or use tools.
+    # 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"
+             "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?'"
+             "- 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?'"
              ),
             MessagesPlaceholder(variable_name="messages"),
         ]
     )
 
-    # Bind tools that this node can use
-    # For brainstorming, human_assistance is key. Search might also be useful.
+    # Tools allowed for brainstorming
     node_tools = [human_assistance]
-    if state.search_enabled and tavily_search_tool: # Check if tavily_search_tool was initialized
+    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_template | llm_with_tools
-
-    # Get the current messages from the state
-    current_messages = state.messages
-    # Log current messages for debugging
-    # print("Messages sent to brainstorming LLM:")
-    # for msg in current_messages:
-    #     print(f"  {msg.type}: {msg.content}")
+    chain = brainstorming_system_prompt | llm_with_tools
 
-    response_message = await chain.ainvoke({"messages": current_messages}, config=config)
-    # print(f"Brainstorming LLM raw response: {response_message}")
+    # Pass current messages from the state to the chain
+    response_message = await chain.ainvoke({"messages": state.messages}, config=config)
 
+    updates = {"messages": [response_message]}
 
-    updates = {"messages": [response_message]} # Add the AI's response to the history
-
-    # Check for the finalization signal in the AI's response content
     if isinstance(response_message, AIMessage) and response_message.content:
-        if response_message.content.startswith("IDEA FINALIZED:"):
+        content = response_message.content.strip()
+
+        if content.startswith("IDEA FINALIZED:"):
             updates["brainstorming_complete"] = True
-            # Optionally, extract the idea name and store it if needed elsewhere in the state
-            # idea_name = response_message.content.replace("IDEA FINALIZED:", "").strip()
-            # updates["finalized_idea_name"] = idea_name # If you add this to GraphProcessingState
-            print(f"✅ Brainstorming complete! Idea: {response_message.content}")
-        elif response_message.tool_calls:
+            updates["tool_call_required"] = False
+            updates["loop_brainstorming"] = False
+            print(f"✅ Brainstorming complete! Idea: {content}")
+
+        elif getattr(response_message, "tool_calls", None):
+            updates["tool_call_required"] = True
+            updates["loop_brainstorming"] = False
             print(f"🛠️ Brainstorming node initiated tool call(s): {response_message.tool_calls}")
+
         else:
-            print(f"💬 Brainstorming node continues discussion: {response_message.content}")
+            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
 
@@ -310,6 +353,32 @@ async def planning_node(state: GraphProcessingState, config=None):
         "messages": response
     }
 
+def brainstorming_routing(state: GraphProcessingState) -> str:
+    print("\n--- brainstorming_routing Edge (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
+    if state.tool_call_required:
+        print('calling tools for brainstorming')
+        return "tools"
+    elif state.loop_brainstorming:
+        print('returning back to brainstorming at the route')
+        return "brainstorming_node"
+    else:
+        print('all good in brainstorming route going back to guidance')
+        return "guidance_node"
 
 def guidance_routing(state: GraphProcessingState) -> str:
 
@@ -358,29 +427,15 @@ def define_workflow() -> CompiledStateGraph:
     workflow.add_node("guidance_node", guidance_node)
     workflow.add_node("brainstorming_node", brainstorming_node)
 
-
-    # workflow.add_node("chatbot", chatbot)
-
     # Edges
     workflow.add_edge("tools", "guidance_node")
-    # workflow.add_edge("planning_node", "assistant_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", "brainstorming_node")
 
-
-
-
-    # workflow.add_conditional_edges(
-    #     "chatbot",
-    #     tools_condition,
-    # )
-
-    # workflow.add_edge("tools", "chatbot")
-    # workflow.add_edge(START, "chatbot")
-
-    # Conditional routing   
-    # workflow.add_conditional_edges("assistant_node", assistant_routing)
     workflow.add_conditional_edges("guidance_node", guidance_routing)
+    workflow.add_conditional_edges("brainstorming_node", brainstorming_routing)
 
     # # Set end nodes
     workflow.set_entry_point("guidance_node")