Workaround: "auto" tool choice requires --enable-auto-tool-choice and --tool-call-parser to be set.

[conjureup96]

I am running a small testbed of Nvidia Sparks plugged into a Mikrotik CRS812-DDQ switch ... with GPUStack coordinating operation of the nodes and running the various models. It all works wonderfully, and I have different applications accessing the GPUStack API (OpenAI-Compatible).

I decided to test the Openagents Docker image, and it spun up without any issues. After opening a shell (/bin/bash) and making a slight mod to the llm_agent.py example file (pointing to the local API) when comments are posted in the guest/general channel I see the agent_runner trying to open sessions via the API.

However, it appears "tool_choice":"auto" is being sent from openagents to the API (packet capture of the interaction also reveals a bunch of extra/unrelated agentworld KVPs - I have no idea where that's coming from). The API then shoots back a nastigram saying the "auto" tool choice requires --enable-auto-tool-choice and --tool-call-parser to be set. The openagent logs show this result as ...

{"error":{"message":""auto" tool choice requires --enable-auto-tool-choice and --tool-call-parser to be set","type":"BadRequestError","param":null,"code":400}}

In the Docs I see the section "LLM Tools and Capabilities: Function Calling and Tool Use", where ToolEnabledAgent(WorkerAgent) is called. Is that the approach that should be taken to interact with a tool-enabled API ... even when my initial tests won't involve tools at all? (I'm doing a simple proof-of-concept where four different agents and a number of humans can interact in a chat channel)

THANKS for any suggestions the group may have!

If you need more details about the capture, logs, or tweaked llm_agent.py just let me know. But this is more of a general question about how to either bypass "tool_choice" being sent to the API or do the most minimal tool implementation in order to create a chat channel. BTW, I'm NOT a coder (but can usually reverse engineer how something works ... so if no one has suggestions I can drill into the ToolEnabledAgent() code to see if I can figure it out!) :P

[linear]

OADEV-35

[conjureup96]

P.S. That "Function Calling and Tool Use" part of the Documentation I mentioned is this one (which may not be related at all ... or it could be exactly what I need to delve into) ...

https://openagents.org/docs/en/python-interface/work-with-llm-based-agents#llm-tools-and-capabilities

[QuanCheng-QC]

Thanks for the detailed report — this is very helpful.

The tool_choice: "auto" behavior you're seeing is not strictly required for basic chat scenarios. It is currently being sent because the example agent is based on ToolEnabledAgent, which implicitly enables tool-calling support.

However, for OpenAI-compatible backends (e.g., vLLM, NIM, GPUStack-based servers), "auto" tool choice requires server-side flags such as:

--enable-auto-tool-choice
--tool-call-parser

Since your PoC does not involve tools at all, there are two minimal approaches:

Option 1 (Recommended for simple chat setups)

Use a plain WorkerAgent instead of ToolEnabledAgent, and ensure no tools are registered. This prevents tools and tool_choice from being sent entirely and improves compatibility with strict OpenAI-compatible APIs.

Option 2

If tool support is desired, start the backend with:
--enable-auto-tool-choice
--tool-call-parser <parser_name>

But for multi-agent chat without tools, Option 1 is cleaner and avoids unnecessary backend requirements.

We may consider improving the default behavior so that tool_choice is only sent when tools are actually registered, to make the framework more compatible with minimal OpenAI-style backends.

Let me know if you'd like a minimal example agent that avoids tool mode entirely.

[conjureup96]

Hi QuanCheng, The scripts I used were based on /network/agents/llm_agent.py which already invokes the WorkerAgent ... class LLMAgent (WorkerAgent) After experimenting with polling vs event-driven approaches, it seems like something in the event-driven code enables tools. I did end up enabling the server-side flags and got past the initial tool hurdle ... and I also disabled the agentworld mod because that was filling the API calls with a ton of extraneous garbage. The interesting thing now is I see the model processing the info and the results coming back to OpenAgents, however they do NOT show up in the channel. My AIs think it's because the responses are arriving as tool output when no tools have been defined in the script to process that output. Here's an example exchange ... # python simple_claude.py 🔄 AgentClient.send_event called for agent claude Event: system.list_mods to system:system Available mod adapters: [] Connector: GRPCNetworkConnector(agent_id=claude, host=localhost, port=8600, connected=True) Connector is_connected: True ╔═════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════╗ ║ 📤 SENDING EVENT ║ ╠═════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════╣ ║ Event: system.list_mods ║ ║ Source: claude ║ ║ Target: system:system ║ ║ ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────── ║ ║ { ║ ║ "agent_id": "claude" ║ ║ } ║ ╚═════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════╝ ✅ EVENT SENT: system.list_mods Success: True Message: Mod list retrieved successfully Response data keys: ['type', 'command', 'mods'] Claude (LLM Agent) is running! Press Ctrl+C to stop. Send a message in the 'general' channel to see it respond. ╔═════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════╗ ║ 📥 RECEIVED EVENT ║ ╠═════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════╣ ║ Event: thread.channel_message.notification ║ ║ Source: admin ║ ║ Target: claude ║ ║ ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────── ║ ║ { ║ ║ "channel": "general", ║ ║ "content": { ║ ║ "text": "Hello Claude, just doing another test. Do you see this message?" ║ ║ }, ║ ║ "message_type": "channel_message", ║ ║ "original_event_id": "admin_1773026390619_ljj0eiw2q" ║ ║ } ║ ╚═════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════╝ 🔧 AGENT_RUNNER: Calling react method for event thread.channel_message.notification ╔═════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════╗ ║ 🎯 STARTING ORCHESTRATION ║ ╠═════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════╣ ║ Thread: thread:thread.channel_message ║ ║ Event: thread.channel_message.notification ║ ╚═════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════╝ ╔═════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════╗ ║ 🔧 AGENT TOOL CALL ║ ╠═════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════╣ ║ Tool: send_text_message ║ ║ Args: "{\"text\": \"Hello back! Yes, I can see your test message and am responding to it.\", \"target_agent_id\": \"admin\"}" ║ ╚═════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════╝ ╔═════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════╗ ║ 🔧 AGENT TOOL CALL ║ ╠═════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════╣ ║ Tool: send_text_message ║ ║ Args: {"text": "Test acknowledged - receiving messages works.", "target_agent_id": "admin"} ║ ╚═════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════╝ ╔═════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════╗ ║ 🔧 AGENT TOOL CALL ║ ╠═════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════╣ ║ Tool: broadcast_text_message ║ ║ Args: {"text": "This is a successful broadcast from Claude in response to the test message."} ║ ╚═════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════╝ ✅ AGENT RESPONSE COMPLETED: 7a226c50 Processing time: 137.20s 🤖 LLM API call detected (response time > 1s) Message marked as processed I think the server-side tool parser on GPUStack slows down the initial response. The following lists what GPUStack will accept for --tool-call-parser { deepseek_v3,deepseek_v31,glm45,granite-20b-fc,granite,hermes,hunyuan_a13b,internlm,jamba,kimi_k2,llama4_pythonic,llama4_json, llama3_json,longcat,minimax,mistral,openai,phi4_mini_json,pythonic,qwen3_coder,qwen3_xml,seed_oss,step3,xlam } The relevant parts of the script seem to be ... async def react(self, context: EventContext): """React to incoming messages using LLM.""" event = context.incoming_event # Skip our own messages if event.source_id == self.agent_id: return # Get message content from payload content = event.payload.get("content") or event.payload.get("text") or " " if not content: return # Use run_agent to generate LLM response try: trajectory = await self.run_agent( context=context, disable_mcp=False, disable_mods=False, instruction=f"Respond to: {content}.", ) note: have tried more explicit instructions to use send_channel_message sted directly back to user, etc, with no impact whatsoever some of the AIs (Gemini3, Claude) think tool defs are needed, something like LLMAgent.tools = [send_channel_message] # Extract the response from the trajectory response = None for action in trajectory.actions: if action.payload and action.payload.get("response"): response = action.payload["response"] break if not response: response = "I'm sorry, I couldn't generate a response." except Exception as e: print(f"LLM error: {e}") response = f"Sorry, I encountered an error: {str(e)[:50]}" # Send the response to the channel messaging = self.client.mod_adapters.get("openagents.mods.workspace.messaging") if messaging: channel = event.payload.get("channel") or "general" note: some of the AIs think this line is a problem (is it?) await messaging.send_channel_message( channel=channel, text=response ) print(f"Responded to {event.source_id}: {response[:50]}...") If you have suggestions on how to debug lack of results appearing in the #general channel, that would be very useful. You also mentioned that there's an approach to disabling tools, but everything I've tried with WorkerAgent and event-based automagically turns tools on. And I prefer that event-driven approach over polling. Sorry for the lagged response ... it took me awhile to delve deeper into the code and observe the messages sent back-n-forth using tcpdump/wireshark. It's very clear to me that the model IS responding just fine, albeit delayed due to the server-side parser (so it's a different problem than the initial one where the API was totally rejecting the session when server-side settings were missing). Regards, Chris aka ConjureUp96

On 2026-03-02 21:16, QuanCheng wrote: QuanCheng-QC left a comment (openagents-org/openagents#285) [1] Thanks for the detailed report -- this is very helpful. The tool_choice: "auto" behavior you're seeing is not strictly required for basic chat scenarios. It is currently being sent because the example agent is based on ToolEnabledAgent, which implicitly enables tool-calling support. However, for OpenAI-compatible backends (e.g., vLLM, NIM, GPUStack-based servers), "auto" tool choice requires server-side flags such as: --enable-auto-tool-choice --tool-call-parser Since your PoC does not involve tools at all, there are two minimal approaches: OPTION 1 (RECOMMENDED FOR SIMPLE CHAT SETUPS) Use a plain WorkerAgent instead of ToolEnabledAgent, and ensure no tools are registered. This prevents tools and tool_choice from being sent entirely and improves compatibility with strict OpenAI-compatible APIs. OPTION 2 If tool support is desired, start the backend with: --enable-auto-tool-choice --tool-call-parser <parser_name> But for multi-agent chat without tools, Option 1 is cleaner and avoids unnecessary backend requirements. We may consider improving the default behavior so that tool_choice is only sent when tools are actually registered, to make the framework more compatible with minimal OpenAI-style backends. Let me know if you'd like a minimal example agent that avoids tool mode entirely. -- Reply to this email directly, view it on GitHub [1], or unsubscribe [2]. You are receiving this because you authored the thread.Message ID: ***@***.***>

Links: ------ [1] #285 (comment) [2] https://github.com/notifications/unsubscribe-auth/B3DGO4RE4INRJM2V2QGRFMD4OZMA5AVCNFSM6AAAAACVNPZ7N6VHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMZTSOBYGU2DMNRWGM

[QuanCheng-QC]

Thanks for digging into this and sharing the traces — this is very helpful.

From the logs you posted, the LLM is clearly producing a response, but it is returning it as tool calls:

send_text_message
send_text_message
broadcast_text_message

So the issue no longer appears to be on the backend side (GPUStack / tool parser). The model is responding and the orchestration layer is detecting the tool calls correctly.

The likely problem is that the example script is still trying to extract a plain text response from:

action.payload["response"]

However, when the model emits tool calls, the trajectory may not contain a final response field at all. Instead, the actions represent tool invocations.

In that case the code path:

if not response:
    response = "I'm sorry, I couldn't generate a response."

will be triggered even though the model already produced a valid tool-based response.

A few things I would suggest checking:

1. Print the entire trajectory.actions structure
   Instead of only looking for payload["response"], dump each action's payload/result so we can confirm whether the trajectory contains tool calls, tool results, or a final assistant text.

2. Temporarily disable mods/tools for comparison

   Try running the same flow with:

   disable_mods=True
   disable_mcp=True
   

   If the model then returns plain text instead of tool calls, that would confirm that the event-driven run_agent() path is implicitly enabling tool capabilities.

3. Normalize message content extraction

   In the sample payload:

   "content": {"text": "..."}
   

   so this line may pass a dict into the instruction:

   content = event.payload.get("content")
   

   It may be safer to extract content["text"] explicitly.

4. Add logging around send_channel_message()

   It would also help to confirm whether send_channel_message() is actually being executed successfully or returning an error.

My current hypothesis is that the script is mixing two output paths:

• plain text response extraction
• tool-call-driven messaging

and the event-driven orchestration path is favoring the latter.

If useful, we can also provide a minimal event-driven example that forces plain text replies (no tool usage) to isolate the behavior further.

[conjureup96]

As requested, here is the entire react/trajectory section ... I tried setting the "disable" options to True earlier but still see Tool responses being returned. That is additional support for what you mention in your second point (that the event context seems to enable tools even when they are not needed). I even tried changing the Instructions to the AI to return results using different text formats. For example, asking it to return as a "send_channel_message" does result in that format (but there doesn't seem to be any handler that can parse that result) ...     async def react(self, context: EventContext):         """React to incoming messages using LLM."""         event = context.incoming_event         # Skip our own messages         if event.source_id == self.agent_id:             return         # Get message content from payload         content = event.payload.get("content") or event.payload.get("text") or ""         if not content:             return         # Use run_agent to generate LLM response         try:             trajectory = await self.run_agent(                 context=context,                 disable_mcp=True,                 disable_mods=True,                 instruction=f"Respond to: {content}. Use send_channel_message NOT reply_channel_message.",             )             # Extract the response from the trajectory             response = None             for action in trajectory.actions:                 if action.payload and action.payload.get("response"):                     response = action.payload["response"]                     break             if not response:                 response = "I'm sorry, I couldn't generate a response."         except Exception as e:             print(f"LLM error: {e}")             response = f"Sorry, I encountered an error: {str(e)[:50]}"         # Send the response to the channel         messaging = self.client.mod_adapters.get("openagents.mods.workspace.messaging")         if messaging:             channel = event.payload.get("channel") or "general"             await messaging.send_channel_message(                 channel=channel,                 text=response             )             print(f"Responded to {event.source_id}: {response[:50]}...") The returned response is ... ╔════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════╗ ║ 🔧 AGENT TOOL CALL     ║ ╠════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════╣ ║ Tool: *send_channel_message*     ║ ║ Args: {"channel": "general", "content": "Hello back! Yes, I'm here and ready to help. What can I do for you today?"}               ║ ╚════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════╝ Here are what the above exchanges look like from the perspective of Wireshark ... POST /v1/chat/completions HTTP/1.1 Host: 192.168.2.201:1080 Accept-Encoding: gzip, deflate Connection: keep-alive Accept: application/json Content-Type: application/json User-Agent: AsyncOpenAI/Python 2.26.0 X-Stainless-Lang: python X-Stainless-Package-Version: 2.26.0 X-Stainless-OS: Linux X-Stainless-Arch: arm64 X-Stainless-Runtime: CPython X-Stainless-Runtime-Version: 3.12.13 Authorization: Bearer gpustack_snipsnipsnip X-Stainless-Async: async:asyncio x-stainless-retry-count: 0 x-stainless-read-timeout: 600 Content-Length: 2418 {"messages":[{"role":"system","content":"You are Claude, a helpful Agent in an OpenAgents network.\n Respond to the user's message in a helpful and friendly way."},{"role":"user","content":"<conversation>\n <threads>\n \n <thread id=\"thread:thread.channel_message\">\n \n <message sender=\"admin\" event_id=\"32679622-72d3-4253-93fa-826b16ec916c\">\n \n <content>{'channel': 'general', 'content': {'text': 'Test 200 ... are you there Claude?'}, 'message_type': 'channel_message', 'original_event_id': 'admin_1773775769517_t5y3bdujl'}</content>\n \n </message>\n \n </thread>\n \n </threads>\n\n <current_interaction>\n <incoming_thread_id>thread:thread.channel_message</incoming_thread_id>\n <incoming_message sender=\"admin\" event_id=\"32679622-72d3-4253-93fa-826b16ec916c\">\n \n <content>{'channel': 'general', 'content': {'text': 'Test 200 ... are you there Claude?'}, 'message_type': 'channel_message', 'original_event_id': 'admin_1773775769517_t5y3bdujl'}</content>\n \n </incoming_message>\n </current_interaction>\n</conversation>\n\nPlease respond to the incoming message based on the context provided. You have access to tools that you can use if needed.\n\nIMPORTANT: When replying to messages, use the message's event_id (not the thread_id) as the reply_to_id parameter.\n- To reply to a channel message: use reply_channel_message with the message's event_id\n- To reply to a direct message: use reply_direct_message with the message's event_id\n- Thread ID is for context only, always use event_id for replies\n\nIn each step, you MUST either:\n1. Call a tool to perform an action, or\n2. Use the finish tool when you've completed all necessary actions.\n\nIf you don't need to use any tools, use the finish tool directly.\n\nRespond to: {'text': 'Test 200 ... are you there Claude?'}. Use send_channel_message NOT reply_channel_message."}],"model":"Claude-4.5-Opus","tool_choice":"auto","tools":[{"type":"function","function":{"name":"finish","description":"Use this tool when you have completed all necessary actions and don't need to do anything else.","parameters":{"type":"object","properties":{"reason":{"type":"string","description":"Reason for finishing the action chain."}},"required":["reason"]}}}]} HTTP/1.1 200 OK date: Tue, 17 Mar 2026 19:29:31 GMT,Tue, 17 Mar 2026 19:29:31 GMT server: istio-envoy content-type: application/json req-cost-time: 16070 req-arrive-time: 1773775771255 resp-start-time: 1773775787326 x-envoy-upstream-service-time: 16018 content-encoding: gzip vary: Accept-Encoding transfer-encoding: chunked {"id":"chatcmpl-caa0ccb0-0f22-44bd-aea3-087e701ed3ca","object":"chat.completion","created":1773775771,"model":"Claude-4.5-Opus","choices":[{"index":0,"message":{"role":"assistant","content":"<think>\nI need to respond to the message \"Test 200 ... are you there Claude?\" in the general channel.\n\nSince this is the first message in the conversation and it's a general channel message, I should use the send_channel_message tool to post my response.\n\nThe user is asking if I'm here, so I'll confirm my presence and ask them what they need help with.\n</think>\n\n","refusal":null,"annotations":null,"audio":null,"function_call":null,"tool_calls":[{"id":"chatcmpl-tool-707d958cf2ba424bb1d6d4cec1ad7d35","type":"function","function":{"name":"send_channel_message","arguments":"{\"channel\": \"general\", \"content\": \"Hello! Yes, I'm here and ready to help. What can I do for you today?\"}"}}],"reasoning_content":null},"logprobs":null,"finish_reason":"tool_calls","stop_reason":null,"token_ids":null}],"service_tier":null,"system_fingerprint":null,"usage":{"prompt_tokens":679,"total_tokens":807,"completion_tokens":128,"prompt_tokens_details":null,"tokens_per_second":9769.23,"time_to_first_token_ms":16070,"time_per_output_token_ms":0.1},"prompt_logprobs":null,"prompt_token_ids":null,"kv_transfer_params":null} POST /v1/chat/completions HTTP/1.1 Host: 192.168.2.201:1080 Accept-Encoding: gzip, deflate Connection: keep-alive Accept: application/json Content-Type: application/json User-Agent: AsyncOpenAI/Python 2.26.0 X-Stainless-Lang: python X-Stainless-Package-Version: 2.26.0 X-Stainless-OS: Linux X-Stainless-Arch: arm64 X-Stainless-Runtime: CPython X-Stainless-Runtime-Version: 3.12.13 Authorization: Bearer gpustack_snipsnipsip X-Stainless-Async: async:asyncio x-stainless-retry-count: 0 x-stainless-read-timeout: 600 Content-Length: 3217 {"messages":[{"role":"system","content":"You are Claude, a helpful Agent in an OpenAgents network.\n Respond to the user's message in a helpful and friendly way."},{"role":"user","content":"<conversation>\n <threads>\n \n <thread id=\"thread:thread.channel_message\">\n \n <message sender=\"admin\" event_id=\"32679622-72d3-4253-93fa-826b16ec916c\">\n \n <content>{'channel': 'general', 'content': {'text': 'Test 200 ... are you there Claude?'}, 'message_type': 'channel_message', 'original_event_id': 'admin_1773775769517_t5y3bdujl'}</content>\n \n </message>\n \n </thread>\n \n </threads>\n\n <current_interaction>\n <incoming_thread_id>thread:thread.channel_message</incoming_thread_id>\n <incoming_message sender=\"admin\" event_id=\"32679622-72d3-4253-93fa-826b16ec916c\">\n \n <content>{'channel': 'general', 'content': {'text': 'Test 200 ... are you there Claude?'}, 'message_type': 'channel_message', 'original_event_id': 'admin_1773775769517_t5y3bdujl'}</content>\n \n </incoming_message>\n </current_interaction>\n</conversation>\n\nPlease respond to the incoming message based on the context provided. You have access to tools that you can use if needed.\n\nIMPORTANT: When replying to messages, use the message's event_id (not the thread_id) as the reply_to_id parameter.\n- To reply to a channel message: use reply_channel_message with the message's event_id\n- To reply to a direct message: use reply_direct_message with the message's event_id\n- Thread ID is for context only, always use event_id for replies\n\nIn each step, you MUST either:\n1. Call a tool to perform an action, or\n2. Use the finish tool when you've completed all necessary actions.\n\nIf you don't need to use any tools, use the finish tool directly.\n\nRespond to: {'text': 'Test 200 ... are you there Claude?'}. Use send_channel_message NOT reply_channel_message."},{"role":"assistant","tool_calls":[{"id":"chatcmpl-tool-707d958cf2ba424bb1d6d4cec1ad7d35","type":"function","function":{"name":"send_channel_message","arguments":"{\"channel\": \"general\", \"content\": \"Hello! Yes, I'm here and ready to help. What can I do for you today?\"}"}}],"content":"<think>\nI need to respond to the message \"Test 200 ... are you there Claude?\" in the general channel.\n\nSince this is the first message in the conversation and it's a general channel message, I should use the send_channel_message tool to post my response.\n\nThe user is asking if I'm here, so I'll confirm my presence and ask them what they need help with.\n</think>\n\n"},{"role":"tool","tool_call_id":"chatcmpl-tool-707d958cf2ba424bb1d6d4cec1ad7d35","content":"Tool 'send_channel_message' not found"}],"model":"Claude-4.5-Opus","tool_choice":"auto","tools":[{"type":"function","function":{"name":"finish","description":"Use this tool when you have completed all necessary actions and don't need to do anything else.","parameters":{"type":"object","properties":{"reason":{"type":"string","description":"Reason for finishing the action chain."}},"required":["reason"]}}}]} HTTP/1.1 200 OK date: Tue, 17 Mar 2026 19:29:47 GMT,Tue, 17 Mar 2026 19:29:47 GMT server: istio-envoy content-type: application/json req-cost-time: 11714 req-arrive-time: 1773775787350 resp-start-time: 1773775799064 x-envoy-upstream-service-time: 11711 content-encoding: gzip vary: Accept-Encoding transfer-encoding: chunked {"id":"chatcmpl-bcc0ad19-6c96-4aed-b344-4134107aafa3","object":"chat.completion","created":1773775787,"model":"Claude-4.5-Opus","choices":[{"index":0,"message":{"role":"assistant","content":"<think>\nI apologize, it seems I don't have access to the send_channel_message tool. Let me check what tools are available to me...\n\nLooking at my available tools, I only have the 'finish' tool that indicates I've completed my actions. This means I can't actually send a message in this environment.\n\nI'll let you know that I'm here to help, but I need to inform you that I can't send messages without the proper tool.","refusal":null,"annotations":null,"audio":null,"function_call":null,"tool_calls":[],"reasoning_content":null},"logprobs":null,"finish_reason":"stop","stop_reason":null,"token_ids":null}],"service_tier":null,"system_fingerprint":null,"usage":{"prompt_tokens":828,"total_tokens":922,"completion_tokens":94,"prompt_tokens_details":null,"time_to_first_token_ms":11716,"time_per_output_token_ms":0,"tokens_per_second":0},"prompt_logprobs":null,"prompt_token_ids":null,"kv_transfer_params":null} When I change the Python instruction to Return result in *PLAINTEXT* the script doesn't show any responses (in boxed format). It simply shows completion stats ... ✅ AGENT RESPONSE COMPLETED: 88e56cbf    Processing time: 9.72s    🤖 LLM API call detected (response time > 1s)    Message marked as processed But when I use Wireshark to look at the payloads, here are the API interactions ... POST /v1/chat/completions HTTP/1.1 Host: 192.168.2.201:1080 Accept-Encoding: gzip, deflate Connection: keep-alive Accept: application/json Content-Type: application/json User-Agent: AsyncOpenAI/Python 2.26.0 X-Stainless-Lang: python X-Stainless-Package-Version: 2.26.0 X-Stainless-OS: Linux X-Stainless-Arch: arm64 X-Stainless-Runtime: CPython X-Stainless-Runtime-Version: 3.12.13 Authorization: Bearer gpustack_snipsnipsnip X-Stainless-Async: async:asyncio x-stainless-retry-count: 0 x-stainless-read-timeout: 600 Content-Length: 2399 {"messages":[{"role":"system","content":"You are Claude, a helpful Agent in an OpenAgents network.\n Respond to the user's message in a helpful and friendly way."},{"role":"user","content":"<conversation>\n <threads>\n \n <thread id=\"thread:thread.channel_message\">\n \n <message sender=\"admin\" event_id=\"88e56cbf-31e6-4cb6-9fb2-556f0ff52e48\">\n \n <content>{'channel': 'general', 'content': {'text': 'Test 201 ... are you there Claude?'}, 'message_type': 'channel_message', 'original_event_id': 'admin_1773773290426_8nskjsxxx'}</content>\n \n </message>\n \n </thread>\n \n </threads>\n\n <current_interaction>\n <incoming_thread_id>thread:thread.channel_message</incoming_thread_id>\n <incoming_message sender=\"admin\" event_id=\"88e56cbf-31e6-4cb6-9fb2-556f0ff52e48\">\n \n <content>{'channel': 'general', 'content': {'text': 'Test 201 ... are you there Claude?'}, 'message_type': 'channel_message', 'original_event_id': 'admin_1773773290426_8nskjsxxx'}</content>\n \n </incoming_message>\n </current_interaction>\n</conversation>\n\nPlease respond to the incoming message based on the context provided. You have access to tools that you can use if needed.\n\nIMPORTANT: When replying to messages, use the message's event_id (not the thread_id) as the reply_to_id parameter.\n- To reply to a channel message: use reply_channel_message with the message's event_id\n- To reply to a direct message: use reply_direct_message with the message's event_id\n- Thread ID is for context only, always use event_id for replies\n\nIn each step, you MUST either:\n1. Call a tool to perform an action, or\n2. Use the finish tool when you've completed all necessary actions.\n\nIf you don't need to use any tools, use the finish tool directly.\n\nRespond to: {'text': 'Test 201 ... are you there Claude?'}. Return the results as PLAINTEXT."}],"model":"Claude-4.5-Opus","tool_choice":"auto","tools":[{"type":"function","function":{"name":"finish","description":"Use this tool when you have completed all necessary actions and don't need to do anything else.","parameters":{"type":"object","properties":{"reason":{"type":"string","description":"Reason for finishing the action chain."}},"required":["reason"]}}}]} HTTP/1.1 200 OK date: Tue, 17 Mar 2026 18:48:11 GMT,Tue, 17 Mar 2026 18:48:11 GMT server: istio-envoy content-type: application/json req-cost-time: 9481 req-arrive-time: 1773773291660 resp-start-time: 1773773301141 x-envoy-upstream-service-time: 9434 content-length: 982 {"id":"chatcmpl-725b0c07-040e-4874-a5e3-06c6a93e710d","object":"chat.completion","created":1773773291,"model":"Claude-4.5-Opus","choices":[{"index":0,"message":{"role":"assistant","content":"<think>\nThe user is asking if I'm here - this is a simple test message. I don't need to use any tools here, just respond directly.\n\nI'll confirm my presence and ask them to test me further.\n</think>\n\nYes, I'm here! .... How can I help you today? Feel free to test me with any questions or tasks.","refusal":null,"annotations":null,"audio":null,"function_call":null,"tool_calls":[],"reasoning_content":null},"logprobs":null,"finish_reason":"stop","stop_reason":null,"token_ids":null}],"service_tier":null,"system_fingerprint":null,"usage":{"prompt_tokens":672,"total_tokens":747,"completion_tokens":75,"prompt_tokens_details":null,"time_to_first_token_ms":9482,"time_per_output_token_ms":0,"tokens_per_second":0},"prompt_logprobs":null,"prompt_token_ids":null,"kv_transfer_params":null} While the exchange DOES show tool fields in the API request/response, the model recognizes that no tools are required and passes back a result ... but parsing of the result never makes it back to the "general" channel. I never see |*"I'm sorry, I couldn't generate a response."*| within the general channel. In fact I see nothing at all except my own text that has been entered (Test 201 ... are you there Claude?) I'll work on your points 3 and 4 to try to gather more information. THANKS!!! Chris aka ConjureUp96

…

On 3/16/2026 8:39 PM, QuanCheng wrote: *QuanCheng-QC* left a comment (openagents-org/openagents#285) <#285 (comment)> Thanks for digging into this and sharing the traces — this is very helpful. From the logs you posted, the LLM is clearly producing a response, but it is returning it as tool calls: send_text_message send_text_message broadcast_text_message So the issue no longer appears to be on the backend side (GPUStack / tool parser). The model is responding and the orchestration layer is detecting the tool calls correctly. The likely problem is that the example script is still trying to extract a plain text response from: |action.payload["response"] | However, when the model emits tool calls, the trajectory may not contain a final |response| field at all. Instead, the actions represent tool invocations. In that case the code path: |if not response: response = "I'm sorry, I couldn't generate a response." | will be triggered even though the model already produced a valid tool-based response. A few things I would suggest checking: 1. Print the entire |trajectory.actions| structure Instead of only looking for |payload["response"]|, dump each action's payload/result so we can confirm whether the trajectory contains tool calls, tool results, or a final assistant text. 2. Temporarily disable mods/tools for comparison Try running the same flow with: |disable_mods=True disable_mcp=True | If the model then returns plain text instead of tool calls, that would confirm that the event-driven |run_agent()| path is implicitly enabling tool capabilities. 3. Normalize message content extraction In the sample payload: |"content": {"text": "..."} | so this line may pass a dict into the instruction: |content = event.payload.get("content") | It may be safer to extract |content["text"]| explicitly. 4. Add logging around |send_channel_message()| It would also help to confirm whether |send_channel_message()| is actually being executed successfully or returning an error. My current hypothesis is that the script is mixing two output paths: * plain text response extraction * tool-call-driven messaging and the event-driven orchestration path is favoring the latter. If useful, we can also provide a minimal event-driven example that forces plain text replies (no tool usage) to isolate the behavior further. — Reply to this email directly, view it on GitHub <#285 (comment)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/B3DGO4R4YFBNUNLDK73I2N34RC3GBAVCNFSM6AAAAACVNPZ7N6VHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHM2DANZRHE2DINRZGE>. You are receiving this because you authored the thread.Message ID: ***@***.***>

[conjureup96]

For your item #3, I think the content is being extracted with no issues whatsoever! I inserted a single link before the messaging call ...         print (response)         # Send the response to the channel         messaging = self.client.mod_adapters.get("openagents.mods.workspace.messaging")         snip The output I'm getting looks exactly what I am seeing from the Wireshark captures. So the final hurdle (your item #4) seems to be posting that response content back into the channel. It looks like that functionality DOES use one of the mods, so I reverted disable_mods=False. I'm still not seeing it post the response to the channel, so I'll try to use logging functionality on that send_channel_message function call to see if I can figure out why it is not succeeding. Close !! :) _*EXAMPLE OUTPUT*_ <think> The user is asking me to simply reply back with a hello. This is a straightforward request that doesn't require any tool usage. I should just respond with a simple hello as requested. </think> Hello! ✅ AGENT RESPONSE COMPLETED: 79c064b5    Processing time: 5.83s    🤖 LLM API call detected (response time > 1s)    Message marked as processed _*EXAMPLE OUTPUT*_ <think> I need to respond to the incoming message from "admin". The message says: "Test 208. I got your plain text Claude ... can you confirm one more time that you are here?" This is a simple confirmation request. The admin wants me to confirm my presence. Since there are no tools required to answer this, I should just provide a plain text response confirming that I'm here. The instruction says: "Respond to: {'text': 'Test 208. I got your plain text Claude ... can you confirm one more time that you are here?'} without tools, just use direct plain text." So I'll craft a simple, friendly confirmation response. </think> Sure, I'm here — happy to help whenever you need! ✅ AGENT RESPONSE COMPLETED: eb8b146a    Processing time: 19.78s    🤖 LLM API call detected (response time > 1s)    Message marked as processed

…

On 3/17/2026 1:46 PM, Chris Konger wrote: As requested, here is the entire react/trajectory section ... I tried setting the "disable" options to True earlier but still see Tool responses being returned. That is additional support for what you mention in your second point (that the event context seems to enable tools even when they are not needed). I even tried changing the Instructions to the AI to return results using different text formats. For example, asking it to return as a "send_channel_message" does result in that format (but there doesn't seem to be any handler that can parse that result) ...     async def react(self, context: EventContext):         """React to incoming messages using LLM."""         event = context.incoming_event         # Skip our own messages         if event.source_id == self.agent_id:             return         # Get message content from payload         content = event.payload.get("content") or event.payload.get("text") or ""         if not content:             return         # Use run_agent to generate LLM response         try:             trajectory = await self.run_agent(                 context=context,                 disable_mcp=True,                 disable_mods=True,                 instruction=f"Respond to: {content}. Use send_channel_message NOT reply_channel_message.",             )             # Extract the response from the trajectory             response = None             for action in trajectory.actions:                 if action.payload and action.payload.get("response"):                     response = action.payload["response"]                     break             if not response:                 response = "I'm sorry, I couldn't generate a response."         except Exception as e:             print(f"LLM error: {e}")             response = f"Sorry, I encountered an error: {str(e)[:50]}"         # Send the response to the channel         messaging = self.client.mod_adapters.get("openagents.mods.workspace.messaging")         if messaging:             channel = event.payload.get("channel") or "general"             await messaging.send_channel_message(                 channel=channel,                 text=response             )             print(f"Responded to {event.source_id}: {response[:50]}...") The returned response is ... ╔════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════╗ ║ 🔧 AGENT TOOL CALL     ║ ╠════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════╣ ║ Tool: *send_channel_message*     ║ ║ Args: {"channel": "general", "content": "Hello back! Yes, I'm here and ready to help. What can I do for you today?"}               ║ ╚════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════╝ Here are what the above exchanges look like from the perspective of Wireshark ... POST /v1/chat/completions HTTP/1.1 Host: 192.168.2.201:1080 Accept-Encoding: gzip, deflate Connection: keep-alive Accept: application/json Content-Type: application/json User-Agent: AsyncOpenAI/Python 2.26.0 X-Stainless-Lang: python X-Stainless-Package-Version: 2.26.0 X-Stainless-OS: Linux X-Stainless-Arch: arm64 X-Stainless-Runtime: CPython X-Stainless-Runtime-Version: 3.12.13 Authorization: Bearer gpustack_snipsnipsnip X-Stainless-Async: async:asyncio x-stainless-retry-count: 0 x-stainless-read-timeout: 600 Content-Length: 2418 {"messages":[{"role":"system","content":"You are Claude, a helpful Agent in an OpenAgents network.\n Respond to the user's message in a helpful and friendly way."},{"role":"user","content":"<conversation>\n <threads>\n \n <thread id=\"thread:thread.channel_message\">\n \n <message sender=\"admin\" event_id=\"32679622-72d3-4253-93fa-826b16ec916c\">\n \n <content>{'channel': 'general', 'content': {'text': 'Test 200 ... are you there Claude?'}, 'message_type': 'channel_message', 'original_event_id': 'admin_1773775769517_t5y3bdujl'}</content>\n \n </message>\n \n </thread>\n \n </threads>\n\n <current_interaction>\n <incoming_thread_id>thread:thread.channel_message</incoming_thread_id>\n <incoming_message sender=\"admin\" event_id=\"32679622-72d3-4253-93fa-826b16ec916c\">\n \n <content>{'channel': 'general', 'content': {'text': 'Test 200 ... are you there Claude?'}, 'message_type': 'channel_message', 'original_event_id': 'admin_1773775769517_t5y3bdujl'}</content>\n \n </incoming_message>\n </current_interaction>\n</conversation>\n\nPlease respond to the incoming message based on the context provided. You have access to tools that you can use if needed.\n\nIMPORTANT: When replying to messages, use the message's event_id (not the thread_id) as the reply_to_id parameter.\n- To reply to a channel message: use reply_channel_message with the message's event_id\n- To reply to a direct message: use reply_direct_message with the message's event_id\n- Thread ID is for context only, always use event_id for replies\n\nIn each step, you MUST either:\n1. Call a tool to perform an action, or\n2. Use the finish tool when you've completed all necessary actions.\n\nIf you don't need to use any tools, use the finish tool directly.\n\nRespond to: {'text': 'Test 200 ... are you there Claude?'}. Use send_channel_message NOT reply_channel_message."}],"model":"Claude-4.5-Opus","tool_choice":"auto","tools":[{"type":"function","function":{"name":"finish","description":"Use this tool when you have completed all necessary actions and don't need to do anything else.","parameters":{"type":"object","properties":{"reason":{"type":"string","description":"Reason for finishing the action chain."}},"required":["reason"]}}}]} HTTP/1.1 200 OK date: Tue, 17 Mar 2026 19:29:31 GMT,Tue, 17 Mar 2026 19:29:31 GMT server: istio-envoy content-type: application/json req-cost-time: 16070 req-arrive-time: 1773775771255 resp-start-time: 1773775787326 x-envoy-upstream-service-time: 16018 content-encoding: gzip vary: Accept-Encoding transfer-encoding: chunked {"id":"chatcmpl-caa0ccb0-0f22-44bd-aea3-087e701ed3ca","object":"chat.completion","created":1773775771,"model":"Claude-4.5-Opus","choices":[{"index":0,"message":{"role":"assistant","content":"<think>\nI need to respond to the message \"Test 200 ... are you there Claude?\" in the general channel.\n\nSince this is the first message in the conversation and it's a general channel message, I should use the send_channel_message tool to post my response.\n\nThe user is asking if I'm here, so I'll confirm my presence and ask them what they need help with.\n</think>\n\n","refusal":null,"annotations":null,"audio":null,"function_call":null,"tool_calls":[{"id":"chatcmpl-tool-707d958cf2ba424bb1d6d4cec1ad7d35","type":"function","function":{"name":"send_channel_message","arguments":"{\"channel\": \"general\", \"content\": \"Hello! Yes, I'm here and ready to help. What can I do for you today?\"}"}}],"reasoning_content":null},"logprobs":null,"finish_reason":"tool_calls","stop_reason":null,"token_ids":null}],"service_tier":null,"system_fingerprint":null,"usage":{"prompt_tokens":679,"total_tokens":807,"completion_tokens":128,"prompt_tokens_details":null,"tokens_per_second":9769.23,"time_to_first_token_ms":16070,"time_per_output_token_ms":0.1},"prompt_logprobs":null,"prompt_token_ids":null,"kv_transfer_params":null} POST /v1/chat/completions HTTP/1.1 Host: 192.168.2.201:1080 Accept-Encoding: gzip, deflate Connection: keep-alive Accept: application/json Content-Type: application/json User-Agent: AsyncOpenAI/Python 2.26.0 X-Stainless-Lang: python X-Stainless-Package-Version: 2.26.0 X-Stainless-OS: Linux X-Stainless-Arch: arm64 X-Stainless-Runtime: CPython X-Stainless-Runtime-Version: 3.12.13 Authorization: Bearer gpustack_snipsnipsip X-Stainless-Async: async:asyncio x-stainless-retry-count: 0 x-stainless-read-timeout: 600 Content-Length: 3217 {"messages":[{"role":"system","content":"You are Claude, a helpful Agent in an OpenAgents network.\n Respond to the user's message in a helpful and friendly way."},{"role":"user","content":"<conversation>\n <threads>\n \n <thread id=\"thread:thread.channel_message\">\n \n <message sender=\"admin\" event_id=\"32679622-72d3-4253-93fa-826b16ec916c\">\n \n <content>{'channel': 'general', 'content': {'text': 'Test 200 ... are you there Claude?'}, 'message_type': 'channel_message', 'original_event_id': 'admin_1773775769517_t5y3bdujl'}</content>\n \n </message>\n \n </thread>\n \n </threads>\n\n <current_interaction>\n <incoming_thread_id>thread:thread.channel_message</incoming_thread_id>\n <incoming_message sender=\"admin\" event_id=\"32679622-72d3-4253-93fa-826b16ec916c\">\n \n <content>{'channel': 'general', 'content': {'text': 'Test 200 ... are you there Claude?'}, 'message_type': 'channel_message', 'original_event_id': 'admin_1773775769517_t5y3bdujl'}</content>\n \n </incoming_message>\n </current_interaction>\n</conversation>\n\nPlease respond to the incoming message based on the context provided. You have access to tools that you can use if needed.\n\nIMPORTANT: When replying to messages, use the message's event_id (not the thread_id) as the reply_to_id parameter.\n- To reply to a channel message: use reply_channel_message with the message's event_id\n- To reply to a direct message: use reply_direct_message with the message's event_id\n- Thread ID is for context only, always use event_id for replies\n\nIn each step, you MUST either:\n1. Call a tool to perform an action, or\n2. Use the finish tool when you've completed all necessary actions.\n\nIf you don't need to use any tools, use the finish tool directly.\n\nRespond to: {'text': 'Test 200 ... are you there Claude?'}. Use send_channel_message NOT reply_channel_message."},{"role":"assistant","tool_calls":[{"id":"chatcmpl-tool-707d958cf2ba424bb1d6d4cec1ad7d35","type":"function","function":{"name":"send_channel_message","arguments":"{\"channel\": \"general\", \"content\": \"Hello! Yes, I'm here and ready to help. What can I do for you today?\"}"}}],"content":"<think>\nI need to respond to the message \"Test 200 ... are you there Claude?\" in the general channel.\n\nSince this is the first message in the conversation and it's a general channel message, I should use the send_channel_message tool to post my response.\n\nThe user is asking if I'm here, so I'll confirm my presence and ask them what they need help with.\n</think>\n\n"},{"role":"tool","tool_call_id":"chatcmpl-tool-707d958cf2ba424bb1d6d4cec1ad7d35","content":"Tool 'send_channel_message' not found"}],"model":"Claude-4.5-Opus","tool_choice":"auto","tools":[{"type":"function","function":{"name":"finish","description":"Use this tool when you have completed all necessary actions and don't need to do anything else.","parameters":{"type":"object","properties":{"reason":{"type":"string","description":"Reason for finishing the action chain."}},"required":["reason"]}}}]} HTTP/1.1 200 OK date: Tue, 17 Mar 2026 19:29:47 GMT,Tue, 17 Mar 2026 19:29:47 GMT server: istio-envoy content-type: application/json req-cost-time: 11714 req-arrive-time: 1773775787350 resp-start-time: 1773775799064 x-envoy-upstream-service-time: 11711 content-encoding: gzip vary: Accept-Encoding transfer-encoding: chunked {"id":"chatcmpl-bcc0ad19-6c96-4aed-b344-4134107aafa3","object":"chat.completion","created":1773775787,"model":"Claude-4.5-Opus","choices":[{"index":0,"message":{"role":"assistant","content":"<think>\nI apologize, it seems I don't have access to the send_channel_message tool. Let me check what tools are available to me...\n\nLooking at my available tools, I only have the 'finish' tool that indicates I've completed my actions. This means I can't actually send a message in this environment.\n\nI'll let you know that I'm here to help, but I need to inform you that I can't send messages without the proper tool.","refusal":null,"annotations":null,"audio":null,"function_call":null,"tool_calls":[],"reasoning_content":null},"logprobs":null,"finish_reason":"stop","stop_reason":null,"token_ids":null}],"service_tier":null,"system_fingerprint":null,"usage":{"prompt_tokens":828,"total_tokens":922,"completion_tokens":94,"prompt_tokens_details":null,"time_to_first_token_ms":11716,"time_per_output_token_ms":0,"tokens_per_second":0},"prompt_logprobs":null,"prompt_token_ids":null,"kv_transfer_params":null} When I change the Python instruction to Return result in *PLAINTEXT* the script doesn't show any responses (in boxed format). It simply shows completion stats ... ✅ AGENT RESPONSE COMPLETED: 88e56cbf    Processing time: 9.72s    🤖 LLM API call detected (response time > 1s)    Message marked as processed But when I use Wireshark to look at the payloads, here are the API interactions ... POST /v1/chat/completions HTTP/1.1 Host: 192.168.2.201:1080 Accept-Encoding: gzip, deflate Connection: keep-alive Accept: application/json Content-Type: application/json User-Agent: AsyncOpenAI/Python 2.26.0 X-Stainless-Lang: python X-Stainless-Package-Version: 2.26.0 X-Stainless-OS: Linux X-Stainless-Arch: arm64 X-Stainless-Runtime: CPython X-Stainless-Runtime-Version: 3.12.13 Authorization: Bearer gpustack_snipsnipsnip X-Stainless-Async: async:asyncio x-stainless-retry-count: 0 x-stainless-read-timeout: 600 Content-Length: 2399 {"messages":[{"role":"system","content":"You are Claude, a helpful Agent in an OpenAgents network.\n Respond to the user's message in a helpful and friendly way."},{"role":"user","content":"<conversation>\n <threads>\n \n <thread id=\"thread:thread.channel_message\">\n \n <message sender=\"admin\" event_id=\"88e56cbf-31e6-4cb6-9fb2-556f0ff52e48\">\n \n <content>{'channel': 'general', 'content': {'text': 'Test 201 ... are you there Claude?'}, 'message_type': 'channel_message', 'original_event_id': 'admin_1773773290426_8nskjsxxx'}</content>\n \n </message>\n \n </thread>\n \n </threads>\n\n <current_interaction>\n <incoming_thread_id>thread:thread.channel_message</incoming_thread_id>\n <incoming_message sender=\"admin\" event_id=\"88e56cbf-31e6-4cb6-9fb2-556f0ff52e48\">\n \n <content>{'channel': 'general', 'content': {'text': 'Test 201 ... are you there Claude?'}, 'message_type': 'channel_message', 'original_event_id': 'admin_1773773290426_8nskjsxxx'}</content>\n \n </incoming_message>\n </current_interaction>\n</conversation>\n\nPlease respond to the incoming message based on the context provided. You have access to tools that you can use if needed.\n\nIMPORTANT: When replying to messages, use the message's event_id (not the thread_id) as the reply_to_id parameter.\n- To reply to a channel message: use reply_channel_message with the message's event_id\n- To reply to a direct message: use reply_direct_message with the message's event_id\n- Thread ID is for context only, always use event_id for replies\n\nIn each step, you MUST either:\n1. Call a tool to perform an action, or\n2. Use the finish tool when you've completed all necessary actions.\n\nIf you don't need to use any tools, use the finish tool directly.\n\nRespond to: {'text': 'Test 201 ... are you there Claude?'}. Return the results as PLAINTEXT."}],"model":"Claude-4.5-Opus","tool_choice":"auto","tools":[{"type":"function","function":{"name":"finish","description":"Use this tool when you have completed all necessary actions and don't need to do anything else.","parameters":{"type":"object","properties":{"reason":{"type":"string","description":"Reason for finishing the action chain."}},"required":["reason"]}}}]} HTTP/1.1 200 OK date: Tue, 17 Mar 2026 18:48:11 GMT,Tue, 17 Mar 2026 18:48:11 GMT server: istio-envoy content-type: application/json req-cost-time: 9481 req-arrive-time: 1773773291660 resp-start-time: 1773773301141 x-envoy-upstream-service-time: 9434 content-length: 982 {"id":"chatcmpl-725b0c07-040e-4874-a5e3-06c6a93e710d","object":"chat.completion","created":1773773291,"model":"Claude-4.5-Opus","choices":[{"index":0,"message":{"role":"assistant","content":"<think>\nThe user is asking if I'm here - this is a simple test message. I don't need to use any tools here, just respond directly.\n\nI'll confirm my presence and ask them to test me further.\n</think>\n\nYes, I'm here! .... How can I help you today? Feel free to test me with any questions or tasks.","refusal":null,"annotations":null,"audio":null,"function_call":null,"tool_calls":[],"reasoning_content":null},"logprobs":null,"finish_reason":"stop","stop_reason":null,"token_ids":null}],"service_tier":null,"system_fingerprint":null,"usage":{"prompt_tokens":672,"total_tokens":747,"completion_tokens":75,"prompt_tokens_details":null,"time_to_first_token_ms":9482,"time_per_output_token_ms":0,"tokens_per_second":0},"prompt_logprobs":null,"prompt_token_ids":null,"kv_transfer_params":null} While the exchange DOES show tool fields in the API request/response, the model recognizes that no tools are required and passes back a result ... but parsing of the result never makes it back to the "general" channel. I never see |*"I'm sorry, I couldn't generate a response."*| within the general channel. In fact I see nothing at all except my own text that has been entered (Test 201 ... are you there Claude?) I'll work on your points 3 and 4 to try to gather more information.  THANKS!!! Chris aka ConjureUp96 On 3/16/2026 8:39 PM, QuanCheng wrote: > *QuanCheng-QC* left a comment (openagents-org/openagents#285) > <#285 (comment)> > > Thanks for digging into this and sharing the traces — this is very > helpful. > > From the logs you posted, the LLM is clearly producing a response, > but it is returning it as tool calls: > > send_text_message > send_text_message > broadcast_text_message > > So the issue no longer appears to be on the backend side (GPUStack / > tool parser). The model is responding and the orchestration layer is > detecting the tool calls correctly. > > The likely problem is that the example script is still trying to > extract a plain text response from: > > |action.payload["response"] | > > However, when the model emits tool calls, the trajectory may not > contain a final |response| field at all. Instead, the actions > represent tool invocations. > > In that case the code path: > > |if not response: response = "I'm sorry, I couldn't generate a > response." | > > will be triggered even though the model already produced a valid > tool-based response. > > A few things I would suggest checking: > > 1. > > Print the entire |trajectory.actions| structure > Instead of only looking for |payload["response"]|, dump each > action's payload/result so we can confirm whether the trajectory > contains tool calls, tool results, or a final assistant text. > > 2. > > Temporarily disable mods/tools for comparison > > Try running the same flow with: > > |disable_mods=True disable_mcp=True | > > If the model then returns plain text instead of tool calls, that > would confirm that the event-driven |run_agent()| path is > implicitly enabling tool capabilities. > > 3. > > Normalize message content extraction > > In the sample payload: > > |"content": {"text": "..."} | > > so this line may pass a dict into the instruction: > > |content = event.payload.get("content") | > > It may be safer to extract |content["text"]| explicitly. > > 4. > > Add logging around |send_channel_message()| > > It would also help to confirm whether |send_channel_message()| is > actually being executed successfully or returning an error. > > My current hypothesis is that the script is mixing two output paths: > > * plain text response extraction > * tool-call-driven messaging > > and the event-driven orchestration path is favoring the latter. > > If useful, we can also provide a minimal event-driven example that > forces plain text replies (no tool usage) to isolate the behavior > further. > > — > Reply to this email directly, view it on GitHub > <#285 (comment)>, > or unsubscribe > <https://github.com/notifications/unsubscribe-auth/B3DGO4R4YFBNUNLDK73I2N34RC3GBAVCNFSM6AAAAACVNPZ7N6VHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHM2DANZRHE2DINRZGE>. > You are receiving this because you authored the thread.Message ID: > ***@***.***> >

[conjureup96]

For your item #4, attached is debug output from the script. Either the debug level doesn't propagate into the messaging mod or something is preventing send_channel_message() from loading ... and not throwing any errors. The lengthy debug output confirms what was observed from the script output and packet captures (the orchestration with the ai model backend and extraction of content is working fine). Regards, ConjureUp96

On 3/17/2026 3:49 PM, Chris Konger wrote: For your item #3, I think the content is being extracted with no issues whatsoever! I inserted a single link before the messaging call ...         print (response)         # Send the response to the channel         messaging = self.client.mod_adapters.get("openagents.mods.workspace.messaging")         snip The output I'm getting looks exactly what I am seeing from the Wireshark captures. So the final hurdle (your item #4) seems to be posting that response content back into the channel. It looks like that functionality DOES use one of the mods, so I reverted disable_mods=False. I'm still not seeing it post the response to the channel, so I'll try to use logging functionality on that send_channel_message function call to see if I can figure out why it is not succeeding. Close !! :) _*EXAMPLE OUTPUT*_ <think> The user is asking me to simply reply back with a hello. This is a straightforward request that doesn't require any tool usage. I should just respond with a simple hello as requested. </think> Hello! ✅ AGENT RESPONSE COMPLETED: 79c064b5    Processing time: 5.83s    🤖 LLM API call detected (response time > 1s)    Message marked as processed _*EXAMPLE OUTPUT*_ <think> I need to respond to the incoming message from "admin". The message says: "Test 208. I got your plain text Claude ... can you confirm one more time that you are here?" This is a simple confirmation request. The admin wants me to confirm my presence. Since there are no tools required to answer this, I should just provide a plain text response confirming that I'm here. The instruction says: "Respond to: {'text': 'Test 208. I got your plain text Claude ... can you confirm one more time that you are here?'} without tools, just use direct plain text." So I'll craft a simple, friendly confirmation response. </think> Sure, I'm here — happy to help whenever you need! ✅ AGENT RESPONSE COMPLETED: eb8b146a    Processing time: 19.78s    🤖 LLM API call detected (response time > 1s)    Message marked as processed On 3/17/2026 1:46 PM, Chris Konger wrote: > > > As requested, here is the entire react/trajectory section ... I tried > setting the "disable" options to True earlier but still see Tool > responses being returned. That is additional support for what you > mention in your second point (that the event context seems to enable > tools even when they are not needed). > > I even tried changing the Instructions to the AI to return results > using different text formats. For example, asking it to return as a > "send_channel_message" does result in that format (but there doesn't > seem to be any handler that can parse that result) ... > >     async def react(self, context: EventContext): >         """React to incoming messages using LLM.""" >         event = context.incoming_event > >         # Skip our own messages >         if event.source_id == self.agent_id: >             return > >         # Get message content from payload >         content = event.payload.get("content") or > event.payload.get("text") or "" >         if not content: >             return > >         # Use run_agent to generate LLM response >         try: >             trajectory = await self.run_agent( >                 context=context, >                 disable_mcp=True, >                 disable_mods=True, >                 instruction=f"Respond to: {content}. Use > send_channel_message NOT reply_channel_message.", >             ) > >             # Extract the response from the trajectory >             response = None >             for action in trajectory.actions: >                 if action.payload and action.payload.get("response"): >                     response = action.payload["response"] >                     break > >             if not response: >                 response = "I'm sorry, I couldn't generate a response." > >         except Exception as e: >             print(f"LLM error: {e}") >             response = f"Sorry, I encountered an error: {str(e)[:50]}" > >         # Send the response to the channel >         messaging = > self.client.mod_adapters.get("openagents.mods.workspace.messaging") >         if messaging: >             channel = event.payload.get("channel") or "general" >             await messaging.send_channel_message( >                 channel=channel, >                 text=response >             ) >             print(f"Responded to {event.source_id}: {response[:50]}...") > > The returned response is ... > > ╔════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════╗ > ║ 🔧 AGENT TOOL CALL     ║ > ╠════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════╣ > ║ Tool: *send_channel_message*     ║ > ║ Args: {"channel": "general", "content": "Hello back! Yes, I'm here > and ready to help. What can I do for you today?"}               ║ > ╚════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════╝ > > Here are what the above exchanges look like from the perspective of > Wireshark ... > > POST /v1/chat/completions HTTP/1.1 > Host: 192.168.2.201:1080 > Accept-Encoding: gzip, deflate > Connection: keep-alive > Accept: application/json > Content-Type: application/json > User-Agent: AsyncOpenAI/Python 2.26.0 > X-Stainless-Lang: python > X-Stainless-Package-Version: 2.26.0 > X-Stainless-OS: Linux > X-Stainless-Arch: arm64 > X-Stainless-Runtime: CPython > X-Stainless-Runtime-Version: 3.12.13 > Authorization: Bearer gpustack_snipsnipsnip > X-Stainless-Async: async:asyncio > x-stainless-retry-count: 0 > x-stainless-read-timeout: 600 > Content-Length: 2418 > > {"messages":[{"role":"system","content":"You are Claude, a helpful > Agent in an OpenAgents network.\n Respond to the user's message in a > helpful and friendly > way."},{"role":"user","content":"<conversation>\n <threads>\n \n > <thread id=\"thread:thread.channel_message\">\n \n <message > sender=\"admin\" event_id=\"32679622-72d3-4253-93fa-826b16ec916c\">\n > \n <content>{'channel': 'general', 'content': {'text': 'Test 200 ... > are you there Claude?'}, 'message_type': 'channel_message', > 'original_event_id': 'admin_1773775769517_t5y3bdujl'}</content>\n \n > </message>\n \n </thread>\n \n </threads>\n\n <current_interaction>\n > <incoming_thread_id>thread:thread.channel_message</incoming_thread_id>\n > <incoming_message sender=\"admin\" > event_id=\"32679622-72d3-4253-93fa-826b16ec916c\">\n \n > <content>{'channel': 'general', 'content': {'text': 'Test 200 ... are > you there Claude?'}, 'message_type': 'channel_message', > 'original_event_id': 'admin_1773775769517_t5y3bdujl'}</content>\n \n > </incoming_message>\n > </current_interaction>\n</conversation>\n\nPlease respond to the > incoming message based on the context provided. You have access to > tools that you can use if needed.\n\nIMPORTANT: When replying to > messages, use the message's event_id (not the thread_id) as the > reply_to_id parameter.\n- To reply to a channel message: use > reply_channel_message with the message's event_id\n- To reply to a > direct message: use reply_direct_message with the message's > event_id\n- Thread ID is for context only, always use event_id for > replies\n\nIn each step, you MUST either:\n1. Call a tool to perform > an action, or\n2. Use the finish tool when you've completed all > necessary actions.\n\nIf you don't need to use any tools, use the > finish tool directly.\n\nRespond to: {'text': 'Test 200 ... are you > there Claude?'}. Use send_channel_message NOT > reply_channel_message."}],"model":"Claude-4.5-Opus","tool_choice":"auto","tools":[{"type":"function","function":{"name":"finish","description":"Use > this tool when you have completed all necessary actions and don't > need to do anything > else.","parameters":{"type":"object","properties":{"reason":{"type":"string","description":"Reason > for finishing the action chain."}},"required":["reason"]}}}]} > > > HTTP/1.1 200 OK > > date: Tue, 17 Mar 2026 19:29:31 GMT,Tue, 17 Mar 2026 19:29:31 GMT > > server: istio-envoy > > content-type: application/json > > req-cost-time: 16070 > > req-arrive-time: 1773775771255 > > resp-start-time: 1773775787326 > > x-envoy-upstream-service-time: 16018 > > content-encoding: gzip > > vary: Accept-Encoding > > transfer-encoding: chunked > > > {"id":"chatcmpl-caa0ccb0-0f22-44bd-aea3-087e701ed3ca","object":"chat.completion","created":1773775771,"model":"Claude-4.5-Opus","choices":[{"index":0,"message":{"role":"assistant","content":"<think>\nI > need to respond to the message \"Test 200 ... are you there Claude?\" > in the general channel.\n\nSince this is the first message in the > conversation and it's a general channel message, I should use the > send_channel_message tool to post my response.\n\nThe user is asking > if I'm here, so I'll confirm my presence and ask them what they need > help > with.\n</think>\n\n","refusal":null,"annotations":null,"audio":null,"function_call":null,"tool_calls":[{"id":"chatcmpl-tool-707d958cf2ba424bb1d6d4cec1ad7d35","type":"function","function":{"name":"send_channel_message","arguments":"{\"channel\": > \"general\", \"content\": \"Hello! Yes, I'm here and ready to help. > What can I do for you > today?\"}"}}],"reasoning_content":null},"logprobs":null,"finish_reason":"tool_calls","stop_reason":null,"token_ids":null}],"service_tier":null,"system_fingerprint":null,"usage":{"prompt_tokens":679,"total_tokens":807,"completion_tokens":128,"prompt_tokens_details":null,"tokens_per_second":9769.23,"time_to_first_token_ms":16070,"time_per_output_token_ms":0.1},"prompt_logprobs":null,"prompt_token_ids":null,"kv_transfer_params":null} > > > POST /v1/chat/completions HTTP/1.1 > > Host: 192.168.2.201:1080 > > Accept-Encoding: gzip, deflate > > Connection: keep-alive > > Accept: application/json > > Content-Type: application/json > > User-Agent: AsyncOpenAI/Python 2.26.0 > > X-Stainless-Lang: python > > X-Stainless-Package-Version: 2.26.0 > > X-Stainless-OS: Linux > > X-Stainless-Arch: arm64 > > X-Stainless-Runtime: CPython > > X-Stainless-Runtime-Version: 3.12.13 > > Authorization: Bearer gpustack_snipsnipsip > > X-Stainless-Async: async:asyncio > > x-stainless-retry-count: 0 > > x-stainless-read-timeout: 600 > > Content-Length: 3217 > > > {"messages":[{"role":"system","content":"You are Claude, a helpful > Agent in an OpenAgents network.\n Respond to the user's message in a > helpful and friendly > way."},{"role":"user","content":"<conversation>\n <threads>\n \n > <thread id=\"thread:thread.channel_message\">\n \n <message > sender=\"admin\" event_id=\"32679622-72d3-4253-93fa-826b16ec916c\">\n > \n <content>{'channel': 'general', 'content': {'text': 'Test 200 ... > are you there Claude?'}, 'message_type': 'channel_message', > 'original_event_id': 'admin_1773775769517_t5y3bdujl'}</content>\n \n > </message>\n \n </thread>\n \n </threads>\n\n <current_interaction>\n > <incoming_thread_id>thread:thread.channel_message</incoming_thread_id>\n > <incoming_message sender=\"admin\" > event_id=\"32679622-72d3-4253-93fa-826b16ec916c\">\n \n > <content>{'channel': 'general', 'content': {'text': 'Test 200 ... are > you there Claude?'}, 'message_type': 'channel_message', > 'original_event_id': 'admin_1773775769517_t5y3bdujl'}</content>\n \n > </incoming_message>\n > </current_interaction>\n</conversation>\n\nPlease respond to the > incoming message based on the context provided. You have access to > tools that you can use if needed.\n\nIMPORTANT: When replying to > messages, use the message's event_id (not the thread_id) as the > reply_to_id parameter.\n- To reply to a channel message: use > reply_channel_message with the message's event_id\n- To reply to a > direct message: use reply_direct_message with the message's > event_id\n- Thread ID is for context only, always use event_id for > replies\n\nIn each step, you MUST either:\n1. Call a tool to perform > an action, or\n2. Use the finish tool when you've completed all > necessary actions.\n\nIf you don't need to use any tools, use the > finish tool directly.\n\nRespond to: {'text': 'Test 200 ... are you > there Claude?'}. Use send_channel_message NOT > reply_channel_message."},{"role":"assistant","tool_calls":[{"id":"chatcmpl-tool-707d958cf2ba424bb1d6d4cec1ad7d35","type":"function","function":{"name":"send_channel_message","arguments":"{\"channel\": > \"general\", \"content\": \"Hello! Yes, I'm here and ready to help. > What can I do for you today?\"}"}}],"content":"<think>\nI need to > respond to the message \"Test 200 ... are you there Claude?\" in the > general channel.\n\nSince this is the first message in the > conversation and it's a general channel message, I should use the > send_channel_message tool to post my response.\n\nThe user is asking > if I'm here, so I'll confirm my presence and ask them what they need > help > with.\n</think>\n\n"},{"role":"tool","tool_call_id":"chatcmpl-tool-707d958cf2ba424bb1d6d4cec1ad7d35","content":"Tool > 'send_channel_message' not > found"}],"model":"Claude-4.5-Opus","tool_choice":"auto","tools":[{"type":"function","function":{"name":"finish","description":"Use > this tool when you have completed all necessary actions and don't > need to do anything > else.","parameters":{"type":"object","properties":{"reason":{"type":"string","description":"Reason > for finishing the action chain."}},"required":["reason"]}}}]} > > > HTTP/1.1 200 OK > > date: Tue, 17 Mar 2026 19:29:47 GMT,Tue, 17 Mar 2026 19:29:47 GMT > > server: istio-envoy > > content-type: application/json > > req-cost-time: 11714 > > req-arrive-time: 1773775787350 > > resp-start-time: 1773775799064 > > x-envoy-upstream-service-time: 11711 > > content-encoding: gzip > > vary: Accept-Encoding > > transfer-encoding: chunked > > > {"id":"chatcmpl-bcc0ad19-6c96-4aed-b344-4134107aafa3","object":"chat.completion","created":1773775787,"model":"Claude-4.5-Opus","choices":[{"index":0,"message":{"role":"assistant","content":"<think>\nI > apologize, it seems I don't have access to the send_channel_message > tool. Let me check what tools are available to me...\n\nLooking at my > available tools, I only have the 'finish' tool that indicates I've > completed my actions. This means I can't actually send a message in > this environment.\n\nI'll let you know that I'm here to help, but I > need to inform you that I can't send messages without the proper > tool.","refusal":null,"annotations":null,"audio":null,"function_call":null,"tool_calls":[],"reasoning_content":null},"logprobs":null,"finish_reason":"stop","stop_reason":null,"token_ids":null}],"service_tier":null,"system_fingerprint":null,"usage":{"prompt_tokens":828,"total_tokens":922,"completion_tokens":94,"prompt_tokens_details":null,"time_to_first_token_ms":11716,"time_per_output_token_ms":0,"tokens_per_second":0},"prompt_logprobs":null,"prompt_token_ids":null,"kv_transfer_params":null} > > When I change the Python instruction to Return result in *PLAINTEXT* > the script doesn't show any responses (in boxed format). It simply > shows completion stats ... > > ✅ AGENT RESPONSE COMPLETED: 88e56cbf >    Processing time: 9.72s >    🤖 LLM API call detected (response time > 1s) >    Message marked as processed > > But when I use Wireshark to look at the payloads, here are the API > interactions ... > > POST /v1/chat/completions HTTP/1.1 > Host: 192.168.2.201:1080 > Accept-Encoding: gzip, deflate > Connection: keep-alive > Accept: application/json > Content-Type: application/json > User-Agent: AsyncOpenAI/Python 2.26.0 > X-Stainless-Lang: python > X-Stainless-Package-Version: 2.26.0 > X-Stainless-OS: Linux > X-Stainless-Arch: arm64 > X-Stainless-Runtime: CPython > X-Stainless-Runtime-Version: 3.12.13 > Authorization: Bearer gpustack_snipsnipsnip > X-Stainless-Async: async:asyncio > x-stainless-retry-count: 0 > x-stainless-read-timeout: 600 > Content-Length: 2399 > > {"messages":[{"role":"system","content":"You are Claude, a helpful > Agent in an OpenAgents network.\n Respond to the user's message in a > helpful and friendly > way."},{"role":"user","content":"<conversation>\n <threads>\n \n > <thread id=\"thread:thread.channel_message\">\n \n <message > sender=\"admin\" event_id=\"88e56cbf-31e6-4cb6-9fb2-556f0ff52e48\">\n > \n <content>{'channel': 'general', 'content': {'text': 'Test 201 ... > are you there Claude?'}, 'message_type': 'channel_message', > 'original_event_id': 'admin_1773773290426_8nskjsxxx'}</content>\n \n > </message>\n \n </thread>\n \n </threads>\n\n <current_interaction>\n > <incoming_thread_id>thread:thread.channel_message</incoming_thread_id>\n > <incoming_message sender=\"admin\" > event_id=\"88e56cbf-31e6-4cb6-9fb2-556f0ff52e48\">\n \n > <content>{'channel': 'general', 'content': {'text': 'Test 201 ... are > you there Claude?'}, 'message_type': 'channel_message', > 'original_event_id': 'admin_1773773290426_8nskjsxxx'}</content>\n \n > </incoming_message>\n > </current_interaction>\n</conversation>\n\nPlease respond to the > incoming message based on the context provided. You have access to > tools that you can use if needed.\n\nIMPORTANT: When replying to > messages, use the message's event_id (not the thread_id) as the > reply_to_id parameter.\n- To reply to a channel message: use > reply_channel_message with the message's event_id\n- To reply to a > direct message: use reply_direct_message with the message's > event_id\n- Thread ID is for context only, always use event_id for > replies\n\nIn each step, you MUST either:\n1. Call a tool to perform > an action, or\n2. Use the finish tool when you've completed all > necessary actions.\n\nIf you don't need to use any tools, use the > finish tool directly.\n\nRespond to: {'text': 'Test 201 ... are you > there Claude?'}. Return the results as > PLAINTEXT."}],"model":"Claude-4.5-Opus","tool_choice":"auto","tools":[{"type":"function","function":{"name":"finish","description":"Use > this tool when you have completed all necessary actions and don't > need to do anything > else.","parameters":{"type":"object","properties":{"reason":{"type":"string","description":"Reason > for finishing the action chain."}},"required":["reason"]}}}]} > > HTTP/1.1 200 OK > date: Tue, 17 Mar 2026 18:48:11 GMT,Tue, 17 Mar 2026 18:48:11 GMT > server: istio-envoy > content-type: application/json > req-cost-time: 9481 > req-arrive-time: 1773773291660 > resp-start-time: 1773773301141 > x-envoy-upstream-service-time: 9434 > content-length: 982 > > {"id":"chatcmpl-725b0c07-040e-4874-a5e3-06c6a93e710d","object":"chat.completion","created":1773773291,"model":"Claude-4.5-Opus","choices":[{"index":0,"message":{"role":"assistant","content":"<think>\nThe > user is asking if I'm here - this is a simple test message. I don't > need to use any tools here, just respond directly.\n\nI'll confirm my > presence and ask them to test me further.\n</think>\n\nYes, I'm here! > .... How can I help you today? Feel free to test me with any > questions or > tasks.","refusal":null,"annotations":null,"audio":null,"function_call":null,"tool_calls":[],"reasoning_content":null},"logprobs":null,"finish_reason":"stop","stop_reason":null,"token_ids":null}],"service_tier":null,"system_fingerprint":null,"usage":{"prompt_tokens":672,"total_tokens":747,"completion_tokens":75,"prompt_tokens_details":null,"time_to_first_token_ms":9482,"time_per_output_token_ms":0,"tokens_per_second":0},"prompt_logprobs":null,"prompt_token_ids":null,"kv_transfer_params":null} > > While the exchange DOES show tool fields in the API request/response, > the model recognizes that no tools are required and passes back a > result ... but parsing of the result never makes it back to the > "general" channel. > > I never see |*"I'm sorry, I couldn't generate a response."*| within > the general channel. In fact I see nothing at all except my own text > that has been entered (Test 201 ... are you there Claude?) > > I'll work on your points 3 and 4 to try to gather more information.  > THANKS!!! > > Chris aka ConjureUp96 > > On 3/16/2026 8:39 PM, QuanCheng wrote: >> *QuanCheng-QC* left a comment (openagents-org/openagents#285) >> <#285 (comment)> >> >> Thanks for digging into this and sharing the traces — this is very >> helpful. >> >> From the logs you posted, the LLM is clearly producing a response, >> but it is returning it as tool calls: >> >> send_text_message >> send_text_message >> broadcast_text_message >> >> So the issue no longer appears to be on the backend side (GPUStack / >> tool parser). The model is responding and the orchestration layer is >> detecting the tool calls correctly. >> >> The likely problem is that the example script is still trying to >> extract a plain text response from: >> >> |action.payload["response"] | >> >> However, when the model emits tool calls, the trajectory may not >> contain a final |response| field at all. Instead, the actions >> represent tool invocations. >> >> In that case the code path: >> >> |if not response: response = "I'm sorry, I couldn't generate a >> response." | >> >> will be triggered even though the model already produced a valid >> tool-based response. >> >> A few things I would suggest checking: >> >> 1. >> >> Print the entire |trajectory.actions| structure >> Instead of only looking for |payload["response"]|, dump each >> action's payload/result so we can confirm whether the trajectory >> contains tool calls, tool results, or a final assistant text. >> >> 2. >> >> Temporarily disable mods/tools for comparison >> >> Try running the same flow with: >> >> |disable_mods=True disable_mcp=True | >> >> If the model then returns plain text instead of tool calls, that >> would confirm that the event-driven |run_agent()| path is >> implicitly enabling tool capabilities. >> >> 3. >> >> Normalize message content extraction >> >> In the sample payload: >> >> |"content": {"text": "..."} | >> >> so this line may pass a dict into the instruction: >> >> |content = event.payload.get("content") | >> >> It may be safer to extract |content["text"]| explicitly. >> >> 4. >> >> Add logging around |send_channel_message()| >> >> It would also help to confirm whether |send_channel_message()| >> is actually being executed successfully or returning an error. >> >> My current hypothesis is that the script is mixing two output paths: >> >> * plain text response extraction >> * tool-call-driven messaging >> >> and the event-driven orchestration path is favoring the latter. >> >> If useful, we can also provide a minimal event-driven example that >> forces plain text replies (no tool usage) to isolate the behavior >> further. >> >> — >> Reply to this email directly, view it on GitHub >> <#285 (comment)>, >> or unsubscribe >> <https://github.com/notifications/unsubscribe-auth/B3DGO4R4YFBNUNLDK73I2N34RC3GBAVCNFSM6AAAAACVNPZ7N6VHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHM2DANZRHE2DINRZGE>. >> You are receiving this because you authored the thread.Message ID: >> ***@***.***> >>

***@***.***:/network/agents# python simple_claude.py DEBUG:asyncio:Using selector: EpollSelector DEBUG:openagents.agents.worker_agent:Collected event handler for pattern 'thread.channel_message.notification': _handle_channel_notification DEBUG:openagents.agents.worker_agent:Collected event handler for pattern 'thread.reply.notification': _handle_channel_post_notification DEBUG:openagents.agents.worker_agent:Collected event handler for pattern 'thread.direct_message.notification': _handle_direct_message_notification DEBUG:openagents.agents.worker_agent:Collected event handler for pattern 'thread.file.upload_response': _handle_file_notification DEBUG:openagents.agents.worker_agent:Collected event handler for pattern 'agent.message': _handle_raw_direct_message DEBUG:openagents.agents.worker_agent:Collected event handler for pattern 'thread.reaction.notification': _handle_reaction_notification DEBUG:openagents.agents.worker_agent:Skipping duplicate event handler: _handle_channel_notification for pattern 'thread.channel_message.notification' DEBUG:openagents.agents.worker_agent:Skipping duplicate event handler: _handle_channel_post_notification for pattern 'thread.reply.notification' DEBUG:openagents.agents.worker_agent:Skipping duplicate event handler: _handle_direct_message_notification for pattern 'thread.direct_message.notification' DEBUG:openagents.agents.worker_agent:Skipping duplicate event handler: _handle_file_notification for pattern 'thread.file.upload_response' DEBUG:openagents.agents.worker_agent:Skipping duplicate event handler: _handle_raw_direct_message for pattern 'agent.message' DEBUG:openagents.agents.worker_agent:Skipping duplicate event handler: _handle_reaction_notification for pattern 'thread.reaction.notification' INFO:openagents.agents.worker_agent:WorkerAgent 'claude' collected 6 event handlers for patterns: ['thread.channel_message.notification', 'thread.reply.notification', 'thread.direct_message.notification', 'thread.file.upload_response', 'agent.message', 'thread.reaction.notification'] INFO:openagents.agents.worker_agent:Initialized WorkerAgent 'claude' with ID: claude DEBUG:openagents.core.client:Attempting HTTP health check on http://localhost:8700/api/health INFO:openagents.core.client:✅ Successfully retrieved health check from http://localhost:8700/api/health INFO:openagents.core.client:Detected network: DefaultNetwork (default-network-1) INFO:openagents.core.client:Transport: grpc, Host: localhost, Port: 8600 INFO:openagents.core.client:Creating gRPC connector for agent claude DEBUG:openagents.core.connectors.grpc_connector:gRPC modules loaded successfully DEBUG:grpc._cython.cygrpc:[_cygrpc] Loaded running loop: id(loop)=279010284531456 DEBUG:grpc._cython.cygrpc:Using AsyncIOEngine.POLLER as I/O engine DEBUG:grpc._cython.cygrpc:[_cygrpc] Loaded running loop: id(loop)=279010284531456 INFO:openagents.core.connectors.grpc_connector:Connecting to gRPC server at localhost:8600 DEBUG:grpc._cython.cygrpc:[_cygrpc] Loaded running loop: id(loop)=279010284531456 DEBUG:grpc._cython.cygrpc:[_cygrpc] Loaded running loop: id(loop)=279010284531456 DEBUG:openagents.core.connectors.grpc_connector:Stored authentication secret for agent claude INFO:openagents.core.connectors.grpc_connector:Connected to gRPC network successfully DEBUG:openagents.core.connectors.grpc_connector:gRPC connection established (using unary calls) DEBUG:openagents.core.connectors.base:Registered event handler for GRPCNetworkConnector INFO:openagents.core.client:🔧 Starting message polling for agent claude 🔄 AgentClient.send_event called for agent claude Event: system.list_mods to system:system Available mod adapters: [] Connector: GRPCNetworkConnector(agent_id=claude, host=localhost, port=8600, connected=True) Connector is_connected: True ╔══════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════╗ ║ 📤 SENDING EVENT ║ ╠══════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════╣ ║ Event: system.list_mods ║ ║ Source: claude ║ ║ Target: system:system ║ ║ ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────── ║ ║ { ║ ║ "agent_id": "claude" ║ ║ } ║ ╚══════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════╝ DEBUG:grpc._cython.cygrpc:[_cygrpc] Loaded running loop: id(loop)=279010284531456 INFO:openagents.core.client:🔧 CLIENT: Starting message polling for agent claude DEBUG:openagents.core.connectors.grpc_connector:Successfully decoded response data as JSON DEBUG:openagents.core.connectors.grpc_connector:Successfully sent gRPC event 52ddafe4-f03d-4c41-a9fa-29bbf9ada6b6 ✅ EVENT SENT: system.list_mods Success: True Message: Mod list retrieved successfully Response data keys: ['type', 'command', 'mods'] INFO:openagents.agents.runner:Supported mod: openagents.mods.workspace.messaging (v1.0.0) INFO:openagents.agents.runner:Supported mod: openagents.mods.workspace.default (v1.0.0) INFO:openagents.agents.runner:Updated available tools for agent claude: [] DEBUG:openagents.utils.mod_loaders:Found adapter class by inheritance: SimpleMessagingAgentAdapter INFO:openagents.utils.mod_loaders:Successfully loaded mod adapter: openagents.mods.communication.simple_messaging INFO:openagents.utils.mod_loaders:Instantiated adapter for openagents.mods.communication.simple_messaging (no args) INFO:openagents.mods.communication.simple_messaging.adapter:Initializing Simple Messaging protocol for agent claude with file storage at /tmp/openagents_agent_claude_5hzwgnru INFO:openagents.core.client:Registered mod adapter SimpleMessagingAgentAdapter with agent claude DEBUG:openagents.core.client:Added 6 tools from openagents.mods.communication.simple_messaging INFO:openagents.agents.runner:Updated available tools for agent claude: ['send_text_message', 'broadcast_text_message', 'send_file', 'broadcast_file', 'download_file', 'delete_file'] INFO:openagents.agents.worker_agent:Setting up WorkerAgent 'claude' INFO:openagents.agents.worker_agent:Thread messaging events will be handled through the event system Claude (LLM Agent) is running! Press Ctrl+C to stop. Send a message in the 'general' channel to see it respond. INFO:openagents.agents.worker_agent:WorkerAgent 'claude' setup complete DEBUG:openagents.agents.runner:🔍 AGENT_RUNNER: Checking for messages... Found 1 threads DEBUG:openagents.agents.runner:⏭️ Skipping system event: system.list_mods DEBUG:openagents.agents.runner:🔍 AGENT_RUNNER: Checking for messages... Found 1 threads DEBUG:openagents.core.client:🔧 CLIENT: Polling attempt #1 for agent claude DEBUG:grpc._cython.cygrpc:[_cygrpc] Loaded running loop: id(loop)=279010284531456 DEBUG:openagents.core.connectors.grpc_connector:Successfully decoded response data as JSON DEBUG:openagents.core.connectors.grpc_connector:Successfully sent gRPC event e200ab8d-7f52-4ab3-bf20-b81eb0ff8cc5 DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Extracted 0 messages from response dict DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Processing 0 polled messages for claude DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Successfully converted 0 messages to Events DEBUG:openagents.agents.runner:🔍 AGENT_RUNNER: Checking for messages... Found 1 threads DEBUG:openagents.core.client:🔧 CLIENT: Polling attempt #2 for agent claude DEBUG:grpc._cython.cygrpc:[_cygrpc] Loaded running loop: id(loop)=279010284531456 DEBUG:openagents.agents.runner:🔍 AGENT_RUNNER: Checking for messages... Found 1 threads DEBUG:openagents.core.connectors.grpc_connector:Successfully decoded response data as JSON DEBUG:openagents.core.connectors.grpc_connector:Successfully sent gRPC event 36cba12f-15a6-496a-8332-2c0d1f8c9da8 DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Extracted 0 messages from response dict DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Processing 0 polled messages for claude DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Successfully converted 0 messages to Events DEBUG:openagents.agents.runner:🔍 AGENT_RUNNER: Checking for messages... Found 1 threads DEBUG:openagents.core.client:🔧 CLIENT: Polling attempt #3 for agent claude DEBUG:grpc._cython.cygrpc:[_cygrpc] Loaded running loop: id(loop)=279010284531456 DEBUG:openagents.core.connectors.grpc_connector:Successfully decoded response data as JSON DEBUG:openagents.core.connectors.grpc_connector:Successfully sent gRPC event c8b718b3-4414-4d2f-b046-dbd93f7396b8 DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Extracted 0 messages from response dict DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Processing 0 polled messages for claude DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Successfully converted 0 messages to Events DEBUG:openagents.agents.runner:🔍 AGENT_RUNNER: Checking for messages... Found 1 threads DEBUG:openagents.core.client:🔧 CLIENT: Polling attempt #4 for agent claude DEBUG:grpc._cython.cygrpc:[_cygrpc] Loaded running loop: id(loop)=279010284531456 DEBUG:openagents.core.connectors.grpc_connector:Successfully decoded response data as JSON DEBUG:openagents.core.connectors.grpc_connector:Successfully sent gRPC event 75bac8bd-1f17-4475-bc6e-faed5ed543b8 DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Extracted 0 messages from response dict DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Processing 0 polled messages for claude DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Successfully converted 0 messages to Events DEBUG:openagents.agents.runner:🔍 AGENT_RUNNER: Checking for messages... Found 1 threads DEBUG:openagents.core.client:🔧 CLIENT: Polling attempt #5 for agent claude DEBUG:grpc._cython.cygrpc:[_cygrpc] Loaded running loop: id(loop)=279010284531456 DEBUG:openagents.core.connectors.grpc_connector:Successfully decoded response data as JSON DEBUG:openagents.core.connectors.grpc_connector:Successfully sent gRPC event cdea2787-f54c-4552-90d6-236ec14996e6 DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Extracted 0 messages from response dict DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Processing 0 polled messages for claude DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Successfully converted 0 messages to Events DEBUG:openagents.agents.runner:🔍 AGENT_RUNNER: Checking for messages... Found 1 threads DEBUG:openagents.core.client:🔧 CLIENT: Polling attempt #6 for agent claude DEBUG:grpc._cython.cygrpc:[_cygrpc] Loaded running loop: id(loop)=279010284531456 DEBUG:openagents.core.connectors.grpc_connector:Successfully decoded response data as JSON DEBUG:openagents.core.connectors.grpc_connector:Successfully sent gRPC event 5ed90182-b9f0-41b9-b790-8f2e00ca643d DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Extracted 0 messages from response dict DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Processing 0 polled messages for claude DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Successfully converted 0 messages to Events DEBUG:openagents.agents.runner:🔍 AGENT_RUNNER: Checking for messages... Found 1 threads DEBUG:openagents.core.client:🔧 CLIENT: Polling attempt #7 for agent claude DEBUG:grpc._cython.cygrpc:[_cygrpc] Loaded running loop: id(loop)=279010284531456 DEBUG:openagents.core.connectors.grpc_connector:Successfully decoded response data as JSON DEBUG:openagents.core.connectors.grpc_connector:Successfully sent gRPC event 5065c6ee-5c52-4288-897e-774496fb5799 DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Extracted 0 messages from response dict DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Processing 0 polled messages for claude DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Successfully converted 0 messages to Events DEBUG:openagents.agents.runner:🔍 AGENT_RUNNER: Checking for messages... Found 1 threads DEBUG:openagents.core.client:🔧 CLIENT: Polling attempt #8 for agent claude DEBUG:grpc._cython.cygrpc:[_cygrpc] Loaded running loop: id(loop)=279010284531456 DEBUG:openagents.core.connectors.grpc_connector:Successfully decoded response data as JSON DEBUG:openagents.core.connectors.grpc_connector:Successfully sent gRPC event fa5ca55b-7979-44ca-8300-4649aa1c37ce DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Extracted 0 messages from response dict DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Processing 0 polled messages for claude DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Successfully converted 0 messages to Events DEBUG:openagents.agents.runner:🔍 AGENT_RUNNER: Checking for messages... Found 1 threads DEBUG:openagents.core.client:🔧 CLIENT: Polling attempt #9 for agent claude DEBUG:grpc._cython.cygrpc:[_cygrpc] Loaded running loop: id(loop)=279010284531456 DEBUG:openagents.core.connectors.grpc_connector:Successfully decoded response data as JSON DEBUG:openagents.core.connectors.grpc_connector:Successfully sent gRPC event 593fa986-03e0-46eb-8f2c-2843b8a39d57 DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Extracted 0 messages from response dict DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Processing 0 polled messages for claude DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Successfully converted 0 messages to Events DEBUG:openagents.agents.runner:🔍 AGENT_RUNNER: Checking for messages... Found 1 threads DEBUG:openagents.core.client:🔧 CLIENT: Polling attempt #10 for agent claude DEBUG:grpc._cython.cygrpc:[_cygrpc] Loaded running loop: id(loop)=279010284531456 DEBUG:openagents.core.connectors.grpc_connector:Successfully decoded response data as JSON DEBUG:openagents.core.connectors.grpc_connector:Successfully sent gRPC event c465321c-8ce4-4628-b525-08a554b49f89 DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Extracted 0 messages from response dict DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Processing 0 polled messages for claude DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Successfully converted 0 messages to Events DEBUG:openagents.agents.runner:🔍 AGENT_RUNNER: Checking for messages... Found 1 threads DEBUG:openagents.core.client:🔧 CLIENT: Polling attempt #11 for agent claude DEBUG:grpc._cython.cygrpc:[_cygrpc] Loaded running loop: id(loop)=279010284531456 DEBUG:openagents.core.connectors.grpc_connector:Successfully decoded response data as JSON DEBUG:openagents.core.connectors.grpc_connector:Successfully sent gRPC event 4c7b8c7b-f827-4c5e-a554-32a1b6d9aef3 DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Extracted 0 messages from response dict DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Processing 0 polled messages for claude DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Successfully converted 0 messages to Events DEBUG:openagents.agents.runner:🔍 AGENT_RUNNER: Checking for messages... Found 1 threads DEBUG:openagents.core.client:🔧 CLIENT: Polling attempt #12 for agent claude DEBUG:grpc._cython.cygrpc:[_cygrpc] Loaded running loop: id(loop)=279010284531456 DEBUG:openagents.core.connectors.grpc_connector:Successfully decoded response data as JSON DEBUG:openagents.core.connectors.grpc_connector:Successfully sent gRPC event e51190ac-e4a3-4443-bfdf-2cc9061eb8b4 DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Extracted 0 messages from response dict DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Processing 0 polled messages for claude DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Successfully converted 0 messages to Events DEBUG:openagents.agents.runner:🔍 AGENT_RUNNER: Checking for messages... Found 1 threads DEBUG:openagents.core.client:🔧 CLIENT: Polling attempt #13 for agent claude DEBUG:grpc._cython.cygrpc:[_cygrpc] Loaded running loop: id(loop)=279010284531456 DEBUG:openagents.core.connectors.grpc_connector:Successfully decoded response data as JSON DEBUG:openagents.core.connectors.grpc_connector:Successfully sent gRPC event ae428b7a-077a-4971-a95c-83d48833f191 DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Extracted 0 messages from response dict DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Processing 0 polled messages for claude DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Successfully converted 0 messages to Events DEBUG:openagents.agents.runner:🔍 AGENT_RUNNER: Checking for messages... Found 1 threads DEBUG:openagents.core.client:🔧 CLIENT: Polling attempt #14 for agent claude DEBUG:grpc._cython.cygrpc:[_cygrpc] Loaded running loop: id(loop)=279010284531456 DEBUG:openagents.core.connectors.grpc_connector:Successfully decoded response data as JSON DEBUG:openagents.core.connectors.grpc_connector:Successfully sent gRPC event a9ba8ea2-2cd4-4a64-bf30-3493c702e8c1 DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Extracted 0 messages from response dict DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Processing 0 polled messages for claude DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Successfully converted 0 messages to Events DEBUG:openagents.agents.runner:🔍 AGENT_RUNNER: Checking for messages... Found 1 threads DEBUG:openagents.core.client:🔧 CLIENT: Polling attempt #15 for agent claude DEBUG:grpc._cython.cygrpc:[_cygrpc] Loaded running loop: id(loop)=279010284531456 DEBUG:openagents.core.connectors.grpc_connector:Successfully decoded response data as JSON DEBUG:openagents.core.connectors.grpc_connector:Successfully sent gRPC event 064c2f69-c7e5-438a-8562-ea33646daa74 DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Extracted 0 messages from response dict DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Processing 0 polled messages for claude DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Successfully converted 0 messages to Events DEBUG:openagents.agents.runner:🔍 AGENT_RUNNER: Checking for messages... Found 1 threads DEBUG:openagents.core.client:🔧 CLIENT: Polling attempt #16 for agent claude DEBUG:grpc._cython.cygrpc:[_cygrpc] Loaded running loop: id(loop)=279010284531456 DEBUG:openagents.core.connectors.grpc_connector:Successfully decoded response data as JSON DEBUG:openagents.core.connectors.grpc_connector:Successfully sent gRPC event 2540874b-168e-4c61-8e9a-4d5b35b118d3 DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Extracted 0 messages from response dict DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Processing 0 polled messages for claude DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Successfully converted 0 messages to Events DEBUG:openagents.agents.runner:🔍 AGENT_RUNNER: Checking for messages... Found 1 threads DEBUG:openagents.core.client:🔧 CLIENT: Polling attempt #17 for agent claude DEBUG:grpc._cython.cygrpc:[_cygrpc] Loaded running loop: id(loop)=279010284531456 DEBUG:openagents.core.connectors.grpc_connector:Successfully decoded response data as JSON DEBUG:openagents.core.connectors.grpc_connector:Successfully sent gRPC event 59191438-5003-47f5-a0f7-e5dfe03a3aa5 DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Extracted 0 messages from response dict DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Processing 0 polled messages for claude DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Successfully converted 0 messages to Events DEBUG:openagents.agents.runner:🔍 AGENT_RUNNER: Checking for messages... Found 1 threads DEBUG:openagents.core.client:🔧 CLIENT: Polling attempt #18 for agent claude DEBUG:grpc._cython.cygrpc:[_cygrpc] Loaded running loop: id(loop)=279010284531456 DEBUG:openagents.core.connectors.grpc_connector:Successfully decoded response data as JSON DEBUG:openagents.core.connectors.grpc_connector:Successfully sent gRPC event 41bc4758-b698-4e7c-9958-58c68ff08ce8 DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Extracted 0 messages from response dict DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Processing 0 polled messages for claude DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Successfully converted 0 messages to Events DEBUG:openagents.agents.runner:🔍 AGENT_RUNNER: Checking for messages... Found 1 threads DEBUG:openagents.core.client:🔧 CLIENT: Polling attempt #19 for agent claude DEBUG:grpc._cython.cygrpc:[_cygrpc] Loaded running loop: id(loop)=279010284531456 DEBUG:openagents.core.connectors.grpc_connector:Successfully decoded response data as JSON DEBUG:openagents.core.connectors.grpc_connector:Successfully sent gRPC event 224261b8-a3d2-4681-98be-2d84bbda200d DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Extracted 0 messages from response dict DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Processing 0 polled messages for claude DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Successfully converted 0 messages to Events DEBUG:openagents.agents.runner:🔍 AGENT_RUNNER: Checking for messages... Found 1 threads DEBUG:openagents.core.client:🔧 CLIENT: Polling attempt #20 for agent claude DEBUG:grpc._cython.cygrpc:[_cygrpc] Loaded running loop: id(loop)=279010284531456 DEBUG:openagents.core.connectors.grpc_connector:Successfully decoded response data as JSON DEBUG:openagents.core.connectors.grpc_connector:Successfully sent gRPC event f2944c29-223c-48cb-9313-9f5c9bbf7aa1 DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Extracted 0 messages from response dict DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Processing 0 polled messages for claude DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Successfully converted 0 messages to Events DEBUG:openagents.agents.runner:🔍 AGENT_RUNNER: Checking for messages... Found 1 threads DEBUG:openagents.core.client:🔧 CLIENT: Polling attempt #21 for agent claude DEBUG:grpc._cython.cygrpc:[_cygrpc] Loaded running loop: id(loop)=279010284531456 DEBUG:openagents.core.connectors.grpc_connector:Successfully decoded response data as JSON DEBUG:openagents.core.connectors.grpc_connector:Successfully sent gRPC event fcc9a42b-93b9-4cc1-b95e-be4c050a116a DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Extracted 0 messages from response dict DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Processing 0 polled messages for claude DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Successfully converted 0 messages to Events DEBUG:openagents.agents.runner:🔍 AGENT_RUNNER: Checking for messages... Found 1 threads DEBUG:openagents.core.client:🔧 CLIENT: Polling attempt #22 for agent claude DEBUG:grpc._cython.cygrpc:[_cygrpc] Loaded running loop: id(loop)=279010284531456 DEBUG:openagents.core.connectors.grpc_connector:Successfully decoded response data as JSON DEBUG:openagents.core.connectors.grpc_connector:Successfully sent gRPC event a53acf71-83e9-4130-8184-d184c4aad580 DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Extracted 0 messages from response dict DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Processing 0 polled messages for claude DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Successfully converted 0 messages to Events DEBUG:openagents.agents.runner:🔍 AGENT_RUNNER: Checking for messages... Found 1 threads DEBUG:openagents.core.client:🔧 CLIENT: Polling attempt #23 for agent claude DEBUG:grpc._cython.cygrpc:[_cygrpc] Loaded running loop: id(loop)=279010284531456 DEBUG:openagents.core.connectors.grpc_connector:Successfully decoded response data as JSON DEBUG:openagents.core.connectors.grpc_connector:Successfully sent gRPC event 315078c1-fd26-4cce-ac53-3e0bb525fab8 DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Extracted 0 messages from response dict DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Processing 0 polled messages for claude DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Successfully converted 0 messages to Events DEBUG:openagents.agents.runner:🔍 AGENT_RUNNER: Checking for messages... Found 1 threads DEBUG:openagents.core.client:🔧 CLIENT: Polling attempt #24 for agent claude DEBUG:grpc._cython.cygrpc:[_cygrpc] Loaded running loop: id(loop)=279010284531456 DEBUG:openagents.core.connectors.grpc_connector:Successfully decoded response data as JSON DEBUG:openagents.core.connectors.grpc_connector:Successfully sent gRPC event 54b8d3ff-e6af-415e-bf1d-96ef519b634f DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Extracted 0 messages from response dict DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Processing 0 polled messages for claude DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Successfully converted 0 messages to Events DEBUG:openagents.agents.runner:🔍 AGENT_RUNNER: Checking for messages... Found 1 threads DEBUG:openagents.core.client:🔧 CLIENT: Polling attempt #25 for agent claude DEBUG:grpc._cython.cygrpc:[_cygrpc] Loaded running loop: id(loop)=279010284531456 DEBUG:openagents.core.connectors.grpc_connector:Successfully decoded response data as JSON DEBUG:openagents.core.connectors.grpc_connector:Successfully sent gRPC event 118358eb-3a0a-4ada-b233-96e0b123d4e6 DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Extracted 0 messages from response dict DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Processing 0 polled messages for claude DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Successfully converted 0 messages to Events DEBUG:openagents.agents.runner:🔍 AGENT_RUNNER: Checking for messages... Found 1 threads DEBUG:openagents.core.client:🔧 CLIENT: Polling attempt #26 for agent claude DEBUG:grpc._cython.cygrpc:[_cygrpc] Loaded running loop: id(loop)=279010284531456 DEBUG:openagents.core.connectors.grpc_connector:Successfully decoded response data as JSON DEBUG:openagents.core.connectors.grpc_connector:Successfully sent gRPC event 1f5e0a8c-66db-4c98-ac73-f424500d2f69 DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Extracted 0 messages from response dict DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Processing 0 polled messages for claude DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Successfully converted 0 messages to Events DEBUG:openagents.agents.runner:🔍 AGENT_RUNNER: Checking for messages... Found 1 threads DEBUG:openagents.core.client:🔧 CLIENT: Polling attempt #27 for agent claude DEBUG:grpc._cython.cygrpc:[_cygrpc] Loaded running loop: id(loop)=279010284531456 DEBUG:openagents.core.connectors.grpc_connector:Successfully decoded response data as JSON DEBUG:openagents.core.connectors.grpc_connector:Successfully sent gRPC event a1f0a35d-e709-44bb-8fdd-62e4c7be7c3e DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Extracted 0 messages from response dict DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Processing 0 polled messages for claude DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Successfully converted 0 messages to Events DEBUG:openagents.agents.runner:🔍 AGENT_RUNNER: Checking for messages... Found 1 threads DEBUG:openagents.core.client:🔧 CLIENT: Polling attempt #28 for agent claude DEBUG:grpc._cython.cygrpc:[_cygrpc] Loaded running loop: id(loop)=279010284531456 DEBUG:openagents.core.connectors.grpc_connector:Successfully decoded response data as JSON DEBUG:openagents.core.connectors.grpc_connector:Successfully sent gRPC event 178451cf-698e-4d2d-9966-7ddac7c40792 DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Extracted 0 messages from response dict DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Processing 0 polled messages for claude DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Successfully converted 0 messages to Events DEBUG:openagents.agents.runner:🔍 AGENT_RUNNER: Checking for messages... Found 1 threads DEBUG:openagents.core.client:🔧 CLIENT: Polling attempt #29 for agent claude DEBUG:grpc._cython.cygrpc:[_cygrpc] Loaded running loop: id(loop)=279010284531456 DEBUG:openagents.core.connectors.grpc_connector:Successfully decoded response data as JSON DEBUG:openagents.core.connectors.grpc_connector:Successfully sent gRPC event c57426e5-3726-487d-b308-c77678ea2227 DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Extracted 0 messages from response dict DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Processing 0 polled messages for claude DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Successfully converted 0 messages to Events DEBUG:openagents.agents.runner:🔍 AGENT_RUNNER: Checking for messages... Found 1 threads DEBUG:openagents.core.client:🔧 CLIENT: Polling attempt #30 for agent claude DEBUG:grpc._cython.cygrpc:[_cygrpc] Loaded running loop: id(loop)=279010284531456 DEBUG:openagents.core.connectors.grpc_connector:Successfully decoded response data as JSON DEBUG:openagents.core.connectors.grpc_connector:Successfully sent gRPC event 7df8beff-16b9-4803-892b-f07034a41d8f DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Extracted 0 messages from response dict DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Processing 0 polled messages for claude DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Successfully converted 0 messages to Events DEBUG:openagents.agents.runner:🔍 AGENT_RUNNER: Checking for messages... Found 1 threads DEBUG:openagents.core.client:🔧 CLIENT: Polling attempt #31 for agent claude DEBUG:grpc._cython.cygrpc:[_cygrpc] Loaded running loop: id(loop)=279010284531456 DEBUG:openagents.core.connectors.grpc_connector:Successfully decoded response data as JSON DEBUG:openagents.core.connectors.grpc_connector:Successfully sent gRPC event a417366b-69fb-4dd5-984f-fd6d9b85a241 DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Extracted 0 messages from response dict DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Processing 0 polled messages for claude DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Successfully converted 0 messages to Events DEBUG:openagents.agents.runner:🔍 AGENT_RUNNER: Checking for messages... Found 1 threads DEBUG:openagents.core.client:🔧 CLIENT: Polling attempt #32 for agent claude DEBUG:grpc._cython.cygrpc:[_cygrpc] Loaded running loop: id(loop)=279010284531456 DEBUG:openagents.core.connectors.grpc_connector:Successfully decoded response data as JSON DEBUG:openagents.core.connectors.grpc_connector:Successfully sent gRPC event da2d78e1-00ca-4d79-badf-9feb8f2ad7ce DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Extracted 0 messages from response dict DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Processing 0 polled messages for claude DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Successfully converted 0 messages to Events DEBUG:openagents.agents.runner:🔍 AGENT_RUNNER: Checking for messages... Found 1 threads DEBUG:openagents.core.client:🔧 CLIENT: Polling attempt #33 for agent claude DEBUG:grpc._cython.cygrpc:[_cygrpc] Loaded running loop: id(loop)=279010284531456 DEBUG:openagents.core.connectors.grpc_connector:Successfully decoded response data as JSON DEBUG:openagents.core.connectors.grpc_connector:Successfully sent gRPC event a8ba2d76-13cc-4784-ab3c-7bc784e79ab7 DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Extracted 0 messages from response dict DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Processing 0 polled messages for claude DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Successfully converted 0 messages to Events DEBUG:openagents.agents.runner:🔍 AGENT_RUNNER: Checking for messages... Found 1 threads DEBUG:openagents.core.client:🔧 CLIENT: Polling attempt #34 for agent claude DEBUG:grpc._cython.cygrpc:[_cygrpc] Loaded running loop: id(loop)=279010284531456 DEBUG:openagents.core.connectors.grpc_connector:Successfully decoded response data as JSON DEBUG:openagents.core.connectors.grpc_connector:Successfully sent gRPC event 2a119292-6a0a-4c19-b9e3-e9104599b224 DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Extracted 0 messages from response dict DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Processing 0 polled messages for claude DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Successfully converted 0 messages to Events DEBUG:openagents.agents.runner:🔍 AGENT_RUNNER: Checking for messages... Found 1 threads DEBUG:openagents.core.client:🔧 CLIENT: Polling attempt #35 for agent claude DEBUG:grpc._cython.cygrpc:[_cygrpc] Loaded running loop: id(loop)=279010284531456 DEBUG:openagents.core.connectors.grpc_connector:Successfully decoded response data as JSON DEBUG:openagents.core.connectors.grpc_connector:Successfully sent gRPC event b23ca6fa-cac9-4e1c-9d3b-e39aed9f9396 DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Extracted 0 messages from response dict DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Processing 0 polled messages for claude DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Successfully converted 0 messages to Events DEBUG:openagents.agents.runner:🔍 AGENT_RUNNER: Checking for messages... Found 1 threads DEBUG:openagents.core.client:🔧 CLIENT: Polling attempt #36 for agent claude DEBUG:grpc._cython.cygrpc:[_cygrpc] Loaded running loop: id(loop)=279010284531456 DEBUG:openagents.core.connectors.grpc_connector:Successfully decoded response data as JSON DEBUG:openagents.core.connectors.grpc_connector:Successfully sent gRPC event b1a212bc-df85-461f-952e-7f079d55b30d DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Extracted 0 messages from response dict DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Processing 0 polled messages for claude DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Successfully converted 0 messages to Events DEBUG:openagents.agents.runner:🔍 AGENT_RUNNER: Checking for messages... Found 1 threads DEBUG:openagents.core.client:🔧 CLIENT: Polling attempt #37 for agent claude DEBUG:grpc._cython.cygrpc:[_cygrpc] Loaded running loop: id(loop)=279010284531456 DEBUG:openagents.core.connectors.grpc_connector:Successfully decoded response data as JSON DEBUG:openagents.core.connectors.grpc_connector:Successfully sent gRPC event 24468621-54b1-48fa-bf8c-fea9c7e34122 DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Extracted 0 messages from response dict DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Processing 0 polled messages for claude DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Successfully converted 0 messages to Events DEBUG:openagents.agents.runner:🔍 AGENT_RUNNER: Checking for messages... Found 1 threads DEBUG:openagents.core.client:🔧 CLIENT: Polling attempt #38 for agent claude DEBUG:grpc._cython.cygrpc:[_cygrpc] Loaded running loop: id(loop)=279010284531456 DEBUG:openagents.core.connectors.grpc_connector:Successfully decoded response data as JSON DEBUG:openagents.core.connectors.grpc_connector:Successfully sent gRPC event 128f399e-8c92-4d31-bcdd-d3fa17006162 DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Extracted 0 messages from response dict DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Processing 0 polled messages for claude DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Successfully converted 0 messages to Events DEBUG:openagents.agents.runner:🔍 AGENT_RUNNER: Checking for messages... Found 1 threads DEBUG:openagents.core.client:🔧 CLIENT: Polling attempt #39 for agent claude DEBUG:grpc._cython.cygrpc:[_cygrpc] Loaded running loop: id(loop)=279010284531456 DEBUG:openagents.core.connectors.grpc_connector:Successfully decoded response data as JSON DEBUG:openagents.core.connectors.grpc_connector:Successfully sent gRPC event 58b65418-dc69-46ed-9b92-9c8cbb26e946 DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Extracted 1 messages from response dict DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Processing 1 polled messages for claude DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Successfully converted message to Event: 29d2f101-eeb3-48ec-bb5d-36301b1a4a74 DEBUG:openagents.core.connectors.grpc_connector:🔧 GRPC: Successfully converted 1 messages to Events ╔══════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════╗ ║ 📥 RECEIVED EVENT ║ ╠══════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════╣ ║ Event: thread.channel_message.notification ║ ║ Source: admin ║ ║ Target: claude ║ ║ ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────── ║ ║ { ║ ║ "channel": "general", ║ ║ "content": { ║ ║ "text": "Hi Claude. Test 210 ... can you reply back with a Hello?" ║ ║ }, ║ ║ "message_type": "channel_message", ║ ║ "original_event_id": "admin_1773785928829_oj9dwqox4" ║ ║ } ║ ╚══════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════╝ INFO:openagents.core.client:📥 RECEIVED EVENT: thread.channel_message.notification | Source: admin | Target: claude DEBUG:openagents.agents.runner:🔍 AGENT_RUNNER: Checking for messages... Found 2 threads 🔧 AGENT_RUNNER: Calling react method for event thread.channel_message.notification DEBUG:openagents.agents.orchestrator:Using event-based LLM logger for agent claude ╔══════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════╗ ║ 🎯 STARTING ORCHESTRATION ║ ╠══════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════╣ ║ Thread: thread:thread.channel_message ║ ║ Event: thread.channel_message.notification ║ ╚══════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════╝ DEBUG:openagents.core.client:🔧 CLIENT: Polling attempt #40 for agent claude DEBUG:grpc._cython.cygrpc:[_cygrpc] Loaded running loop: id(loop)=279010284531456 DEBUG:openai._base_client:Request options: {'method': 'post', 'url': '/chat/completions', 'files': None, 'idempotency_key': 'stainless-python-retry-2d1e5e37-ed38-4da8-a152-a5f09498c1ea', 'content': None, 'json_data': {'messages': [{'role': 'system', 'content': "You are Claude, a helpful Agent in an OpenAgents network.\n Respond to the user's message in a helpful and friendly way."}, {'role': 'user', 'content': '<conversation>\n <threads>\n \n <thread id="thread:thread.channel_message">\n \n <message sender="admin" event_id="29d2f101-eeb3-48ec-bb5d-36301b1a4a74">\n \n <content>{\'channel\': \'general\', \'content\': {\'text\

[conjureup96]

Re: your item #4 ... I was able to get Claude's responses seen in the channel by modifying the example script as follows: <        messaging = self.client.mod_adapters.get("openagents.mods.workspace.messaging") <        if messaging: <            channel = "general" <            await messaging.send_channel_message( <                channel=channel, <                text=f"Response: {response}" <                )         ws = self.workspace()         await ws.channel("#general").post(response) That also allowed me to remove the workspace messaging mod dependency. When I enabled debugging, send_channel_message() never seemed to appear in the output. I tried several alternatives for the "text=" line and none worked. The "ws" method DOES seem to work though. I've been testing different responses to omit the display of reasoning output and keeping responses short unless details are requested. So far Claude always sends the <think></think> output ... although it is much shorter now unless I ask for a lengthier response. I'll do the same tests with Gemini, DeepSeek, GPT, etc. Maybe as a group they can figure out what I was doing wrong. ;P If you find an explanation of why the send_channel_message() approach doesn't work please let me know.  :)  Thanks again for the assistance !! Regards, Chris aka ConjureUp96

…

On 3/17/2026 4:39 PM, Chris Konger wrote: For your item #4, attached is debug output from the script. Either the debug level doesn't propagate into the messaging mod or something is preventing send_channel_message() from loading ... and not throwing any errors. The lengthy debug output confirms what was observed from the script output and packet captures (the orchestration with the ai model backend and extraction of content is working fine). Regards, ConjureUp96 On 3/17/2026 3:49 PM, Chris Konger wrote: > > > For your item #3, I think the content is being extracted with no > issues whatsoever! > > I inserted a single link before the messaging call ... > >         print (response) > >         # Send the response to the channel >         messaging = > self.client.mod_adapters.get("openagents.mods.workspace.messaging") >         snip > > The output I'm getting looks exactly what I am seeing from the > Wireshark captures. > > So the final hurdle (your item #4) seems to be posting that response > content back into the channel. It looks like that functionality DOES > use one of the mods, so I reverted disable_mods=False. > > I'm still not seeing it post the response to the channel, so I'll try > to use logging functionality on that send_channel_message function > call to see if I can figure out why it is not succeeding. Close !! :) > > _*EXAMPLE OUTPUT*_ > > <think> > The user is asking me to simply reply back with a hello. This is a > straightforward request that doesn't require any tool usage. > > I should just respond with a simple hello as requested. > </think> > > Hello! > ✅ AGENT RESPONSE COMPLETED: 79c064b5 >    Processing time: 5.83s >    🤖 LLM API call detected (response time > 1s) >    Message marked as processed > > _*EXAMPLE OUTPUT*_ > > <think> > I need to respond to the incoming message from "admin". The message > says: "Test 208. I got your plain text Claude ... can you confirm one > more time that you are here?" > > This is a simple confirmation request. The admin wants me to confirm > my presence. > > Since there are no tools required to answer this, I should just > provide a plain text response confirming that I'm here. > > The instruction says: "Respond to: {'text': 'Test 208. I got your > plain text Claude ... can you confirm one more time that you are > here?'} without tools, just use direct plain text." > > So I'll craft a simple, friendly confirmation response. > </think> > > Sure, I'm here — happy to help whenever you need! > ✅ AGENT RESPONSE COMPLETED: eb8b146a >    Processing time: 19.78s >    🤖 LLM API call detected (response time > 1s) >    Message marked as processed > > On 3/17/2026 1:46 PM, Chris Konger wrote: >> >> >> As requested, here is the entire react/trajectory section ... I >> tried setting the "disable" options to True earlier but still see >> Tool responses being returned. That is additional support for what >> you mention in your second point (that the event context seems to >> enable tools even when they are not needed). >> >> I even tried changing the Instructions to the AI to return results >> using different text formats. For example, asking it to return as a >> "send_channel_message" does result in that format (but there doesn't >> seem to be any handler that can parse that result) ... >> >>     async def react(self, context: EventContext): >>         """React to incoming messages using LLM.""" >>         event = context.incoming_event >> >>         # Skip our own messages >>         if event.source_id == self.agent_id: >>             return >> >>         # Get message content from payload >>         content = event.payload.get("content") or >> event.payload.get("text") or "" >>         if not content: >>             return >> >>         # Use run_agent to generate LLM response >>         try: >>             trajectory = await self.run_agent( >>                 context=context, >>                 disable_mcp=True, >>                 disable_mods=True, >> instruction=f"Respond to: {content}. Use send_channel_message NOT >> reply_channel_message.", >>             ) >> >>             # Extract the response from the trajectory >>             response = None >>             for action in trajectory.actions: >>                 if action.payload and action.payload.get("response"): >>                     response = action.payload["response"] >>                     break >> >>             if not response: >>                 response = "I'm sorry, I couldn't generate a response." >> >>         except Exception as e: >>             print(f"LLM error: {e}") >>             response = f"Sorry, I encountered an error: {str(e)[:50]}" >> >>         # Send the response to the channel >>         messaging = >> self.client.mod_adapters.get("openagents.mods.workspace.messaging") >>         if messaging: >>             channel = event.payload.get("channel") or "general" >>             await messaging.send_channel_message( >>                 channel=channel, >>                 text=response >>             ) >>             print(f"Responded to {event.source_id}: {response[:50]}...") >> >> The returned response is ... >> >> ╔════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════╗ >> ║ 🔧 AGENT TOOL CALL     ║ >> ╠════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════╣ >> ║ Tool: *send_channel_message*     ║ >> ║ Args: {"channel": "general", "content": "Hello back! Yes, I'm here >> and ready to help. What can I do for you today?"}               ║ >> ╚════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════╝ >> >> Here are what the above exchanges look like from the perspective of >> Wireshark ... >> >> POST /v1/chat/completions HTTP/1.1 >> Host: 192.168.2.201:1080 >> Accept-Encoding: gzip, deflate >> Connection: keep-alive >> Accept: application/json >> Content-Type: application/json >> User-Agent: AsyncOpenAI/Python 2.26.0 >> X-Stainless-Lang: python >> X-Stainless-Package-Version: 2.26.0 >> X-Stainless-OS: Linux >> X-Stainless-Arch: arm64 >> X-Stainless-Runtime: CPython >> X-Stainless-Runtime-Version: 3.12.13 >> Authorization: Bearer gpustack_snipsnipsnip >> X-Stainless-Async: async:asyncio >> x-stainless-retry-count: 0 >> x-stainless-read-timeout: 600 >> Content-Length: 2418 >> >> {"messages":[{"role":"system","content":"You are Claude, a helpful >> Agent in an OpenAgents network.\n Respond to the user's message in a >> helpful and friendly >> way."},{"role":"user","content":"<conversation>\n <threads>\n \n >> <thread id=\"thread:thread.channel_message\">\n \n <message >> sender=\"admin\" >> event_id=\"32679622-72d3-4253-93fa-826b16ec916c\">\n \n >> <content>{'channel': 'general', 'content': {'text': 'Test 200 ... >> are you there Claude?'}, 'message_type': 'channel_message', >> 'original_event_id': 'admin_1773775769517_t5y3bdujl'}</content>\n \n >> </message>\n \n </thread>\n \n </threads>\n\n >> <current_interaction>\n >> <incoming_thread_id>thread:thread.channel_message</incoming_thread_id>\n >> <incoming_message sender=\"admin\" >> event_id=\"32679622-72d3-4253-93fa-826b16ec916c\">\n \n >> <content>{'channel': 'general', 'content': {'text': 'Test 200 ... >> are you there Claude?'}, 'message_type': 'channel_message', >> 'original_event_id': 'admin_1773775769517_t5y3bdujl'}</content>\n \n >> </incoming_message>\n >> </current_interaction>\n</conversation>\n\nPlease respond to the >> incoming message based on the context provided. You have access to >> tools that you can use if needed.\n\nIMPORTANT: When replying to >> messages, use the message's event_id (not the thread_id) as the >> reply_to_id parameter.\n- To reply to a channel message: use >> reply_channel_message with the message's event_id\n- To reply to a >> direct message: use reply_direct_message with the message's >> event_id\n- Thread ID is for context only, always use event_id for >> replies\n\nIn each step, you MUST either:\n1. Call a tool to perform >> an action, or\n2. Use the finish tool when you've completed all >> necessary actions.\n\nIf you don't need to use any tools, use the >> finish tool directly.\n\nRespond to: {'text': 'Test 200 ... are you >> there Claude?'}. Use send_channel_message NOT >> reply_channel_message."}],"model":"Claude-4.5-Opus","tool_choice":"auto","tools":[{"type":"function","function":{"name":"finish","description":"Use >> this tool when you have completed all necessary actions and don't >> need to do anything >> else.","parameters":{"type":"object","properties":{"reason":{"type":"string","description":"Reason >> for finishing the action chain."}},"required":["reason"]}}}]} >> >> >> HTTP/1.1 200 OK >> >> date: Tue, 17 Mar 2026 19:29:31 GMT,Tue, 17 Mar 2026 19:29:31 GMT >> >> server: istio-envoy >> >> content-type: application/json >> >> req-cost-time: 16070 >> >> req-arrive-time: 1773775771255 >> >> resp-start-time: 1773775787326 >> >> x-envoy-upstream-service-time: 16018 >> >> content-encoding: gzip >> >> vary: Accept-Encoding >> >> transfer-encoding: chunked >> >> >> {"id":"chatcmpl-caa0ccb0-0f22-44bd-aea3-087e701ed3ca","object":"chat.completion","created":1773775771,"model":"Claude-4.5-Opus","choices":[{"index":0,"message":{"role":"assistant","content":"<think>\nI >> need to respond to the message \"Test 200 ... are you there >> Claude?\" in the general channel.\n\nSince this is the first message >> in the conversation and it's a general channel message, I should use >> the send_channel_message tool to post my response.\n\nThe user is >> asking if I'm here, so I'll confirm my presence and ask them what >> they need help >> with.\n</think>\n\n","refusal":null,"annotations":null,"audio":null,"function_call":null,"tool_calls":[{"id":"chatcmpl-tool-707d958cf2ba424bb1d6d4cec1ad7d35","type":"function","function":{"name":"send_channel_message","arguments":"{\"channel\": >> \"general\", \"content\": \"Hello! Yes, I'm here and ready to help. >> What can I do for you >> today?\"}"}}],"reasoning_content":null},"logprobs":null,"finish_reason":"tool_calls","stop_reason":null,"token_ids":null}],"service_tier":null,"system_fingerprint":null,"usage":{"prompt_tokens":679,"total_tokens":807,"completion_tokens":128,"prompt_tokens_details":null,"tokens_per_second":9769.23,"time_to_first_token_ms":16070,"time_per_output_token_ms":0.1},"prompt_logprobs":null,"prompt_token_ids":null,"kv_transfer_params":null} >> >> >> POST /v1/chat/completions HTTP/1.1 >> >> Host: 192.168.2.201:1080 >> >> Accept-Encoding: gzip, deflate >> >> Connection: keep-alive >> >> Accept: application/json >> >> Content-Type: application/json >> >> User-Agent: AsyncOpenAI/Python 2.26.0 >> >> X-Stainless-Lang: python >> >> X-Stainless-Package-Version: 2.26.0 >> >> X-Stainless-OS: Linux >> >> X-Stainless-Arch: arm64 >> >> X-Stainless-Runtime: CPython >> >> X-Stainless-Runtime-Version: 3.12.13 >> >> Authorization: Bearer gpustack_snipsnipsip >> >> X-Stainless-Async: async:asyncio >> >> x-stainless-retry-count: 0 >> >> x-stainless-read-timeout: 600 >> >> Content-Length: 3217 >> >> >> {"messages":[{"role":"system","content":"You are Claude, a helpful >> Agent in an OpenAgents network.\n Respond to the user's message in a >> helpful and friendly >> way."},{"role":"user","content":"<conversation>\n <threads>\n \n >> <thread id=\"thread:thread.channel_message\">\n \n <message >> sender=\"admin\" >> event_id=\"32679622-72d3-4253-93fa-826b16ec916c\">\n \n >> <content>{'channel': 'general', 'content': {'text': 'Test 200 ... >> are you there Claude?'}, 'message_type': 'channel_message', >> 'original_event_id': 'admin_1773775769517_t5y3bdujl'}</content>\n \n >> </message>\n \n </thread>\n \n </threads>\n\n >> <current_interaction>\n >> <incoming_thread_id>thread:thread.channel_message</incoming_thread_id>\n >> <incoming_message sender=\"admin\" >> event_id=\"32679622-72d3-4253-93fa-826b16ec916c\">\n \n >> <content>{'channel': 'general', 'content': {'text': 'Test 200 ... >> are you there Claude?'}, 'message_type': 'channel_message', >> 'original_event_id': 'admin_1773775769517_t5y3bdujl'}</content>\n \n >> </incoming_message>\n >> </current_interaction>\n</conversation>\n\nPlease respond to the >> incoming message based on the context provided. You have access to >> tools that you can use if needed.\n\nIMPORTANT: When replying to >> messages, use the message's event_id (not the thread_id) as the >> reply_to_id parameter.\n- To reply to a channel message: use >> reply_channel_message with the message's event_id\n- To reply to a >> direct message: use reply_direct_message with the message's >> event_id\n- Thread ID is for context only, always use event_id for >> replies\n\nIn each step, you MUST either:\n1. Call a tool to perform >> an action, or\n2. Use the finish tool when you've completed all >> necessary actions.\n\nIf you don't need to use any tools, use the >> finish tool directly.\n\nRespond to: {'text': 'Test 200 ... are you >> there Claude?'}. Use send_channel_message NOT >> reply_channel_message."},{"role":"assistant","tool_calls":[{"id":"chatcmpl-tool-707d958cf2ba424bb1d6d4cec1ad7d35","type":"function","function":{"name":"send_channel_message","arguments":"{\"channel\": >> \"general\", \"content\": \"Hello! Yes, I'm here and ready to help. >> What can I do for you today?\"}"}}],"content":"<think>\nI need to >> respond to the message \"Test 200 ... are you there Claude?\" in the >> general channel.\n\nSince this is the first message in the >> conversation and it's a general channel message, I should use the >> send_channel_message tool to post my response.\n\nThe user is asking >> if I'm here, so I'll confirm my presence and ask them what they need >> help >> with.\n</think>\n\n"},{"role":"tool","tool_call_id":"chatcmpl-tool-707d958cf2ba424bb1d6d4cec1ad7d35","content":"Tool >> 'send_channel_message' not >> found"}],"model":"Claude-4.5-Opus","tool_choice":"auto","tools":[{"type":"function","function":{"name":"finish","description":"Use >> this tool when you have completed all necessary actions and don't >> need to do anything >> else.","parameters":{"type":"object","properties":{"reason":{"type":"string","description":"Reason >> for finishing the action chain."}},"required":["reason"]}}}]} >> >> >> HTTP/1.1 200 OK >> >> date: Tue, 17 Mar 2026 19:29:47 GMT,Tue, 17 Mar 2026 19:29:47 GMT >> >> server: istio-envoy >> >> content-type: application/json >> >> req-cost-time: 11714 >> >> req-arrive-time: 1773775787350 >> >> resp-start-time: 1773775799064 >> >> x-envoy-upstream-service-time: 11711 >> >> content-encoding: gzip >> >> vary: Accept-Encoding >> >> transfer-encoding: chunked >> >> >> {"id":"chatcmpl-bcc0ad19-6c96-4aed-b344-4134107aafa3","object":"chat.completion","created":1773775787,"model":"Claude-4.5-Opus","choices":[{"index":0,"message":{"role":"assistant","content":"<think>\nI >> apologize, it seems I don't have access to the send_channel_message >> tool. Let me check what tools are available to me...\n\nLooking at >> my available tools, I only have the 'finish' tool that indicates >> I've completed my actions. This means I can't actually send a >> message in this environment.\n\nI'll let you know that I'm here to >> help, but I need to inform you that I can't send messages without >> the proper >> tool.","refusal":null,"annotations":null,"audio":null,"function_call":null,"tool_calls":[],"reasoning_content":null},"logprobs":null,"finish_reason":"stop","stop_reason":null,"token_ids":null}],"service_tier":null,"system_fingerprint":null,"usage":{"prompt_tokens":828,"total_tokens":922,"completion_tokens":94,"prompt_tokens_details":null,"time_to_first_token_ms":11716,"time_per_output_token_ms":0,"tokens_per_second":0},"prompt_logprobs":null,"prompt_token_ids":null,"kv_transfer_params":null} >> >> When I change the Python instruction to Return result in *PLAINTEXT* >> the script doesn't show any responses (in boxed format). It simply >> shows completion stats ... >> >> ✅ AGENT RESPONSE COMPLETED: 88e56cbf >>    Processing time: 9.72s >>    🤖 LLM API call detected (response time > 1s) >>    Message marked as processed >> >> But when I use Wireshark to look at the payloads, here are the API >> interactions ... >> >> POST /v1/chat/completions HTTP/1.1 >> Host: 192.168.2.201:1080 >> Accept-Encoding: gzip, deflate >> Connection: keep-alive >> Accept: application/json >> Content-Type: application/json >> User-Agent: AsyncOpenAI/Python 2.26.0 >> X-Stainless-Lang: python >> X-Stainless-Package-Version: 2.26.0 >> X-Stainless-OS: Linux >> X-Stainless-Arch: arm64 >> X-Stainless-Runtime: CPython >> X-Stainless-Runtime-Version: 3.12.13 >> Authorization: Bearer gpustack_snipsnipsnip >> X-Stainless-Async: async:asyncio >> x-stainless-retry-count: 0 >> x-stainless-read-timeout: 600 >> Content-Length: 2399 >> >> {"messages":[{"role":"system","content":"You are Claude, a helpful >> Agent in an OpenAgents network.\n Respond to the user's message in a >> helpful and friendly >> way."},{"role":"user","content":"<conversation>\n <threads>\n \n >> <thread id=\"thread:thread.channel_message\">\n \n <message >> sender=\"admin\" >> event_id=\"88e56cbf-31e6-4cb6-9fb2-556f0ff52e48\">\n \n >> <content>{'channel': 'general', 'content': {'text': 'Test 201 ... >> are you there Claude?'}, 'message_type': 'channel_message', >> 'original_event_id': 'admin_1773773290426_8nskjsxxx'}</content>\n \n >> </message>\n \n </thread>\n \n </threads>\n\n >> <current_interaction>\n >> <incoming_thread_id>thread:thread.channel_message</incoming_thread_id>\n >> <incoming_message sender=\"admin\" >> event_id=\"88e56cbf-31e6-4cb6-9fb2-556f0ff52e48\">\n \n >> <content>{'channel': 'general', 'content': {'text': 'Test 201 ... >> are you there Claude?'}, 'message_type': 'channel_message', >> 'original_event_id': 'admin_1773773290426_8nskjsxxx'}</content>\n \n >> </incoming_message>\n >> </current_interaction>\n</conversation>\n\nPlease respond to the >> incoming message based on the context provided. You have access to >> tools that you can use if needed.\n\nIMPORTANT: When replying to >> messages, use the message's event_id (not the thread_id) as the >> reply_to_id parameter.\n- To reply to a channel message: use >> reply_channel_message with the message's event_id\n- To reply to a >> direct message: use reply_direct_message with the message's >> event_id\n- Thread ID is for context only, always use event_id for >> replies\n\nIn each step, you MUST either:\n1. Call a tool to perform >> an action, or\n2. Use the finish tool when you've completed all >> necessary actions.\n\nIf you don't need to use any tools, use the >> finish tool directly.\n\nRespond to: {'text': 'Test 201 ... are you >> there Claude?'}. Return the results as >> PLAINTEXT."}],"model":"Claude-4.5-Opus","tool_choice":"auto","tools":[{"type":"function","function":{"name":"finish","description":"Use >> this tool when you have completed all necessary actions and don't >> need to do anything >> else.","parameters":{"type":"object","properties":{"reason":{"type":"string","description":"Reason >> for finishing the action chain."}},"required":["reason"]}}}]} >> >> HTTP/1.1 200 OK >> date: Tue, 17 Mar 2026 18:48:11 GMT,Tue, 17 Mar 2026 18:48:11 GMT >> server: istio-envoy >> content-type: application/json >> req-cost-time: 9481 >> req-arrive-time: 1773773291660 >> resp-start-time: 1773773301141 >> x-envoy-upstream-service-time: 9434 >> content-length: 982 >> >> {"id":"chatcmpl-725b0c07-040e-4874-a5e3-06c6a93e710d","object":"chat.completion","created":1773773291,"model":"Claude-4.5-Opus","choices":[{"index":0,"message":{"role":"assistant","content":"<think>\nThe >> user is asking if I'm here - this is a simple test message. I don't >> need to use any tools here, just respond directly.\n\nI'll confirm >> my presence and ask them to test me further.\n</think>\n\nYes, I'm >> here! .... How can I help you today? Feel free to test me with any >> questions or >> tasks.","refusal":null,"annotations":null,"audio":null,"function_call":null,"tool_calls":[],"reasoning_content":null},"logprobs":null,"finish_reason":"stop","stop_reason":null,"token_ids":null}],"service_tier":null,"system_fingerprint":null,"usage":{"prompt_tokens":672,"total_tokens":747,"completion_tokens":75,"prompt_tokens_details":null,"time_to_first_token_ms":9482,"time_per_output_token_ms":0,"tokens_per_second":0},"prompt_logprobs":null,"prompt_token_ids":null,"kv_transfer_params":null} >> >> While the exchange DOES show tool fields in the API >> request/response, the model recognizes that no tools are required >> and passes back a result ... but parsing of the result never makes >> it back to the "general" channel. >> >> I never see |*"I'm sorry, I couldn't generate a response."*| within >> the general channel. In fact I see nothing at all except my own text >> that has been entered (Test 201 ... are you there Claude?) >> >> I'll work on your points 3 and 4 to try to gather more information.  >> THANKS!!! >> >> Chris aka ConjureUp96 >> >> On 3/16/2026 8:39 PM, QuanCheng wrote: >>> *QuanCheng-QC* left a comment (openagents-org/openagents#285) >>> <#285 (comment)> >>> >>> Thanks for digging into this and sharing the traces — this is very >>> helpful. >>> >>> From the logs you posted, the LLM is clearly producing a response, >>> but it is returning it as tool calls: >>> >>> send_text_message >>> send_text_message >>> broadcast_text_message >>> >>> So the issue no longer appears to be on the backend side (GPUStack >>> / tool parser). The model is responding and the orchestration layer >>> is detecting the tool calls correctly. >>> >>> The likely problem is that the example script is still trying to >>> extract a plain text response from: >>> >>> |action.payload["response"] | >>> >>> However, when the model emits tool calls, the trajectory may not >>> contain a final |response| field at all. Instead, the actions >>> represent tool invocations. >>> >>> In that case the code path: >>> >>> |if not response: response = "I'm sorry, I couldn't generate a >>> response." | >>> >>> will be triggered even though the model already produced a valid >>> tool-based response. >>> >>> A few things I would suggest checking: >>> >>> 1. >>> >>> Print the entire |trajectory.actions| structure >>> Instead of only looking for |payload["response"]|, dump each >>> action's payload/result so we can confirm whether the >>> trajectory contains tool calls, tool results, or a final >>> assistant text. >>> >>> 2. >>> >>> Temporarily disable mods/tools for comparison >>> >>> Try running the same flow with: >>> >>> |disable_mods=True disable_mcp=True | >>> >>> If the model then returns plain text instead of tool calls, >>> that would confirm that the event-driven |run_agent()| path is >>> implicitly enabling tool capabilities. >>> >>> 3. >>> >>> Normalize message content extraction >>> >>> In the sample payload: >>> >>> |"content": {"text": "..."} | >>> >>> so this line may pass a dict into the instruction: >>> >>> |content = event.payload.get("content") | >>> >>> It may be safer to extract |content["text"]| explicitly. >>> >>> 4. >>> >>> Add logging around |send_channel_message()| >>> >>> It would also help to confirm whether |send_channel_message()| >>> is actually being executed successfully or returning an error. >>> >>> My current hypothesis is that the script is mixing two output paths: >>> >>> * plain text response extraction >>> * tool-call-driven messaging >>> >>> and the event-driven orchestration path is favoring the latter. >>> >>> If useful, we can also provide a minimal event-driven example that >>> forces plain text replies (no tool usage) to isolate the behavior >>> further. >>> >>> — >>> Reply to this email directly, view it on GitHub >>> <#285 (comment)>, >>> or unsubscribe >>> <https://github.com/notifications/unsubscribe-auth/B3DGO4R4YFBNUNLDK73I2N34RC3GBAVCNFSM6AAAAACVNPZ7N6VHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHM2DANZRHE2DINRZGE>. >>> You are receiving this because you authored the thread.Message ID: >>> ***@***.***> >>>