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docs: note primary image selection uses the simple agent type

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mason5052
2026-06-19 04:45:19 +07:00
committed by Sergey Kozyrenko
parent 900cbffc8e
commit e9a6769116
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README.md
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@@ -2693,7 +2693,7 @@ See the official Docker documentation for [registry mirrors](https://docs.docker
A flow that fails immediately with `failed to select primary docker image via llm call` usually indicates a problem with the configured LLM backend, not with Docker or the image registry. Older PentAGI versions reported the same failure as `failed to get primary docker image`, which led users to debug Docker even though the registry was healthy.
When a flow starts, PentAGI makes its first LLM call to choose the primary Docker image for the task. If that call fails, the error is surfaced at this image-selection step. A message such as `API returned unexpected status code: 502` or `404` in this context is returned by the LLM backend, not by Docker Hub.
When a flow starts, PentAGI makes its first LLM call to choose the primary Docker image for the task. This image-selection call runs through the `simple` agent type, so a failure here points at the model assigned to that agent type rather than at Docker. A message such as `API returned unexpected status code: 502` or `404` in this context is returned by the LLM backend, not by Docker Hub.
This is distinct from the registry reachability problems described above: if Docker pulls succeed and the Compose stack starts, but flow creation still fails at image selection, investigate the LLM backend rather than Docker.
@@ -2701,7 +2701,7 @@ To diagnose:
1. Check PentAGI logs first: `docker logs pentagi`.
2. Check the logs of your configured LLM backend (the server behind your provider or `LLM_SERVER_URL`).
3. Verify that the base URL, API key, and model name in [Custom LLM Provider Configuration](#custom-llm-provider-configuration) are correct and reachable from the container.
3. Verify that the base URL, API key, and model name in [Custom LLM Provider Configuration](#custom-llm-provider-configuration) are correct and reachable from the container. If you assign different models per agent type, check the model used by the `simple` agent type, since image selection runs through it.
4. For custom, OpenAI-compatible, vLLM, or SGLang backends, confirm that the model supports tool calling (function calling) and that the matching tool-call parser is enabled. A missing or mismatched tool-call parser is a known cause of this failure.
## Development