From e9a676911631db162002c26d526bf89951d22a18 Mon Sep 17 00:00:00 2001 From: mason5052 Date: Sat, 13 Jun 2026 22:52:42 -0400 Subject: [PATCH] docs: note primary image selection uses the simple agent type --- README.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index bce31ece..94cf673f 100644 --- a/README.md +++ b/README.md @@ -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