[minimax M3 Bug] Bug Report: Raw internal tool-call tokens (]<]minimax[>[) leaking into minimax-m3 response content with stop chat
Nessuno ha ancora preso questa issue.
Valutazione
- Difficoltà
- 4/5
- Tempo stimato
- 3-5 giorni
- Idoneità per principianti
- 42/100
Direzione di ricerca
Inizia riproducendo il problema tramite l'endpoint /v1/chat/completions con richieste sia in streaming sia non in streaming, utilizzando il modello minimax-m3 e gli schemi degli strumenti. Confronta le risposte riuscite con i casi in cui ]<]minimax>[ appare in message.content. Il lavoro è completato quando le chiamate agli strumenti vengono restituite sistematicamente nel campo strutturato tool_calls, oppure quando i payload malformati producono un errore esplicito e rilevabile invece di una risposta 200 con token grezzi.
Scritto dal modello di indicizzazione a partire dal testo della issue.
Descrizione
Which inference path did you use?
Other
Inference parameters
No response
Prompt / input
leaking into minimax-m3 response content
Expected behavior
Bug Report: Raw internal tool-call tokens (]<]minimax[>[) leaking into minimax-m3 response content
Actual behavior
when i coding with minimax m3 some times got this and stop chat , some times got continuously
minimax m3 ai:
Let me read that part to confirm.
I need to continue with Step 1. Let me read the run_one function to find where to add the state initialization Tuner.]<]minimax[>[<tool_call>
]<]minimax[>[]<]minimax[>[C:\encher\src\main.rs]<]minimax[>[]<]minimax[>[<start_line>130]<]minimax[>[</start_line>]<]minimax[>[<end_line>165]<]minimax[>[</end_line>]<]minimax[>[
]<]minimax[>[</tool_call>
Additional context
##################
i ask with it claude , say:
Bug Report (from claude): Raw internal tool-call tokens (]<]minimax[>[) leaking into minimax-m3 response content (
Summary
When using the minimax-m3 model through the Kilo Gateway / Kimchi API (OpenAI-compatible chat/completions endpoint), the model's internal tool-call boundary tokens (]<]minimax[>[) sometimes leak directly into the visible message.content field instead of being parsed into a proper structured tool_calls array. This produces garbled, unusable output on the client side and causes the calling application (an AI coding agent) to stall or fail mid-task.
Environment
- Model:
minimax-m3(accessed askimchi/minimax-m3via Kilo Gateway) - Endpoint:
/v1/chat/completions(OpenAI-compatible), both streaming and non-streaming - Client: OpenAI-compatible coding agent (opencode), via a local proxy that otherwise forwards requests unmodified
- Frequency: Intermittent — occurs "suddenly" and sometimes repeats for multiple consecutive requests before stopping
Expected behavior
When the model wants to invoke a tool/function, the response should contain a properly structured tool_calls array:
{
"choices": [{
"message": {
"role": "assistant",
"content": null,
"tool_calls": [{
"id": "call_...",
"type": "function",
"function": { "name": "...", "arguments": "{...}" }
}]
}
}]
}
Actual behavior
The model's raw internal boundary/delimiter tokens appear directly in message.content as plain text, wrapping what looks like an internal tool-call payload that was never converted into the structured format.
Reproduction examples (captured from live responses)
Example:
Debug derive conflict (BlendMode already has Debug). Fix:]<]minimax[>[ ]<]minimax[>[]<]minimax[>[C:\Users\yumin\Desktop\other\no\cons\tun\src\lib.rs]<]minimax[>[]<]minimax[>[/// Selected configuration for one scene.
#[derive(Debug, Clone, Copy, Debug)]
pub struct ConfigChoice { ... }
]<]minimax[>[]<]minimax[>[cargo test --release --manifest-path "..." --lib 2>&1 | grep -E "(test result|FAILED|error)" | head -10]<]minimax[>[]<]minimax[><]minimax[>[]<]minimax[>[
Observations
- The ]<]minimax[>[ sequence appears to function as an internal delimiter marking the boundaries of a tool call (target file path, code diff/content, and a shell command each appear as separate segments between markers).
- In Example 1, the payload between markers matches the shape of a code-edit tool call: file path → old/new code content → a test command → a numeric value (possibly a timeout in ms).
- This occurs on both streaming and non-streaming requests.
- Client-side retries of the same request sometimes succeed with a properly formatted tool_calls response, suggesting this is non-deterministic / load- or path-dependent on the gateway or model-serving side rather than a fixed per-request issue.
Impact
- Any client relying on structured
tool_calls(coding agents, function-calling integrations) receives unusable output and cannot execute the intended action. - Silent failures: there is no error status/code returned — the response is
200 OKwith malformed content, so clients that don't specifically pattern-match for this can't distinguish it from a legitimate (if unusual) text response.
Suggested fix directions
- Ensure the tool-call parsing/finalization step on the gateway (or model-serving layer) always converts these internal delimiter-wrapped segments into the structured
tool_callsfield before returning the response, for both streaming and non-streaming paths. - If the delimiter tokens are ever unparseable for some segments, return an explicit error (e.g.
finish_reason: "content_filter"or a5xx) rather than200 OKwith raw tokens incontent, so clients can detect and retry deterministically instead of silently receiving garbage. - Investigate why this is intermittent — whether it correlates with specific prompt/tool-schema shapes, concurrent load, or a specific upstream replica/version of
minimax-m3.
- Lingua principale
- Nessun dato sulla lingua
- Stelle
- 490
- Fork
- 59
- Metriche di merge delle PR
- Nessuna PR unita negli ultimi 30g
Preparare l'ambiente
Questo progetto non fornisce container di sviluppo, Dockerfile né guida per i contributori, quindi l'ambiente è a tuo carico: parti dal suo README e consulta la nostra guida al primo contributo per i passaggi generali.
Come iniziare
- Leggi tutta la issue e poi la guida ai contributi del progetto.
- Commenta sulla issue per dire che te ne occupi tu — evita che due persone facciano lo stesso lavoro.
- Fai un fork del repository e lavora su un branch.
- Apri una pull request che faccia riferimento al numero della issue.
Altre issue di MiniMax-AI/MiniMax-M3
-
Difficoltà 1/5 Meno di un'ora Idoneità per principianti 90/100
MiniMax-AI/MiniMax-M3#34 · 1 reazione ·
-
[M2.7 Bug]Apertabug
Difficoltà 4/5 3-5 giorni Idoneità per principianti 45/100
MiniMax-AI/MiniMax-M3#35 ·
-
enhancement
Difficoltà 4/5 3-5 giorni Idoneità per principianti 45/100
MiniMax-AI/MiniMax-M3#33 ·
-
Difficoltà 2/5 1-3 ore Idoneità per principianti 48/100
MiniMax-AI/MiniMax-M3#32 ·
-
Difficoltà 4/5 3-5 giorni Idoneità per principianti 35/100
MiniMax-AI/MiniMax-M3#30 ·
Tutte le issue di MiniMax-AI/MiniMax-M3
Issue simili
-
agent: ready area: agent area: monitoring priority: normal type: bug
Difficoltà 2/5 1-3 ore Idoneità per principianti 78/100
dkritarth/scopewatch#200 ·
I maintainer di solito rispondono entro 1 giorno
-
Difficoltà 2/5 1-3 ore Idoneità per principianti 62/100
awslabs/agentcore-samples#2185 ·
I maintainer di solito rispondono entro 1 giorno
-
Difficoltà 2/5 1-3 ore Idoneità per principianti 86/100
UKGovernmentBEIS/inspect_ai#5802 ·
I maintainer di solito rispondono entro 2 giorni
-
area:retrieval
Difficoltà 2/5 1-3 ore Idoneità per principianti 82/100
RailtownAI/railtracks#1653 ·
I maintainer di solito rispondono entro 2 giorni
-
enhancement good first issue
Difficoltà 2/5 1-3 ore Idoneità per principianti 66/100
asasemahmed/FullDots#10 ·