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feat(sambanova): add MiniMax-M3, drop M2.5 #2418

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feat(sambanova): add MiniMax-M3, drop M2.5 #2418

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6 changes: 3 additions & 3 deletions docs/docs/usage-guide/changing_a_model.md
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Original file line number Diff line number Diff line change
Expand Up @@ -164,12 +164,12 @@ key = ... # your Groq api key

### SambaNova

To use MiniMax-M2.7 model with SambaNova, for example, set:
To use MiniMax-M3 model with SambaNova, for example, set:

```toml
[config] # in configuration.toml
model = "sambanova/MiniMax-M2.7"
fallback_models = ["sambanova/MiniMax-M2.5"]
model = "sambanova/MiniMax-M3"
fallback_models = ["sambanova/MiniMax-M2.7"]
[sambanova] # in .secrets.toml
key = ... # your SambaNova api key
```
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2 changes: 1 addition & 1 deletion pr_agent/algo/__init__.py
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Expand Up @@ -226,8 +226,8 @@
'groq/meta-llama/llama-4-scout-17b-16e-instruct': 131072,
'groq/llama-3.3-70b-versatile': 128000,
'groq/llama-3.1-8b-instant': 128000,
'sambanova/MiniMax-M3': 192000,
'sambanova/MiniMax-M2.7': 192000,
'sambanova/MiniMax-M2.5': 160000,

@qodo-free-for-open-source-projects qodo-free-for-open-source-projects Bot Jun 2, 2026

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Action required

1. Removed model breaks configs 🐞 Bug ☼ Reliability

By deleting sambanova/MiniMax-M2.5 from MAX_TOKENS, any existing deployment still configured
with that model id will now raise an exception at runtime when token budgeting calls
get_max_tokens(). The default custom_model_max_tokens is non-positive, so there is no fallback
path and the agent fails fast.
Agent Prompt 
## Issue description
`MAX_TOKENS` no longer contains `sambanova/MiniMax-M2.5`, but the codebase treats missing models as a hard error. This creates a breaking change for any user config that still references the removed model id (either as `config.model` or in `fallback_models`).

## Issue Context
`get_max_tokens(model)` raises if the model is not in `MAX_TOKENS` and `config.custom_model_max_tokens` is not positive. The default configuration sets `custom_model_max_tokens=-1`, so most users will hit the exception path.

## Fix Focus Areas
Choose one of these approaches:
- Re-add `sambanova/MiniMax-M2.5` into `MAX_TOKENS` (optionally comment as deprecated), so existing configs continue to work.
- Or add an alias/migration in `get_max_tokens()` (and any other model-normalization code) that maps `sambanova/MiniMax-M2.5` -> `sambanova/MiniMax-M2.7` (or keeps the old 160k cap) while preserving new recommended defaults.

References:
- pr_agent/algo/__init__.py[226-233]
- pr_agent/algo/utils.py[992-1013]
- pr_agent/settings/configuration.toml[30-35]

ⓘ Copy this prompt and use it to remediate the issue with your preferred AI generation tools

@naorpeled naorpeled Jun 3, 2026

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@octo-patch please bring back this model 🙏

'sambanova/Meta-Llama-3.3-70B-Instruct': 128000,
'sambanova/gpt-oss-120b': 128000,
'sambanova/DeepSeek-V3.1': 128000,
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2 changes: 1 addition & 1 deletion tests/unittest/test_litellm_api_key_guard.py
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Expand Up @@ -315,7 +315,7 @@ async def test_sambanova_key_forwarded_for_non_ollama_model(self, monkeypatch):

assert litellm.api_key == sambanova_key
await handler.chat_completion(
model="sambanova/MiniMax-M2.7", system="sys", user="usr"
model="sambanova/MiniMax-M3", system="sys", user="usr"
)

assert mock_call.call_args[1].get("api_key") == sambanova_key
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