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Feat: add kimi-k2.5 (#12852)
### What problem does this PR solve? Add kimi-k2.5 ### Type of change - [x] New Feature (non-breaking change which adds functionality)
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@ -994,6 +994,13 @@
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"model_type": "chat",
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"is_tools": true
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},
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{
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"llm_name": "kimi-k2.5",
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"tags": "LLM,CHAT,256k",
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"max_tokens": 256000,
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"model_type": "chat",
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"is_tools": true
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},
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{
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"llm_name": "kimi-latest",
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"tags": "LLM,CHAT,8k,32k,128k",
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@ -5578,4 +5585,4 @@
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]
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}
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]
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}
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}
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@ -1180,13 +1180,30 @@ class LiteLLMBase(ABC):
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return LLMErrorCode.ERROR_GENERIC
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def _clean_conf(self, gen_conf):
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gen_conf = deepcopy(gen_conf) if gen_conf else {}
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if self.provider == SupportedLiteLLMProvider.HunYuan:
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unsupported = ["presence_penalty", "frequency_penalty"]
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for key in unsupported:
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gen_conf.pop(key, None)
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if "max_tokens" in gen_conf:
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del gen_conf["max_tokens"]
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elif "kimi-k2.5" in self.model_name.lower():
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reasoning = gen_conf.pop("reasoning", None) # will never get one here, handle this later
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thinking = {"type": "enabled"} # enable thinking by default
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if reasoning is not None:
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thinking = {"type": "enabled"} if reasoning else {"type": "disabled"}
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elif not isinstance(thinking, dict) or thinking.get("type") not in {"enabled", "disabled"}:
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thinking = {"type": "disabled"}
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gen_conf["thinking"] = thinking
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thinking_enabled = thinking.get("type") == "enabled"
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gen_conf["temperature"] = 1.0 if thinking_enabled else 0.6
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gen_conf["top_p"] = 0.95
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gen_conf["n"] = 1
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gen_conf["presence_penalty"] = 0.0
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gen_conf["frequency_penalty"] = 0.0
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gen_conf.pop("max_tokens", None)
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return gen_conf
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async def async_chat(self, system, history, gen_conf, **kwargs):
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