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resolve conflicts with main and adapt MiniMax

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Re-bin
2026-02-10 16:27:10 +00:00
parent 3c8eadffed f8de53c7c1
commit 39dd7feb28
21 changed files with 3548 additions and 180 deletions
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148
nanobot/providers/litellm_provider.py
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@@ -1,5 +1,6 @@
"""LiteLLM provider implementation for multi-provider support."""
import json
import os
from typing import Any
@@ -7,6 +8,7 @@ import litellm
from litellm import acompletion
from nanobot.providers.base import LLMProvider, LLMResponse, ToolCallRequest
from nanobot.providers.registry import find_by_model, find_gateway
class LiteLLMProvider(LLMProvider):
@@ -14,7 +16,8 @@ class LiteLLMProvider(LLMProvider):
LLM provider using LiteLLM for multi-provider support.
Supports OpenRouter, Anthropic, OpenAI, Gemini, MiniMax, and many other providers through
a unified interface.
a unified interface. Provider-specific logic is driven by the registry
(see providers/registry.py) — no if-elif chains needed here.
"""
def __init__(
@@ -23,61 +26,78 @@ class LiteLLMProvider(LLMProvider):
api_base: str | None = None,
default_model: str = "anthropic/claude-opus-4-5",
extra_headers: dict[str, str] | None = None,
provider_name: str | None = None,
):
super().__init__(api_key, api_base)
self.default_model = default_model
self.extra_headers = extra_headers or {}
# Detect OpenRouter by api_key prefix or explicit api_base
self.is_openrouter = (
(api_key and api_key.startswith("sk-or-")) or
(api_base and "openrouter" in api_base)
)
# Detect gateway / local deployment.
# provider_name (from config key) is the primary signal;
# api_key / api_base are fallback for auto-detection.
self._gateway = find_gateway(provider_name, api_key, api_base)
# Detect AiHubMix by api_base
self.is_aihubmix = bool(api_base and "aihubmix" in api_base)
# Track if using custom endpoint (vLLM, etc.)
self.is_vllm = bool(api_base) and not self.is_openrouter and not self.is_aihubmix
# Configure LiteLLM based on provider
# Configure environment variables
if api_key:
if self.is_openrouter:
# OpenRouter mode - set key
os.environ["OPENROUTER_API_KEY"] = api_key
elif self.is_aihubmix:
# AiHubMix gateway - OpenAI-compatible
os.environ["OPENAI_API_KEY"] = api_key
elif self.is_vllm:
# vLLM/custom endpoint - uses OpenAI-compatible API
os.environ["HOSTED_VLLM_API_KEY"] = api_key
elif "deepseek" in default_model:
os.environ.setdefault("DEEPSEEK_API_KEY", api_key)
elif "anthropic" in default_model:
os.environ.setdefault("ANTHROPIC_API_KEY", api_key)
elif "openai" in default_model or "gpt" in default_model:
os.environ.setdefault("OPENAI_API_KEY", api_key)
elif "gemini" in default_model.lower():
os.environ.setdefault("GEMINI_API_KEY", api_key)
elif "zhipu" in default_model or "glm" in default_model or "zai" in default_model:
os.environ.setdefault("ZAI_API_KEY", api_key)
os.environ.setdefault("ZHIPUAI_API_KEY", api_key)
elif "dashscope" in default_model or "qwen" in default_model.lower():
os.environ.setdefault("DASHSCOPE_API_KEY", api_key)
elif "groq" in default_model:
os.environ.setdefault("GROQ_API_KEY", api_key)
elif "moonshot" in default_model or "kimi" in default_model:
os.environ.setdefault("MOONSHOT_API_KEY", api_key)
os.environ.setdefault("MOONSHOT_API_BASE", api_base or "https://api.moonshot.cn/v1")
elif "minimax" in default_model.lower():
os.environ.setdefault("MINIMAX_API_KEY", api_key)
os.environ.setdefault("MINIMAX_API_BASE", api_base or "https://api.minimax.io/v1")
self._setup_env(api_key, api_base, default_model)
if api_base:
litellm.api_base = api_base
# Disable LiteLLM logging noise
litellm.suppress_debug_info = True
# Drop unsupported parameters for providers (e.g., gpt-5 rejects some params)
litellm.drop_params = True
def _setup_env(self, api_key: str, api_base: str | None, model: str) -> None:
"""Set environment variables based on detected provider."""
spec = self._gateway or find_by_model(model)
if not spec:
return
# Gateway/local overrides existing env; standard provider doesn't
if self._gateway:
os.environ[spec.env_key] = api_key
else:
os.environ.setdefault(spec.env_key, api_key)
# Resolve env_extras placeholders:
# {api_key} → user's API key
# {api_base} → user's api_base, falling back to spec.default_api_base
effective_base = api_base or spec.default_api_base
for env_name, env_val in spec.env_extras:
resolved = env_val.replace("{api_key}", api_key)
resolved = resolved.replace("{api_base}", effective_base)
os.environ.setdefault(env_name, resolved)
def _resolve_model(self, model: str) -> str:
"""Resolve model name by applying provider/gateway prefixes."""
if self._gateway:
# Gateway mode: apply gateway prefix, skip provider-specific prefixes
prefix = self._gateway.litellm_prefix
if self._gateway.strip_model_prefix:
model = model.split("/")[-1]
if prefix and not model.startswith(f"{prefix}/"):
model = f"{prefix}/{model}"
return model
# Standard mode: auto-prefix for known providers
spec = find_by_model(model)
if spec and spec.litellm_prefix:
if not any(model.startswith(s) for s in spec.skip_prefixes):
model = f"{spec.litellm_prefix}/{model}"
return model
def _apply_model_overrides(self, model: str, kwargs: dict[str, Any]) -> None:
"""Apply model-specific parameter overrides from the registry."""
model_lower = model.lower()
spec = find_by_model(model)
if spec:
for pattern, overrides in spec.model_overrides:
if pattern in model_lower:
kwargs.update(overrides)
return
async def chat(
self,
@@ -100,35 +120,8 @@ class LiteLLMProvider(LLMProvider):
Returns:
LLMResponse with content and/or tool calls.
"""
model = model or self.default_model
model = self._resolve_model(model or self.default_model)
# Auto-prefix model names for known providers
# (keywords, target_prefix, skip_if_starts_with)
_prefix_rules = [
(("glm", "zhipu"), "zai", ("zhipu/", "zai/", "openrouter/", "hosted_vllm/")),
(("qwen", "dashscope"), "dashscope", ("dashscope/", "openrouter/")),
(("moonshot", "kimi"), "moonshot", ("moonshot/", "openrouter/")),
(("minimax",), "minimax", ("minimax/", "openrouter/")),
(("gemini",), "gemini", ("gemini/",)),
]
model_lower = model.lower()
for keywords, prefix, skip in _prefix_rules:
if any(kw in model_lower for kw in keywords) and not any(model.startswith(s) for s in skip):
model = f"{prefix}/{model}"
break
# Gateway/endpoint-specific prefixes (detected by api_base/api_key, not model name)
if self.is_openrouter and not model.startswith("openrouter/"):
model = f"openrouter/{model}"
elif self.is_aihubmix:
model = f"openai/{model.split('/')[-1]}"
elif self.is_vllm:
model = f"hosted_vllm/{model}"
# kimi-k2.5 only supports temperature=1.0
if "kimi-k2.5" in model.lower():
temperature = 1.0
kwargs: dict[str, Any] = {
"model": model,
"messages": messages,
@@ -136,7 +129,14 @@ class LiteLLMProvider(LLMProvider):
"temperature": temperature,
}
# Pass api_base directly for custom endpoints (vLLM, etc.)
# Apply model-specific overrides (e.g. kimi-k2.5 temperature)
self._apply_model_overrides(model, kwargs)
# Pass api_key directly — more reliable than env vars alone
if self.api_key:
kwargs["api_key"] = self.api_key
# Pass api_base for custom endpoints
if self.api_base:
kwargs["api_base"] = self.api_base
@@ -169,7 +169,6 @@ class LiteLLMProvider(LLMProvider):
# Parse arguments from JSON string if needed
args = tc.function.arguments
if isinstance(args, str):
import json
try:
args = json.loads(args)
except json.JSONDecodeError:
@@ -189,11 +188,14 @@ class LiteLLMProvider(LLMProvider):
"total_tokens": response.usage.total_tokens,
}
reasoning_content = getattr(message, "reasoning_content", None)
return LLMResponse(
content=message.content,
tool_calls=tool_calls,
finish_reason=choice.finish_reason or "stop",
usage=usage,
reasoning_content=reasoning_content,
)
def get_default_model(self) -> str: