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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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1
nanobot/providers/base.py
View File

@@ -20,6 +20,7 @@ class LLMResponse:
tool_calls: list[ToolCallRequest] = field(default_factory=list)
finish_reason: str = "stop"
usage: dict[str, int] = field(default_factory=dict)
reasoning_content: str | None = None # Kimi, DeepSeek-R1 etc.
@property
def has_tool_calls(self) -> bool:

148
nanobot/providers/litellm_provider.py
View File

@@ -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:

359
nanobot/providers/registry.py Normal file
View File

@@ -0,0 +1,359 @@
"""
Provider Registry — single source of truth for LLM provider metadata.
Adding a new provider:
1. Add a ProviderSpec to PROVIDERS below.
2. Add a field to ProvidersConfig in config/schema.py.
Done. Env vars, prefixing, config matching, status display all derive from here.
Order matters — it controls match priority and fallback. Gateways first.
Every entry writes out all fields so you can copy-paste as a template.
"""
from __future__ import annotations
from dataclasses import dataclass
from typing import Any
@dataclass(frozen=True)
class ProviderSpec:
"""One LLM provider's metadata. See PROVIDERS below for real examples.
Placeholders in env_extras values:
{api_key} — the user's API key
{api_base} — api_base from config, or this spec's default_api_base
"""
# identity
name: str # config field name, e.g. "dashscope"
keywords: tuple[str, ...] # model-name keywords for matching (lowercase)
env_key: str # LiteLLM env var, e.g. "DASHSCOPE_API_KEY"
display_name: str = "" # shown in `nanobot status`
# model prefixing
litellm_prefix: str = "" # "dashscope" → model becomes "dashscope/{model}"
skip_prefixes: tuple[str, ...] = () # don't prefix if model already starts with these
# extra env vars, e.g. (("ZHIPUAI_API_KEY", "{api_key}"),)
env_extras: tuple[tuple[str, str], ...] = ()
# gateway / local detection
is_gateway: bool = False # routes any model (OpenRouter, AiHubMix)
is_local: bool = False # local deployment (vLLM, Ollama)
detect_by_key_prefix: str = "" # match api_key prefix, e.g. "sk-or-"
detect_by_base_keyword: str = "" # match substring in api_base URL
default_api_base: str = "" # fallback base URL
# gateway behavior
strip_model_prefix: bool = False # strip "provider/" before re-prefixing
# per-model param overrides, e.g. (("kimi-k2.5", {"temperature": 1.0}),)
model_overrides: tuple[tuple[str, dict[str, Any]], ...] = ()
@property
def label(self) -> str:
return self.display_name or self.name.title()
# ---------------------------------------------------------------------------
# PROVIDERS — the registry. Order = priority. Copy any entry as template.
# ---------------------------------------------------------------------------
PROVIDERS: tuple[ProviderSpec, ...] = (
# === Gateways (detected by api_key / api_base, not model name) =========
# Gateways can route any model, so they win in fallback.
# OpenRouter: global gateway, keys start with "sk-or-"
ProviderSpec(
name="openrouter",
keywords=("openrouter",),
env_key="OPENROUTER_API_KEY",
display_name="OpenRouter",
litellm_prefix="openrouter", # claude-3 → openrouter/claude-3
skip_prefixes=(),
env_extras=(),
is_gateway=True,
is_local=False,
detect_by_key_prefix="sk-or-",
detect_by_base_keyword="openrouter",
default_api_base="https://openrouter.ai/api/v1",
strip_model_prefix=False,
model_overrides=(),
),
# AiHubMix: global gateway, OpenAI-compatible interface.
# strip_model_prefix=True: it doesn't understand "anthropic/claude-3",
# so we strip to bare "claude-3" then re-prefix as "openai/claude-3".
ProviderSpec(
name="aihubmix",
keywords=("aihubmix",),
env_key="OPENAI_API_KEY", # OpenAI-compatible
display_name="AiHubMix",
litellm_prefix="openai", # → openai/{model}
skip_prefixes=(),
env_extras=(),
is_gateway=True,
is_local=False,
detect_by_key_prefix="",
detect_by_base_keyword="aihubmix",
default_api_base="https://aihubmix.com/v1",
strip_model_prefix=True, # anthropic/claude-3 → claude-3 → openai/claude-3
model_overrides=(),
),
# === Standard providers (matched by model-name keywords) ===============
# Anthropic: LiteLLM recognizes "claude-*" natively, no prefix needed.
ProviderSpec(
name="anthropic",
keywords=("anthropic", "claude"),
env_key="ANTHROPIC_API_KEY",
display_name="Anthropic",
litellm_prefix="",
skip_prefixes=(),
env_extras=(),
is_gateway=False,
is_local=False,
detect_by_key_prefix="",
detect_by_base_keyword="",
default_api_base="",
strip_model_prefix=False,
model_overrides=(),
),
# OpenAI: LiteLLM recognizes "gpt-*" natively, no prefix needed.
ProviderSpec(
name="openai",
keywords=("openai", "gpt"),
env_key="OPENAI_API_KEY",
display_name="OpenAI",
litellm_prefix="",
skip_prefixes=(),
env_extras=(),
is_gateway=False,
is_local=False,
detect_by_key_prefix="",
detect_by_base_keyword="",
default_api_base="",
strip_model_prefix=False,
model_overrides=(),
),
# DeepSeek: needs "deepseek/" prefix for LiteLLM routing.
ProviderSpec(
name="deepseek",
keywords=("deepseek",),
env_key="DEEPSEEK_API_KEY",
display_name="DeepSeek",
litellm_prefix="deepseek", # deepseek-chat → deepseek/deepseek-chat
skip_prefixes=("deepseek/",), # avoid double-prefix
env_extras=(),
is_gateway=False,
is_local=False,
detect_by_key_prefix="",
detect_by_base_keyword="",
default_api_base="",
strip_model_prefix=False,
model_overrides=(),
),
# Gemini: needs "gemini/" prefix for LiteLLM.
ProviderSpec(
name="gemini",
keywords=("gemini",),
env_key="GEMINI_API_KEY",
display_name="Gemini",
litellm_prefix="gemini", # gemini-pro → gemini/gemini-pro
skip_prefixes=("gemini/",), # avoid double-prefix
env_extras=(),
is_gateway=False,
is_local=False,
detect_by_key_prefix="",
detect_by_base_keyword="",
default_api_base="",
strip_model_prefix=False,
model_overrides=(),
),
# Zhipu: LiteLLM uses "zai/" prefix.
# Also mirrors key to ZHIPUAI_API_KEY (some LiteLLM paths check that).
# skip_prefixes: don't add "zai/" when already routed via gateway.
ProviderSpec(
name="zhipu",
keywords=("zhipu", "glm", "zai"),
env_key="ZAI_API_KEY",
display_name="Zhipu AI",
litellm_prefix="zai", # glm-4 → zai/glm-4
skip_prefixes=("zhipu/", "zai/", "openrouter/", "hosted_vllm/"),
env_extras=(
("ZHIPUAI_API_KEY", "{api_key}"),
),
is_gateway=False,
is_local=False,
detect_by_key_prefix="",
detect_by_base_keyword="",
default_api_base="",
strip_model_prefix=False,
model_overrides=(),
),
# DashScope: Qwen models, needs "dashscope/" prefix.
ProviderSpec(
name="dashscope",
keywords=("qwen", "dashscope"),
env_key="DASHSCOPE_API_KEY",
display_name="DashScope",
litellm_prefix="dashscope", # qwen-max → dashscope/qwen-max
skip_prefixes=("dashscope/", "openrouter/"),
env_extras=(),
is_gateway=False,
is_local=False,
detect_by_key_prefix="",
detect_by_base_keyword="",
default_api_base="",
strip_model_prefix=False,
model_overrides=(),
),
# Moonshot: Kimi models, needs "moonshot/" prefix.
# LiteLLM requires MOONSHOT_API_BASE env var to find the endpoint.
# Kimi K2.5 API enforces temperature >= 1.0.
ProviderSpec(
name="moonshot",
keywords=("moonshot", "kimi"),
env_key="MOONSHOT_API_KEY",
display_name="Moonshot",
litellm_prefix="moonshot", # kimi-k2.5 → moonshot/kimi-k2.5
skip_prefixes=("moonshot/", "openrouter/"),
env_extras=(
("MOONSHOT_API_BASE", "{api_base}"),
),
is_gateway=False,
is_local=False,
detect_by_key_prefix="",
detect_by_base_keyword="",
default_api_base="https://api.moonshot.ai/v1", # intl; use api.moonshot.cn for China
strip_model_prefix=False,
model_overrides=(
("kimi-k2.5", {"temperature": 1.0}),
),
),
# MiniMax: needs "minimax/" prefix for LiteLLM routing.
# Uses OpenAI-compatible API at api.minimax.io/v1.
ProviderSpec(
name="minimax",
keywords=("minimax",),
env_key="MINIMAX_API_KEY",
display_name="MiniMax",
litellm_prefix="minimax", # MiniMax-M2.1 → minimax/MiniMax-M2.1
skip_prefixes=("minimax/", "openrouter/"),
env_extras=(),
is_gateway=False,
is_local=False,
detect_by_key_prefix="",
detect_by_base_keyword="",
default_api_base="https://api.minimax.io/v1",
strip_model_prefix=False,
model_overrides=(),
),
# === Local deployment (matched by config key, NOT by api_base) =========
# vLLM / any OpenAI-compatible local server.
# Detected when config key is "vllm" (provider_name="vllm").
ProviderSpec(
name="vllm",
keywords=("vllm",),
env_key="HOSTED_VLLM_API_KEY",
display_name="vLLM/Local",
litellm_prefix="hosted_vllm", # Llama-3-8B → hosted_vllm/Llama-3-8B
skip_prefixes=(),
env_extras=(),
is_gateway=False,
is_local=True,
detect_by_key_prefix="",
detect_by_base_keyword="",
default_api_base="", # user must provide in config
strip_model_prefix=False,
model_overrides=(),
),
# === Auxiliary (not a primary LLM provider) ============================
# Groq: mainly used for Whisper voice transcription, also usable for LLM.
# Needs "groq/" prefix for LiteLLM routing. Placed last — it rarely wins fallback.
ProviderSpec(
name="groq",
keywords=("groq",),
env_key="GROQ_API_KEY",
display_name="Groq",
litellm_prefix="groq", # llama3-8b-8192 → groq/llama3-8b-8192
skip_prefixes=("groq/",), # avoid double-prefix
env_extras=(),
is_gateway=False,
is_local=False,
detect_by_key_prefix="",
detect_by_base_keyword="",
default_api_base="",
strip_model_prefix=False,
model_overrides=(),
),
)
# ---------------------------------------------------------------------------
# Lookup helpers
# ---------------------------------------------------------------------------
def find_by_model(model: str) -> ProviderSpec | None:
"""Match a standard provider by model-name keyword (case-insensitive).
Skips gateways/local — those are matched by api_key/api_base instead."""
model_lower = model.lower()
for spec in PROVIDERS:
if spec.is_gateway or spec.is_local:
continue
if any(kw in model_lower for kw in spec.keywords):
return spec
return None
def find_gateway(
provider_name: str | None = None,
api_key: str | None = None,
api_base: str | None = None,
) -> ProviderSpec | None:
"""Detect gateway/local provider.
Priority:
1. provider_name — if it maps to a gateway/local spec, use it directly.
2. api_key prefix — e.g. "sk-or-" → OpenRouter.
3. api_base keyword — e.g. "aihubmix" in URL → AiHubMix.
A standard provider with a custom api_base (e.g. DeepSeek behind a proxy)
will NOT be mistaken for vLLM — the old fallback is gone.
"""
# 1. Direct match by config key
if provider_name:
spec = find_by_name(provider_name)
if spec and (spec.is_gateway or spec.is_local):
return spec
# 2. Auto-detect by api_key prefix / api_base keyword
for spec in PROVIDERS:
if spec.detect_by_key_prefix and api_key and api_key.startswith(spec.detect_by_key_prefix):
return spec
if spec.detect_by_base_keyword and api_base and spec.detect_by_base_keyword in api_base:
return spec
return None
def find_by_name(name: str) -> ProviderSpec | None:
"""Find a provider spec by config field name, e.g. "dashscope"."""
for spec in PROVIDERS:
if spec.name == name:
return spec
return None