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refactor: replace provider if-elif chains with declarative registry

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Re-bin 2026-02-08 07:29:31 +00:00
parent 00185f2bee
commit 299d8b33b3
5 changed files with 474 additions and 110 deletions
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48
README.md
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@ -20,6 +20,7 @@
## 📢 News
- **2026-02-08** 🔧 Refactored Providers — adding a new LLM provider only takes just 2 steps! Check [here](#providers).
- **2026-02-07** 🚀 Released v0.1.3.post5 with Qwen support & several improvements! Check [here](https://github.com/HKUDS/nanobot/releases/tag/v0.1.3.post5) for details.
- **2026-02-06** ✨ Added Moonshot/Kimi provider, Discord integration, and enhanced security hardening!
- **2026-02-05** ✨ Added Feishu channel, DeepSeek provider, and enhanced scheduled tasks support!
@ -355,6 +356,53 @@ Config file: `~/.nanobot/config.json`
| `gemini` | LLM (Gemini direct) | [aistudio.google.com](https://aistudio.google.com) |
| `aihubmix` | LLM (API gateway, access to all models) | [aihubmix.com](https://aihubmix.com) |
| `dashscope` | LLM (Qwen) | [dashscope.console.aliyun.com](https://dashscope.console.aliyun.com) |
| `moonshot` | LLM (Moonshot/Kimi) | [platform.moonshot.cn](https://platform.moonshot.cn) |
| `zhipu` | LLM (Zhipu GLM) | [open.bigmodel.cn](https://open.bigmodel.cn) |
| `vllm` | LLM (local, any OpenAI-compatible server) | — |
<details>
<summary><b>Adding a New Provider (Developer Guide)</b></summary>
nanobot uses a **Provider Registry** (`nanobot/providers/registry.py`) as the single source of truth.
Adding a new provider only takes **2 steps** — no if-elif chains to touch.
**Step 1.** Add a `ProviderSpec` entry to `PROVIDERS` in `nanobot/providers/registry.py`:
```python
ProviderSpec(
name="myprovider", # config field name
keywords=("myprovider", "mymodel"), # model-name keywords for auto-matching
env_key="MYPROVIDER_API_KEY", # env var for LiteLLM
display_name="My Provider", # shown in `nanobot status`
litellm_prefix="myprovider", # auto-prefix: model → myprovider/model
skip_prefixes=("myprovider/",), # don't double-prefix
)
```
**Step 2.** Add a field to `ProvidersConfig` in `nanobot/config/schema.py`:
```python
class ProvidersConfig(BaseModel):
...
myprovider: ProviderConfig = ProviderConfig()
```
That's it! Environment variables, model prefixing, config matching, and `nanobot status` display will all work automatically.
**Common `ProviderSpec` options:**
| Field | Description | Example |
|-------|-------------|---------|
| `litellm_prefix` | Auto-prefix model names for LiteLLM | `"dashscope"` → `dashscope/qwen-max` |
| `skip_prefixes` | Don't prefix if model already starts with these | `("dashscope/", "openrouter/")` |
| `env_extras` | Additional env vars to set | `(("ZHIPUAI_API_KEY", "{api_key}"),)` |
| `model_overrides` | Per-model parameter overrides | `(("kimi-k2.5", {"temperature": 1.0}),)` |
| `is_gateway` | Can route any model (like OpenRouter) | `True` |
| `detect_by_key_prefix` | Detect gateway by API key prefix | `"sk-or-"` |
| `detect_by_base_keyword` | Detect gateway by API base URL | `"openrouter"` |
| `strip_model_prefix` | Strip existing prefix before re-prefixing | `True` (for AiHubMix) |
</details>
### Security

33
nanobot/cli/commands.py
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@ -635,25 +635,24 @@ def status():
console.print(f"Workspace: {workspace} {'[green]✓[/green]' if workspace.exists() else '[red]✗[/red]'}")
if config_path.exists():
from nanobot.providers.registry import PROVIDERS
console.print(f"Model: {config.agents.defaults.model}")
# Check API keys
has_openrouter = bool(config.providers.openrouter.api_key)
has_anthropic = bool(config.providers.anthropic.api_key)
has_openai = bool(config.providers.openai.api_key)
has_gemini = bool(config.providers.gemini.api_key)
has_zhipu = bool(config.providers.zhipu.api_key)
has_vllm = bool(config.providers.vllm.api_base)
has_aihubmix = bool(config.providers.aihubmix.api_key)
console.print(f"OpenRouter API: {'[green]✓[/green]' if has_openrouter else '[dim]not set[/dim]'}")
console.print(f"Anthropic API: {'[green]✓[/green]' if has_anthropic else '[dim]not set[/dim]'}")
console.print(f"OpenAI API: {'[green]✓[/green]' if has_openai else '[dim]not set[/dim]'}")
console.print(f"Gemini API: {'[green]✓[/green]' if has_gemini else '[dim]not set[/dim]'}")
console.print(f"Zhipu AI API: {'[green]✓[/green]' if has_zhipu else '[dim]not set[/dim]'}")
console.print(f"AiHubMix API: {'[green]✓[/green]' if has_aihubmix else '[dim]not set[/dim]'}")
vllm_status = f"[green]✓ {config.providers.vllm.api_base}[/green]" if has_vllm else "[dim]not set[/dim]"
console.print(f"vLLM/Local: {vllm_status}")
# Check API keys from registry
for spec in PROVIDERS:
p = getattr(config.providers, spec.name, None)
if p is None:
continue
if spec.is_local:
# Local deployments show api_base instead of api_key
if p.api_base:
console.print(f"{spec.label}: [green]✓ {p.api_base}[/green]")
else:
console.print(f"{spec.label}: [dim]not set[/dim]")
else:
has_key = bool(p.api_key)
console.print(f"{spec.label}: {'[green]✓[/green]' if has_key else '[dim]not set[/dim]'}")
if __name__ == "__main__":

47
nanobot/config/schema.py
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@ -125,29 +125,23 @@ class Config(BaseSettings):
"""Get expanded workspace path."""
return Path(self.agents.defaults.workspace).expanduser()
# Default base URLs for API gateways
_GATEWAY_DEFAULTS = {"openrouter": "https://openrouter.ai/api/v1", "aihubmix": "https://aihubmix.com/v1"}
def get_provider(self, model: str | None = None) -> ProviderConfig | None:
"""Get matched provider config (api_key, api_base, extra_headers). Falls back to first available."""
model = (model or self.agents.defaults.model).lower()
p = self.providers
# Keyword → provider mapping (order matters: gateways first)
keyword_map = {
"aihubmix": p.aihubmix, "openrouter": p.openrouter,
"deepseek": p.deepseek, "anthropic": p.anthropic, "claude": p.anthropic,
"openai": p.openai, "gpt": p.openai, "gemini": p.gemini,
"zhipu": p.zhipu, "glm": p.zhipu, "zai": p.zhipu,
"dashscope": p.dashscope, "qwen": p.dashscope,
"groq": p.groq, "moonshot": p.moonshot, "kimi": p.moonshot, "vllm": p.vllm,
}
for kw, provider in keyword_map.items():
if kw in model and provider.api_key:
return provider
# Fallback: gateways first (can serve any model), then specific providers
all_providers = [p.openrouter, p.aihubmix, p.anthropic, p.openai, p.deepseek,
p.gemini, p.zhipu, p.dashscope, p.moonshot, p.vllm, p.groq]
return next((pr for pr in all_providers if pr.api_key), None)
from nanobot.providers.registry import PROVIDERS
model_lower = (model or self.agents.defaults.model).lower()
# Match by keyword (order follows PROVIDERS registry)
for spec in PROVIDERS:
p = getattr(self.providers, spec.name, None)
if p and any(kw in model_lower for kw in spec.keywords) and p.api_key:
return p
# Fallback: gateways first, then others (follows registry order)
for spec in PROVIDERS:
p = getattr(self.providers, spec.name, None)
if p and p.api_key:
return p
return None
def get_api_key(self, model: str | None = None) -> str | None:
"""Get API key for the given model. Falls back to first available key."""
@ -156,13 +150,16 @@ class Config(BaseSettings):
def get_api_base(self, model: str | None = None) -> str | None:
"""Get API base URL for the given model. Applies default URLs for known gateways."""
from nanobot.providers.registry import PROVIDERS
p = self.get_provider(model)
if p and p.api_base:
return p.api_base
# Default URLs for known gateways (openrouter, aihubmix)
for name, url in self._GATEWAY_DEFAULTS.items():
if p == getattr(self.providers, name):
return url
# Only gateways get a default URL here. Standard providers (like Moonshot)
# handle their base URL via env vars in _setup_env, NOT via api_base —
# otherwise find_gateway() would misdetect them as local/vLLM.
for spec in PROVIDERS:
if spec.is_gateway and spec.default_api_base and p == getattr(self.providers, spec.name, None):
return spec.default_api_base
return None
class Config:

133
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, 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__(
@ -28,47 +31,17 @@ class LiteLLMProvider(LLMProvider):
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 from api_key and api_base
self._gateway = find_gateway(api_key, api_base)
# Detect AiHubMix by api_base
self.is_aihubmix = bool(api_base and "aihubmix" in api_base)
# Backwards-compatible flags (used by tests and possibly external code)
self.is_openrouter = bool(self._gateway and self._gateway.name == "openrouter")
self.is_aihubmix = bool(self._gateway and self._gateway.name == "aihubmix")
self.is_vllm = bool(self._gateway and self._gateway.is_local)
# 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")
self._setup_env(api_key, api_base, default_model)
if api_base:
litellm.api_base = api_base
@ -76,6 +49,55 @@ class LiteLLMProvider(LLMProvider):
# Disable LiteLLM logging noise
litellm.suppress_debug_info = True
def _setup_env(self, api_key: str, api_base: str | None, model: str) -> None:
"""Set environment variables based on detected provider."""
if self._gateway:
# Gateway / local: direct set (not setdefault)
os.environ[self._gateway.env_key] = api_key
return
# Standard provider: match by model name
spec = find_by_model(model)
if spec:
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,
messages: list[dict[str, Any]],
@ -97,35 +119,8 @@ 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/")),
(("gemini",), "gemini", ("gemini/",)),
]
if not (self.is_vllm or self.is_openrouter or self.is_aihubmix):
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,
@ -133,6 +128,9 @@ class LiteLLMProvider(LLMProvider):
"temperature": temperature,
}
# Apply model-specific overrides (e.g. kimi-k2.5 temperature)
self._apply_model_overrides(model, kwargs)
# Pass api_base directly for custom endpoints (vLLM, etc.)
if self.api_base:
kwargs["api_base"] = self.api_base
@ -166,7 +164,6 @@ 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:

323
nanobot/providers/registry.py Normal file
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@ -0,0 +1,323 @@
"""
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}),
),
),
# === Local deployment (fallback: unknown api_base → assume local) ======
# vLLM / any OpenAI-compatible local server.
# If api_base is set but doesn't match a known gateway, we land here.
# Placed before Groq so vLLM wins the fallback when both are configured.
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(api_key: str | None, api_base: str | None) -> ProviderSpec | None:
"""Detect gateway/local by api_key prefix or api_base substring.
Fallback: unknown api_base → treat as local (vLLM)."""
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
if api_base:
return next((s for s in PROVIDERS if s.is_local), None)
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