This commit is contained in:
Re-bin 2026-02-18 02:51:16 +00:00
commit 74bec26698
4 changed files with 68 additions and 13 deletions

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@ -574,7 +574,7 @@ Config file: `~/.nanobot/config.json`
| Provider | Purpose | Get API Key |
|----------|---------|-------------|
| `custom` | Any OpenAI-compatible endpoint | — |
| `custom` | Any OpenAI-compatible endpoint (direct, no LiteLLM) | — |
| `openrouter` | LLM (recommended, access to all models) | [openrouter.ai](https://openrouter.ai) |
| `anthropic` | LLM (Claude direct) | [console.anthropic.com](https://console.anthropic.com) |
| `openai` | LLM (GPT direct) | [platform.openai.com](https://platform.openai.com) |
@ -623,7 +623,7 @@ nanobot agent -m "Hello!"
<details>
<summary><b>Custom Provider (Any OpenAI-compatible API)</b></summary>
If your provider is not listed above but exposes an **OpenAI-compatible API** (e.g. Together AI, Fireworks, Azure OpenAI, self-hosted endpoints), use the `custom` provider:
Connects directly to any OpenAI-compatible endpoint — LM Studio, llama.cpp, Together AI, Fireworks, Azure OpenAI, or any self-hosted server. Bypasses LiteLLM; model name is passed as-is.
```json
{
@ -641,7 +641,7 @@ If your provider is not listed above but exposes an **OpenAI-compatible API** (e
}
```
> The `custom` provider routes through LiteLLM's OpenAI-compatible path. It works with any endpoint that follows the OpenAI chat completions API format. The model name is passed directly to the endpoint without any prefix.
> For local servers that don't require a key, set `apiKey` to any non-empty string (e.g. `"no-key"`).
</details>

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@ -280,18 +280,27 @@ This file stores important information that should persist across sessions.
def _make_provider(config: Config):
"""Create LiteLLMProvider from config. Exits if no API key found."""
"""Create the appropriate LLM provider from config."""
from nanobot.providers.litellm_provider import LiteLLMProvider
from nanobot.providers.openai_codex_provider import OpenAICodexProvider
from nanobot.providers.custom_provider import CustomProvider
model = config.agents.defaults.model
provider_name = config.get_provider_name(model)
p = config.get_provider(model)
# OpenAI Codex (OAuth): don't route via LiteLLM; use the dedicated implementation.
# OpenAI Codex (OAuth)
if provider_name == "openai_codex" or model.startswith("openai-codex/"):
return OpenAICodexProvider(default_model=model)
# Custom: direct OpenAI-compatible endpoint, bypasses LiteLLM
if provider_name == "custom":
return CustomProvider(
api_key=p.api_key if p else "no-key",
api_base=config.get_api_base(model) or "http://localhost:8000/v1",
default_model=model,
)
from nanobot.providers.registry import find_by_name
spec = find_by_name(provider_name)
if not model.startswith("bedrock/") and not (p and p.api_key) and not (spec and spec.is_oauth):

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@ -0,0 +1,47 @@
"""Direct OpenAI-compatible provider — bypasses LiteLLM."""
from __future__ import annotations
from typing import Any
import json_repair
from openai import AsyncOpenAI
from nanobot.providers.base import LLMProvider, LLMResponse, ToolCallRequest
class CustomProvider(LLMProvider):
def __init__(self, api_key: str = "no-key", api_base: str = "http://localhost:8000/v1", default_model: str = "default"):
super().__init__(api_key, api_base)
self.default_model = default_model
self._client = AsyncOpenAI(api_key=api_key, base_url=api_base)
async def chat(self, messages: list[dict[str, Any]], tools: list[dict[str, Any]] | None = None,
model: str | None = None, max_tokens: int = 4096, temperature: float = 0.7) -> LLMResponse:
kwargs: dict[str, Any] = {"model": model or self.default_model, "messages": messages,
"max_tokens": max(1, max_tokens), "temperature": temperature}
if tools:
kwargs.update(tools=tools, tool_choice="auto")
try:
return self._parse(await self._client.chat.completions.create(**kwargs))
except Exception as e:
return LLMResponse(content=f"Error: {e}", finish_reason="error")
def _parse(self, response: Any) -> LLMResponse:
choice = response.choices[0]
msg = choice.message
tool_calls = [
ToolCallRequest(id=tc.id, name=tc.function.name,
arguments=json_repair.loads(tc.function.arguments) if isinstance(tc.function.arguments, str) else tc.function.arguments)
for tc in (msg.tool_calls or [])
]
u = response.usage
return LLMResponse(
content=msg.content, tool_calls=tool_calls, finish_reason=choice.finish_reason or "stop",
usage={"prompt_tokens": u.prompt_tokens, "completion_tokens": u.completion_tokens, "total_tokens": u.total_tokens} if u else {},
reasoning_content=getattr(msg, "reasoning_content", None),
)
def get_default_model(self) -> str:
return self.default_model

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@ -54,6 +54,9 @@ class ProviderSpec:
# OAuth-based providers (e.g., OpenAI Codex) don't use API keys
is_oauth: bool = False # if True, uses OAuth flow instead of API key
# Direct providers bypass LiteLLM entirely (e.g., CustomProvider)
is_direct: bool = False
@property
def label(self) -> str:
return self.display_name or self.name.title()
@ -65,18 +68,14 @@ class ProviderSpec:
PROVIDERS: tuple[ProviderSpec, ...] = (
# === Custom (user-provided OpenAI-compatible endpoint) =================
# No auto-detection — only activates when user explicitly configures "custom".
# === Custom (direct OpenAI-compatible endpoint, bypasses LiteLLM) ======
ProviderSpec(
name="custom",
keywords=(),
env_key="OPENAI_API_KEY",
env_key="",
display_name="Custom",
litellm_prefix="openai",
skip_prefixes=("openai/",),
is_gateway=True,
strip_model_prefix=True,
litellm_prefix="",
is_direct=True,
),
# === Gateways (detected by api_key / api_base, not model name) =========