91 lines
3.1 KiB
Python
91 lines
3.1 KiB
Python
import os
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from typing import Any, Optional
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from langchain_openai import ChatOpenAI
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from .base_client import BaseLLMClient, normalize_content
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from .validators import validate_model
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class NormalizedChatOpenAI(ChatOpenAI):
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"""ChatOpenAI with normalized content output.
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The Responses API returns content as a list of typed blocks
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(reasoning, text, etc.). This normalizes to string for consistent
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downstream handling.
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"""
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def invoke(self, input, config=None, **kwargs):
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return normalize_content(super().invoke(input, config, **kwargs))
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# Kwargs forwarded from user config to ChatOpenAI
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_PASSTHROUGH_KWARGS = (
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"timeout", "max_retries", "reasoning_effort",
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"api_key", "callbacks", "http_client", "http_async_client",
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)
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# Provider base URLs and API key env vars
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_PROVIDER_CONFIG = {
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"xai": ("https://api.x.ai/v1", "XAI_API_KEY"),
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"openrouter": ("https://openrouter.ai/api/v1", "OPENROUTER_API_KEY"),
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"ollama": ("http://localhost:11434/v1", None),
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}
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class OpenAIClient(BaseLLMClient):
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"""Client for OpenAI, Ollama, OpenRouter, and xAI providers.
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For native OpenAI models, uses the Responses API (/v1/responses) which
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supports reasoning_effort with function tools across all model families
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(GPT-4.1, GPT-5). Third-party compatible providers (xAI, OpenRouter,
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Ollama) use standard Chat Completions.
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"""
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def __init__(
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self,
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model: str,
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base_url: Optional[str] = None,
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provider: str = "openai",
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**kwargs,
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):
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super().__init__(model, base_url, **kwargs)
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self.provider = provider.lower()
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def get_llm(self) -> Any:
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"""Return configured ChatOpenAI instance."""
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self.warn_if_unknown_model()
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llm_kwargs = {"model": self.model}
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# Provider-specific base URL and auth
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if self.provider in _PROVIDER_CONFIG:
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base_url, api_key_env = _PROVIDER_CONFIG[self.provider]
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llm_kwargs["base_url"] = base_url
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if api_key_env:
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api_key = os.environ.get(api_key_env)
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if api_key:
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llm_kwargs["api_key"] = api_key
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else:
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llm_kwargs["api_key"] = "ollama"
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elif self.provider == "llamacpp":
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base_url = os.environ.get("BACKEND_URL") or os.environ.get("LLAMACPP_BASE_URL", "http://localhost:8080/v1")
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llm_kwargs["base_url"] = base_url
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llm_kwargs["api_key"] = "no-key-needed" # llama-server doesn't require auth
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elif self.base_url:
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llm_kwargs["base_url"] = self.base_url
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# Forward user-provided kwargs
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for key in _PASSTHROUGH_KWARGS:
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if key in self.kwargs:
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llm_kwargs[key] = self.kwargs[key]
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# Native OpenAI: use Responses API for consistent behavior across
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# all model families. Third-party providers use Chat Completions.
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if self.provider == "openai":
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llm_kwargs["use_responses_api"] = True
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return NormalizedChatOpenAI(**llm_kwargs)
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def validate_model(self) -> bool:
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"""Validate model for the provider."""
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return validate_model(self.provider, self.model)
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