97 lines
3.4 KiB
Python
97 lines
3.4 KiB
Python
import os
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import socket
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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
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from .validators import validate_model
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class OllamaConnectionError(Exception):
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"""Raised when Ollama server is not running or not accessible."""
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pass
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def _check_ollama_connection(host: str = "localhost", port: int = 11434, timeout: float = 2.0) -> bool:
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"""Check if Ollama server is running and accessible."""
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try:
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sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
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sock.settimeout(timeout)
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result = sock.connect_ex((host, port))
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sock.close()
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return result == 0
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except (socket.error, OSError):
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return False
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class UnifiedChatOpenAI(ChatOpenAI):
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"""ChatOpenAI subclass that strips temperature/top_p for GPT-5 family models.
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GPT-5 family models use reasoning natively. temperature/top_p are only
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accepted when reasoning.effort is 'none'; with any other effort level
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(or for older GPT-5/GPT-5-mini/GPT-5-nano which always reason) the API
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rejects these params. Langchain defaults temperature=0.7, so we must
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strip it to avoid errors.
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Non-GPT-5 models (GPT-4.1, xAI, Ollama, etc.) are unaffected.
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"""
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def __init__(self, **kwargs):
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if "gpt-5" in kwargs.get("model", "").lower():
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kwargs.pop("temperature", None)
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kwargs.pop("top_p", None)
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super().__init__(**kwargs)
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class OpenAIClient(BaseLLMClient):
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"""Client for OpenAI, Ollama, OpenRouter, and xAI providers."""
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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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llm_kwargs = {"model": self.model}
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if self.provider == "xai":
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llm_kwargs["base_url"] = "https://api.x.ai/v1"
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api_key = os.environ.get("XAI_API_KEY")
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if api_key:
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llm_kwargs["api_key"] = api_key
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elif self.provider == "openrouter":
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llm_kwargs["base_url"] = "https://openrouter.ai/api/v1"
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api_key = os.environ.get("OPENROUTER_API_KEY")
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if api_key:
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llm_kwargs["api_key"] = api_key
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elif self.provider == "ollama":
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# Check if Ollama is running before creating client
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if not _check_ollama_connection():
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raise OllamaConnectionError(
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"Ollama server is not running. Please start it with:\n"
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" • macOS/Linux: ollama serve\n"
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" • Or install from: https://ollama.ai\n"
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" • Default port: 11434"
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)
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llm_kwargs["base_url"] = "http://localhost:11434/v1"
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llm_kwargs["api_key"] = "ollama" # Ollama 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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for key in ("timeout", "max_retries", "reasoning_effort", "api_key", "callbacks", "http_client", "http_async_client"):
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if key in self.kwargs:
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llm_kwargs[key] = self.kwargs[key]
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return UnifiedChatOpenAI(**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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