mirror of
https://github.com/affaan-m/everything-claude-code.git
synced 2026-04-15 14:33:33 +08:00
74b91cb3f3
- Fix gui() function import in __init__.py (use cli.selector) - Fix prompt builder system message merging logic - Add default max_tokens for Anthropic API in claude.py - Fix openai tool_call arguments parsing with json.loads - Fix test_builder.py PromptConfig import and assertions
115 lines
4.0 KiB
Python
115 lines
4.0 KiB
Python
"""OpenAI provider adapter."""
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from __future__ import annotations
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import json
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import os
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from typing import Any
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from openai import OpenAI
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from llm.core.interface import (
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AuthenticationError,
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ContextLengthError,
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LLMProvider,
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RateLimitError,
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)
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from llm.core.types import LLMInput, LLMOutput, Message, ModelInfo, ProviderType, ToolCall
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class OpenAIProvider(LLMProvider):
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provider_type = ProviderType.OPENAI
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def __init__(self, api_key: str | None = None, base_url: str | None = None) -> None:
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self.client = OpenAI(api_key=api_key or os.environ.get("OPENAI_API_KEY"), base_url=base_url)
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self._models = [
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ModelInfo(
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name="gpt-4o",
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provider=ProviderType.OPENAI,
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supports_tools=True,
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supports_vision=True,
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max_tokens=4096,
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context_window=128000,
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),
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ModelInfo(
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name="gpt-4o-mini",
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provider=ProviderType.OPENAI,
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supports_tools=True,
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supports_vision=True,
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max_tokens=4096,
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context_window=128000,
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),
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ModelInfo(
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name="gpt-4-turbo",
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provider=ProviderType.OPENAI,
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supports_tools=True,
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supports_vision=True,
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max_tokens=4096,
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context_window=128000,
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),
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ModelInfo(
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name="gpt-3.5-turbo",
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provider=ProviderType.OPENAI,
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supports_tools=True,
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supports_vision=False,
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max_tokens=4096,
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context_window=16385,
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),
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]
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def generate(self, input: LLMInput) -> LLMOutput:
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try:
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params: dict[str, Any] = {
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"model": input.model or "gpt-4o-mini",
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"messages": [msg.to_dict() for msg in input.messages],
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"temperature": input.temperature,
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}
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if input.max_tokens:
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params["max_tokens"] = input.max_tokens
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if input.tools:
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params["tools"] = [tool.to_dict() for tool in input.tools]
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response = self.client.chat.completions.create(**params)
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choice = response.choices[0]
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tool_calls = None
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if choice.message.tool_calls:
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tool_calls = [
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ToolCall(
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id=tc.id or "",
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name=tc.function.name,
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arguments={} if not tc.function.arguments else json.loads(tc.function.arguments),
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)
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for tc in choice.message.tool_calls
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]
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return LLMOutput(
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content=choice.message.content or "",
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tool_calls=tool_calls,
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model=response.model,
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usage={
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"prompt_tokens": response.usage.prompt_tokens,
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"completion_tokens": response.usage.completion_tokens,
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"total_tokens": response.usage.total_tokens,
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},
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stop_reason=choice.finish_reason,
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)
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except Exception as e:
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msg = str(e)
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if "401" in msg or "authentication" in msg.lower():
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raise AuthenticationError(msg, provider=ProviderType.OPENAI) from e
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if "429" in msg or "rate_limit" in msg.lower():
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raise RateLimitError(msg, provider=ProviderType.OPENAI) from e
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if "context" in msg.lower() and "length" in msg.lower():
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raise ContextLengthError(msg, provider=ProviderType.OPENAI) from e
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raise
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def list_models(self) -> list[ModelInfo]:
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return self._models.copy()
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def validate_config(self) -> bool:
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return bool(self.client.api_key)
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def get_default_model(self) -> str:
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return "gpt-4o-mini"
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