mirror of
https://github.com/catlog22/Claude-Code-Workflow.git
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bf66b095c7
- Create ccw-litellm Python package with AbstractEmbedder and AbstractLLMClient interfaces - Add BaseEmbedder abstraction and factory pattern to codex-lens for pluggable backends - Implement API Settings dashboard page for provider credentials and custom endpoints - Add REST API routes for CRUD operations on providers and endpoints - Extend CLI with --model parameter for custom endpoint routing - Integrate existing context-cache for @pattern file resolution - Add provider model registry with predefined models per provider type - Include i18n translations (en/zh) for all new UI elements 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
46 lines
1.3 KiB
Python
46 lines
1.3 KiB
Python
from __future__ import annotations
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import asyncio
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from abc import ABC, abstractmethod
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from dataclasses import dataclass
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from typing import Any, Literal, Sequence
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@dataclass(frozen=True, slots=True)
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class ChatMessage:
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role: Literal["system", "user", "assistant", "tool"]
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content: str
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@dataclass(frozen=True, slots=True)
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class LLMResponse:
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content: str
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raw: Any | None = None
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class AbstractLLMClient(ABC):
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"""LiteLLM-like client interface.
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Implementers only need to provide synchronous methods; async wrappers are
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provided via `asyncio.to_thread`.
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"""
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@abstractmethod
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def chat(self, messages: Sequence[ChatMessage], **kwargs: Any) -> LLMResponse:
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"""Chat completion for a sequence of messages."""
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@abstractmethod
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def complete(self, prompt: str, **kwargs: Any) -> LLMResponse:
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"""Text completion for a prompt."""
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async def achat(self, messages: Sequence[ChatMessage], **kwargs: Any) -> LLMResponse:
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"""Async wrapper around `chat` using a worker thread by default."""
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return await asyncio.to_thread(self.chat, messages, **kwargs)
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async def acomplete(self, prompt: str, **kwargs: Any) -> LLMResponse:
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"""Async wrapper around `complete` using a worker thread by default."""
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return await asyncio.to_thread(self.complete, prompt, **kwargs)
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