mirror of
https://github.com/affaan-m/everything-claude-code.git
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b39d2244cf
- add Vite and Redis pattern skills from closed stale PRs - add frontend-slides support assets - port skill-comply runner fixes and LLM prompt/provider regressions - harden agent frontmatter validation and sync catalog counts
118 lines
4.3 KiB
Python
118 lines
4.3 KiB
Python
"""Claude provider adapter."""
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from __future__ import annotations
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import os
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from typing import Any
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from anthropic import Anthropic
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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 ClaudeProvider(LLMProvider):
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provider_type = ProviderType.CLAUDE
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def __init__(self, api_key: str | None = None, base_url: str | None = None) -> None:
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self.client = Anthropic(api_key=api_key or os.environ.get("ANTHROPIC_API_KEY"), base_url=base_url)
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self._models = [
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ModelInfo(
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name="claude-opus-4-5",
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provider=ProviderType.CLAUDE,
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supports_tools=True,
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supports_vision=True,
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max_tokens=8192,
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context_window=200000,
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),
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ModelInfo(
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name="claude-sonnet-4-7",
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provider=ProviderType.CLAUDE,
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supports_tools=True,
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supports_vision=True,
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max_tokens=8192,
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context_window=200000,
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),
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ModelInfo(
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name="claude-haiku-4-7",
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provider=ProviderType.CLAUDE,
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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=200000,
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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 "claude-sonnet-4-7",
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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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else:
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params["max_tokens"] = 8192 # required by Anthropic API
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if input.tools:
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params["tools"] = [tool.to_anthropic_tool() for tool in input.tools]
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response = self.client.messages.create(**params)
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text_parts: list[str] = []
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tool_calls: list[ToolCall] = []
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for block in response.content or []:
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block_type = getattr(block, "type", None)
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if block_type == "text":
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text = getattr(block, "text", "")
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if text:
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text_parts.append(text)
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elif block_type == "tool_use":
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raw_arguments = getattr(block, "input", {})
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arguments = (
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raw_arguments.copy()
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if isinstance(raw_arguments, dict)
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else getattr(raw_arguments, "__dict__", {}).copy()
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)
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tool_calls.append(
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ToolCall(
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id=getattr(block, "id", ""),
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name=getattr(block, "name", ""),
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arguments=arguments,
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)
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)
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return LLMOutput(
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content="".join(text_parts),
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tool_calls=tool_calls or None,
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model=response.model,
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usage={
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"input_tokens": response.usage.input_tokens,
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"output_tokens": response.usage.output_tokens,
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},
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stop_reason=response.stop_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.CLAUDE) 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.CLAUDE) 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.CLAUDE) 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 "claude-sonnet-4-7"
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