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114 lines
3.8 KiB
Python
114 lines
3.8 KiB
Python
from __future__ import annotations
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import typing
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import traceback
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import anthropic
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from .. import entities, errors, requester
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from .. import entities, errors
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from ....core import entities as core_entities
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from ... import entities as llm_entities
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from ...tools import entities as tools_entities
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from ....utils import image
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@requester.requester_class("anthropic-messages")
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class AnthropicMessages(requester.LLMAPIRequester):
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"""Anthropic Messages API 请求器"""
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client: anthropic.AsyncAnthropic
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async def initialize(self):
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self.client = anthropic.AsyncAnthropic(
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api_key="",
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base_url=self.ap.provider_cfg.data['requester']['anthropic-messages']['base-url'],
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timeout=self.ap.provider_cfg.data['requester']['anthropic-messages']['timeout'],
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proxies=self.ap.proxy_mgr.get_forward_proxies()
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)
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async def call(
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self,
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model: entities.LLMModelInfo,
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messages: typing.List[llm_entities.Message],
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funcs: typing.List[tools_entities.LLMFunction] = None,
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) -> llm_entities.Message:
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self.client.api_key = model.token_mgr.get_token()
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args = self.ap.provider_cfg.data['requester']['anthropic-messages']['args'].copy()
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args["model"] = model.name if model.model_name is None else model.model_name
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# 处理消息
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# system
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system_role_message = None
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for i, m in enumerate(messages):
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if m.role == "system":
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system_role_message = m
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messages.pop(i)
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break
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if isinstance(system_role_message, llm_entities.Message) \
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and isinstance(system_role_message.content, str):
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args['system'] = system_role_message.content
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req_messages = []
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for m in messages:
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if isinstance(m.content, str) and m.content.strip() != "":
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req_messages.append(m.dict(exclude_none=True))
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elif isinstance(m.content, list):
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# m.content = [
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# c for c in m.content if c.type == "text"
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# ]
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# if len(m.content) > 0:
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# req_messages.append(m.dict(exclude_none=True))
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msg_dict = m.dict(exclude_none=True)
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for i, ce in enumerate(m.content):
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if ce.type == "image_url":
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base64_image, image_format = await image.qq_image_url_to_base64(ce.image_url.url)
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alter_image_ele = {
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"type": "image",
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"source": {
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"type": "base64",
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"media_type": f"image/{image_format}",
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"data": base64_image
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}
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}
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msg_dict["content"][i] = alter_image_ele
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req_messages.append(msg_dict)
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args["messages"] = req_messages
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# anthropic的tools处在beta阶段，sdk不稳定，故暂时不支持
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#
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# if funcs:
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# tools = await self.ap.tool_mgr.generate_tools_for_openai(funcs)
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# if tools:
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# args["tools"] = tools
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try:
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resp = await self.client.messages.create(**args)
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return llm_entities.Message(
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content=resp.content[0].text,
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role=resp.role
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)
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except anthropic.AuthenticationError as e:
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raise errors.RequesterError(f'api-key 无效: {e.message}')
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except anthropic.BadRequestError as e:
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raise errors.RequesterError(str(e.message))
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except anthropic.NotFoundError as e:
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if 'model: ' in str(e):
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raise errors.RequesterError(f'模型无效: {e.message}')
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else:
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raise errors.RequesterError(f'请求地址无效: {e.message}')
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