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LangBot/pkg/provider/modelmgr/requesters/anthropicmsgs.py
T
2024-12-24 11:26:33 +08:00

121 lines
4.0 KiB
Python

from __future__ import annotations
import typing
import traceback
import base64
import anthropic
import httpx
from .. import entities, errors, requester
from .. import entities, errors
from ....core import entities as core_entities
from ... import entities as llm_entities
from ...tools import entities as tools_entities
from ....utils import image
@requester.requester_class("anthropic-messages")
class AnthropicMessages(requester.LLMAPIRequester):
"""Anthropic Messages API 请求器"""
client: anthropic.AsyncAnthropic
async def initialize(self):
httpx_client = anthropic._base_client.AsyncHttpxClientWrapper(
base_url=self.ap.provider_cfg.data['requester']['anthropic-messages']['base-url'],
# cast to a valid type because mypy doesn't understand our type narrowing
timeout=typing.cast(httpx.Timeout, self.ap.provider_cfg.data['requester']['anthropic-messages']['timeout']),
limits=anthropic._constants.DEFAULT_CONNECTION_LIMITS,
follow_redirects=True,
proxies=self.ap.proxy_mgr.get_forward_proxies()
)
self.client = anthropic.AsyncAnthropic(
api_key="",
http_client=httpx_client,
)
async def call(
self,
query: core_entities.Query,
model: entities.LLMModelInfo,
messages: typing.List[llm_entities.Message],
funcs: typing.List[tools_entities.LLMFunction] = None,
) -> llm_entities.Message:
self.client.api_key = model.token_mgr.get_token()
args = self.ap.provider_cfg.data['requester']['anthropic-messages']['args'].copy()
args["model"] = model.name if model.model_name is None else model.model_name
# 处理消息
# system
system_role_message = None
for i, m in enumerate(messages):
if m.role == "system":
system_role_message = m
messages.pop(i)
break
if isinstance(system_role_message, llm_entities.Message) \
and isinstance(system_role_message.content, str):
args['system'] = system_role_message.content
req_messages = []
for m in messages:
if isinstance(m.content, str) and m.content.strip() != "":
req_messages.append(m.dict(exclude_none=True))
elif isinstance(m.content, list):
msg_dict = m.dict(exclude_none=True)
for i, ce in enumerate(m.content):
if ce.type == "image_base64":
image_b64, image_format = await image.extract_b64_and_format(ce.image_base64)
alter_image_ele = {
"type": "image",
"source": {
"type": "base64",
"media_type": f"image/{image_format}",
"data": image_b64
}
}
msg_dict["content"][i] = alter_image_ele
req_messages.append(msg_dict)
args["messages"] = req_messages
# anthropic的tools处在beta阶段,sdk不稳定,故暂时不支持
#
# if funcs:
# tools = await self.ap.tool_mgr.generate_tools_for_openai(funcs)
# if tools:
# args["tools"] = tools
try:
resp = await self.client.messages.create(**args)
return llm_entities.Message(
content=resp.content[0].text,
role=resp.role
)
except anthropic.AuthenticationError as e:
raise errors.RequesterError(f'api-key 无效: {e.message}')
except anthropic.BadRequestError as e:
raise errors.RequesterError(str(e.message))
except anthropic.NotFoundError as e:
if 'model: ' in str(e):
raise errors.RequesterError(f'模型无效: {e.message}')
else:
raise errors.RequesterError(f'请求地址无效: {e.message}')