100 lines
3.7 KiB
Python
100 lines
3.7 KiB
Python
import json
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from typing import List
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from aiohttp import ClientSession
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from mautrix.types import MessageEvent
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from mautrix.util.config import BaseProxyConfig
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import maubot_llmplus
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import maubot_llmplus.platforms
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from maubot_llmplus.platforms import Platform, ChatCompletion
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from maubot_llmplus.plugin import AbsExtraConfigPlugin
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class Ollama(Platform):
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def __init__(self, config: BaseProxyConfig, http: ClientSession) -> None:
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super().__init__(config, http)
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async def create_chat_completion(self, plugin: AbsExtraConfigPlugin, evt: MessageEvent) -> ChatCompletion:
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full_context = []
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context = await maubot_llmplus.platforms.get_context(plugin, self, evt)
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full_context.extend(list(context))
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endpoint = f"{self.url}/api/chat"
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req_body = {'model': self.model, 'messages': full_context, 'stream': False}
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headers = {'Content-Type': 'application/json'}
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async with self.http.post(endpoint, headers=headers, json=req_body) as response:
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# plugin.log.debug(f"响应内容：{response.status}, {await response.json()}")
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if response.status != 200:
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return ChatCompletion(
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message={},
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finish_reason=f"http status {response.status}",
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model=None
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)
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response_json = await response.json()
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return ChatCompletion(
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message=response_json['message'],
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finish_reason='success',
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model=response_json['model']
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)
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async def list_models(self) -> List[str]:
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full_url = f"{self.url}/api/tags"
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async with self.http.get(full_url) as response:
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if response.status != 200:
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return []
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response_data = await response.json()
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return [f"- {model['model']}" for model in response_data['models']]
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def get_type(self) -> str:
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return "local_ai"
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class LmStudio(Platform) :
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temperature: int
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def __init__(self, config: BaseProxyConfig, http: ClientSession) -> None:
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super().__init__(config, http)
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self.temperature = self.config['temperature']
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pass
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async def create_chat_completion(self, plugin: AbsExtraConfigPlugin, evt: MessageEvent) -> ChatCompletion:
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full_context = []
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context = await maubot_llmplus.platforms.get_context(plugin, self, evt)
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full_context.extend(list(context))
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endpoint = f"{self.url}/v1/chat/completions"
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headers = {"content-type": "application/json"}
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req_body = {"model": self.model, "messages": full_context, "temperature": self.temperature, "stream": False}
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async with self.http.post(
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endpoint, headers=headers, data=json.dumps(req_body)
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) as response:
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# plugin.log.debug(f"响应内容：{response.status}, {await response.json()}")
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if response.status != 200:
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return ChatCompletion(
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message={},
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finish_reason=f"Error: {await response.text()}",
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model=None
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)
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response_json = await response.json()
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choice = response_json["choices"][0]
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return ChatCompletion(
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message=choice["message"],
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finish_reason=choice["finish_reason"],
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model=choice.get("model", None)
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)
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async def list_models(self) -> List[str]:
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full_url = f"{self.url}/v1/models"
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async with self.http.get(full_url) as response:
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if response.status != 200:
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return []
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response_data = await response.json()
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return [f"- {m['id']}" for m in response_data["data"]]
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def get_type(self) -> str:
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return "local_ai"
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