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5f010823aa
Fixes # None Before submitting If you want to review, please refer to the quick start example provided in langchain/chains/dialogue_answering/main.py. You may need to set the openaikey and the following startup parameters: --dialogue-path: the location of the dialogue file, --embedding-model: the HuggingFaceEmbeddings model to use (defaults to GanymedeNil/text2vec-large-chinese) if not specified. Regarding the format of the dialogue file, please refer to the following information: ```text sun: Has the offline model been run? glide-the: Yes, it has been run, but the results are not very satisfactory. glide-the: It lacks chat intelligence and falls far behind in terms of logic and reasoning. sun: Are you available for voice chat? glide-the: I'm considering using this offline model: https://huggingface.co/chat glide-the: voice chat okay. glide-the: You can take a look at the dev_agent branch of the langchain-chatglm project. glide-the: There's a dialogue model question-answering example under the agent. sun: Alright. glide-the: The specified chat record file is exported from WeChat. ```
37 lines
1.4 KiB
Python
37 lines
1.4 KiB
Python
import sys
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import os
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import argparse
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import asyncio
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from argparse import Namespace
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sys.path.append(os.path.dirname(os.path.abspath(__file__)) + '/../../')
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from chains.dialogue_answering import *
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from langchain.llms import OpenAI
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from models.base import (BaseAnswer,
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AnswerResult)
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import models.shared as shared
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from models.loader.args import parser
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from models.loader import LoaderCheckPoint
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async def dispatch(args: Namespace):
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args_dict = vars(args)
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shared.loaderCheckPoint = LoaderCheckPoint(args_dict)
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llm_model_ins = shared.loaderLLM()
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if not os.path.isfile(args.dialogue_path):
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raise FileNotFoundError(f'Invalid dialogue file path for demo mode: "{args.dialogue_path}"')
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llm = OpenAI(temperature=0)
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dialogue_instance = DialogueWithSharedMemoryChains(zero_shot_react_llm=llm, ask_llm=llm_model_ins, params=args_dict)
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dialogue_instance.agent_chain.run(input="What did David say before, summarize it")
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if __name__ == '__main__':
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parser.add_argument('--dialogue-path', default='', type=str, help='dialogue-path')
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parser.add_argument('--embedding-model', default='', type=str, help='embedding-model')
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args = parser.parse_args(['--dialogue-path', '/home/dmeck/Downloads/log.txt',
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'--embedding-mode', '/media/checkpoint/text2vec-large-chinese/'])
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loop = asyncio.new_event_loop()
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asyncio.set_event_loop(loop)
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loop.run_until_complete(dispatch(args))
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