pip install -U chatllm
计划推出国内 oneapi，支持各种主流大模型，兼容openai客户端生态。
from chatllm.applications import ChatBase
qa = ChatBase()
qa.load_llm(model_name_or_path="THUDM/chatglm-6b")
for i in qa(query='周杰伦是谁', knowledge_base='周杰伦是傻子'):
print(i, end='')
# 根据已知信息无法回答该问题，因为周杰伦是中国内地流行歌手、演员、音乐制作人、导演，
# 是具有一定的知名度和专业能力的人物，没有提供足够的信息无法判断他是傻子。
# 服务端
pip install "chatllm[openai]" && chatllm-run openai <本地模型地址>
pip install openaiimport openai
openai.api_base = 'http://0.0.0.0:8000/v1'
openai.api_key = 'chatllm'
prompt = "你好"
completion = openai.Completion.create(prompt=prompt, stream=True, model="text-davinci-003")
for c in completion:
print(c.choices[0].text, end='')
# 你好👋!我是人工智能助手 ChatGLM-6B,很高兴见到你，欢迎问我任何问题。
不定期更新免费keysfrom meutils.pipe import *
from chatllm.llmchain.applications import ChatOCR
llm = ChatOCR()
file_path = "data/invoice.jpg"
llm.display(file_path, 700)
llm.chat('识别编号,公司名称,开票日期,开票人,收款人,复核人,金额', file_path=file_path) | xprint
pip install "chatllm" && chatllm-run webui --name chatmind
pip install "chatllm[pdf]" && chatllm-run webui --name chatpdf
from chatllm.applications.chatpdf import ChatPDF
qa = ChatPDF(encode_model='nghuyong/ernie-3.0-nano-zh')
qa.load_llm(model_name_or_path="THUDM/chatglm-6b")
qa.create_index('财报.pdf') # 构建知识库
for i in qa(query='东北证券主营业务'):
print(i, end='')
# 根据已知信息，东北证券的主营业务为证券业务。公司作为证券公司，主要从事证券经纪、证券投资咨询、与证券交易、
# 证券投资活动有关的财务顾问、证券承销与保荐、证券自营、融资融券、证券投资基金代销和代销金融产品待业务。
| 量化等级 | 最低 GPU 显存（推理） | 最低 GPU 显存（高效参数微调） |
|---|---|---|
| FP16（无量化） | 13 GB | 14 GB |
| INT8 | 8 GB | 9 GB |
| INT4 | 6 GB | 7 GB |
ChatLLM 应用
多路召回
增加更多 LLM 模型支持
增加更多 Embedding 模型支持
增加一键启动 webui
chatllm-run webui --name chatpdf增加 API 支持
chatllm-run openai <本地模型地址> --host 127.0.0.1 --port 8000
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We found that chatllm demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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