Spaces:
Running
on
T4
Running
on
T4
thomas-yanxin
commited on
Commit
•
ed22028
1
Parent(s):
38a1665
fix bug
Browse files
app.py
CHANGED
@@ -102,11 +102,13 @@ def get_knowledge_based_answer(query,
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prompt = PromptTemplate(template=prompt_template,
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input_variables=["context", "question"])
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chatLLM = ChatLLM()
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chatLLM.load_model(model_name_or_path=llm_model_dict[large_language_model])
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chatLLM.history = chat_history[-history_len:] if history_len > 0 else []
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knowledge_chain = RetrievalQA.from_llm(
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llm=chatLLM,
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@@ -177,14 +179,14 @@ if __name__ == "__main__":
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large_language_model = gr.Dropdown(
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list(llm_model_dict.keys()),
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label="large language model",
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value="ChatGLM-6B-
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embedding_model = gr.Dropdown(list(embedding_model_dict.keys()),
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label="Embedding model",
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value="text2vec-base")
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file = gr.File(label='请上传知识库文件',
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file_types=['.txt', '.md', '.docx'
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use_web = gr.Radio(["True", "False"], label="Web Search",
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value="False"
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prompt = PromptTemplate(template=prompt_template,
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input_variables=["context", "question"])
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chatLLM = ChatLLM()
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chatLLM.history = chat_history[-history_len:] if history_len > 0 else []
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if large_language_model == "Minimax":
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chatLLM.model = 'Minimax'
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else:
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chatLLM.load_model(model_name_or_path=llm_model_dict[large_language_model])
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chatLLM.temperature = temperature
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chatLLM.top_p = top_p
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knowledge_chain = RetrievalQA.from_llm(
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llm=chatLLM,
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large_language_model = gr.Dropdown(
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list(llm_model_dict.keys()),
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label="large language model",
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value="ChatGLM-6B-int4")
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embedding_model = gr.Dropdown(list(embedding_model_dict.keys()),
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label="Embedding model",
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value="text2vec-base")
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file = gr.File(label='请上传知识库文件',
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file_types=['.txt', '.md', '.docx'])
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use_web = gr.Radio(["True", "False"], label="Web Search",
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value="False"
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