fengtc commited on
Commit
6e4a868
·
1 Parent(s): c559a2e

Update app.py

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Files changed (1) hide show
  1. app.py +9 -3
app.py CHANGED
@@ -28,6 +28,9 @@ import langchain
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  import os
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  OPENAI_API_KEY=os.getenv('OPENAI_API_KEY')
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  # 嵌入模型
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  #embeddings = OpenAIEmbeddings()
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  embeddings = HuggingFaceEmbeddings(model_name="BAAI/bge-large-en")
@@ -35,16 +38,19 @@ embeddings = HuggingFaceEmbeddings(model_name="BAAI/bge-large-en")
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  # 加载数据
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  #docsearch = FAISS.from_texts(texts, embeddings)
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  docsearch = FAISS.load_local("./faiss_index", embeddings)
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- chain = load_qa_chain(OpenAI(temperature=0,model_name="gpt-3.5-turbo", verbose=True), chain_type="stuff",verbose=True)
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- template="您是回答所有ANSYS软件使用查询的得力助手,如果所问的内容不在范围内,请回答您提的问题不在本知识库内,请重新提问. {input_language} to {output_language}."
 
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  system_message_prompt = SystemMessagePromptTemplate.from_template(template)
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  human_template="{text}"
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  human_message_prompt = HumanMessagePromptTemplate.from_template(human_template)
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- #prompt = "您是回答所有ANSYS软件使用查询的得力助手,如果所问的内容不在范围内,请回答您提的问题不在本知识库内,请重新提问,所有问题必需用中文回答"
 
 
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  def predict(message, history):
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  history_langchain_format = []
 
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  import os
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  OPENAI_API_KEY=os.getenv('OPENAI_API_KEY')
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+
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+
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+
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  # 嵌入模型
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  #embeddings = OpenAIEmbeddings()
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  embeddings = HuggingFaceEmbeddings(model_name="BAAI/bge-large-en")
 
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  # 加载数据
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  #docsearch = FAISS.from_texts(texts, embeddings)
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  docsearch = FAISS.load_local("./faiss_index", embeddings)
 
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+ #chain = load_qa_chain(OpenAI(temperature=0,model_name="gpt-3.5-turbo",prompt=chat_prompt), chain_type="stuff",verbose=True)
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+
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+ template="您是回答ANSYS软件使用查询的得力助手,所有回复必需用中文 {input_language} to {output_language}."
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  system_message_prompt = SystemMessagePromptTemplate.from_template(template)
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  human_template="{text}"
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  human_message_prompt = HumanMessagePromptTemplate.from_template(human_template)
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+ chat_prompt = ChatPromptTemplate.from_messages([system_message_prompt, human_message_prompt])
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+ chain = load_qa_chain(OpenAI(temperature=0,model_name="gpt-3.5-turbo",prompt=chat_prompt), chain_type="stuff",verbose=True)
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+
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  def predict(message, history):
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  history_langchain_format = []