Update app.py

app.py

@@ -16,47 +16,42 @@ from langchain.llms import TextGen
 import os
 OPENAI_API_KEY=os.getenv('OPENAI_API_KEY')
 
-#分割文档
-text_splitter = CharacterTextSplitter(
-     separator="\n",
-     chunk_size=1000,
-     chunk_overlap=200,
-     length_function=len
- )
-
-texts = text_splitter.split_text("./output_1.txt")
-
 # 嵌入模型
 #embeddings = OpenAIEmbeddings()
-embeddings = HuggingFaceEmbeddings(model_name="sentence-transformers/all-mpnet-base-v2")
+embeddings = HuggingFaceEmbeddings(model_name="BAAI/bge-large-en")
 
 # 加载数据
-docsearch = FAISS.from_texts(texts, embeddings)
+#docsearch = FAISS.from_texts(texts, embeddings)
+docsearch = FAISS.load_local("./bge-large-en_faiss_index/faiss_index", embeddings)
 
-model_url = "http://36.103.234.50:5000"
 
-llm = TextGen(model_url=model_url)
+chain = load_qa_chain(OpenAI(), chain_type="stuff",verbose=True)
 
-chain = load_qa_chain(llm)
+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"
 
 def predict(message, history):
-    history_langchain_format = []
-    for human, ai in history:
-        history_langchain_format.append(HumanMessage(content=human))
-        history_langchain_format.append(AIMessage(content=ai))
-    history_langchain_format.append(HumanMessage(content=message))
-    docs = docsearch.similarity_search(message)
-    response = chain.run(input_documents=docs, question=message)
-    
+    history_openai_format = []
+    for human, assistant in history:
+        history_openai_format.append({"role": "system", "content": prompt })
+        history_openai_format.append({"role": "user", "content": human })
+        history_openai_format.append({"role": "assistant", "content":assistant})
+    history_openai_format.append({"role": "user", "content": message})
+
+    response = openai.ChatCompletion.create(
+        model='gpt-3.5-turbo',
+        messages= history_openai_format,         
+        temperature=1.0,
+        stream=True
+    )
 
     partial_message = ""
     for chunk in response:
-        if len(chunk) != 0:
-            partial_message = partial_message + chunk
-            yield partial_message 
-
-    
-    return response
-
-gr.ChatInterface(predict).queue().launch()
-
+        if len(chunk['choices'][0]['delta']) != 0:
+            partial_message = partial_message + chunk['choices'][0]['delta']['content']
+            yield partial_message    
+   
+gr.ChatInterface(predict,
+    textbox=gr.Textbox(placeholder="请输入您的问题", container=False, scale=7),
+    title="欢迎使用ANSYS软件AI机器人",
+    examples=["你是谁?", "请介绍一下Fluent 软件的用户界面说明", "请用关于春天写一首100字的诗","数学题：小红有3元钱，小红买了2斤香蕉，香蕉的价格是每斤1元。问小红一共花了多少钱?","请用表格做一份学生课程表"],
+                description="🦊请避免输入有违公序良俗的问题，模型可能无法回答不合适的问题🐇",).queue().launch(auth=(USER, PASS))