SungBeom commited on
Commit
d23f041
1 Parent(s): 7c801ef

Update app.py

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Files changed (1) hide show
  1. app.py +6 -4
app.py CHANGED
@@ -39,11 +39,11 @@ stage_analyzer_chain = LLMChain(
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  output_key="stage_number")
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  user_response_prompt = load_prompt("./templates/user_response_prompt.json")
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- llm = ChatOpenAI(model='gpt-3.5-turbo', temperature=0.0)
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  user_response_chain = LLMChain(
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  llm=llm,
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  prompt=user_response_prompt,
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- verbose=True,
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  output_key="user_responses"
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  )
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@@ -175,8 +175,8 @@ Last user saying: {input}
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  conversation_stages_dict = {
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  "1": "Start: Start the conversation by introducing yourself. Be polite and respectful while maintaining a professional tone of conversation.",
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  "2": "Analyze: Identify the user's preferences in order to make wine recommendations. Ask questions to understand the preferences of your users in order to make wine recommendations. Ask only one question at a time. The wine database tool is not available here.",
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- "3": "Recommendation: Recommend the right wine based on the user's preferences identified. Recommendations must be limited to wines in wine database, and you can use tools to do this.",
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- "4": "After recommendation: After making a wine recommendation, it asks if the user likes the wine you recommended, and if they do, it provides a link and image to it. Otherwise, it takes you back to the recommendation stage.",
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  "5": "Close: When you're done, say goodbye to the user.",
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  "6": "Question and Answering: This is where you answer the user's questions. To answer user question, you can use the search tool or the wine database tool.",
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  "7": "Not in the given steps: This step is for when none of the steps between 1 and 6 apply.",
@@ -295,6 +295,8 @@ with gr.Blocks(css='#chatbot .overflow-y-auto{height:750px}') as demo:
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  stage_history += stage_number if stage_history == "stage history: " else ", " + stage_number
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  response = agent_executor.run({'input':user_response, 'conversation_history': pre_conversation_history, 'stage_number': stage_number})
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  conversation_history += "이우선: " + response + "\n"
 
 
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  response = response.split('<END_OF_TURN>')[0]
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  chat_history.append((user_response, response))
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  user_response_examples = []
 
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  output_key="stage_number")
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  user_response_prompt = load_prompt("./templates/user_response_prompt.json")
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+ llm = ChatOpenAI(model='gpt-4', temperature=0.5)
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  user_response_chain = LLMChain(
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  llm=llm,
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  prompt=user_response_prompt,
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+ verbose=False,
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  output_key="user_responses"
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  )
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  conversation_stages_dict = {
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  "1": "Start: Start the conversation by introducing yourself. Be polite and respectful while maintaining a professional tone of conversation.",
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  "2": "Analyze: Identify the user's preferences in order to make wine recommendations. Ask questions to understand the preferences of your users in order to make wine recommendations. Ask only one question at a time. The wine database tool is not available here.",
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+ "3": "Recommendation: Recommend the right wine based on the user's preferences identified. Recommendations must be limited to wines in wine database, and you can use tools to do this. After making a wine recommendation, it asks if the user likes the wine you recommended.",
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+ "4": "After recommendation: If the user likes the wine you recommended, provides a link and image of wine. Otherwise, it takes you back to the recommendation stage.",
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  "5": "Close: When you're done, say goodbye to the user.",
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  "6": "Question and Answering: This is where you answer the user's questions. To answer user question, you can use the search tool or the wine database tool.",
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  "7": "Not in the given steps: This step is for when none of the steps between 1 and 6 apply.",
 
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  stage_history += stage_number if stage_history == "stage history: " else ", " + stage_number
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  response = agent_executor.run({'input':user_response, 'conversation_history': pre_conversation_history, 'stage_number': stage_number})
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  conversation_history += "이우선: " + response + "\n"
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+ for line in conversation_history.split('\n'):
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+ print(line)
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  response = response.split('<END_OF_TURN>')[0]
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  chat_history.append((user_response, response))
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  user_response_examples = []