shukdevdatta123 commited on
Commit
6427929
·
verified ·
1 Parent(s): 76fbbc1

Update generate_answer.py

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Files changed (1) hide show
  1. generate_answer.py +9 -6
generate_answer.py CHANGED
@@ -1,11 +1,15 @@
 
 
1
  import os
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  from glob import glob
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  import openai
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  from dotenv import load_dotenv
 
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  from langchain.embeddings import OpenAIEmbeddings
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  from langchain.vectorstores import Chroma
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  from langchain.document_loaders import PyPDFLoader
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  from langchain.text_splitter import RecursiveCharacterTextSplitter
 
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  from langchain_community.chat_models import ChatOpenAI
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  from langchain.chains import RetrievalQA
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  from langchain.memory import ConversationBufferMemory
@@ -18,13 +22,12 @@ openai.api_key = api_key
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  def base_model_chatbot(messages):
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  system_message = [
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- {"role": "system", "content": "You are a helpful AI chatbot, that answers questions asked by User."}
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  ]
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  messages = system_message + messages
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  response = openai.ChatCompletion.create(
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- model="gpt-3.5-turbo",
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- messages=messages,
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- max_tokens=1500 # Increase max_tokens limit
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  )
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  return response.choices[0].message['content']
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@@ -66,11 +69,11 @@ class ConversationalRetrievalChain:
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  retriever=retriever,
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  memory=memory,
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  )
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-
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  def with_pdf_chatbot(messages):
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  """Main function to execute the QA system."""
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  query = messages[-1]['content'].strip()
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  qa_chain = ConversationalRetrievalChain().create_chain()
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  result = qa_chain({"query": query})
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- return result['result']
 
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+ ### generate_answer.py
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+
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  import os
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  from glob import glob
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  import openai
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  from dotenv import load_dotenv
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+
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  from langchain.embeddings import OpenAIEmbeddings
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  from langchain.vectorstores import Chroma
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  from langchain.document_loaders import PyPDFLoader
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  from langchain.text_splitter import RecursiveCharacterTextSplitter
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+
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  from langchain_community.chat_models import ChatOpenAI
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  from langchain.chains import RetrievalQA
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  from langchain.memory import ConversationBufferMemory
 
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  def base_model_chatbot(messages):
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  system_message = [
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+ {"role": "system", "content": "You are an helpful AI chatbot, that answers questions asked by User."}
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  ]
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  messages = system_message + messages
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  response = openai.ChatCompletion.create(
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+ model="gpt-3.5-turbo", # Ensure the model is specified correctly
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+ messages=messages
 
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  )
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  return response.choices[0].message['content']
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  retriever=retriever,
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  memory=memory,
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  )
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+
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  def with_pdf_chatbot(messages):
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  """Main function to execute the QA system."""
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  query = messages[-1]['content'].strip()
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  qa_chain = ConversationalRetrievalChain().create_chain()
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  result = qa_chain({"query": query})
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+ return result['result']