ecepekaslan commited on
Commit
b6dfad6
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1 Parent(s): 6e74c0b

Upload app.py

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Files changed (1) hide show
  1. app.py +40 -40
app.py CHANGED
@@ -37,54 +37,54 @@ def chat(temperature, model_name):
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  tmp_file.write(uploaded_file.getvalue())
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  tmp_file_path = tmp_file.name
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- loader = CSVLoader(file_path=tmp_file_path, encoding="utf-8")
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- data = loader.load()
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- embeddings = OpenAIEmbeddings()
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- vectors = FAISS.from_documents(data, embeddings)
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- chain = ConversationalRetrievalChain.from_llm(llm = ChatOpenAI(temperature=0.0,model_name='gpt-3.5-turbo', openai_api_key=user_api_key),
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- retriever=vectors.as_retriever())
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- def conversational_chat(query):
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-
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- result = chain({"question": query, "chat_history": st.session_state['history']})
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- st.session_state['history'].append((query, result["answer"]))
 
 
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- return result["answer"]
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-
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- if 'history' not in st.session_state:
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- st.session_state['history'] = []
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- if 'generated' not in st.session_state:
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- st.session_state['generated'] = ["Hello ! Ask me anything about " + uploaded_file.name + " 🤗"]
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-
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- if 'past' not in st.session_state:
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- st.session_state['past'] = ["Hey ! 👋"]
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-
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- #container for the chat history
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- response_container = st.container()
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- #container for the user's text input
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- container = st.container()
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- with container:
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- with st.form(key='my_form', clear_on_submit=True):
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- user_input = st.text_input("Query:", placeholder="Talk about your csv data here (:", key='input')
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- submit_button = st.form_submit_button(label='Send')
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-
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- if submit_button and user_input:
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- output = conversational_chat(user_input)
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-
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- st.session_state['past'].append(user_input)
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- st.session_state['generated'].append(output)
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-
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- if st.session_state['generated']:
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- with response_container:
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- for i in range(len(st.session_state['generated'])):
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- message(st.session_state["past"][i], is_user=True, key=str(i) + '_user', avatar_style="big-smile")
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- message(st.session_state["generated"][i], key=str(i), avatar_style="thumbs")
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  # Main App
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  st.markdown(
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  """
 
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  tmp_file.write(uploaded_file.getvalue())
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  tmp_file_path = tmp_file.name
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+ loader = CSVLoader(file_path=tmp_file_path, encoding="utf-8")
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+ data = loader.load()
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+ embeddings = OpenAIEmbeddings()
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+ vectors = FAISS.from_documents(data, embeddings)
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+ chain = ConversationalRetrievalChain.from_llm(llm = ChatOpenAI(temperature=0.0,model_name='gpt-3.5-turbo', openai_api_key=user_api_key),
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+ retriever=vectors.as_retriever())
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+ def conversational_chat(query):
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+
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+ result = chain({"question": query, "chat_history": st.session_state['history']})
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+ st.session_state['history'].append((query, result["answer"]))
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+
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+ return result["answer"]
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+ if 'history' not in st.session_state:
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+ st.session_state['history'] = []
 
 
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+ if 'generated' not in st.session_state:
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+ st.session_state['generated'] = ["Hello ! Ask me anything about " + uploaded_file.name + " 🤗"]
 
 
 
 
 
 
 
 
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+ if 'past' not in st.session_state:
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+ st.session_state['past'] = ["Hey ! 👋"]
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+ #container for the chat history
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+ response_container = st.container()
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+ #container for the user's text input
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+ container = st.container()
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+
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+ with container:
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+ with st.form(key='my_form', clear_on_submit=True):
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+
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+ user_input = st.text_input("Query:", placeholder="Talk about your csv data here (:", key='input')
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+ submit_button = st.form_submit_button(label='Send')
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+
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+ if submit_button and user_input:
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+ output = conversational_chat(user_input)
 
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+ st.session_state['past'].append(user_input)
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+ st.session_state['generated'].append(output)
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+
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+ if st.session_state['generated']:
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+ with response_container:
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+ for i in range(len(st.session_state['generated'])):
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+ message(st.session_state["past"][i], is_user=True, key=str(i) + '_user', avatar_style="big-smile")
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+ message(st.session_state["generated"][i], key=str(i), avatar_style="thumbs")
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+
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  # Main App
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  st.markdown(
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  """