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app.py

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+import os
+
+import docx2txt
+from dotenv import load_dotenv
+
+from langchain.chat_models import ChatOpenAI
+from langchain.schema import (
+    SystemMessage,
+    HumanMessage,
+    AIMessage
+)
+from langchain.embeddings.openai import OpenAIEmbeddings
+
+from langchain.text_splitter import CharacterTextSplitter
+from langchain.vectorstores import Chroma
+
+import streamlit as st
+from streamlit_chat import message
+
+load_dotenv()
+
+
+os.environ["OPENAI_API_KEY"] = os.getenv("OPENAI_API_KEY")
+llm = ChatOpenAI(temperature=0.3, model="gpt-3.5-turbo")
+embeddings = OpenAIEmbeddings()
+
+
+@st.cache_data
+def load_into_chroma(docs):
+    text_splitter = CharacterTextSplitter(chunk_size=500, chunk_overlap=50)
+    docs = text_splitter.split_documents(text_splitter)
+    global db_chroma
+    db_chroma = Chroma.from_documents(docs, embeddings)
+
+
+def generate_content(query, call_transcript):
+    # relevant_docs = db_chroma.similarity_search(query)
+    system_prompt = f"""You are a professional writer of motivational letters.\
+You will be given a content from a knowledge base below, delimited by triple \
+backticks. Your job is to use knowledge from this data and write a \
+motivational letter for graduate school application. Only write content \
+using data from the knowledgebase, do not claim facts from outside of it. \
+Make the letter very personal with regards to the knowledge base.
+
+Knowledge Base: ```{call_transcript}```
+"""
+    system_message = SystemMessage(content=system_prompt)
+    human_message = HumanMessage(content=query)
+    message = [system_message, human_message]
+    response = llm(message)
+    return response.content
+
+
+system_session_prompt = """As a professional writer of motivational letters, \
+your task is to write a sales proposal provided to you according to \
+the required changes. You will make the recommended changes to the \
+sales proposal and return the entire proposal with thse changes. \
+Your job depends on the answers you provide so play close attention to \
+the queries you recieve.
+"""
+
+
+def main():
+    st.title("ChatGPT 🤖 Powered Chatbot")
+    st.header("Sales Proposal Generator")
+
+    uploaded_file = st.file_uploader("Upload a word file", type="docx")
+    if "messages" not in st.session_state:
+        st.session_state.messages = [AIMessage(content="How can I help you?")]
+    if uploaded_file is not None:
+        # extract text from word file
+        call_transcript = docx2txt.process(uploaded_file)
+        # load_into_chroma(call_transcript)
+
+        with st.sidebar:
+            user_input = st.text_area("Enter your query: ", key="user_input")
+            st.session_state.messages.append(HumanMessage(content=user_input))
+
+            if st.button("Generate content"):
+                with st.spinner("GPT is thinking..."):
+                    response = generate_content(user_input, call_transcript)
+                    st.session_state.messages.append(AIMessage(content=response))
+
+    # display message history
+    messages = st.session_state.get('messages', [])
+    for i in range(len(messages)):
+        if i % 2 == 0:
+            message(messages[i].content, is_user=False, key=str(i) + '_user')
+        else:
+            message(messages[i].content, is_user=True, key=str(i) + '_ai')
+
+
+if __name__ == '__main__':
+    main()

requirements.txt

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+docx2txt
+openai
+langchain
+pinecone-client
+streamlit
+streamlit_chat
+python-dotenv
+tiktoken