nickmuchi commited on
Commit
a3155e0
Β·
1 Parent(s): 4dfafae

Update app.py

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Files changed (1) hide show
  1. app.py +17 -6
app.py CHANGED
@@ -3,10 +3,21 @@ import streamlit as st
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  from langchain.embeddings import HuggingFaceInstructEmbeddings, HuggingFaceEmbeddings
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  from langchain.vectorstores.faiss import FAISS
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- from langchain.chains import VectorDBQA
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  from huggingface_hub import snapshot_download
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- from langchain import OpenAI
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- from langchain import PromptTemplate
 
 
 
 
 
 
 
 
 
 
 
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  st.set_page_config(page_title="CFA Level 1", page_icon="πŸ“–")
@@ -144,7 +155,7 @@ def get_answer(question):
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  api_key = os.environ["OPENAI_API_KEY"]
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  ##### main ####
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- user_input = st.text_input("Your question", "Who are you?", key="input")
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  col1, col2 = st.columns([10, 1])
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@@ -160,8 +171,8 @@ if ask:
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  with st.spinner("this can take about a minute for your first question because some models have to be downloaded πŸ₯ΊπŸ‘‰πŸ»πŸ‘ˆπŸ»"):
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  try:
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  answer, pages, extract = get_answer(question=user_input)
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- except:
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- st.write(f"Error with Download")
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  st.stop()
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  st.write(f"{answer}")
 
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  from langchain.embeddings import HuggingFaceInstructEmbeddings, HuggingFaceEmbeddings
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  from langchain.vectorstores.faiss import FAISS
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+ from langchain.chains import ChatVectorDBChain
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  from huggingface_hub import snapshot_download
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+ from langchain.chat_models import ChatOpenAI
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+ from langchain.prompts.chat import (
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+ ChatPromptTemplate,
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+ SystemMessagePromptTemplate,
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+ AIMessagePromptTemplate,
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+ HumanMessagePromptTemplate,
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+ )
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+ from langchain.schema import (
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+ AIMessage,
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+ HumanMessage,
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+ SystemMessage
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+ )
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+
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  st.set_page_config(page_title="CFA Level 1", page_icon="πŸ“–")
 
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  api_key = os.environ["OPENAI_API_KEY"]
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  ##### main ####
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+ user_input = st.text_input("Your question", "What is an MBS and who are the main issuer and investors of the MBS market?", key="input")
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  col1, col2 = st.columns([10, 1])
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  with st.spinner("this can take about a minute for your first question because some models have to be downloaded πŸ₯ΊπŸ‘‰πŸ»πŸ‘ˆπŸ»"):
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  try:
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  answer, pages, extract = get_answer(question=user_input)
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+ except as e:
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+ st.write(f"Error with Download: {e}")
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  st.stop()
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  st.write(f"{answer}")