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Author: pythoninoffice

langchain_examples/invoice_autoquery.py

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+from dotenv import dotenv_values
+from langchain.chains import RetrievalQA
+from langchain.document_loaders import PyPDFLoader
+from langchain.embeddings import OpenAIEmbeddings
+from langchain.llms import OpenAI
+from langchain.vectorstores import Chroma
+import os
+import streamlit as st
+from streamlit_chat import message
+
+api_keys=dotenv_values()
+os.environ['OPENAI_API_KEY'] = dotenv_values()['openai_api_key'] #set environment variable
+folder_path =r"some_folder"
+files = os.listdir(folder_path)
+docs = []
+for file in files:
+    loader = PyPDFLoader(rf"{folder_path}\{file}")
+    page = loader.load_and_split()[0]
+    docs.append(page)
+
+embeddings = OpenAIEmbeddings()
+db = Chroma.from_documents(docs, embeddings)
+retriever = db.as_retriever(search_kwargs={'k': len(docs)})
+    
+qa = RetrievalQA.from_chain_type(llm=OpenAI(model_name='gpt-4', temperature=0), 
+                                 chain_type="stuff", 
+                                 retriever=retriever,
+                                 verbose=True)
+
+st.set_page_config(
+    page_title="Invoice AutoQuery",
+    page_icon=":robot:"
+)
+
+st.header("Invoice AutoQuery :robot_face:")
+
+if 'ai' not in st.session_state:
+    st.session_state['ai'] = []
+if 'human' not in st.session_state:
+    st.session_state['human'] = []
+    
+def get_text():
+    input_text = st.text_input('Enter your query here:', key='input', placeholder='Your q?')
+    return input_text
+
+
+user_input=get_text()
+if user_input:
+    output = qa.run(user_input)
+    
+    st.session_state['human'].append(user_input)
+    st.session_state['ai'].append(output)
+
+if st.session_state['ai']:
+    for i in range(len(st.session_state['ai']) -1, -1, -1):
+        message(st.session_state['ai'][i], key=str(i))
+        message(st.session_state['human'][i], is_user=True, key=str(i) + '_user')
+
+