updated file for bot

app.py

@@ -1,11 +1,73 @@
-from flask import Flask,request,jsonify
+from flask import Flask, request, jsonify
+from dotenv import load_dotenv
+from PyPDF2 import PdfReader
+from langchain.text_splitter import CharacterTextSplitter
+from langchain.embeddings import OpenAIEmbeddings
+from langchain.vectorstores import FAISS
+from langchain.chat_models import ChatOpenAI
+from langchain.memory import ConversationBufferMemory
+from langchain.chains import ConversationalRetrievalChain
+import os
 
-app=Flask(__name__)
+app = Flask(__name__)
+
+load_dotenv()
+OPENAI_API_KEY = os.getenv('OPENAI_API_KEY')
+
+def get_pdf_text(pdf_docs):
+    text = ""
+    for pdf in pdf_docs:
+        pdf_reader = PdfReader(pdf)
+        for page in pdf_reader.pages:
+            text += page.extract_text()
+    return text
+
+def get_text_chunks(text):
+    text_splitter = CharacterTextSplitter(
+        separator="\n",
+        chunk_size=1000,
+        chunk_overlap=200,
+        length_function=len
+    )
+    chunks = text_splitter.split_text(text)
+    return chunks
+
+def get_vectorstore(text_chunks):
+    embeddings = OpenAIEmbeddings()
+    vectorstore = FAISS.from_texts(texts=text_chunks, embedding=embeddings)
+    return vectorstore
+
+def get_conversation_chain(vectorstore):
+    llm = ChatOpenAI()
+    memory = ConversationBufferMemory(
+        memory_key='chat_history', return_messages=True)
+    conversation_chain = ConversationalRetrievalChain.from_llm(
+        llm=llm,
+        retriever=vectorstore.as_retriever(),
+        memory=memory
+    )
+    return conversation_chain
+
+@app.route('/upload', methods=['POST'])
+def upload_files():
+    if 'files' not in request.files:
+        return jsonify({"error": "No file part in the request"}), 400
+    files = request.files.getlist('files')
+    raw_text = get_pdf_text(files)
+    text_chunks = get_text_chunks(raw_text)
+    vectorstore = get_vectorstore(text_chunks)
+    global conversation_chain
+    conversation_chain = get_conversation_chain(vectorstore)
+    return jsonify({"status": "Files processed successfully"}), 200
+
+@app.route('/query', methods=['POST'])
+def query():
+    if 'question' not in request.json:
+        return jsonify({"error": "No question provided"}), 400
+    question = request.json['question']
+    if 'conversation_chain' not in globals():
+        return jsonify({"error": "No conversation chain initialized. Please upload documents first."}), 400
+    
+    response = conversation_chain({'question': question})
+    return jsonify({"response": response['answer']})
 
-@app.route("/query",methods=["POST"])
-def hello():
-    question=request.json["query"]
-    if question=="hi":
-        return {"hi":"whatsup"}
-    else:
-        return {"ask":"by hi"}