Create app.py

app.py

@@ -0,0 +1,66 @@
+import os
+import gradio as gr
+from langchain.document_loaders import PyMuPDFLoader
+from langchain.text_splitter import RecursiveCharacterTextSplitter
+from langchain.vectorstores import Chroma
+from langchain.embeddings import OpenAIEmbeddings
+from langchain.chat_models import ChatOpenAI
+from langchain.chains import RetrievalQA
+
+import os
+os.environ['CURL_CA_BUNDLE'] = ''
+# Initialize conversation history
+conversation_history = ""
+
+def main(api_key, pdf_path, user_input):
+    global conversation_history  # Declare as global to update it
+
+    os.environ["OPENAI_API_KEY"] = api_key
+
+    persist_directory = "./storage"
+
+    loader = PyMuPDFLoader(pdf_path.name)
+    documents = loader.load()
+
+    text_splitter = RecursiveCharacterTextSplitter(chunk_size=512, chunk_overlap=10)
+    texts = text_splitter.split_documents(documents)
+
+    embeddings = OpenAIEmbeddings()
+    vectordb = Chroma.from_documents(documents=texts, 
+                                     embedding=embeddings,
+                                     persist_directory=persist_directory)
+    vectordb.persist()
+
+    retriever = vectordb.as_retriever(search_kwargs={"k": 3})
+    llm = ChatOpenAI(model_name='gpt-4')
+
+    qa = RetrievalQA.from_chain_type(llm=llm, chain_type="stuff", retriever=retriever)
+
+    # Update conversation history with the user's latest question
+    conversation_history += f"User: {user_input}\n"
+
+    query = f"{conversation_history}###Prompt {user_input}"
+    try:
+        llm_response = qa(query)
+        response_text = llm_response["result"]
+
+        # Update conversation history with the model's latest answer
+        conversation_history += f"Model: {response_text}\n"
+
+        return conversation_history  # Return the entire conversation history
+    except Exception as err:
+        return f'Exception occurred. Please try again: {str(err)}'
+
+iface = gr.Interface(
+    fn=main, 
+    inputs=[
+        gr.inputs.Textbox(label="OpenAI API Key", type="password"),
+        gr.inputs.File(label="Upload PDF"),
+        gr.inputs.Textbox(label="Enter Query")
+    ], 
+    outputs="text",
+    live=False,
+    show_submit_button=True,
+    description="Enter your OpenAI API Key, upload a PDF, and enter a query to get a response."
+)
+iface.launch(share=True)