Update app.py

app.py

@@ -1,8 +1,51 @@
+import os
+from langchain.chains import RetrievalQA
+from langchain.llms import OpenAI
+from langchain.document_loaders import PyPDFLoader
+from langchain.indexes import VectorstoreIndexCreator
+from langchain.text_splitter import CharacterTextSplitter
+from langchain.embeddings import OpenAIEmbeddings
+from langchain.vectorstores import Chroma
 import gradio as gr
+import tempfile
 
-def square_number(input_number):
-    return input_number ** 2
 
-custom_slider = gr.inputs.Slider(minimum=0, maximum=10, step=0.1, default=5, label="Select a number:")
-iface = gr.Interface(fn=square_number, inputs=custom_slider, outputs="text", description="Enter a number and get its square.")
+def qa(file, openaikey, query, chain_type, k):
+    os.environ["OPENAI_API_KEY"] = openaikey
+
+    # load document
+    loader = PyPDFLoader(file.name)
+    documents = loader.load()
+    # split the documents into chunks
+    text_splitter = CharacterTextSplitter(chunk_size=1000, chunk_overlap=0)
+    texts = text_splitter.split_documents(documents)
+    # select which embeddings we want to use
+    embeddings = OpenAIEmbeddings()
+    # create the vectorestore to use as the index
+    db = Chroma.from_documents(texts, embeddings)
+    # expose this index in a retriever interface
+    retriever = db.as_retriever(
+        search_type="similarity", search_kwargs={"k": k})
+    # create a chain to answer questions
+    qa = RetrievalQA.from_chain_type(
+        llm=OpenAI(), chain_type=chain_type, retriever=retriever, return_source_documents=True)
+    result = qa({"query": query})
+    print(result['result'])
+    return result["result"]
+
+
+iface = gr.Interface(
+    fn=qa, 
+    inputs=[
+        gr.inputs.File(label="Upload PDF"),
+        gr.inputs.Textbox(label="OpenAI API Key"),
+        gr.inputs.Textbox(label="Your question"),
+        gr.inputs.Dropdown(choices=['stuff', 'map_reduce', "refine", "map_rerank"], label="Chain type"),
+        gr.inputs.Slider(minimum=1, maximum=5, default=2, label="Number of relevant chunks"),
+    ], 
+    outputs="text",
+    title="Question Answering with your PDF file",
+    description="Upload a PDF file, enter OpenAI API key, type a question and get your answer."
+)
+
 iface.launch()