Create app.py

app.py

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+from PyPDF2 import PdfReader
+import gradio as gr
+from langchain.text_splitter import RecursiveCharacterTextSplitter
+from langchain.llms import HuggingFaceHub
+from langchain.embeddings import HuggingFaceEmbeddings
+from langchain.vectorstores import Chroma
+from langchain.chains import RetrievalQA
+from langchain.document_loaders import PyMuPDFLoader
+import os
+from huggingface_hub import InferenceClient
+
+os.environ["HUGGINGFACEHUB_API_TOKEN"] = "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"
+# client = InferenceClient(token="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")
+
+def load_doc(pdf_doc):
+
+    loader = PyMuPDFLoader(pdf_doc.name)
+    documents = loader.load()
+    embedding = HuggingFaceEmbeddings()
+    text_splitter = RecursiveCharacterTextSplitter(chunk_size=1000, chunk_overlap=200)
+    text = text_splitter.split_documents(documents)
+    db = Chroma.from_documents(text, embedding)
+    llm = HuggingFaceHub(repo_id="OpenAssistant/oasst-sft-1-pythia-12b", model_kwargs={"temperature": 1.0, "max_length": 256})
+    global chain
+    chain = RetrievalQA.from_chain_type(llm=llm,chain_type="stuff",retriever=db.as_retriever())
+    return 'Document has successfully been loaded'
+
+def answer_query(query):
+    question = query
+    return chain.run(question)
+
+html = """
+<div style="text-align:center; max width: 700px;">
+    <h1>ChatPDF</h1>
+    <p> Upload a PDF File, then click on Load PDF File <br>
+    Once the document has been loaded you can begin chatting with the PDF)
+</div>"""
+
+css = """container{max-width:700px; margin-left:auto; margin-right:auto,padding:20px}"""
+
+    gr.HTML(html)
+    with gr.Column():
+        gr.Markdown('ChatPDF')
+        pdf_doc = gr.File(label="Load a pdf",file_types=['.pdf'],type='file')
+        with gr.Row():
+            load_pdf = gr.Button('Load pdf file',variant="primary")
+            status = gr.Textbox(label="Status",placeholder='',interactive=False)
+
+
+        with gr.Row():
+            input = gr.Textbox(label="type in your question")
+            output = gr.Textbox(label="output")
+        submit_query = gr.Button("submit",variant="primary")
+
+        load_pdf.click(load_doc,inputs=pdf_doc,outputs=status)
+
+        submit_query.click(answer_query,input,output)
+
+demo.launch(share=True)