Delete test1.py

test1.py

@@ -1,56 +0,0 @@
-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
-
-os.environ["HUGGINGFACEHUB_API_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}"""
-with gr.Blocks(css=css,theme=gr.themes.Monochrome()) as demo:
-    gr.HTML(html)
-    with gr.Column():
-        gr.Markdown('ChatPDF')
-        pdf_doc = gr.File(label="Load a pdf",file_types=['.pdf','.docx'],type='file')
-        with gr.Row():
-            load_pdf = gr.Button('Load pdf file')
-            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")
-
-        load_pdf.click(load_doc,inputs=pdf_doc,outputs=status)
-
-        submit_query.click(answer_query,input,output)
-
-demo.launch()