Update app.py
Browse files
app.py
CHANGED
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@@ -28,12 +28,12 @@ from langchain.document_loaders import PyPDFLoader
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from langchain.indexes import VectorstoreIndexCreator
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import tempfile
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os.environ["OPENAI_API_KEY"] = "sk-
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query1=" "
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def loading_pdf():
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return "Loading..."
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def pdf_changes(pdf_doc,
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loader = OnlinePDFLoader(pdf_doc.name)
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documents = loader.load()
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@@ -56,7 +56,7 @@ def pdf_changes(pdf_doc, repo_id):
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)
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system_template="""You are a helpful chatbot used by the user to chat with pdf documents. Only answer the questions by using information provided in the context provided to you. If there is no relavant context, tell 'Hmm, I'm not sure'.
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----------------
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{summaries}"""
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@@ -92,7 +92,7 @@ def bot(history):
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def infer(question):
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global query1
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openai.api_key = "sk-
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prompt_text = question
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if prompt_text:
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query1 = query1 + "\nUser: " + prompt_text + "\nBot: "
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@@ -112,9 +112,9 @@ css="""
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"""
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title = """
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<div style="text-align: center;max-width: 700px;">
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<h1>Chat with PDF</h1>
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<p style="text-align: center;">Upload a .PDF from your computer, click the "Load PDF" button, <br />
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when everything is ready, you can start asking questions about the pdf ;)</p>
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</div>
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"""
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@@ -122,10 +122,11 @@ title = """
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with gr.Blocks(css=css,theme = gr.themes.Soft()) as demo:
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with gr.Column(elem_id="col-container"):
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with gr.Column():
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pdf_doc = gr.File(label="Load a pdf", file_types=['.pdf'], type="file")
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#repo_id = gr.Dropdown(label="LLM", choices=["google/flan-ul2", "OpenAssistant/oasst-sft-1-pythia-12b", "bigscience/bloomz"], value="google/flan-ul2")
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with gr.Row():
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langchain_status = gr.Textbox(label="Status", placeholder="", interactive=False)
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@@ -136,7 +137,7 @@ with gr.Blocks(css=css,theme = gr.themes.Soft()) as demo:
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submit_btn = gr.Button("Send message")
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#load_pdf.click(loading_pdf, None, langchain_status, queue=False)
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#repo_id.change(pdf_changes, inputs=[pdf_doc], outputs=[langchain_status], queue=False)
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load_pdf.click(pdf_changes, inputs=[pdf_doc], outputs=[langchain_status], queue=False)
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question.submit(add_text, [chatbot, question], [chatbot, question]).then(
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bot, chatbot, chatbot
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)
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@@ -144,4 +145,4 @@ with gr.Blocks(css=css,theme = gr.themes.Soft()) as demo:
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bot, chatbot, chatbot
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)
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demo.launch()
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from langchain.indexes import VectorstoreIndexCreator
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import tempfile
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os.environ["OPENAI_API_KEY"] = "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"
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query1=" "
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def loading_pdf():
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return "Loading..."
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def pdf_changes(pdf_doc, prompt):
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loader = OnlinePDFLoader(pdf_doc.name)
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documents = loader.load()
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)
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system_template="""You are a helpful chatbot used by the user to chat with pdf documents. Only answer the questions by using information provided in the context provided to you. If there is no relavant context, tell 'Hmm, I'm not sure'."""+prompt+"""
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----------------
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{summaries}"""
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def infer(question):
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global query1
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openai.api_key = "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"
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prompt_text = question
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if prompt_text:
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query1 = query1 + "\nUser: " + prompt_text + "\nBot: "
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"""
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title = """
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<div style="text-align: center; max-width: 700px;">
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<h1 style="color: #4545FF;">Chat with PDF</h1>
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<p style="text-align: center; color: #4545FF;">Upload a .PDF from your computer, click the "Load PDF" button, <br />
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when everything is ready, you can start asking questions about the pdf ;)</p>
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</div>
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"""
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with gr.Blocks(css=css,theme = gr.themes.Soft()) as demo:
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with gr.Column(elem_id="col-container"):
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#gr.HTML(title)
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with gr.Column():
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pdf_doc = gr.File(label="Load a pdf", file_types=['.pdf'], type="file")
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prompt = gr.Textbox(label="Behaviour Prompt", placeholder="Reply to all questions as a rap / Reply to all questions in Hindi etc. ")
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#repo_id = gr.Dropdown(label="LLM", choices=["google/flan-ul2", "OpenAssistant/oasst-sft-1-pythia-12b", "bigscience/bloomz"], value="google/flan-ul2")
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with gr.Row():
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langchain_status = gr.Textbox(label="Status", placeholder="", interactive=False)
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submit_btn = gr.Button("Send message")
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#load_pdf.click(loading_pdf, None, langchain_status, queue=False)
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#repo_id.change(pdf_changes, inputs=[pdf_doc], outputs=[langchain_status], queue=False)
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load_pdf.click(pdf_changes, inputs=[pdf_doc,prompt], outputs=[langchain_status], queue=False)
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question.submit(add_text, [chatbot, question], [chatbot, question]).then(
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bot, chatbot, chatbot
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)
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bot, chatbot, chatbot
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)
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demo.launch(debug=True)
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