Spaces:
Sleeping
Sleeping
clementsan
commited on
Commit
•
51d2a09
1
Parent(s):
6e8daa8
Update UI with new step
Browse files
app.py
CHANGED
@@ -285,16 +285,21 @@ def demo():
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collection_name = gr.State()
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gr.Markdown(
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"""<center><h2>PDF-based chatbot
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<h3>Ask any questions about your PDF documents, along with follow-ups</h3>
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""")
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with gr.Row():
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document = gr.Files(height=100, file_count="multiple", file_types=["pdf"], interactive=True, label="Upload your PDF documents (single or multiple)")
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# upload_btn = gr.UploadButton("Loading document...", height=100, file_count="multiple", file_types=["pdf"], scale=1)
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with gr.Row():
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db_btn = gr.Radio(["ChromaDB"], label="Vector database type", value = "ChromaDB", type="index", info="Choose your vector database")
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with gr.Accordion("Advanced options - Document text splitter", open=False):
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@@ -305,9 +310,9 @@ def demo():
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with gr.Row():
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db_progress = gr.Textbox(label="Vector database initialization", value="None")
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with gr.Row():
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db_btn = gr.Button("Generate vector database
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with gr.Tab("Step
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with gr.Row():
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llm_btn = gr.Radio(list_llm_simple, \
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label="LLM models", value = list_llm_simple[0], type="index", info="Choose your LLM model")
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@@ -321,9 +326,9 @@ def demo():
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with gr.Row():
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llm_progress = gr.Textbox(value="None",label="QA chain initialization")
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with gr.Row():
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qachain_btn = gr.Button("Initialize
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with gr.Tab("Step
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chatbot = gr.Chatbot(height=300)
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with gr.Accordion("Advanced - Document references", open=False):
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with gr.Row():
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@@ -336,10 +341,10 @@ def demo():
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doc_source3 = gr.Textbox(label="Reference 3", lines=2, container=True, scale=20)
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source3_page = gr.Number(label="Page", scale=1)
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with gr.Row():
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msg = gr.Textbox(placeholder="Type message", container=True)
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with gr.Row():
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submit_btn = gr.Button("Submit")
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clear_btn = gr.ClearButton([msg, chatbot])
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# Preprocessing events
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#upload_btn.upload(upload_file, inputs=[upload_btn], outputs=[document])
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collection_name = gr.State()
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gr.Markdown(
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"""<center><h2>PDF-based chatbot</center></h2>
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<h3>Ask any questions about your PDF documents, along with follow-ups</h3>""")
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gr.Markdown(
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"""<b>Note:</b> This AI assistant, using Langchain and open-source LLMs, performs retrieval-augmented generation (RAG) from your PDF documents. \
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The user interface explicitely shows multiple steps to help understand the RAG workflow.
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This chatbot takes past questions into account when generating answers (via conversational memory), and includes document references for clarity purposes.<br>
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<br><b>Warning:</b> This space uses the free CPU Basic hardware from Hugging Face. Some steps and LLM models used below (free inference endpoints) can take some time to generate a reply.
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""")
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with gr.Tab("Step 1 - Upload PDF"):
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with gr.Row():
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document = gr.Files(height=100, file_count="multiple", file_types=["pdf"], interactive=True, label="Upload your PDF documents (single or multiple)")
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# upload_btn = gr.UploadButton("Loading document...", height=100, file_count="multiple", file_types=["pdf"], scale=1)
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with gr.Tab("Step 2 - Process document"):
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with gr.Row():
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db_btn = gr.Radio(["ChromaDB"], label="Vector database type", value = "ChromaDB", type="index", info="Choose your vector database")
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with gr.Accordion("Advanced options - Document text splitter", open=False):
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with gr.Row():
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db_progress = gr.Textbox(label="Vector database initialization", value="None")
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with gr.Row():
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db_btn = gr.Button("Generate vector database")
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with gr.Tab("Step 3 - Initialize QA chain"):
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with gr.Row():
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llm_btn = gr.Radio(list_llm_simple, \
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label="LLM models", value = list_llm_simple[0], type="index", info="Choose your LLM model")
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with gr.Row():
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llm_progress = gr.Textbox(value="None",label="QA chain initialization")
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with gr.Row():
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qachain_btn = gr.Button("Initialize Question Answering chain")
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with gr.Tab("Step 4 - Chatbot"):
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chatbot = gr.Chatbot(height=300)
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with gr.Accordion("Advanced - Document references", open=False):
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with gr.Row():
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doc_source3 = gr.Textbox(label="Reference 3", lines=2, container=True, scale=20)
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source3_page = gr.Number(label="Page", scale=1)
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with gr.Row():
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msg = gr.Textbox(placeholder="Type message (e.g. 'What is this document about?')", container=True)
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with gr.Row():
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submit_btn = gr.Button("Submit message")
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clear_btn = gr.ClearButton([msg, chatbot], value="Clear conversation")
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# Preprocessing events
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#upload_btn.upload(upload_file, inputs=[upload_btn], outputs=[document])
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