Spaces:
Running
on
Zero
Running
on
Zero
Update app.py
Browse files
app.py
CHANGED
@@ -32,7 +32,8 @@ Provide a concise answer in markdown format with citations [1], [2], etc."""
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@spaces.GPU(duration=120) # Allow up to 120 seconds of GPU time
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def generate_answer(prompt: str) -> str:
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"""Generate a concise research answer using GPU."""
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-
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answer_start = response.find("Provide a concise") + len("Provide a concise answer in markdown format with citations [1], [2], etc.")
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return response[answer_start:].strip() if answer_start > -1 else "No detailed answer generated."
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@@ -66,7 +67,7 @@ def process_deep_research(query: str, history: list):
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prompt = format_prompt(query, web_results)
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answer = generate_answer(prompt)
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# Convert
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new_history = history + [{"role": "user", "content": query}, {"role": "assistant", "content": answer}]
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return answer, sources_html, new_history
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@@ -174,7 +175,6 @@ with gr.Blocks(title="Deep Research Engine - ZeroGPU", css=css) as demo:
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answer, sources, new_history = process_deep_research(query, history)
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return answer, sources, new_history
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# Remove _js parameter from click event
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search_btn.click(
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fn=handle_search,
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inputs=[search_input, history_state],
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@@ -185,7 +185,6 @@ with gr.Blocks(title="Deep Research Engine - ZeroGPU", css=css) as demo:
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outputs=[history_state]
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)
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# Remove _js parameter from submit event
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search_input.submit(
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fn=handle_search,
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inputs=[search_input, history_state],
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@spaces.GPU(duration=120) # Allow up to 120 seconds of GPU time
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def generate_answer(prompt: str) -> str:
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"""Generate a concise research answer using GPU."""
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# Use max_new_tokens instead of max_length to allow new token generation
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response = generator(prompt, max_new_tokens=150, num_return_sequences=1, truncation=True)[0]["generated_text"]
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answer_start = response.find("Provide a concise") + len("Provide a concise answer in markdown format with citations [1], [2], etc.")
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return response[answer_start:].strip() if answer_start > -1 else "No detailed answer generated."
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prompt = format_prompt(query, web_results)
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answer = generate_answer(prompt)
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# Convert history to messages format (role/content)
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new_history = history + [{"role": "user", "content": query}, {"role": "assistant", "content": answer}]
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return answer, sources_html, new_history
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answer, sources, new_history = process_deep_research(query, history)
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return answer, sources, new_history
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search_btn.click(
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fn=handle_search,
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inputs=[search_input, history_state],
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outputs=[history_state]
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)
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search_input.submit(
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fn=handle_search,
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inputs=[search_input, history_state],
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