Update app.py
Browse files
app.py
CHANGED
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@@ -53,6 +53,9 @@ async def get_response_with_search(query, model, use_embeddings, num_calls=3, te
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system_message = """ You are a world-class AI system, capable of complex reasoning and reflection.
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Reason through the query inside <thinking> tags, and then provide your final response inside <output> tags.
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If you detect that you made a mistake in your reasoning at any point, correct yourself inside <reflection> tags."""
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user_message = f"""Using the following context from web search results:
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@@ -130,7 +133,7 @@ def create_gradio_interface():
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demo = gr.ChatInterface(
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respond,
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additional_inputs=[
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gr.Dropdown(choices=MODELS, label="Select Model", value=MODELS[
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gr.Slider(minimum=0.1, maximum=1.0, value=0.2, step=0.1, label="Temperature"),
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gr.Slider(minimum=1, maximum=5, value=1, step=1, label="Number of API Calls"),
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gr.Checkbox(label="Use Embeddings", value=True),
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system_message = """ You are a world-class AI system, capable of complex reasoning and reflection.
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Reason through the query inside <thinking> tags, and then provide your final response inside <output> tags.
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Providing comprehensive and accurate information based on web search results is essential.
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Your goal is to synthesize the given context into a coherent and detailed response that directly addresses the user's query.
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Please ensure that your response is well-structured, factual, and cites sources where appropriate.
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If you detect that you made a mistake in your reasoning at any point, correct yourself inside <reflection> tags."""
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user_message = f"""Using the following context from web search results:
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demo = gr.ChatInterface(
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respond,
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additional_inputs=[
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gr.Dropdown(choices=MODELS, label="Select Model", value=MODELS[3]),
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gr.Slider(minimum=0.1, maximum=1.0, value=0.2, step=0.1, label="Temperature"),
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gr.Slider(minimum=1, maximum=5, value=1, step=1, label="Number of API Calls"),
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gr.Checkbox(label="Use Embeddings", value=True),
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