Update app.py
Browse files
app.py
CHANGED
@@ -8,10 +8,13 @@ print(os.environ)
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openai.api_base = os.environ.get("OPENAI_API_BASE")
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openai.api_key = os.environ.get("OPENAI_API_KEY")
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BASE_SYSTEM_MESSAGE = """
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def make_prediction(prompt, max_tokens=None, temperature=None, top_p=None, top_k=None, repetition_penalty=None):
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completion = openai.Completion.create(model="Open-Orca/
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for chunk in completion:
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yield chunk["choices"][0]["text"]
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@@ -72,11 +75,11 @@ with gr.Blocks(css=CSS) as demo:
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with gr.Row():
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with gr.Column():
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gr.Markdown(f"""
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## This demo is an unquantized GPU chatbot of [
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Brought to you by your friends at Alignment Lab AI, OpenChat, and Open Access AI Collective!
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""")
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with gr.Row():
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gr.Markdown("# π
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with gr.Row():
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#chatbot = gr.Chatbot().style(height=500)
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chatbot = gr.Chatbot(elem_id="chatbot")
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@@ -94,7 +97,7 @@ with gr.Blocks(css=CSS) as demo:
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with gr.Row():
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with gr.Column():
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max_tokens = gr.Slider(20, 1000, label="Max Tokens", step=20, value=500)
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temperature = gr.Slider(0.
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top_p = gr.Slider(0.0, 1.0, label="Top P", step=0.05, value=0.95)
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top_k = gr.Slider(0, 100, label="Top K", step=1, value=40)
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repetition_penalty = gr.Slider(0.0, 2.0, label="Repetition Penalty", step=0.1, value=1.1)
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openai.api_base = os.environ.get("OPENAI_API_BASE")
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openai.api_key = os.environ.get("OPENAI_API_KEY")
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BASE_SYSTEM_MESSAGE = """I am MistralOra. I was trained by Alignment Lab AI.
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I carefully provide accurate, factual, thoughtful, nuanced answers and am brilliant at reasoning.
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I am an assistant who thinks through their answers step-by-step to be sure I always get the right answer.
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I think more clearly if I write out my thought process in a scratchpad manner first; therefore, I always explain background context, assumptions, and step-by-step thinking BEFORE trying to answer a question."""
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def make_prediction(prompt, max_tokens=None, temperature=None, top_p=None, top_k=None, repetition_penalty=None):
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completion = openai.Completion.create(model="Open-Orca/Mistral-7B-OpenOrca", prompt=prompt, max_tokens=max_tokens, temperature=temperature, top_p=top_p, top_k=top_k, repetition_penalty=repetition_penalty, stream=True, stop=["</s>", "<|im_end|>"])
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for chunk in completion:
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yield chunk["choices"][0]["text"]
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with gr.Row():
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with gr.Column():
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gr.Markdown(f"""
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## This demo is an unquantized GPU chatbot of [Mistral-7B-OpenOrca](https://huggingface.co/Open-Orca/Mistral-7B-OpenOrca)
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Brought to you by your friends at Alignment Lab AI, OpenChat, and Open Access AI Collective!
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""")
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with gr.Row():
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gr.Markdown("# π Mistral-7B-OpenOrca Playground Space! π")
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with gr.Row():
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#chatbot = gr.Chatbot().style(height=500)
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chatbot = gr.Chatbot(elem_id="chatbot")
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with gr.Row():
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with gr.Column():
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max_tokens = gr.Slider(20, 1000, label="Max Tokens", step=20, value=500)
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temperature = gr.Slider(0.1, 2.0, label="Temperature", step=0.1, value=0.8)
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top_p = gr.Slider(0.0, 1.0, label="Top P", step=0.05, value=0.95)
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top_k = gr.Slider(0, 100, label="Top K", step=1, value=40)
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repetition_penalty = gr.Slider(0.0, 2.0, label="Repetition Penalty", step=0.1, value=1.1)
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