CreitinGameplays
commited on
Commit
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46f3679
1
Parent(s):
add6648
Update app.py
Browse files
app.py
CHANGED
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import gradio as gr
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from huggingface_hub import InferenceClient
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import random
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def chat_inf(system_prompt, prompt, history, client_choice, seed, temp, tokens, top_p, rep_p):
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client = clients[int(client_choice) - 1]
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if not history:
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history = []
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hist_len = 0
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if history:
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hist_len = len(history)
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print(hist_len)
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generate_kwargs = dict(
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temperature=temp,
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max_new_tokens=tokens,
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top_p=top_p,
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repetition_penalty=rep_p,
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do_sample=True,
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seed=seed,
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)
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formatted_prompt = format_prompt(f"{system_prompt}, {prompt}", history)
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stream = client.text_generation(formatted_prompt, **generate_kwargs, stream=True, details=True,
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return_full_text=False)
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output = ""
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for response in stream:
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output += response.token.text
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yield [(prompt, output)]
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history.append((prompt, output))
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yield history
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def clear_fn():
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return None
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rand_val = random.randint(1, 1111111111111111)
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def check_rand(inp, val):
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if inp is True:
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return gr.Slider(label="Seed", minimum=1, maximum=1111111111111111, value=random.randint(1, 1111111111111111))
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else:
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return gr.Slider(label="Seed", minimum=1, maximum=1111111111111111, value=int(val))
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with gr.Blocks() as app:
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gr.HTML(
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"""<center><h1 style='font-size:xx-large;'>Models</h1></center>""")
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with gr.Group():
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with gr.Row():
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client_choice = gr.Dropdown(label="Models", type='index', choices=[c for c in models], value=models[0],
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interactive=True)
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chat_b = gr.Chatbot(height=500)
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with gr.Group():
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with gr.Row():
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with gr.Column(scale=1):
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with gr.Group():
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rand = gr.Checkbox(label="Random Seed", value=True)
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seed = gr.Slider(label="Seed", minimum=1, maximum=1111111111111111, step=1, value=rand_val)
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tokens = gr.Slider(label="Max new tokens", value=6400, minimum=0, maximum=8000, step=64,
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interactive=True, visible=True, info="The maximum number of tokens")
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with gr.Column(scale=1):
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with gr.Group():
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temp = gr.Slider(label="Temperature", step=0.01, minimum=0.01, maximum=1.0, value=0.9)
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top_p = gr.Slider(label="Top-P", step=0.01, minimum=0.01, maximum=1.0, value=0.9)
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rep_p = gr.Slider(label="Repetition Penalty", step=0.1, minimum=0.1, maximum=2.0, value=1.0)
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with gr.Group():
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with gr.Row():
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with gr.Column(scale=3):
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sys_inp = gr.Textbox(label="System Prompt (optional)")
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inp = gr.Textbox(label="Prompt")
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with gr.Row():
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btn = gr.Button("Chat")
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stop_btn = gr.Button("Stop")
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clear_btn = gr.Button("Clear")
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chat_sub = inp.submit(check_rand, [rand, seed], seed).then(chat_inf,
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[sys_inp, inp, chat_b, client_choice, seed, temp, tokens,
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top_p, rep_p], chat_b)
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go = btn.click(check_rand, [rand, seed], seed).then(chat_inf,
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[sys_inp, inp, chat_b, client_choice, seed, temp, tokens, top_p,
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rep_p], chat_b)
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stop_btn.click(None, None, None, cancels=[go, chat_sub])
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clear_btn.click(clear_fn, None, [chat_b])
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app.queue(default_concurrency_limit=10).launch()
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import gradio as gr
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def conversation(prompt="", max_tokens=128):
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# Integrate your Bloom 3b model here to generate response based on prompt and max_tokens
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# Replace this with the actual call to your Bloom 3b model
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response = "Bloom 3b is currently unavailable. Try again later!"
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return response
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interface = gr.Interface(
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fn=conversation,
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inputs=[
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gr.Textbox(label="Text Prompt", value="<|system|> You are a helpful AI assistant </s> <|prompter|> What is an AI? </s> <|assistant|>"),
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gr.Slider(minimum=1, maximum=1024, label="Max New Tokens", value=128),
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],
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outputs=gr.Textbox(label="AI Assistant Response"), # Textbox for the response
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title="Bloom 3b Conversational Assistant",
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description="Talk to Bloom 3b using a text prompt and adjust the maximum number tokens for response generation.",
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)
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interface.launch()
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