import os import gradio as gr from text_generation import Client from share_btn import community_icon_html, loading_icon_html, share_js, share_btn_css HF_TOKEN = os.environ.get("HF_TOKEN", None) API_URL = " https://api-inference.huggingface.co/models/BigCode/octocoder" theme = gr.themes.Monochrome( primary_hue="indigo", secondary_hue="blue", neutral_hue="slate", radius_size=gr.themes.sizes.radius_sm, font=[ gr.themes.GoogleFont("Open Sans"), "ui-sans-serif", "system-ui", "sans-serif", ], ) client = Client( API_URL, headers={"Authorization": f"Bearer {HF_TOKEN}"}, ) def generate(query: str, temperature=0.9, max_new_tokens=256, top_p=0.95, repetition_penalty=1.0, ): if query.endswith("."): prompt = f"Question: {query}\n\nAnswer:" else: prompt = f"Question: {query}.\n\nAnswer:" temperature = float(temperature) if temperature < 1e-2: temperature = 1e-2 top_p = float(top_p) generate_kwargs = dict( temperature=temperature, max_new_tokens=max_new_tokens, top_p=top_p, repetition_penalty=repetition_penalty, do_sample=True, seed=42, ) stream = client.generate_stream(prompt, **generate_kwargs) output = "" previous_token = "" for response in stream: if response.token.text == "<|endoftext|>": return output else: output += response.token.text previous_token = response.token.text yield output return output def process_example(**krwags): for x in generate(**krwags): pass return x css = ".generating {visibility: hidden}" monospace_css = """ #q-input textarea { font-family: monospace, 'Consolas', Courier, monospace; } """ css += share_btn_css + monospace_css description = """ <div style="text-align: center;"> <center><img src='https://raw.githubusercontent.com/bigcode-project/octopack/31f3320f098703c7910e43492c39366eeea68d83/banner.png' width='70%'/></center> <br> <h1><u> OctoCoder Demo </u></h1> </div> <br> <div style="text-align: center;"> <p>This is a demo to demonstrate the capabilities of <a href="https://huggingface.co/bigcode/octocoder">OctoCoder</a> model by showing how it can be used to generate code by following the instructions provided in the input.</p> <p><strong>OctoCoder</strong> is an instruction tuned model with 15.5B parameters created by finetuning StarCoder on CommitPackFT & OASST</p> </div> """ disclaimer = """⚠️<b>Any use or sharing of this demo constitues your acceptance of the BigCode [OpenRAIL-M](https://huggingface.co/spaces/bigcode/bigcode-model-license-agreement) License Agreement and the use restrictions included within.</b>\ <br>**Intended Use**: this app and its [supporting model](https://huggingface.co/bigcode) are provided for demonstration purposes; not to serve as replacement for human expertise. For more details on the model's limitations in terms of factuality and biases, see the [model card.](https://huggingface.co/bigcode)""" examples = [ ['Please write a function in Python that performs bubble sort.', 256], ['''Explain the following piece of code def count_unique(s): s = s.lower() s_split = list(s) valid_chars = [char for char in s_split if char.isalpha() or char == " "] valid_sentence = "".join(valid_chars) uniques = set(valid_sentence.split(" ")) return len(uniques)''', 512], [ 'Write an efficient Python function that takes a given text and returns its Morse code equivalent without using any third party library', 512], ['Write a html and css code to render a clock', 8000], ] with gr.Blocks(theme=theme, analytics_enabled=False, css=css) as demo: with gr.Column(): gr.Markdown(description) with gr.Row(): with gr.Column(): with gr.Accordion("Settings", open=True): with gr.Row(): column_1, column_2 = gr.Column(), gr.Column() with column_1: temperature = gr.Slider( label="Temperature", value=0.2, minimum=0.0, maximum=1.0, step=0.05, interactive=True, info="Higher values produce more diverse outputs", ) max_new_tokens = gr.Slider( label="Max new tokens", value=256, minimum=0, maximum=8192, step=64, interactive=True, info="The maximum numbers of new tokens", ) with column_2: top_p = gr.Slider( label="Top-p (nucleus sampling)", value=0.90, minimum=0.0, maximum=1, step=0.05, interactive=True, info="Higher values sample more low-probability tokens", ) repetition_penalty = gr.Slider( label="Repetition penalty", value=1.2, minimum=1.0, maximum=2.0, step=0.05, interactive=True, info="Penalize repeated tokens", ) with gr.Row(): with gr.Column(): instruction = gr.Textbox( placeholder="Enter your query here", lines=5, label="Input", elem_id="q-input", ) submit = gr.Button("Generate", variant="primary") output = gr.Code(elem_id="q-output", lines=30, label="Output") gr.Markdown(disclaimer) with gr.Group(elem_id="share-btn-container"): community_icon = gr.HTML(community_icon_html, visible=True) loading_icon = gr.HTML(loading_icon_html, visible=True) share_button = gr.Button( "Share to community", elem_id="share-btn", visible=True ) gr.Examples( examples=examples, inputs=[instruction, max_new_tokens], cache_examples=False, fn=process_example, outputs=[output], ) submit.click( generate, inputs=[instruction, temperature, max_new_tokens, top_p, repetition_penalty], outputs=[output], ) share_button.click(None, [], [], _js=share_js) demo.queue(concurrency_count=16).launch(debug=True)