subu4444/code-generation

1import json2import os3import shutil4import requests5 6import gradio as gr7from huggingface_hub import Repository8from text_generation import Client9 10HF_TOKEN = "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"11 12API_URL = "https://api-inference.huggingface.co/models/bigcode/starcoder"13API_URL_BASE ="https://api-inference.huggingface.co/models/bigcode/starcoderbase"14API_URL_PLUS = "https://api-inference.huggingface.co/models/bigcode/starcoderplus"15 16FIM_PREFIX = "<fim_prefix>"17FIM_MIDDLE = "<fim_middle>"18FIM_SUFFIX = "<fim_suffix>"19 20FIM_INDICATOR = "<FILL_HERE>"21 22FORMATS = """## Model Formats23 24The model is pretrained on code and is formatted with special tokens in addition to the pure code data,\25such as prefixes specifying the source of the file or tokens separating code from a commit message.\26Use these templates to explore the model's capacities:27 28### 1. Prefixes 🏷️29For pure code files, use any combination of the following prefixes:30 31```32<reponame>REPONAME<filename>FILENAME<gh_stars>STARS\ncode<|endoftext|>33```34STARS can be one of: 0, 1-10, 10-100, 100-1000, 1000+35 36### 2. Commits 💾37The commits data is formatted as follows:38 39```40<commit_before>code<commit_msg>text<commit_after>code<|endoftext|>41```42 43### 3. Jupyter Notebooks 📓44The model is trained on Jupyter notebooks as Python scripts and structured formats like:45 46```47<start_jupyter><jupyter_text>text<jupyter_code>code<jupyter_output>output<jupyter_text>48```49 50### 4. Issues 🐛51We also trained on GitHub issues using the following formatting:52```53<issue_start><issue_comment>text<issue_comment>...<issue_closed>54```55 56### 5. Fill-in-the-middle 🧩57Fill in the middle requires rearranging the model inputs. The playground handles this for you - all you need is to specify where to fill:58```59code before<FILL_HERE>code after60```61"""62 63theme = gr.themes.Monochrome(64    primary_hue="indigo",65    secondary_hue="blue",66    neutral_hue="slate",67    radius_size=gr.themes.sizes.radius_sm,68    font=[69        gr.themes.GoogleFont("Open Sans"),70        "ui-sans-serif",71        "system-ui",72        "sans-serif",73    ],74)75 76client = Client(77    API_URL,78    headers={"Authorization": f"Bearer {HF_TOKEN}"},79)80client_base = Client(81    API_URL_BASE, headers={"Authorization": f"Bearer {HF_TOKEN}"},82)83client_plus = Client(84    API_URL_PLUS, headers={"Authorization": f"Bearer {HF_TOKEN}"},85)86 87def generate(88    prompt, temperature=0.9, max_new_tokens=256, top_p=0.95, repetition_penalty=1.0, version="StarCoder",89):90 91    temperature = float(temperature)92    if temperature < 1e-2:93        temperature = 1e-294    top_p = float(top_p)95    fim_mode = False96 97    generate_kwargs = dict(98        temperature=temperature,99        max_new_tokens=max_new_tokens,100        top_p=top_p,101        repetition_penalty=repetition_penalty,102        do_sample=True,103        seed=42,104    )105 106    if FIM_INDICATOR in prompt:107        fim_mode = True108        try:109            prefix, suffix = prompt.split(FIM_INDICATOR)110        except:111            raise ValueError(f"Only one {FIM_INDICATOR} allowed in prompt!")112        prompt = f"{FIM_PREFIX}{prefix}{FIM_SUFFIX}{suffix}{FIM_MIDDLE}"113 114    if version == "StarCoder":115        stream = client.generate_stream(prompt, **generate_kwargs)116    elif version == "StarCoderPlus":117        stream = client_plus.generate_stream(prompt, **generate_kwargs)118    else:119        stream = client_base.generate_stream(prompt, **generate_kwargs)120 121    if fim_mode:122        output = prefix123    else:124        output = prompt125 126    previous_token = ""127    for response in stream:128        if response.token.text == "<|endoftext|>":129            if fim_mode:130                output += suffix131            else:132                return output133        else:134            output += response.token.text135        previous_token = response.token.text136        yield output137    return output138 139 140examples = [141    "X_train, y_train, X_test, y_test = train_test_split(X, y, test_size=0.1)\n\n# Train a logistic regression model, predict the labels on the test set and compute the accuracy score",142    "// Returns every other value in the array as a new array.\nfunction everyOther(arr) {",143    "Poor English: She no went to the market. Corrected English:",144    "def alternating(list1, list2):\n   results = []\n   for i in range(min(len(list1), len(list2))):\n       results.append(list1[i])\n       results.append(list2[i])\n   if len(list1) > len(list2):\n       <FILL_HERE>\n   else:\n       results.extend(list2[i+1:])\n   return results",145]146 147 148def process_example(args):149    for x in generate(args):150        pass151    return x152 153 154css = ".generating {visibility: hidden}"155 156monospace_css = """157#q-input textarea {158    font-family: monospace, 'Consolas', Courier, monospace;159}160"""161 162 163css +=  monospace_css + ".gradio-container {color: black}"164 165 166description = """167<div style="text-align: center;">168    <h1> ⭐ StarCoder <span style='color: #e6b800;'>Models</span> Playground</h1>169</div>170<div style="text-align: left;">171    <p>This is a demo to generate text and code with the following StarCoder models:</p>172    <ul>173        <li><a href="https://huggingface.co/bigcode/starcoderplus" style='color: #e6b800;'>StarCoderPlus</a>: A finetuned version of StarCoderBase on English web data, making it strong in both English text and code generation.</li>174        <li><a href="https://huggingface.co/bigcode/starcoderbase" style='color: #e6b800;'>StarCoderBase</a>: A code generation model trained on 80+ programming languages, providing broad language coverage for code generation tasks.</li>175        <li><a href="https://huggingface.co/bigcode/starcoder" style='color: #e6b800;'>StarCoder</a>: A finetuned version of StarCoderBase specifically focused on Python, while also maintaining strong performance on other programming languages.</li>176    </ul>177    <p><b>Please note:</b> These models are not designed for instruction purposes. If you're looking for instruction or want to chat with a fine-tuned model, you can visit the <a href="https://huggingface.co/spaces/HuggingFaceH4/starchat-playground">StarChat Playground</a>.</p>178</div>179"""180disclaimer = """⚠️<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>\181 <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.](hf.co/bigcode)"""182 183with gr.Blocks(theme=theme, analytics_enabled=False, css=css) as demo:184    with gr.Column():185        gr.Markdown(description)186        with gr.Row():187            version = gr.Dropdown(188                        ["StarCoderPlus", "StarCoderBase", "StarCoder"],189                        value="StarCoder",190                        label="Model",191                        info="Choose a model from the list",192                        )193        with gr.Row():194            with gr.Column():195                instruction = gr.Textbox(196                    placeholder="Enter your code here",197                    lines=5,198                    label="Input",199                    elem_id="q-input",200                )201                submit = gr.Button("Generate", variant="primary")202                output = gr.Code(elem_id="q-output", lines=30, label="Output")203                with gr.Row():204                    with gr.Column():205                        with gr.Accordion("Advanced settings", open=False):206                            with gr.Row():207                                column_1, column_2 = gr.Column(), gr.Column()208                                with column_1:209                                    temperature = gr.Slider(210                                        label="Temperature",211                                        value=0.2,212                                        minimum=0.0,213                                        maximum=1.0,214                                        step=0.05,215                                        interactive=True,216                                        info="Higher values produce more diverse outputs",217                                    )218                                    max_new_tokens = gr.Slider(219                                        label="Max new tokens",220                                        value=256,221                                        minimum=0,222                                        maximum=8192,223                                        step=64,224                                        interactive=True,225                                        info="The maximum numbers of new tokens",226                                    )227                                with column_2:228                                    top_p = gr.Slider(229                                        label="Top-p (nucleus sampling)",230                                        value=0.90,231                                        minimum=0.0,232                                        maximum=1,233                                        step=0.05,234                                        interactive=True,235                                        info="Higher values sample more low-probability tokens",236                                    )237                                    repetition_penalty = gr.Slider(238                                        label="Repetition penalty",239                                        value=1.2,240                                        minimum=1.0,241                                        maximum=2.0,242                                        step=0.05,243                                        interactive=True,244                                        info="Penalize repeated tokens",245                                    )246                                    247                gr.Markdown(disclaimer)248                with gr.Group(elem_id="share-btn-container"):249                    share_button = gr.Button(250                        "Share to community", elem_id="share-btn", visible=True251                    )252                gr.Examples(253                    examples=examples,254                    inputs=[instruction],255                    cache_examples=False,256                    fn=process_example,257                    outputs=[output],258                )259                gr.Markdown(FORMATS)260 261    submit.click(262        generate,263        inputs=[instruction, temperature, max_new_tokens, top_p, repetition_penalty, version],264        outputs=[output],265    )266demo.queue(concurrency_count=16).launch(debug=True)