Create app.py

app.py

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+import json
+import os
+import shutil
+import requests
+
+import gradio as gr
+from huggingface_hub import Repository
+from text_generation import Client
+
+HF_TOKEN = "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"
+
+API_URL = "https://api-inference.huggingface.co/models/bigcode/starcoder"
+API_URL_BASE ="https://api-inference.huggingface.co/models/bigcode/starcoderbase"
+API_URL_PLUS = "https://api-inference.huggingface.co/models/bigcode/starcoderplus"
+
+FIM_PREFIX = "<fim_prefix>"
+FIM_MIDDLE = "<fim_middle>"
+FIM_SUFFIX = "<fim_suffix>"
+
+FIM_INDICATOR = "<FILL_HERE>"
+
+FORMATS = """## Model Formats
+
+The model is pretrained on code and is formatted with special tokens in addition to the pure code data,\
+such as prefixes specifying the source of the file or tokens separating code from a commit message.\
+Use these templates to explore the model's capacities:
+
+### 1. Prefixes 🏷️
+For pure code files, use any combination of the following prefixes:
+
+```
+<reponame>REPONAME<filename>FILENAME<gh_stars>STARS\ncode<|endoftext|>
+```
+STARS can be one of: 0, 1-10, 10-100, 100-1000, 1000+
+
+### 2. Commits 💾
+The commits data is formatted as follows:
+
+```
+<commit_before>code<commit_msg>text<commit_after>code<|endoftext|>
+```
+
+### 3. Jupyter Notebooks 📓
+The model is trained on Jupyter notebooks as Python scripts and structured formats like:
+
+```
+<start_jupyter><jupyter_text>text<jupyter_code>code<jupyter_output>output<jupyter_text>
+```
+
+### 4. Issues 🐛
+We also trained on GitHub issues using the following formatting:
+```
+<issue_start><issue_comment>text<issue_comment>...<issue_closed>
+```
+
+### 5. Fill-in-the-middle 🧩
+Fill in the middle requires rearranging the model inputs. The playground handles this for you - all you need is to specify where to fill:
+```
+code before<FILL_HERE>code after
+```
+"""
+
+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}"},
+)
+client_base = Client(
+    API_URL_BASE, headers={"Authorization": f"Bearer {HF_TOKEN}"},
+)
+client_plus = Client(
+    API_URL_PLUS, headers={"Authorization": f"Bearer {HF_TOKEN}"},
+)
+
+def generate(
+    prompt, temperature=0.9, max_new_tokens=256, top_p=0.95, repetition_penalty=1.0, version="StarCoder",
+):
+
+    temperature = float(temperature)
+    if temperature < 1e-2:
+        temperature = 1e-2
+    top_p = float(top_p)
+    fim_mode = False
+
+    generate_kwargs = dict(
+        temperature=temperature,
+        max_new_tokens=max_new_tokens,
+        top_p=top_p,
+        repetition_penalty=repetition_penalty,
+        do_sample=True,
+        seed=42,
+    )
+
+    if FIM_INDICATOR in prompt:
+        fim_mode = True
+        try:
+            prefix, suffix = prompt.split(FIM_INDICATOR)
+        except:
+            raise ValueError(f"Only one {FIM_INDICATOR} allowed in prompt!")
+        prompt = f"{FIM_PREFIX}{prefix}{FIM_SUFFIX}{suffix}{FIM_MIDDLE}"
+
+    if version == "StarCoder":
+        stream = client.generate_stream(prompt, **generate_kwargs)
+    elif version == "StarCoderPlus":
+        stream = client_plus.generate_stream(prompt, **generate_kwargs)
+    else:
+        stream = client_base.generate_stream(prompt, **generate_kwargs)
+
+    if fim_mode:
+        output = prefix
+    else:
+        output = prompt
+
+    previous_token = ""
+    for response in stream:
+        if response.token.text == "<|endoftext|>":
+            if fim_mode:
+                output += suffix
+            else:
+                return output
+        else:
+            output += response.token.text
+        previous_token = response.token.text
+        yield output
+    return output
+
+
+examples = [
+    "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",
+    "// Returns every other value in the array as a new array.\nfunction everyOther(arr) {",
+    "Poor English: She no went to the market. Corrected English:",
+    "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",
+]
+
+
+def process_example(args):
+    for x in generate(args):
+        pass
+    return x
+
+
+css = ".generating {visibility: hidden}"
+
+monospace_css = """
+#q-input textarea {
+    font-family: monospace, 'Consolas', Courier, monospace;
+}
+"""
+
+
+css +=  monospace_css + ".gradio-container {color: black}"
+
+
+description = """
+<div style="text-align: center;">
+    <h1> ⭐ StarCoder <span style='color: #e6b800;'>Models</span> Playground</h1>
+</div>
+<div style="text-align: left;">
+    <p>This is a demo to generate text and code with the following StarCoder models:</p>
+    <ul>
+        <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>
+        <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>
+        <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>
+    </ul>
+    <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>
+</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.](hf.co/bigcode)"""
+
+with gr.Blocks(theme=theme, analytics_enabled=False, css=css) as demo:
+    with gr.Column():
+        gr.Markdown(description)
+        with gr.Row():
+            version = gr.Dropdown(
+                        ["StarCoderPlus", "StarCoderBase", "StarCoder"],
+                        value="StarCoder",
+                        label="Model",
+                        info="Choose a model from the list",
+                        )
+        with gr.Row():
+            with gr.Column():
+                instruction = gr.Textbox(
+                    placeholder="Enter your code 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")
+                with gr.Row():
+                    with gr.Column():
+                        with gr.Accordion("Advanced settings", open=False):
+                            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",
+                                    )
+                                    
+                gr.Markdown(disclaimer)
+                with gr.Group(elem_id="share-btn-container"):
+                    share_button = gr.Button(
+                        "Share to community", elem_id="share-btn", visible=True
+                    )
+                gr.Examples(
+                    examples=examples,
+                    inputs=[instruction],
+                    cache_examples=False,
+                    fn=process_example,
+                    outputs=[output],
+                )
+                gr.Markdown(FORMATS)
+
+    submit.click(
+        generate,
+        inputs=[instruction, temperature, max_new_tokens, top_p, repetition_penalty, version],
+        outputs=[output],
+    )
+demo.queue(concurrency_count=16).launch(debug=True)