Add application file

app.py

@@ -1,7 +1,125 @@
 import gradio as gr
+import os
 
-def greet(name):
-    return "Hello " + name + "!!"
+FIM_PREFIX = "<fim_prefix>"
+FIM_MIDDLE = "<fim_middle>"
+FIM_SUFFIX = "<fim_suffix>"
+FIM_INDICATOR = "<FILL_HERE>"
 
-iface = gr.Interface(fn=greet, inputs="text", outputs="text")
-iface.launch()
+API_URL_BASE ="https://api-inference.huggingface.co/models/bigcode/starcoderbase"
+HF_TOKEN = os.environ.get("HF_TOKEN", None)
+
+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",
+    ],
+)
+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;">
+    <p>This is a demo to generate code with <a href="https://huggingface.co/bigcode/starcoder" style='color: #e6b800;'>StarCoder</a></p>
+</div>
+"""
+
+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) {",
+    "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",
+]
+
+client_base = Client(
+    API_URL_BASE, 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)
+    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
+def process_example(args):
+    for x in generate(args):
+        pass
+    return x
+
+with gr.Blocks(theme=theme, analytics_enabled=False, css=css) as demo:
+    with gr.Column():
+        gr.Markdown(description)
+        with gr.Row():
+            with gr.Column():
+                instruction = gr.Textbox(
+                    placeholder="Enter your code here",
+                    label="Code",
+                    elem_id="q-input",
+                )
+                submit = gr.Button("Generate", variant="primary")
+                output = gr.Code(elem_id="q-output", lines=30)
+            gr.Examples(
+                    examples=examples,
+                    inputs=[instruction],
+                    cache_examples=False,
+                    fn=process_example,
+                    outputs=[output],
+                )
+
+demo.queue(concurrency_count=16).launch(debug=True)