Create app.py

app.py

@@ -0,0 +1,92 @@
+import os
+import gradio as gr
+from functools import partial
+from huggingface_hub import InferenceClient
+
+css = """
+#generate_button {
+    transition: background-color 1s ease-out, color 1s ease-out; border-color 1s ease-out;
+}
+"""
+
+
+def generate(prompt: str, hf_token: str, model: str):
+    messages = [{"role": "user", "content": prompt}]
+    if hf_token is None or not hf_token.strip():
+        hf_token = os.getenv("HUGGINGFACE_API_KEY")
+    client = InferenceClient(model, token=hf_token)
+    model_name = model.split("/")[1]
+    response = f"**{model_name}**\n\n"
+    for msg in client.chat_completion(messages, max_tokens=600, stream=True):
+        token = msg.choices[0].delta.content
+        response += token
+        yield response
+
+
+def clear_token():
+    # returns a textbox with visibility set to False
+    # this will update the hf_token widget thus hiding it
+    return gr.Textbox(visible=False)
+
+
+with gr.Blocks(css=css, theme="gradio/soft") as demo:
+    gr.Markdown("<center><h1>Code LLM Explorer</h1></center>")
+
+    prompt = gr.Textbox(
+        label="Prompt",
+        lines=2,  # default two lines length
+        max_lines=5,  # the Textbox entends upto 5 lines length
+        info="Type your Prompt here",
+        show_label=False,
+        value="Write Bubble Sort in Python",
+    )
+
+    hf_token = gr.Textbox(
+        label="HuggingFace Token",
+        type="password",
+        placeholder="Your Hugging Face Token",
+        show_label=False,
+    )
+
+    # gr.Group() will group the two buttons together
+    # so there will be no gap between two buttons
+    with gr.Group():
+        with gr.Row() as button_row:
+            # variant: 'primary' for main call-to-action, 'secondary' for a more subdued style, 'stop' for a stop button.
+            generate_btn = gr.Button(
+                "Run", elem_id="generate_button", variant="primary", size="sm"
+            )
+            view_code = gr.Button(
+                "View Code", elem_id="generate_button", variant="secondary", size="sm"
+            )
+
+    with gr.Row() as output_row:
+        codellama_output = gr.Markdown("codellama/CodeLlama-34b-Instruct-hf")
+        stablecode_output = gr.Markdown("stabilityai/stable-code-instruct-3b")
+        deepseek_output = gr.Markdown("deepseek-ai/deepseek-coder-33b-instruct")
+
+    gr.on(
+        [prompt.submit, generate_btn.click], clear_token, inputs=None, outputs=hf_token
+    ).then(
+        fn=partial(generate, model="codellama/CodeLlama-34b-Instruct-hf"),
+        inputs=[prompt, hf_token],
+        outputs=codellama_output,
+    )
+
+    gr.on(
+        [prompt.submit, generate_btn.click], clear_token, inputs=None, outputs=hf_token
+    ).then(
+        fn=partial(generate, model="stabilityai/stable-code-instruct-3b"),
+        inputs=[prompt, hf_token],
+        outputs=stablecode_output,
+    )
+
+    gr.on(
+        [prompt.submit, generate_btn.click], clear_token, inputs=None, outputs=hf_token
+    ).then(
+        fn=partial(generate, model="microsoft/Phi-3-mini-4k-instruct"),
+        inputs=[prompt, hf_token],
+        outputs=deepseek_output,
+    )
+
+demo.launch()