Create app.py

app.py

@@ -0,0 +1,86 @@
+import gradio as gr
+import torch
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import spaces
+
+title = """# 🤵Welcome to SAK's CodBot 💻 (A Coding ChatBot) ⭐⭐⭐"""
+description = """CodingBot is an open-source coding language model that delivers excellent performance.
+
+CodingBot leverages LlamaforCausalLM.
+
+CodingBot supports 'java', 'javascript', 'c++', 'c#', 'c', 'html', 'java_server_pages', 'python', 'php', 'go', 'kotlin', 'swift', 'dart', 'shell', 'json', 'lua', 'matlab', 'yaml', 'css', 'rust', 'sql', 'ruby', 'tex', 'objective-c', 'powershell', 'ocaml', 'groovy', 'cmake', 'julia', 'perl', 'assembly', 'haskell', 'fortran', 'pascal', 'rmarkdown', 'scala', 'visual_basic', 'verilog', 'prolog', 'r', 'dockerfile','cobol', 'batchfile', 'toml', 'lisp', 'erlang', 'coffeescript', 'makefile', 'clojure', 'elixir'
+  ```
+**Demo by [Sunder Ali Khowaja](https://sander-ali.github.io) - [X](https://x.com/SunderAKhowaja) -[Github](https://github.com/sander-ali) -[Hugging Face](https://huggingface.co/SunderAli17)**
+"""
+
+# Define the device and model path
+device = "cuda" if torch.cuda.is_available() else "cpu"
+model_path = "SunderAli17/CodingBot"
+
+# Load the tokenizer and model
+tokenizer = AutoTokenizer.from_pretrained(model_path)
+model = AutoModelForCausalLM.from_pretrained(model_path, device_map="auto").eval()
+
+@spaces.GPU(duration=130)
+def generate_code(system_prompt, user_prompt, max_length):
+    messages = [
+        {"role": "system", "content": system_prompt},
+        {"role": "user", "content": user_prompt}
+    ]
+    text = tokenizer.apply_chat_template(
+        messages,
+        tokenize=False,
+        add_generation_prompt=True
+    )
+    model_inputs = tokenizer([text], return_tensors="pt").to(device)
+
+    generated_ids = model.generate(
+        model_inputs.input_ids,
+        max_new_tokens=max_length,
+        eos_token_id=tokenizer.eos_token_id  
+    )
+    generated_ids = [
+        output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids)
+    ]
+
+    response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]
+    return response
+
+theme = gr.themes.Soft(
+    font=[gr.themes.GoogleFont('Source Code Pro'), gr.themes.GoogleFont('Public Sans'), 'system-ui', 'sans-serif'],
+)
+js_func = """
+function refresh() {
+    const url = new URL(window.location);
+    if (url.searchParams.get('__theme') !== 'dark') {
+        url.searchParams.set('__theme', 'dark');
+        window.location.href = url.href;
+    }
+}
+"""
+with gr.Blocks(js = js_func, theme = theme) as SAK:
+    gr.Markdown(title)
+    gr.Markdown(description)
+
+    system_prompt_input = gr.Textbox(
+        label="👨‍💻 CodBot Instruction:",
+        value="Hello Sir! how are you today? I am here to generate clear and concise code examples for you.",
+        lines=2
+    )
+    user_prompt_input = gr.Code(
+        label="❓ Coding Prompt 💻",
+        value="Write an object detection code using YOLOv10 in Python",
+        language="python",
+        lines=15
+    )
+    code_output = gr.Code(label="👨‍💻 CodBot", language='python', lines=50, interactive=True)
+    max_length_slider = gr.Slider(minimum=1, maximum=1800, value=650, label="Max Token Length")
+
+    generate_button = gr.Button("Generate Code")
+    generate_button.click(
+        generate_code,
+        inputs=[system_prompt_input, user_prompt_input, max_length_slider],
+        outputs=code_output
+    )
+
+SAK.queue().launch(debug=True, share=True)