app.py

import torch
import gradio as gr
from transformers import AutoTokenizer, AutoModelForCausalLM

REPO_ID  = "Tbain20/olmo2-1b-eeg-v11"
PREFIX_I = "### Instruction:\n"
PREFIX_R = "\n\n### Response:\n"

print("Loading tokenizer...")
tokenizer = AutoTokenizer.from_pretrained("allenai/OLMo-2-1124-7B")

print("Loading model...")
model = AutoModelForCausalLM.from_pretrained(
    REPO_ID,
    ignore_mismatched_sizes=True,
)
model.eval()
print("Ready")

@torch.no_grad()
def generate_code(prompt):
    if not prompt.strip():
        return "Please enter a prompt."
    full = PREFIX_I + prompt.strip() + PREFIX_R
    ids  = tokenizer(full, return_tensors="pt").input_ids
    out  = model.generate(
        ids,
        max_new_tokens=600,
        do_sample=True,
        temperature=0.7,
        top_k=40,
        pad_token_id=tokenizer.eos_token_id,
        eos_token_id=tokenizer.eos_token_id,
    )
    generated = out[0][ids.shape[1]:]
    result = tokenizer.decode(generated, skip_special_tokens=True).strip()
    # If cut off mid-function add a note
    if result and not result.rstrip().endswith((')', 'return', 'pass')) and result.count('def ') > 0:
        result += "\n    # [Note: generation truncated — use local demo for complete output]"
    return result

EXAMPLES = [
    ["Write a Python function using MNE to filter EEG for beta waves (13-30 Hz)"],
    ["Write a Python function to compute beta band PSD using Welch method"],
    ["Write a Python function to load TDT block and extract RSn1 stream"],
]

with gr.Blocks(title="OLMo EEG Code Generator") as demo:
    gr.Markdown("""# OLMo EEG Code Generator
### NDML Lab — Cleveland Clinic

**Note:** This demo runs on CPU and may truncate long functions.  
For complete output use the lab server: `http://100.104.177.70:7860`""")
    prompt_box   = gr.Textbox(label="Prompt", lines=3,
        placeholder="Write a Python function to...")
    generate_btn = gr.Button("Generate", variant="primary")
    output_box   = gr.Textbox(label="Generated Code", lines=25)
    gr.Examples(examples=EXAMPLES, inputs=prompt_box)
    generate_btn.click(fn=generate_code, inputs=prompt_box, outputs=output_box)
    prompt_box.submit(fn=generate_code, inputs=prompt_box, outputs=output_box)

demo.launch()