chore: add HF Space demo scaffold and push-to-hub utility (Gradio app, requirements, README); run pre-commit formatting

Author: SHA888

.hf_export/space-med-vllm-demo/README.md

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+# Med vLLM Demo (Config-first)
+
+This Space demonstrates loading `MedicalModelConfig` from the Hub and provides a minimal UI for NER / Classification / Generation.
+
+- Loads config from: `Junaidi-AI/med-vllm`
+- Uses placeholders for inference so the UI is responsive without heavy models.
+- Extend by wiring real inference pipelines or adapters later.
+
+Run locally:
+
+```bash
+pip install -r requirements.txt
+python app.py
+```

.hf_export/space-med-vllm-demo/app.py

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+import os
+import gradio as gr
+
+from medvllm.medical.config.models.medical_config import MedicalModelConfig
+
+HF_REPO_ID = os.getenv("MEDVLLM_DEMO_REPO", "Junaidi-AI/med-vllm")
+
+
+def load_config(repo_id: str):
+    try:
+        cfg = MedicalModelConfig.from_pretrained(repo_id)
+        return cfg
+    except Exception as e:
+        raise gr.Error(f"Failed to load config from {repo_id}: {e}")
+
+
+CFG = load_config(HF_REPO_ID)
+
+
+def run_task(task_type: str, text: str):
+    # This demo focuses on configuration-driven UX.
+    # Inference backends can be wired later (e.g., adapters / pipelines).
+    if not text.strip():
+        return "", "Please enter text"
+
+    if task_type == "ner":
+        # Placeholder: echo entities based on naive regex matches for demo purposes only.
+        import re
+
+        entities = []
+        for ent in CFG.medical_entity_types:
+            # naive token contains match
+            if re.search(rf"\b{re.escape(ent)}\b", text, flags=re.IGNORECASE):
+                entities.append({"text": ent, "label": ent.upper(), "start": 0, "end": 0})
+        highlighted = text
+        for ent in entities:
+            highlighted = highlighted.replace(ent["text"], f"[{ent['text']}:{ent['label']}]")
+        return highlighted, str({"entities": entities})
+
+    elif task_type == "classification":
+        # Placeholder: pick first label if present
+        labels = CFG.classification_labels or ["positive", "negative"]
+        return labels[0], f"labels={labels}"
+
+    else:  # generation
+        # Placeholder: echo text with a note
+        return text + "\n\n[generated: demo placeholder]", "generation demo"
+
+
+def build_ui():
+    with gr.Blocks(title="Med vLLM Demo (Config-first)") as demo:
+        gr.Markdown(
+            """
+            # Med vLLM Demo (Config-first)
+            This Space loads `MedicalModelConfig` from the Hub and demonstrates a simple, config-driven UI.
+
+            - Repo: {repo}
+            - Task: {task}
+            - Model: {model}
+            - Version: {ver}
+            """.format(repo=HF_REPO_ID, task=CFG.task_type, model=CFG.model, ver=CFG.config_version)
+        )
+        with gr.Row():
+            task = gr.Radio(
+                choices=["ner", "classification", "generation"],
+                value=CFG.task_type,
+                label="Task",
+            )
+            text = gr.Textbox(label="Input Text", lines=6, placeholder="Enter clinical text...")
+        with gr.Row():
+            primary = gr.Button("Run")
+        with gr.Row():
+            out_primary = gr.Textbox(label="Primary Output")
+            out_secondary = gr.Textbox(label="Details")
+
+        def _on_click(t, x):
+            return run_task(t, x)
+
+        primary.click(_on_click, inputs=[task, text], outputs=[out_primary, out_secondary])
+    return demo
+
+
+if __name__ == "__main__":
+    demo = build_ui()
+    demo.launch(server_name="0.0.0.0", server_port=int(os.getenv("PORT", 7860)))

.hf_export/space-med-vllm-demo/requirements.txt

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+gradio>=4.0.0
+medvllm

scripts/hf/push_checkpoints.py

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+#!/usr/bin/env python3
+"""
+Utility to push a local folder (checkpoints, adapters, or artifacts) to the Hugging Face Hub.
+
+Examples:
+    python scripts/hf/push_checkpoints.py \
+        --repo-id Junaidi-AI/med-vllm \
+        --local-path outputs/ner-checkpoint \
+        --path-in-repo checkpoints/ner-2025-09-23 \
+        --commit-message "Add NER checkpoint"
+
+If you need to create a PR instead of pushing to main directly, add --create-pr.
+To rely on credentials saved via `hf auth login`, do not set HF_TOKEN or unset it for this run.
+
+    env -u HF_TOKEN python scripts/hf/push_checkpoints.py ...
+"""
+
+from __future__ import annotations
+
+import argparse
+import os
+import sys
+from pathlib import Path
+
+from huggingface_hub import HfApi
+
+
+def parse_args() -> argparse.Namespace:
+    p = argparse.ArgumentParser(description="Push a local folder to the Hugging Face Hub")
+    p.add_argument("--repo-id", required=True, help="Target repo id, e.g. org/name or user/name")
+    p.add_argument(
+        "--local-path",
+        required=True,
+        help="Local file or folder to upload (can be a single file or a directory)",
+    )
+    p.add_argument(
+        "--path-in-repo",
+        default=None,
+        help="Destination path in repo (defaults to same name as local-path)",
+    )
+    p.add_argument(
+        "--repo-type",
+        default="model",
+        choices=["model", "dataset", "space"],
+        help="Repo type on the Hub",
+    )
+    p.add_argument(
+        "--commit-message",
+        default="Upload artifacts",
+        help="Commit title / first line",
+    )
+    p.add_argument(
+        "--commit-description",
+        default=None,
+        help="Optional commit description (body)",
+    )
+    p.add_argument(
+        "--create-pr",
+        action="store_true",
+        help="Upload changes as a Pull Request instead of pushing to the default branch",
+    )
+    p.add_argument(
+        "--revision",
+        default=None,
+        help="Optional branch name or refs/pr/X reference to push against",
+    )
+    return p.parse_args()
+
+
+def main() -> int:
+    args = parse_args()
+
+    local_path = Path(args.local_path)
+    if not local_path.exists():
+        print(f"[ERROR] Local path does not exist: {local_path}")
+        return 2
+
+    # Respect existing saved credential; avoid env HF_TOKEN overriding by allowing caller to unset it.
+    api = HfApi()
+
+    # Use HfApi.upload_folder for directories, or upload_file for single files
+    try:
+        if local_path.is_dir():
+            commit = api.upload_folder(
+                repo_id=args.repo_id,
+                repo_type=args.repo_type,
+                folder_path=str(local_path),
+                path_in_repo=(args.path_in_repo or local_path.name),
+                commit_message=args.commit_message,
+                commit_description=args.commit_description,
+                create_pr=args.create_pr,
+                revision=args.revision,
+            )
+        else:
+            # Single file
+            commit = api.upload_file(
+                repo_id=args.repo_id,
+                repo_type=args.repo_type,
+                path_or_fileobj=str(local_path),
+                path_in_repo=(args.path_in_repo or local_path.name),
+                commit_message=args.commit_message,
+                commit_description=args.commit_description,
+                create_pr=args.create_pr,
+                revision=args.revision,
+            )
+    except Exception as e:
+        print(f"[ERROR] Upload failed: {e}")
+        return 3
+
+    print(commit)
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())