update code

README.md

@@ -8,6 +8,9 @@ sdk_version: 5.49.1
 python_version: 3.11
 app_file: app.py
 pinned: false
+hf_oauth: true
+hf_oauth_scopes:
+  - inference-api
 license: mit
 short_description: Explain Music Scores through analysis.
 ---
@@ -21,4 +24,3 @@ Scoreprompts is a tool that leverages large language models to analyze and expla
 - Upload music scores in various formats.
 - Utilize large language models to generate explanations.
 - User-friendly interface for easy interaction.
-

app.py

@@ -100,6 +100,17 @@ def _extract_first_json(text: str) -> dict:
     return obj
 
 
+def _resolve_hf_token(oauth_token: gr.OAuthToken | None) -> str:
+    if oauth_token and getattr(oauth_token, "token", None):
+        return oauth_token.token
+    if os.getenv("SPACE_ID") or os.getenv("SPACE_HOST"):
+        raise ValueError("Please sign in with Hugging Face to run inference.")
+    env_token = os.getenv("HF_TOKEN")
+    if env_token:
+        return env_token
+    raise ValueError("No Hugging Face token available. Please sign in with the Login button.")
+
+
 def _chat_json(
     client: InferenceClient,
     system_prompt: str,
@@ -265,6 +276,7 @@ def run_pipeline(
     max_tokens_writer: int,
     temperature_writer: float,
     force_cpu: bool,
+    oauth_token: gr.OAuthToken | None = None,
 ):
     logs: list[str] = []
 
@@ -276,6 +288,7 @@ def run_pipeline(
         log_fn("Starting run")
         if not file_path:
             raise ValueError("No file uploaded.")
+        hf_token = _resolve_hf_token(oauth_token)
         score_path = Path(file_path)
         score_id = score_path.stem
 
@@ -500,7 +513,7 @@ def run_pipeline(
         chunk = bundles[0]
         log_fn(f"Schema chunk measures={chunk['chunk']['measure_start']}..{chunk['chunk']['measure_end']}")
 
-        client = InferenceClient(model_id)
+        client = InferenceClient(model_id, token=hf_token)
         t0 = time.time()
         bar_facts = _chat_json(
             client,
@@ -564,6 +577,9 @@ def run_pipeline(
 with gr.Blocks(title="ScorePrompts Prompt Builder") as demo:
     gr.Markdown("# ScorePrompts Prompt Builder (Gradio)")
     gr.Markdown("Note: this demo only reports the first chunk (default bars_per_chunk). Increase the Bars per chunk slider to include more measures.")
+    gr.Markdown("Sign in with Hugging Face to enable Inference API access.")
+    with gr.Row():
+        gr.LoginButton()
     with gr.Row():
         file_in = gr.File(label="Upload MusicXML (.musicxml/.xml/.mxl)", type="filepath")
         model_id = gr.Textbox(
@@ -611,4 +627,4 @@ with gr.Blocks(title="ScorePrompts Prompt Builder") as demo:
     )
 
 if __name__ == "__main__":
-    demo.queue().launch()
+    demo.queue().launch()

requirements.txt

@@ -36,6 +36,10 @@ music21>=8.0.0
 
 # Gradio and Hugging Face Spaces
 gradio>=4.0.0
+authlib==1.6.6
+cffi==2.0.0
+cryptography==46.0.4
+itsdangerous==2.2.0
 
 # Experiment tracking
 wandb>=0.13.0
@@ -63,4 +67,3 @@ git+https://github.com/manoskary/analysisgnn.git@musicbert_integration
 
 # ScorePrompts dependency as a private GitHub repo
 # git+https://x-access-token:${GITHUB_TOKEN}@github.com/manoskary/scoreprompts.git@main
-