Update app.py

app.py

@@ -24,17 +24,28 @@ def install_package(package, version=None):
         raise
 
 
-# Required packages — ORDER MATTERS:
-#   tokenizers must be pinned before transformers so pip does not upgrade it.
-#   transformers 5.x dropped the "summarization" pipeline task entirely,
-#   so we pin to 4.46.3 (last v4 release) which still has it.
-#   tokenizers 0.21.4 is required by transformers 4.46.3 and has
-#   pre-built abi3 wheels that work on Python 3.13 without Rust compilation.
+def force_install(package_spec):
+    """Install a package unconditionally, overriding whatever version is present."""
+    print(f"Force-installing {package_spec}...")
+    try:
+        subprocess.check_call([
+            sys.executable, "-m", "pip", "install", "--no-cache-dir", package_spec
+        ])
+    except subprocess.CalledProcessError as e:
+        print(f"Failed to force-install {package_spec}: {e}")
+        raise
+
+
+# Phase 1 — install missing packages.
+# Notes:
+#   - tokenizers is NOT pre-pinned here; transformers 4.46.3 pulls tokenizers 0.20.3
+#     which already ships native cp313 wheels, so no Rust compilation is needed.
+#   - transformers is pinned to 4.46.3 (last v4 release) because v5 dropped the
+#     "summarization" pipeline task entirely.
 required_packages = {
     "gradio": None,
     "torch": None,
-    "tokenizers": "0.21.4",    # must come before transformers; abi3 wheel works on Py3.13
-    "transformers": "4.46.3",  # last v4 release; still supports the summarization pipeline
+    "transformers": "4.46.3",
 }
 
 for package, version in required_packages.items():
@@ -44,7 +55,22 @@ for package, version in required_packages.items():
     except ImportError:
         install_package(package, version)
 
-# Import packages
+# Phase 2 — fix the huggingface_hub version AFTER transformers has run.
+#
+# Problem: transformers 4.46.3 requires huggingface-hub<1.0, so pip picks
+#   the latest <1.0 release (currently 0.36.x).  Starting around hub 0.30,
+#   get_session() returns an httpx.Client when httpx is present on the system.
+#   transformers' own hub.py calls get_session().head(..., allow_redirects=...),
+#   which is a requests-style kwarg that httpx rejects with:
+#     TypeError: Client.head() got an unexpected keyword argument 'allow_redirects'
+#
+# Fix: force hub back to 0.28.1 — the last release that uses requests (not httpx)
+#   for get_session(), while still satisfying:
+#     - transformers 4.46.3 requirement: >=0.23.2, <1.0   ✓
+#     - gradio requirement:              >=0.28.1           ✓
+force_install("huggingface_hub==0.28.1")
+
+# Now safe to import everything
 import gradio as gr
 import torch
 from transformers import pipeline
@@ -97,7 +123,6 @@ def summarize_text(text, model_name, summary_length, num_beams):
 
     try:
         global summarizer
-        # Reload pipeline on CPU whenever the model changes
         summarizer = pipeline("summarization", model=model_name, device=-1)
 
         length_mapping = {