Update app.py

app.py

@@ -1,27 +1,22 @@
-import os
 from fastapi import FastAPI
 from pydantic import BaseModel
 from transformers import pipeline, AutoTokenizer
+import os
 import uvicorn
 
-# Create a custom cache directory inside app folder
-os.environ["TRANSFORMERS_CACHE"] = "/app/hf_cache"
-
 app = FastAPI()
 
-HF_AUTH_TOKEN = os.environ.get("HF_TOKEN")
-MODEL_NAME = "VincentMuriuki/legal-summarizer"
+# Safe local cache directory for HF models
+os.environ["TRANSFORMERS_CACHE"] = "/app/cache"
+os.environ["HF_HOME"] = "/app/hf"
 
-summarizer = pipeline(
-    "summarization",
-    model=MODEL_NAME,
-    use_auth_token=HF_AUTH_TOKEN
-)
+# Read Hugging Face token from environment
+HF_AUTH_TOKEN = os.getenv("HF_TOKEN")
 
-tokenizer = AutoTokenizer.from_pretrained(
-    MODEL_NAME,
-    use_auth_token=HF_AUTH_TOKEN
-)
+# Load model and tokenizer using auth token
+MODEL_NAME = "VincentMuriuki/legal-summarizer"
+summarizer = pipeline("summarization", model=MODEL_NAME, use_auth_token=HF_AUTH_TOKEN)
+tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME, use_auth_token=HF_AUTH_TOKEN)
 
 class SummarizeInput(BaseModel):
     text: str
@@ -48,4 +43,4 @@ def chunk_text(data: ChunkInput):
     return {"chunks": chunks}
 
 if _name_ == "_main_":
-    uvicorn.run(app, host="0.0.0.0", port=7860)
+    uvicorn.run(app, host="0.0.0.0", port=7860)