Update app.py

app.py

@@ -2,12 +2,26 @@ import os
 from fastapi import FastAPI
 from transformers import AutoModelForCausalLM, AutoTokenizer
 
-os.environ["HF_HOME"] = "/app/cache"
+# Set cache directories to /tmp which is writable
+os.environ["TRANSFORMERS_CACHE"] = "/tmp/transformers_cache"
+os.environ["HF_HOME"] = "/tmp/hf_home"
+os.environ["XDG_CACHE_HOME"] = "/tmp/cache"
 
-# Load model
-model_name = "mynuddin/chatbot"  
-tokenizer = AutoTokenizer.from_pretrained(model_name)
-model = AutoModelForCausalLM.from_pretrained(model_name).to("cpu")
+# Create cache directories if they don't exist
+os.makedirs("/tmp/transformers_cache", exist_ok=True)
+os.makedirs("/tmp/hf_home", exist_ok=True)
+os.makedirs("/tmp/cache", exist_ok=True)
+
+# Load model with explicit cache directory
+model_name = "mynuddin/chatbot"
+tokenizer = AutoTokenizer.from_pretrained(
+    model_name,
+    cache_dir="/tmp/model_cache"
+)
+model = AutoModelForCausalLM.from_pretrained(
+    model_name,
+    cache_dir="/tmp/model_cache"
+).to("cpu")
 
 app = FastAPI()
 
@@ -16,4 +30,4 @@ def generate_text(prompt: str):
     inputs = tokenizer(prompt, return_tensors="pt")
     output = model.generate(**inputs, max_length=128)
     generated_text = tokenizer.decode(output[0], skip_special_tokens=True)
-    return {"generated_query": generated_text}
+    return {"generated_query": generated_text}