Update app.py

app.py

@@ -9,9 +9,9 @@ import torch
 # Hugging Face token stored in Spaces secrets
 HF_TOKEN = os.environ.get("HF_TOKEN")
 
-# Persistent model path in Space filesystem
-MODEL_PATH = "./mistral" 
-CACHE_DIR = "./.cache/huggingface"
+# Writable model path and cache directory in Spaces
+MODEL_PATH = "/tmp/mistral"
+CACHE_DIR = "/tmp/.cache/huggingface"
 
 # Ensure directories exist
 os.makedirs(MODEL_PATH, exist_ok=True)
@@ -22,7 +22,7 @@ os.environ["HF_HOME"] = CACHE_DIR
 
 # Download model if not already present
 if not os.listdir(MODEL_PATH):
-    print("Downloading Mistral model...")
+    print("Downloading Mistral model to /tmp...")
     snapshot_download(
         repo_id="mistralai/Mistral-7B-Instruct-v0.3",
         repo_type="model",
@@ -30,7 +30,7 @@ if not os.listdir(MODEL_PATH):
         use_auth_token=HF_TOKEN
     )
 else:
-    print("Model already exists. Skipping download.")
+    print("Model already exists in /tmp. Skipping download.")
 
 # Load tokenizer and model from local path
 tokenizer = AutoTokenizer.from_pretrained(MODEL_PATH)
@@ -49,7 +49,7 @@ def find_and_download_annual_report(company):
     query = f"site:example.com {company} annual report filetype:pdf"
     pdf_url = search_pdf_url(query)
     if pdf_url:
-        local_path = download_pdf(pdf_url, save_dir="./pdfs")
+        local_path = download_pdf(pdf_url, save_dir="/tmp/pdfs")
         return f"Downloaded: {local_path}"
     return "No PDF found"
 
@@ -79,3 +79,4 @@ with gr.Blocks() as demo:
 demo.launch(server_name="0.0.0.0", server_port=7860)
 
 
+