add persistant storage

app.py

@@ -15,8 +15,17 @@ import numpy as np
 os.environ["GRADIO_ANALYTICS_ENABLED"] = "False"
 CONVERSION_SCRIPT = "./llama.cpp/convert_hf_to_gguf.py"
 
+# Set up persistent storage paths
 log_dir = "/data/logs"
+downloads_dir = "/data/downloads"
+outputs_dir = "/data/outputs"
+models_dir = "/data/models"
+
+# Create directories if they don't exist
 os.makedirs(log_dir, exist_ok=True)
+os.makedirs(downloads_dir, exist_ok=True)
+os.makedirs(outputs_dir, exist_ok=True)
+os.makedirs(models_dir, exist_ok=True)
 
 logging.basicConfig(
     filename=os.path.join(log_dir, "app.log"),
@@ -50,7 +59,8 @@ Original model: https://huggingface.co/{model_id}
 Run them directly with [llama.cpp](https://github.com/ggml-org/llama.cpp), or any other llama.cpp based project
 ## Prompt format
 ```
-<｜begin▁of▁sentence｜>{{system_prompt}}<｜User｜>{{prompt}}<｜Assistant｜><｜end▁of▁sentence｜><｜Assistant｜>
+{{system_prompt}}
+{{prompt}}
 ```
 ## Download a file (not the whole branch) from below:
 | Filename | Quant type | File Size | Split |
@@ -278,13 +288,14 @@ def process_model(
         )
         dl_pattern += [pattern]
 
-        os.makedirs("downloads", exist_ok=True)
-        os.makedirs("outputs", exist_ok=True)
+        # Use persistent directories
+        model_download_dir = os.path.join(downloads_dir, model_name)
+        os.makedirs(model_download_dir, exist_ok=True)
 
-        with tempfile.TemporaryDirectory(dir="outputs") as outdir:
+        with tempfile.TemporaryDirectory(dir=outputs_dir) as outdir:
             fp16 = str(Path(outdir) / f"{model_name}.fp16.gguf")
 
-            with tempfile.TemporaryDirectory(dir="downloads") as tmpdir:
+            with tempfile.TemporaryDirectory(dir=model_download_dir) as tmpdir:
                 local_dir = Path(tmpdir) / model_name
                 api.snapshot_download(
                     repo_id=model_id,