Update app.py

switching from json to pandas

app.py

@@ -11,7 +11,8 @@ from enum import Enum
 
 OWNER = "EnergyStarAI"
 COMPUTE_SPACE = f"{OWNER}/launch-computation-example"
-REQUESTS_DATASET_PATH = f"{OWNER}/requests_debug"
+requests_dset = load_dataset("EnergyStarAI/requests_debug", split="test")
+
 
 TOKEN = os.environ.get("DEBUG")
 API = HfApi(token=TOKEN)
@@ -112,9 +113,11 @@ def add_new_eval(
     #    return styled_error("Could not get your model information. Please fill it up properly.")
 
     model_size = get_model_size(model_info=model_info, precision=precision)
-
+    
     print("Adding request")
 
+    requests_dset = requests.to_pandas()
+    
     request_dict = {
         "model": repo_id,
         "precision": precision,
@@ -127,46 +130,19 @@ def add_new_eval(
         #"private": False,
     #}
 
-    out_file = f"{model_name}_eval_request_{precision}.json"
-    temp_out_path = f"./temp/{REQUESTS_DATASET_PATH}/{model_owner}/"
-    temp_out_file = f"./temp/{REQUESTS_DATASET_PATH}/{model_owner}/{out_file}"
-    print("Making directory to output results at %s" % temp_out_path)
-    os.makedirs(temp_out_path, exist_ok=True)
-
     print("Writing out temp request file to %s" % temp_out_file)
-    with open(temp_out_file, "w+") as f:
-        f.write(json.dumps(request_dict))
-
-    print("Uploading request to Dataset repo at %s" % REQUESTS_DATASET_PATH)
-    API.upload_file(
-        path_or_fileobj=temp_out_file,
-        path_in_repo=f"{model_owner}/{out_file}",
-        repo_id=REQUESTS_DATASET_PATH,
-        repo_type="dataset",
-        commit_message=f"Adding {model_name} to requests queue.",
-    )
-
-    # Remove the local file
-    os.remove(temp_out_file)
+    df_request_dict = pd.DataFrame({'name':request_dict.keys(), 'value':request_dict.values()})
+    df_final = pd.concat([requests_dset, df_request_dict], ignore_index=True)
+    updated_dset =Dataset.from_pandas(requests_dset)
+    updated_dset.push_to_hub("EnergyStarAI/requests_debug", split="test")
     
     print("Starting compute space at %s " % COMPUTE_SPACE)
     return start_compute_space()
 
 def print_existing_models():
     model_list= []
-    requests_dataset = snapshot_download('EnergyStarAI/requests_debug', token=TOKEN, repo_type="dataset", allow_patterns="*.json")
-    for dir, path, files in os.walk(requests_dataset):
-        for fid in files:
-            file_path = os.path.join(dir, fid)
-            with open(file_path) as fp:
-                request = json.load(fp)
-                status = request['status']
-                if status == 'COMPLETE':
-                    status = request['status']
-                    model = request['model']
-                    task = request['task']
-                    model_list.append([model, task])
-    return model_list
+    requests = load_dataset("EnergyStarAI/requests_debug", split="test")
+requests_dset = requests.to_pandas()