Add success message

app.py

@@ -1,17 +1,14 @@
 import json
 import os
-import re
 import shutil
-import subprocess
 from datetime import datetime
 from pathlib import Path
 
-import requests
 import streamlit as st
 from dotenv import load_dotenv
 from huggingface_hub import HfApi, Repository
 
-from validate import validate_submission
+from utils import http_post, validate_json
 
 if Path(".env").is_file():
     load_dotenv(".env")
@@ -22,29 +19,6 @@ HF_AUTONLP_BACKEND_API = os.getenv("HF_AUTONLP_BACKEND_API")
 LOCAL_REPO = "submission_repo"
 
 
-def get_auth_headers(token: str, prefix: str = "autonlp"):
-    return {"Authorization": f"{prefix} {token}"}
-
-
-def http_post(
-    path: str,
-    token: str,
-    payload=None,
-    domain: str = HF_AUTONLP_BACKEND_API,
-    suppress_logs: bool = False,
-    **kwargs,
-) -> requests.Response:
-    """HTTP POST request to the AutoNLP API, raises UnreachableAPIError if the API cannot be reached"""
-    try:
-        response = requests.post(
-            url=domain + path, json=payload, headers=get_auth_headers(token=token), allow_redirects=True, **kwargs
-        )
-    except requests.exceptions.ConnectionError:
-        print("❌ Failed to reach AutoNLP API, check your internet connection")
-    response.raise_for_status()
-    return response
-
-
 ###########
 ### APP ###
 ###########
@@ -59,18 +33,29 @@ GEM aims to:
 - audit data and models and present results via data cards and model robustness reports.
 - develop standards for evaluation of generated text using both automated and human metrics.
 
-Use this page to submit your predcitions to the benchmark.
+Use this page to submit your system's predictions to the benchmark.
 """
 )
 
 with st.form(key="form"):
     # Flush local repo
     shutil.rmtree(LOCAL_REPO, ignore_errors=True)
+    submission_errors = 0
     uploaded_file = st.file_uploader("Upload submission.json file", type=["json"])
 
-    if uploaded_file is not None:
-        data = str(uploaded_file.read(), "utf-8")
-        json_data = json.loads(data)
+    if uploaded_file:
+        if uploaded_file.name != "submission.json":
+            st.error(f"⛔ Invalid filename. Please upload a submission.json file.")
+            submission_errors += 1
+        else:
+            data = str(uploaded_file.read(), "utf-8")
+            json_data = json.loads(data)
+            is_valid, message = validate_json(json_data)
+            if is_valid:
+                st.success(message)
+            else:
+                st.error(message)
+                submission_errors += 1
 
     with st.expander("Submission format"):
         st.markdown(
@@ -110,19 +95,28 @@ with st.form(key="form"):
         type="password",
         help="You can generate an access token via your 🤗 Hub settings. See the [docs](https://huggingface.co/docs/hub/security#user-access-tokens) for more details",
     )
+    if token:
+        try:
+            user_info = HfApi().whoami(token)
+        except Exception as e:
+            st.error("⛔ Invalid access token")
+            submission_errors += 1
 
     submit_button = st.form_submit_button("Make Submission")
 
-if submit_button:
-    validate_submission(json_data)
-    user_info = HfApi().whoami(token)
+if submit_button and submission_errors == 0:
+    st.write("⏳ Preparing submission for evaluation ...")
     user_name = user_info["name"]
     submission_name = json_data["submission_name"]
 
     # Create submission dataset under benchmarks ORG
     dataset_repo_url = f"https://huggingface.co/datasets/benchmarks/gem-{user_name}"
     repo = Repository(
-        local_dir=LOCAL_REPO, clone_from=dataset_repo_url, repo_type="dataset", private=True, use_auth_token=HF_TOKEN
+        local_dir=LOCAL_REPO,
+        clone_from=dataset_repo_url,
+        repo_type="dataset",
+        private=True,
+        use_auth_token=HF_TOKEN,
     )
     submission_metadata = {"benchmark": "gem", "type": "prediction", "submission_name": submission_name}
     repo.repocard_metadata_save(submission_metadata)
@@ -151,10 +145,14 @@ if submit_button:
         "split": "test",
         "config": None,
     }
-    json_resp = http_post(path="/evaluate/create", payload=payload, token=HF_TOKEN).json()
-    st.write(json_data["submission_name"])
-    st.write(commit_sha)
-    st.write(json_resp)
+    json_resp = http_post(
+        path="/evaluate/create", payload=payload, token=HF_TOKEN, domain=HF_AUTONLP_BACKEND_API
+    ).json()
+
+    if json_resp["status"] == 1:
+        st.success(f"✅ Submission {submission_name} was successfully submitted to the evaluation queue!")
+    else:
+        st.error("🙈 Oh noes! There was an error submitting your submission. Please contact the organisers")
 
     # Flush local repo
     shutil.rmtree(LOCAL_REPO, ignore_errors=True)

validate.py → utils.py

@@ -1,34 +1,45 @@
 import json
 
 import jsonschema
+import requests
 import streamlit as st
 
 
-def get_schema():
-    """This function loads the given schema available"""
+def load_schema():
+    """Load the GEM schema"""
     with open("schema.json", "r", encoding="utf8") as file:
         schema = json.load(file)
     return schema
 
 
 def validate_json(json_data):
-    execute_api_schema = get_schema()
+    execute_api_schema = load_schema()
     try:
         jsonschema.validate(instance=json_data, schema=execute_api_schema)
     except jsonschema.exceptions.ValidationError as err:
-        err = "Submission does not match GEM schema!"
+        err = "❌ Submission does not match GEM schema. Please fix the submission file 🙈"
         return False, err
 
-    message = "Submission matches GEM schema!"
+    message = "✅ Submission matches GEM schema!"
     return True, message
 
 
-def validate_submission(submission_data):
-    is_valid, message = validate_json(submission_data)
+def get_auth_headers(token: str, prefix: str = "autonlp"):
+    return {"Authorization": f"{prefix} {token}"}
 
-    if is_valid:
-        st.write("All submission files validated! ✨ 🚀 ✨")
-        st.write("Now you can make a submission 🤗")
-    else:
-        st.write(message)
-        st.write("Please fix the submission files 🙈")
+
+def http_post(
+    path: str,
+    token: str,
+    payload=None,
+    domain: str = None,
+) -> requests.Response:
+    """HTTP POST request to the AutoNLP API, raises UnreachableAPIError if the API cannot be reached"""
+    try:
+        response = requests.post(
+            url=domain + path, json=payload, headers=get_auth_headers(token=token), allow_redirects=True
+        )
+    except requests.exceptions.ConnectionError:
+        print("❌ Failed to reach AutoNLP API, check your internet connection")
+    response.raise_for_status()
+    return response