Enable project approvals

app.py

@@ -510,8 +510,8 @@ with st.form(key="form"):
                     ).json()
                     print(f"INFO -- Dataset creation response: {data_json_resp}")
                     if data_json_resp["download_status"] == 1:
-                        train_json_resp = http_get(
-                            path=f"/projects/{project_json_resp['id']}/data/start_process",
+                        train_json_resp = http_post(
+                            path=f"/projects/{project_json_resp['id']}/data/start_processing",
                             token=HF_TOKEN,
                             domain=AUTOTRAIN_BACKEND_API,
                         ).json()
@@ -548,6 +548,8 @@ with st.form(key="form"):
                             )
                             print("INFO -- Pushing evaluation job logs to the Hub")
                             evaluation_log = {}
+                            evaluation_log["project_id"] = project_json_resp["id"]
+                            evaluation_log["is_evaluated"] = False
                             evaluation_log["payload"] = project_payload
                             evaluation_log["project_creation_response"] = project_json_resp
                             evaluation_log["dataset_creation_response"] = data_json_resp

requirements.txt

@@ -4,6 +4,7 @@ streamlit==1.10.0
 datasets<2.3
 evaluate<0.2
 jsonlines
+typer[rich]
 # Dataset specific deps
 py7zr<0.19
 openpyxl<3.1

run_evaluation_jobs.py

@@ -0,0 +1,44 @@
+import os
+from pathlib import Path
+
+import typer
+from datasets import load_dataset
+from dotenv import load_dotenv
+from rich import print
+
+from utils import http_get, http_post
+
+if Path(".env").is_file():
+    load_dotenv(".env")
+
+HF_TOKEN = os.getenv("HF_TOKEN")
+AUTOTRAIN_TOKEN = os.getenv("AUTOTRAIN_TOKEN")
+AUTOTRAIN_USERNAME = os.getenv("AUTOTRAIN_USERNAME")
+AUTOTRAIN_BACKEND_API = os.getenv("AUTOTRAIN_BACKEND_API")
+
+
+def main():
+    logs_df = load_dataset("autoevaluate/evaluation-job-logs", use_auth_token=True, split="train").to_pandas()
+    evaluated_projects_ds = load_dataset("autoevaluate/evaluated-project-ids", use_auth_token=True, split="train")
+    projects_df = logs_df.copy()[(~logs_df["project_id"].isnull()) & (logs_df["is_evaluated"] == False)]
+    projects_to_approve = projects_df["project_id"].astype(int).tolist()
+
+    for project_id in projects_to_approve:
+        project_status = http_get(
+            path=f"/projects/{project_id}",
+            token=HF_TOKEN,
+            domain=AUTOTRAIN_BACKEND_API,
+        ).json()
+        if project_status["status"] == 3:
+            train_job_resp = http_post(
+                path=f"/projects/{project_id}/start_training",
+                token=HF_TOKEN,
+                domain=AUTOTRAIN_BACKEND_API,
+            ).json()
+            print(f"🏃‍♂️ Project {project_id} approval response: {train_job_resp}")
+            # if train_job_resp["approved"] == True:
+            #     # Update evaluation status
+
+
+if __name__ == "__main__":
+    typer.run(main)