Merge pull request #5 from macrocosm-os/features/api-model-data

api.py

@@ -126,6 +126,26 @@ def validator():
         utils.make_validator_dataframe(validator_df, model_data).to_dict(orient='records')
         )
 
+@app.route('/model-data', methods=['GET'])
+def model_data():
+    """
+    Get the model data
+    Returns:
+    - model_data: List of dicts (from list of ModelData)
+    - winner_data: dict containing top earning miners
+    """
+    model_data = state_vars["model_data"]
+    winner_data = {
+                f"{c.namespace}/{c.name} ({c.commit[0:8]}) · (τ{round(c.emission, 2):,})": c.incentive
+                for c in model_data
+                if c.incentive
+            }
+
+    return jsonify({
+        'model_data': [md.to_dict() for md in model_data],
+        'winner_data': winner_data
+        })
+
 
 if __name__ == '__main__':
     

utils.py

@@ -14,7 +14,7 @@ import numpy as np
 import bittensor as bt
 
 from dotenv import load_dotenv
-from dataclasses import dataclass
+from dataclasses import dataclass, asdict
 from typing import Dict, List, Any, Optional, Tuple
 from bittensor.extrinsics.serving import get_metadata
 
@@ -28,7 +28,7 @@ load_dotenv()
 WANDB_TOKEN = os.environ.get("WANDB_API_KEY", None)
 SUBTENSOR_ENDPOINT = os.environ.get("SUBTENSOR_ENDPOINT", None)
 VALIDATOR_WANDB_PROJECT = "opentensor-dev/pretraining-subnet"
-BENCHMARK_WANDB_PROJECT = "pretraining-benchmark-data"
+BENCHMARK_WANDB_PROJECT = "steffenc/pretraining-benchmark-data"
 BENCHMARK_FLAG = os.environ.get("BENCHMARK_FLAG", None)
 
 @dataclass
@@ -66,7 +66,9 @@ class ModelData:
             incentive=incentive,
             emission=emission,
         )
-
+        
+    def to_dict(self):
+        return asdict(self)
 
 def run_with_retries(func, *args, **kwargs):
     for i in range(0, RETRIES):