Use chain identity

app.py

@@ -5,6 +5,7 @@ from dataclasses import dataclass
 from datetime import datetime
 from zoneinfo import ZoneInfo
 
+import bittensor as bt
 import gradio as gr
 import numpy as np
 import plotly.graph_objects as go
@@ -12,35 +13,24 @@ import wandb
 from substrateinterface import Keypair
 from wandb.apis.public import Run
 
-HOTKEYS_TO_KNOWN_VALIDATORS: dict[str, str] = {
-    "5GKH9FPPnWSUoeeTJp19wVtd84XqFW4pyK2ijV2GsFbhTrP1": "Taostats & Corcel",
-    "5F4tQyWrhfGVcNhoqeiNsR6KjD4wMZ2kfhLj4oHYuyHbZAc3": "Openτensor Foundaτion",
-    "5FFApaS75bv5pJHfAp2FVLBj9ZaXuFDjEypsaBNc1wCfe52v": "RoundTable21",
-    "5HEo565WAy4Dbq3Sv271SAi7syBSofyfhhwRNjFNSM2gP9M2": "Foundry",
-    "5HK5tp6t2S59DywmHRWPBVJeJ86T61KjurYqeooqj8sREpeN": "Bittensor Guru",
-    "5GP7c3fFazW9GXK8Up3qgu2DJBk8inu4aK9TZy3RuoSWVCMi": "Datura",
-    "5EhvL1FVkQPpMjZX4MAADcW42i3xPSF1KiCpuaxTYVr28sux": "TAO-Validator.com",
-    "5E4z3h9yVhmQyCFWNbY9BPpwhx4xFiPwq3eeqmBgVF6KULde": "Tensorplex Labs",
-    "5Hb63SvXBXqZ8zw6mwW1A39fHdqUrJvohXgepyhp2jgWedSB": "Miner's Union Validator",
-    "5CXRfP2ekFhe62r7q3vppRajJmGhTi7vwvb2yr79jveZ282w": "Rizzo",
-    "5CVS9d1NcQyWKUyadLevwGxg6LgBcF9Lik6NSnbe5q59jwhE": "Ary van der Touw",
-    "5Fq5v71D4LX8Db1xsmRSy6udQThcZ8sFDqxQFwnUZ1BuqY5A": "NorthTensor",
-    "5CsvRJXuR955WojnGMdok1hbhffZyB4N5ocrv82f3p5A2zVp": "Owl Ventures",
-    "5HNQURvmjjYhTSksi8Wfsw676b4owGwfLR2BFAQzG7H3HhYf": "Neural Internet",
-    "5DvTpiniW9s3APmHRYn8FroUWyfnLtrsid5Mtn5EwMXHN2ed": "FirstTensor.com",
-}
-
 WANDB_RUN_PATH = os.environ["WANDB_RUN_PATH"]
 SOURCE_VALIDATOR_UID = int(os.environ["SOURCE_VALIDATOR_UID"])
 
 START_DATE = datetime(2024, 9, 17)
+NET_UID = 39
 REFRESH_RATE = 60 * 30  # 30 minutes
 GRAPH_HISTORY_DAYS = 30
 MAX_GRAPH_ENTRIES = 10
 
 wandb_api = wandb.Api()
 demo = gr.Blocks(css=".typewriter {font-family: 'JMH Typewriter', sans-serif;}", fill_height=True, fill_width=True)
+
+subtensor = bt.subtensor()
+metagraph = bt.metagraph(netuid=NET_UID)
+bt.logging.disable_logging()
+
 runs: dict[int, list[Run]] = {}
+validator_identities: dict[int, str] = {}
 
 
 @dataclass
@@ -251,22 +241,36 @@ def fetch_wandb_data():
     runs = dict(sorted(runs.items(), key=lambda item: item[0]))
 
 
+def fetch_identities():
+    validator_identities.clear()
+    for uid in range(metagraph.n.item()):
+        if metagraph.validator_trust[uid]:
+            identity = subtensor.substrate.query('SubtensorModule', 'Identities', [metagraph.coldkeys[uid]])
+            if identity != None:
+                validator_identities[uid] = identity.value["name"]
+
+
+def get_validator_name(validator_uid: int) -> str:
+    if validator_uid in validator_identities:
+        return validator_identities[validator_uid]
+    else:
+        return metagraph.hotkeys[validator_uid]
+
+
 def get_choices() -> list[tuple[str, int]]:
     choices: list[tuple[str, int]] = []
     for uid, run in runs.items():
-        hotkey = run[0].config["hotkey"]
         benchmarks = dict(run[0].summary.get("benchmarks", {}))
         finished = any("winner" in value for value in benchmarks.values())
         progress_text = "Finished" if finished else "In Progress"
-        if hotkey in HOTKEYS_TO_KNOWN_VALIDATORS:
-            choices.append((f"{uid} - {HOTKEYS_TO_KNOWN_VALIDATORS[hotkey]} ({progress_text})", uid))
-        else:
-            choices.append((str(f"{uid} - {hotkey}"), uid))
+        choices.append((f"{uid} - {get_validator_name(uid)} ({progress_text})", uid))
     return choices
 
 
 def refresh():
+    metagraph.sync(subtensor=subtensor)
     fetch_wandb_data()
+    fetch_identities()
     demo.clear()
     now = datetime.now(tz=ZoneInfo("America/New_York"))
 
@@ -298,7 +302,6 @@ def refresh():
                 label="Source Validator"
             )
 
-
             leaderboard = gr.components.Dataframe(
                 create_leaderboard(runs[dropdown.value]),
                 headers=["Uid", "Winner", "Model", "Score", "Gen Time", "Similarity", "Size", "VRAM Usage", "Power Usage", "Hotkey"],

requirements.txt

@@ -1,5 +1,6 @@
 black
 gradio
+bittensor
 wandb
 substrate-interface
 plotly