Update app.py

app.py

@@ -24,12 +24,20 @@ EVALUATION_HEADER = """<h3 align="center">Shows the latest internal evaluation s
 H4_TOKEN = os.environ.get("H4_TOKEN", None)
 API = HfApi(token=H4_TOKEN)
 REPO_ID = "winglian/finetuning_subnet_leaderboard"
-METAGRAPH_RETRIES = 5
-METAGRAPH_DELAY_SECS = 3
+METAGRAPH_RETRIES = 10
+METAGRAPH_DELAY_SECS = 30
 NETUID = 6
 SUBNET_START_BLOCK = 2225782
 SECONDS_PER_BLOCK = 12
 
+@dataclass
+class Competition:
+    id: str
+    name: str
+
+COMPETITIONS = [Competition(id="m1", name="mistral-7b"), Competition(id="g1", name="gemma-2b")]
+DEFAULT_COMPETITION_ID = "g1"
+
 def get_subtensor_and_metagraph() -> typing.Tuple[bt.subtensor, bt.metagraph]:
     for i in range(0, METAGRAPH_RETRIES):
         try:
@@ -53,6 +61,7 @@ class ModelData:
     block: int
     incentive: float
     emission: float
+    competition: str
 
     @classmethod
     def from_compressed_str(cls, uid: int, hotkey: str, cs: str, block: int, incentive: float, emission: float):
@@ -65,6 +74,7 @@ class ModelData:
             name=tokens[1],
             commit=tokens[2] if tokens[2] != "None" else None,
             hash=tokens[3] if tokens[3] != "None" else None,
+            competition=tokens[4] if len(tokens) > 4 and tokens[4] != "None" else DEFAULT_COMPETITION_ID,
             block=block,
             incentive=incentive,
             emission=emission
@@ -173,33 +183,37 @@ with demo:
 
     gr.HTML(value=get_next_update())
 
-    gr.Label(
-        value={ f"{c.namespace}/{c.name} ({c.commit[0:8]}) · ${round(c.emission * tao_price, 2):,} (τ{round(c.emission, 2):,})": c.incentive for c in leaderboard_df if c.incentive},
-        num_top_classes=10,
-    )
+    with gr.Tabs():
+        for competition in COMPETITIONS:
+            with gr.Tab(competition.name):
 
-
-    with gr.Accordion("Validator Stats"):
-        validator_table = gr.components.Dataframe(
-            value=[
-                [uid, int(validator_df[uid][1]), round(validator_df[uid][0], 4)] + [validator_df[uid][-1].get(c.uid) for c in leaderboard_df if c.incentive]
-                for uid, _ in sorted(
-                    zip(validator_df.keys(), [validator_df[x][1] for x in validator_df.keys()]),
-                    key=lambda x: x[1],
-                    reverse=True
+                gr.Label(
+                    value={ f"{c.namespace}/{c.name} ({c.commit[0:8]}, UID={c.uid}) · ${round(c.emission * tao_price, 2):,} (τ{round(c.emission, 2):,})": c.incentive for c in leaderboard_df if c.incentive and c.competition == competition.id},
+                    num_top_classes=10,
                 )
-            ],
-            headers=["UID", "Stake (τ)", "V-Trust"] + [f"{c.namespace}/{c.name} ({c.commit[0:8]})" for c in leaderboard_df if c.incentive],
-            datatype=["number", "number", "number"] + ["number" for c in leaderboard_df if c.incentive],
-            interactive=False,
-            visible=True,
-        )
+
+
+        with gr.Accordion("Validator Stats"):
+            validator_table = gr.components.Dataframe(
+                value=[
+                    [uid, int(validator_df[uid][1]), round(validator_df[uid][0], 4)] + [validator_df[uid][-1].get(c.uid) for c in leaderboard_df if c.incentive]
+                    for uid, _ in sorted(
+                        zip(validator_df.keys(), [validator_df[x][1] for x in validator_df.keys()]),
+                        key=lambda x: x[1],
+                        reverse=True
+                    )
+                ],
+                headers=["UID", "Stake (τ)", "V-Trust"] + [f"{c.namespace}/{c.name} ({c.commit[0:8]})" for c in leaderboard_df if c.incentive],
+                datatype=["number", "number", "number"] + ["number" for c in leaderboard_df if c.incentive],
+                interactive=False,
+                visible=True,
+            )
 
 def restart_space():
     API.restart_space(repo_id=REPO_ID, token=H4_TOKEN)
 
 scheduler = BackgroundScheduler()
-scheduler.add_job(restart_space, "interval", seconds=60 * 10) # restart every 5 minutes
+scheduler.add_job(restart_space, "interval", seconds=60 * 10) # restart every 10 minutes
 scheduler.start()
 
 demo.launch()