Update app.py

app.py

@@ -4,14 +4,12 @@ import typing
 from bittensor.extrinsics.serving import get_metadata
 from dataclasses import dataclass
 import requests
-import wandb
 import math
 import os
 import datetime
 import time
 from dotenv import load_dotenv
 from huggingface_hub import HfApi
-from apscheduler.schedulers.background import BackgroundScheduler
 
 load_dotenv()
 
@@ -76,9 +74,9 @@ def get_tao_price() -> float:
         try:
             return float(requests.get("https://api.kucoin.com/api/v1/market/stats?symbol=TAO-USDT").json()["data"]["last"])
         except:
-                if i == METAGRAPH_RETRIES - 1:
-                    raise
-                time.sleep(METAGRAPH_DELAY_SECS)
+            if i == METAGRAPH_RETRIES - 1:
+                raise
+            time.sleep(METAGRAPH_DELAY_SECS)
         raise RuntimeError()
 
 def get_validator_weights(metagraph: bt.metagraph) -> typing.Dict[int, typing.Tuple[float, int, typing.Dict[int, float]]]:
@@ -112,7 +110,7 @@ def get_subnet_data(subtensor: bt.subtensor, metagraph: bt.metagraph) -> typing.
 
         model_data = None
         try:
-            model_data = ModelData.from_compressed_str(uid, hotkey, chain_str, block, incentive, emission)    
+            model_data = ModelData.from_compressed_str(uid, hotkey, chain_str, block, incentive, emission)
         except:
             continue
 
@@ -121,7 +119,7 @@ def get_subnet_data(subtensor: bt.subtensor, metagraph: bt.metagraph) -> typing.
 
 def floatable(x) -> bool:
     return (isinstance(x, float) and not math.isnan(x) and not math.isinf(x)) or isinstance(x, int)
-    
+
 def get_float_score(key: str, history) -> typing.Tuple[typing.Optional[float], bool]:
     if key in history:
         data = list(history[key])
@@ -144,32 +142,6 @@ def get_sample(uid, history) -> typing.Optional[typing.Tuple[str, str]]:
             return prompt, response
     return None
 
-def get_scores(uids: typing.List[int]) -> typing.Dict[int, typing.Dict[str, typing.Optional[float | str]]]:
-    api = wandb.Api()
-    runs = list(api.runs(VALIDATOR_WANDB_PROJECT))
-
-    result = {}
-    for run in runs:
-        history = run.history()
-        for uid in uids:
-            if uid in result.keys():
-                continue
-            perplexity, perplexity_fresh = get_float_score(f"perplexity_data.{uid}", history)
-            win_rate, win_rate_fresh = get_float_score(f"win_rate_data.{uid}", history)
-            win_total, win_total_fresh = get_float_score(f"win_total_data.{uid}", history)
-            weight, weight_fresh = get_float_score(f"weight_data.{uid}", history)
-            sample = get_sample(uid, history)
-            result[uid] = {
-                "perplexity": perplexity,
-                "win_rate": win_rate,
-                "win_total": win_total,
-                "weight": weight,
-                "sample": sample,
-                "fresh": perplexity_fresh and win_rate_fresh and win_total_fresh
-            }
-        if len(result.keys()) == len(uids):
-            break
-    return result
 
 def format_score(uid, scores, key) -> typing.Optional[float]:
     if uid in scores:
@@ -192,8 +164,6 @@ tao_price = get_tao_price()
 leaderboard_df = get_subnet_data(subtensor, metagraph)
 leaderboard_df.sort(key=lambda x: x.incentive, reverse=True)
 
-scores = get_scores([x.uid for x in leaderboard_df])
-
 current_block = metagraph.block.item()
 next_update = next_tempo(
     SUBNET_START_BLOCK,
@@ -214,19 +184,6 @@ def get_next_update():
     delta = next_update_time - now
     return f"""<div align="center" style="font-size: larger;">Next reward update: <b>{blocks_to_go}</b> blocks (~{int(delta.total_seconds() // 60)} minutes)</div>"""
 
-def leaderboard_data(show_stale: bool):
-    value = [
-        [
-            f'[{c.namespace}/{c.name} ({c.commit[0:8]})](https://huggingface.co/{c.namespace}/{c.name}/commit/{c.commit})',
-            format_score(c.uid, scores, "win_rate"),
-            format_score(c.uid, scores, "perplexity"),
-            format_score(c.uid, scores, "weight"),
-            c.uid,
-            c.block
-        ] for c in leaderboard_df if scores[c.uid]["fresh"] or show_stale
-    ]
-    return value
-
 demo = gr.Blocks(css=".typewriter {font-family: 'JMH Typewriter', sans-serif;}")
 with demo:
     gr.HTML(FONT)
@@ -240,7 +197,7 @@ with demo:
         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.Accordion("Evaluation Stats"):
         gr.HTML(EVALUATION_HEADER)
 
@@ -251,27 +208,16 @@ with demo:
                     with gr.Tab(f"{entry.namespace}/{entry.name} ({entry.commit[0:8]})"):
                         gr.Chatbot([sample])
 
-        show_stale = gr.Checkbox(label="Show Stale", interactive=True)
-        leaderboard_table = gr.components.Dataframe(
-            value=leaderboard_data(show_stale.value),
-            headers=["Name", "Win Rate", "Perplexity", "Weight", "UID", "Block"],
-            datatype=["markdown", "number", "number", "number", "number", "number"],
-            elem_id="leaderboard-table",
-            interactive=False,
-            visible=True,
-        )
-        gr.HTML(EVALUATION_DETAILS)
-        show_stale.change(leaderboard_data, [show_stale], leaderboard_table)
 
     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
-                    )
+                    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],
@@ -279,11 +225,4 @@ with demo:
             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 * 15) # restart every 15 minutes
-scheduler.start()
-
 demo.launch()