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import json
import numpy as np
from tqdm import tqdm
from pymilvus import connections, Collection
connections.connect("default", host="127.0.0.1", port="19530")
col = Collection("sumobot_states")
def encode_state(state_str):
# Parse numeric values from your formatted string
parts = dict(item.split('=') for item in state_str.strip('.').split(', '))
return np.array([
float(parts["AngleToEnemy"]) / 180.0, # normalize angle
float(parts["AngleToEnemyScore"]),
float(parts["DistanceToEnemyScore"]),
float(parts["NearBorderArenaScore"]),
float(parts["FacingToArena"]),
], dtype=np.float32)
BATCH_SIZE = 5000
DATA_PATH = "cleaned_dataset.jsonl"
batch_vecs, batch_actions = [], []
with open(DATA_PATH, "r") as f:
for line in tqdm(f, desc="Reading dataset"):
item = json.loads(line)
vec = encode_state(item["state"])
batch_vecs.append(vec.tolist())
batch_actions.append(item["action"])
if len(batch_vecs) >= BATCH_SIZE:
col.insert([batch_vecs, batch_actions])
batch_vecs, batch_actions = [], []
# Insert remainder
if batch_vecs:
col.insert([batch_vecs, batch_actions])
col.flush()
print("✅ All data inserted & flushed to Milvus.")
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