added model

requirements.txt

@@ -1,5 +1,6 @@
-streamlit>=1.28
+# requirements.txt
+streamlit>=1.33
+torch>=2.3          # adjust to whatever you trained with
+scipy               # for Spearman correlation in p1p1
 requests
-huggingface_hub>=0.23      # if you pull the model from the Hub
-joblib                      # if you pickle weights
-scrython    
+huggingface_hub>=0.23

src/draft_model.py

@@ -0,0 +1,60 @@
+from pathlib import Path
+import json
+import torch
+from typing import List, Dict
+
+from huggingface_hub import hf_hub_download
+
+from src.models.winrate_model import Winrate_Model
+from src.training import train_mlp
+from src.utils import utils
+
+
+MODEL_REPO = "TimoBertram/MTG_Model_FIN/"
+CFG_FILE = "config.json"
+MODEL_FILE = "network.pt"
+
+
+DATA_REPO = "TimoBertram/MTG_Drafting_Dataset/"
+CARD_FILE = "cards_eoe.json"
+ENCODING_FILE = "card_encodings.pt"
+
+class DraftModel:
+    def __init__(self, model_path: str):
+        self.device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+
+        cfg_path = hf_hub_download(
+            repo_id=MODEL_REPO, filename=CFG_FILE, repo_type="model"
+        )
+        weight_path = hf_hub_download(
+            repo_id=MODEL_REPO, filename=MODEL_FILE, repo_type="model"
+        )
+
+        # ---- load network ---------------------------------------------------
+        cfg = open(cfg_path, "r")
+        cfg.pop("name", None)
+
+        self.net = train_mlp.MLP_CrossAttention(**cfg).to(self.device)
+        self.net.load_state_dict(torch.load(Path(model_path) / "network.pt", map_location=self.device))
+        self.net.eval()
+
+        # ---- embeddings – one-time load ------------------------------------
+        self.embed_dict = utils.get_embedding_dict(
+            hf_hub_download(repo_id=DATA_REPO, filename=ENCODING_FILE, repo_type="dataset"),
+            add_nontransformed=True
+        )
+
+    # --------------------------------------------------------------------- #
+    # Public API expected by streamlit_app.py                               #
+    # --------------------------------------------------------------------- #
+    @torch.no_grad()
+    def predict(self, pack: List[Dict], picks: List[Dict], deck: List[Dict]) -> Dict:
+        names = [c["name"] for c in pack]
+
+        def embed(name):  # helper
+            return utils.get_card_embeddings((name,), embedding_dict=self.embed_dict)[0]
+
+        card_t = torch.stack([embed(n) for n in names]).unsqueeze(0).to(self.device)
+        deck_t = torch.zeros((1, 45, self.emb_size), device=self.device)
+
+        return torch.softmax(self.net(card_t, deck_t), dim=1).squeeze(0).cpu().numpy().tolist()

src/streamlit_app.py

@@ -22,19 +22,8 @@ from typing import Dict, List
 import requests
 import streamlit as st
 
-# -----------------------------------------------------------------------------
-# Disable telemetry write‑outs (avoids PermissionError: /.streamlit on Spaces)
-# -----------------------------------------------------------------------------
-try:
-    from streamlit.runtime.metrics_util import disable_gather_usage_stats
+from draft_model import DraftModel
 
-    disable_gather_usage_stats()
-except Exception:
-    st.set_option("browser.gatherUsageStats", False)
-
-# -----------------------------------------------------------------------------
-# 0. Constants & helpers
-# -----------------------------------------------------------------------------
 
 SUPPORTED_SETS_PATH = Path("supported_sets.txt")
 st.write("Running Streamlit", st.__version__)
@@ -49,14 +38,9 @@ def get_supported_sets(path: Path = SUPPORTED_SETS_PATH) -> List[str]:
     return []
 
 
-# -----------------------------------------------------------------------------
-# 1. Model & ranking stubs
-# -----------------------------------------------------------------------------
-
 @st.cache_resource(show_spinner="Loading draft model …")
 def load_model():
-    # 🔄 Replace with your own pipeline or `hf_hub_download` call
-    return None
+    return DraftModel() 
 
 
 @st.cache_data(show_spinner="Calculating card rankings …")