Upload inference_local.py with huggingface_hub

inference_local.py

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+import json
+import unicodedata
+from llama_cpp import Llama
+
+# ─────────────────────────────────────────────
+# CONFIG
+# ─────────────────────────────────────────────
+GGUF_PATH = "./football-extractor-q4.gguf"
+
+SYSTEM_PROMPT = (
+    "You are a football data extraction assistant. "
+    "Extract structured data from the message and return ONLY a valid JSON array. "
+    "Each object in the array must have exactly these keys: "
+    "league, team_1, team_2, prediction, date, odds. "
+    "If a field is missing, use null. No extra text, no markdown."
+)
+
+# ─────────────────────────────────────────────
+# LOAD MODEL (runs on Mac Metal / CPU)
+# ─────────────────────────────────────────────
+llm = Llama(
+    model_path=GGUF_PATH,
+    n_ctx=2048,        # context window
+    n_gpu_layers=-1,   # offload all layers to Metal GPU
+    verbose=False,
+)
+print("✅ Model loaded")
+
+# ─────────────────────────────────────────────
+# HELPERS
+# ─────────────────────────────────────────────
+def clean_input(text: str) -> str:
+    """Strip bold unicode characters (e.g. Telegram bold)."""
+    return ''.join(
+        c for c in unicodedata.normalize('NFKD', text)
+        if not unicodedata.combining(c)
+    )
+
+def fix_keys(results: list) -> list:
+    """Fix 'match' key → team_1 / team_2 if model returns it."""
+    for item in results:
+        if "match" in item and "team_1" not in item:
+            parts = item.pop("match").split(" - ", 1)
+            item["team_1"] = parts[0].strip() if len(parts) > 0 else None
+            item["team_2"] = parts[1].strip() if len(parts) > 1 else None
+    return results
+
+def normalize(result: list) -> list:
+    keys = ["league", "team_1", "team_2", "prediction", "date", "odds"]
+    if result and not isinstance(result[0], (dict, list)):
+        return [dict(zip(keys, result))]
+    normalized = []
+    for item in result:
+        if isinstance(item, str):
+            try:
+                item = json.loads(item)
+            except:
+                continue
+        if isinstance(item, list):
+            item = dict(zip(keys, item))
+        if isinstance(item, dict):
+            normalized.append(item)
+    return normalized
+
+# ─────────────────────────────────────────────
+# INFERENCE
+# ─────────────────────────────────────────────
+def extract(text: str, debug: bool = False) -> list:
+    text = clean_input(text)
+
+    response = llm.create_chat_completion(
+        messages=[
+            {"role": "system", "content": SYSTEM_PROMPT},
+            {"role": "user",   "content": text},
+        ],
+        temperature=0.0,
+        max_tokens=512,
+        stop=["<|im_end|>", "<|endoftext|>"],
+    )
+
+    raw = response["choices"][0]["message"]["content"].strip()
+
+    if debug:
+        print(f"[raw] {repr(raw)}")
+
+    try:
+        result = json.loads(raw)
+        result = normalize(result if isinstance(result, list) else [result])
+        result = fix_keys(result)
+        return result
+    except json.JSONDecodeError:
+        print(f"[!] Could not parse JSON:\n{raw}")
+        return []
+
+# ─────────────────────────────────────────────
+# TEST
+# ─────────────────────────────────────────────
+if __name__ == "__main__":
+    tests = [
+        # single tip
+        """⚽️ Prediction of the Day ⚽️
+Date: 24/03/2026
+League: Eerste divisie Netherlands
+Match: FC Emmen - SC Cambuur
+Kick off: 20:00 WAT
+✅Over 1.5
+✅Odds @1.13 on BETANO""",
+
+        # multi tip real format
+        """⚽️ 𝐏𝐫𝐞𝐝𝐢𝐜𝐭𝐢𝐨𝐧 𝐨𝐟 𝐭𝐡𝐞 𝐃𝐚𝐲 ⚽️
+𝐃𝐚𝐭𝐞: 24/03/2026
+𝐋𝐞𝐚𝐠𝐮𝐞: League 1 England
+𝐌𝐚𝐭𝐜𝐡: Doncaster Rovers - Port Vale
+𝐊𝐢𝐜𝐤 𝐨𝐟𝐟: 20:45 WAT
+✅Under 3.5
+✅Odds @1.36 on BETANO
+⚽️ 𝗙𝗼𝗼𝘁𝗯𝗮𝗹𝗹 𝗧𝗶𝗽 𝟮 ⚽️
+𝐃𝐚𝐭𝐞: 24/03/2026
+𝐋𝐞𝐚𝐠𝐮𝐞: La Liga
+𝐌𝐚𝐭𝐜𝐡: Real Madrid - Barcelona
+𝐊𝐢𝐜𝐤 𝐨𝐟𝐟: 21:00 WAT
+✅1X
+✅Odds @1.42 on BETANO""",
+
+        # noisy missing date
+        """wow predictions
+MATCH: Juventus VS Napoli
+League: Serie A
+we forecast Over 2.5
+Odds 1.75""",
+    ]
+
+    for i, test in enumerate(tests, 1):
+        print(f"\n{'='*50}")
+        print(f"TEST {i}: {test[:80]}...")
+        result = extract(test)
+        print(json.dumps(result, indent=2, ensure_ascii=False))