Delete api_inference.py

api_inference.py

@@ -1,84 +0,0 @@
-# api_inference.py
-import torch
-from transformers import AutoTokenizer, AutoModel, AutoConfig
-from flask import Flask, request, jsonify
-import os, json
-
-app = Flask(__name__)
-
-# === Load Model ===
-MODEL_DIR = os.path.dirname(os.path.abspath(__file__))
-
-print(f"🔍 Loading model from {MODEL_DIR} ...")
-
-try:
-    # --- Register your custom model class ---
-    from transformers.models.auto.modeling_auto import MODEL_MAPPING
-    from snp_universal_embedding import CustomSNPModel
-
-    # Register custom class to handle 'custom_snp' type
-    class DummyConfig(AutoConfig):
-        model_type = "custom_snp"
-
-    MODEL_MAPPING.register(DummyConfig, CustomSNPModel)
-
-    # Load model and tokenizer
-    config = AutoConfig.from_pretrained(MODEL_DIR, trust_remote_code=True)
-    tokenizer = AutoTokenizer.from_pretrained(MODEL_DIR)
-    model = AutoModel.from_pretrained(MODEL_DIR, config=config, trust_remote_code=True)
-    model.eval()
-
-    print("✅ Custom SNP model loaded successfully.")
-except Exception as e:
-    print("❌ Error loading custom model:", e)
-    raise e
-
-
-# === Define Endpoints ===
-@app.route("/")
-def index():
-    return jsonify({
-        "status": "SNP Universal Embedding API running",
-        "endpoints": ["/embed", "/reason"]
-    })
-
-
-@app.route("/embed", methods=["POST"])
-def embed():
-    try:
-        data = request.get_json()
-        text = data.get("text", "")
-        if not text:
-            return jsonify({"error": "No text provided"}), 400
-
-        inputs = tokenizer(text, return_tensors="pt")
-        with torch.no_grad():
-            outputs = model(**inputs)
-            if isinstance(outputs, dict) and "last_hidden_state" in outputs:
-                embedding = outputs["last_hidden_state"].mean(dim=1).squeeze().tolist()
-            else:
-                embedding = outputs.mean(dim=1).squeeze().tolist()
-
-        return jsonify({"embedding": embedding})
-    except Exception as e:
-        return jsonify({"error": str(e)}), 500
-
-
-@app.route("/health")
-def health():
-    return "ok", 200
-
-
-@app.route("/reason", methods=["POST"])
-def reason():
-    data = request.get_json()
-    text = data.get("text", "")
-    return jsonify({
-        "text": text,
-        "reasoning_status": "Feature in development for SNP reasoning structure"
-    })
-
-
-if __name__ == "__main__":
-    port = int(os.environ.get("PORT", 8080))
-    app.run(host="0.0.0.0", port=port)