Update model type in embedding generation to 'text-embedding-3-small' for consistency

main.py

@@ -114,7 +114,7 @@ def generate_embedding(model, text: str, model_type: str) -> List[float]:
             convert_to_tensor=True
         )
         embedding = np.array(t.Tensor.cpu(chunk_embedding)).tolist()
-    elif model_type == "openai":
+    elif model_type == "text-embedding-3-small":
         response = model.embeddings.create(
             input=text,
             model="text-embedding-3-small"
@@ -128,7 +128,7 @@ def generate_embedding(model, text: str, model_type: str) -> List[float]:
 def search_query(client, st_model, query: str, df: pd.DataFrame, n: int = 1) -> List[Dict]:
     # Generate embeddings for both models
     mpnet_embedding = generate_embedding(st_model, query, "all-mpnet-base-v2")
-    openai_embedding = generate_embedding(client, query, "openai")
+    openai_embedding = generate_embedding(client, query, "text-embedding-3-small")
     
     # Calculate similarities
     df['mpnet_similarities'] = df.all_mpnet_embedding.apply(
@@ -156,7 +156,7 @@ def search_query(client, st_model, query: str, df: pd.DataFrame, n: int = 1) ->
         results.append({
             "text": row["ext"],
             "similarity": float(row["openai_similarities"]),
-            "model_type": "openai"
+            "model_type": "text-embedding-3-small"
         })
     
     return results