Update app.py

app.py

@@ -5,8 +5,10 @@ import os
 from google import genai
 from google.genai import types
 import spacy
-
+from sentence_transformers import SentenceTransformer, SimilarityFunction
 from dotenv import load_dotenv
+import numpy as np
+
 
 load_dotenv()
 HF_API_KEY = os.environ["HF_API_KEY"]
@@ -50,6 +52,14 @@ stitched_radiohead_lyrics = stitch_lyrics(radiohead_lyrics)
 stitched_kendrick_lyrics = stitch_lyrics(kendrick_lyrics)
 stitched_grateful_dead_lyrics = stitch_lyrics(grateful_dead_lyrics)
 
+encoder_model = SentenceTransformer('sentence-transformers/all-MiniLM-L6-v2', 
+                                    backend='openvino'
+                                    )
+#radiohead_embeddings = encoder_model.encode(stitched_radiohead_lyrics)
+kendrick_embeddings = encoder_model.encode(stitched_kendrick_lyrics)
+#grateful_dead_embeddings = encoder_model.encode(stitched_grateful_dead_lyrics)
+
+
 # Initialize Hugging Face Inference Client
 client = InferenceClient(#provider="hf-inference",
                           token=HF_API_KEY)
@@ -86,12 +96,19 @@ def chat_with_musician(user_input, history, artist):
     if artist == "Kendrick Lamar":
         #lyric_response = find_most_relevant_lyric(stitched_kendrick_lyrics, 
         #                gemma_response)
-        result = client.sentence_similarity(
-                gemma_response,
-                other_sentences= stitched_kendrick_lyrics,
-                #model="sentence-transformers/all-MiniLM-L6-v2",
-                )
-        lyric_response = stitched_kendrick_lyrics[result["similarity_scores"].index(max(result["similarity_scores"]))]     
+        #result = client.sentence_similarity(
+        #        gemma_response,
+        #        other_sentences= stitched_kendrick_lyrics,
+        #        model="sentence-transformers/all-MiniLM-L6-v2",
+        #        )
+        encoded_gemma = encoder_model.encode(gemma_response)
+        similarity_result = encoder_model.similarity(
+            encoded_gemma,
+            kendrick_embeddings,
+            similarity_function=SimilarityFunction.COSINE,
+        )
+        result_max_index = np.argmax(similarity_result)
+        lyric_response = stitched_kendrick_lyrics[result_max_index]
     if artist == "Google Gemma":
         lyric_response = gemma_response
     return lyric_response