Update app.py

app.py

@@ -69,8 +69,9 @@ file_extractor = {
 
 # Embedding model and index initialization (to be populated by uploaded files)
 # embed_model = HuggingFaceEmbedding(model_name="BAAI/bge-small-en-v1.5")   ## Works good
-embed_model = HuggingFaceEmbedding(model_name="BAAI/bge-large-en")    ## works good
-embed_model = HuggingFaceEmbedding(model_name="NeuML/pubmedbert-base-embeddings")
+embed_model1 = HuggingFaceEmbedding(model_name="BAAI/bge-large-en")    ## works good
+embed_model2 = HuggingFaceEmbedding(model_name="NeuML/pubmedbert-base-embeddings")
+embed_model = embed_model1+embed_model2
 # sentence-transformers/distilbert-base-nli-mean-tokens
 # BAAI/bge-large-en
 # embed_model = HuggingFaceEmbedding(model_name="sentence-transformers/all-MiniLM-L6-v2")
@@ -106,7 +107,10 @@ def respond(message, history):
         # Initialize the LLM with the selected model
         llm = HuggingFaceInferenceAPI(
             model_name=selected_model_name,
-            maxTokens = 4096
+            contextWindow = 4096,
+            maxTokens = 4096,
+            temperature=0.7,
+            topP=0.95,
             # token=os.getenv("TOKEN")
         )