Update app.py

app.py

@@ -68,9 +68,9 @@ file_extractor = {
 }
 
 # Embedding model and index initialization (to be populated by uploaded files)
-# embed_model = HuggingFaceEmbedding(model_name="BAAI/bge-small-en-v1.5")
-embed_model = HuggingFaceEmbedding(model_name="BAAI/bge-large-en")
-
+# 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")
 # sentence-transformers/distilbert-base-nli-mean-tokens
 # BAAI/bge-large-en
 # embed_model = HuggingFaceEmbedding(model_name="sentence-transformers/all-MiniLM-L6-v2")
@@ -106,6 +106,7 @@ def respond(message, history):
         # Initialize the LLM with the selected model
         llm = HuggingFaceInferenceAPI(
             model_name=selected_model_name,
+            maxTokens = 4096
             # token=os.getenv("TOKEN")
         )