use google embeddings and add cache clearance feature

app.py

@@ -23,6 +23,7 @@ llm_svc = LLMService(logger, config.SYSTEM_PROMPT, store.get_chroma_instance().a
 def respond(user_input, history):
     if user_input == "clear_chat_history_aisdb_override":
         llm_svc.store={}
+        return "Memory Cache cleared"
     response = llm_svc.conversational_rag_chain().invoke(
         {"input": user_input},
         config={"configurable": {"session_id": "abc"}},
@@ -32,12 +33,6 @@ def respond(user_input, history):
 
 if __name__ == '__main__':
     logging.info("Starting AIVIz Bot")
+    chatbot = gr.Chatbot(placeholder="<strong>AISDb Chatbot</strong><br>Ask Me Anything")
 
-    # Using ChatInterface to create the chatbot interface
-    chat_interface = gr.ChatInterface(
-        fn=respond,
-        title="AISDb Bot",
-        description="LLM's are prone to hallucinations"
-    )
-
-    chat_interface.launch(share=True)
+    gr.ChatInterface(fn=respond, type="messages",title="AISDb ChatBot", chatbot=chatbot).launch(share=True)

stores/chroma.py

@@ -5,7 +5,7 @@ from langchain_chroma import Chroma
 class ChromaDB:
     def __init__(self, embeddings):
         self._persistent_directory = "embeddings"
-        model_name = "sentence-transformers/all-mpnet-base-v2"
+        model_name = "models/text-embedding-004"
         model_kwargs = {'device': 'cpu'}
         encode_kwargs = {'normalize_embeddings': False}
         self.embeddings = embeddings