Update agent.py

agent.py

@@ -19,7 +19,7 @@ from langchain_openai import ChatOpenAI
 
 from langchain.tools import Tool
 from code_interpreter import CodeInterpreter
-from langchain_chroma import Chroma
+#from langchain_chroma import Chroma
 from langchain_core.messages import AIMessage
 
 interpreter_instance = CodeInterpreter()
@@ -27,6 +27,8 @@ interpreter_instance = CodeInterpreter()
 
 load_dotenv()
 OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
+SUPABASE_URL = os.environ.get("SUPABASE_URL")
+SUPABASE_SERVICE_KEY = os.environ.get("SUPABASE_SERVICE_KEY")
 
 ### ======================================== MATHEMATICAL TOOLS ======================================== ###
 
@@ -232,6 +234,9 @@ execute_code_multilang_tool = Tool(
 
 embeddings = HuggingFaceEmbeddings(model_name="sentence-transformers/all-mpnet-base-v2")
 
+"""
+Using chroma database
+
 vector_store = Chroma(
     collection_name="gaia_dataset",
     embedding_function=embeddings,
@@ -243,25 +248,22 @@ create_retriever_tool = create_retriever_tool(
     name="Question Search",
     description="A tool to retrieve similar questions from a vector store.",
 )
-
 """
+
+# Using supabase database
 # build a retriever
-embeddings = HuggingFaceEmbeddings(model_name="sentence-transformers/all-mpnet-base-v2") #  dim=768
-supabase: Client = create_client(
-    os.environ.get("SUPABASE_URL"), 
-    os.environ.get("SUPABASE_SERVICE_KEY"))
+supabase: Client = create_client(SUPABASE_URL, SUPABASE_SERVICE_KEY)
 vector_store = SupabaseVectorStore(
+    embedding=embeddings,
     client=supabase,
-    embedding= embeddings,
-    table_name="documents",
-    query_name="match_documents_langchain",
+    table_name="gaia_dataset",
+    query_name="match_documents",
 )
 create_retriever_tool = create_retriever_tool(
     retriever=vector_store.as_retriever(),
     name="Question Search",
     description="A tool to retrieve similar questions from a vector store.",
 )
-"""
 
 
 # load the system prompt from the file