change chroma db path

email_ai.py

@@ -9,7 +9,7 @@ from langchain_core.messages import HumanMessage, SystemMessage
 from langchain_text_splitters import RecursiveCharacterTextSplitter
 from langchain_huggingface import HuggingFaceEmbeddings
 
-from langchain.vectorstores import Chroma
+# from langchain.vectorstores import Chroma
 from langchain.schema.runnable import RunnablePassthrough
 
 # from langchain_openai import ChatOpenAI
@@ -18,6 +18,7 @@ from langchain.prompts import ChatPromptTemplate
 import google.generativeai as genai
 import os
 from dotenv import load_dotenv
+import chromadb
 
 # Load environment variables
 load_dotenv()
@@ -30,8 +31,20 @@ def initialize_conversation():
     
     llm = ChatGoogleGenerativeAI(model="gemini-1.5-flash-latest", api_key=gemini_api_key)
     embeddings_model = HuggingFaceEmbeddings()
-    db = Chroma(persist_directory="/Users/daddy/aimlprojects/email_ai/chroma_langchain_db1", embedding_function=embeddings_model)
-    chroma_retriever = db.as_retriever(search_kwargs={"k":50})
+
+    # client = chromadb.PersistentClient()
+    # Connect to your ChromaDB instance
+    client = chromadb.PersistentClient(path="chroma_langchain_db1")
+
+    # collection_names = client.list_collections()
+
+    # for name in collection_names:
+    #     print(name)
+
+    insurance_collection = client.get_collection(name='langchain', embedding_function=embeddings_model)
+
+    # db = Chroma(persist_directory="/Users/daddy/aimlprojects/email_ai/chroma_langchain_db1", embedding_function=embeddings_model)
+    chroma_retriever = insurance_collection.as_retriever(search_kwargs={"k":50})
 
     return llm, chroma_retriever
 # initialize_conversation()
@@ -72,4 +85,7 @@ def get_chat_model_completions(llm, chroma_retriever, query):
     # print(response.content)
     return response
 # response=get_chat_model_completions(initialize_conversation(), query)
-# print(response.response)
+# print(response.response)
+
+if __name__ == "__main__":
+    initialize_conversation()