added persistent_directory to chroma client

app.py

@@ -20,6 +20,7 @@ import os
 dotenv.load_dotenv()
 config = ConfigParser()
 config.read('innovation_pathfinder_ai/config.ini')
+persist_directory = config.get('main', 'VECTOR_DATABASE_LOCATION')
 
 logger = logger.get_console_logger("app")
 
@@ -28,7 +29,9 @@ app = FastAPI()
 def initialize_chroma_db() -> Chroma:
     collection_name = config.get('main', 'CONVERSATION_COLLECTION_NAME')
     
-    client = chromadb.PersistentClient()
+    client = chromadb.PersistentClient(
+        path=persist_directory
+        )
     
     collection = client.get_or_create_collection(
     name=collection_name,

innovation_pathfinder_ai/knowledge_base/placeholder.txt

@@ -0,0 +1 @@
+this file is needed

innovation_pathfinder_ai/structured_tools/structured_tools.py

@@ -37,6 +37,7 @@ from configparser import ConfigParser
 
 config = ConfigParser()
 config.read('innovation_pathfinder_ai/config.ini')
+persist_directory = config.get('main', 'VECTOR_DATABASE_LOCATION')
 
 @tool
 def memory_search(query:str) -> str:
@@ -44,7 +45,7 @@ def memory_search(query:str) -> str:
         This is your primary source to start your search with checking what you already have learned from the past, before going online."""
     # Since we have more than one collections we should change the name of this tool
     client = chromadb.PersistentClient(
-    # path=persist_directory,
+     path=persist_directory,
     )
     
     collection_name = config.get('main', 'CONVERSATION_COLLECTION_NAME')
@@ -70,7 +71,7 @@ def knowledgeBase_search(query:str) -> str:
     """Search the internal knowledge base for research papers and relevent chunks"""
     # Since we have more than one collections we should change the name of this tool
     client = chromadb.PersistentClient(
-    # path=persist_directory,
+     path=persist_directory,
     )
     
     collection_name="ArxivPapers"
@@ -144,7 +145,7 @@ def embed_arvix_paper(paper_id:str) -> None:
     paper.download_pdf(dirpath=pdf_directory, filename=f"{number_without_period}.pdf")
     
     client = chromadb.PersistentClient(
-    # path=persist_directory,
+     path=persist_directory,
     )
     
     collection_name="ArxivPapers"

innovation_pathfinder_ai/vector_store/chroma_vector_store.py

@@ -31,9 +31,7 @@ import os
 dotenv.load_dotenv()
 config = ConfigParser()
 config.read('innovation_pathfinder_ai/config.ini')
-
-VECTOR_DATABASE_LOCATION = config.get('main', 'VECTOR_DATABASE_LOCATION')
-
+persist_directory = config.get('main', 'VECTOR_DATABASE_LOCATION')
 
 
 def read_markdown_file(file_path: str) -> str:
@@ -91,7 +89,7 @@ def add_markdown_to_collection(
     splits = text_splitter.split_documents(md_header_splits)
 
     client = chromadb.PersistentClient(
-        # path=persist_directory,
+         path=persist_directory,
         )
 
 
@@ -176,7 +174,7 @@ def add_pdf_to_vector_store(
         
     
     client = chromadb.PersistentClient(
-    # path=persist_directory,
+     path=persist_directory,
     )
     
     collection = client.get_or_create_collection(
@@ -210,7 +208,7 @@ if __name__ == "__main__":
     collection_name="ArxivPapers"
     
     client = chromadb.PersistentClient(
-    # path=persist_directory,
+     path=persist_directory,
     )
     
     # delete existing collection
@@ -238,7 +236,7 @@ if __name__ == "__main__":
     
     #create the cliient using Chroma's library
     client = chromadb.PersistentClient(
-    # path=persist_directory,
+     path=persist_directory,
     )
     
     # This is an example collection name