Update gradio_embedding.py

gradio_embedding.py

@@ -1,37 +1,37 @@
-from langchain_community.document_loaders.text import TextLoader
-from langchain_community.vectorstores import Chroma
-from langchain_text_splitters import RecursiveCharacterTextSplitter
-from setup import *
-
-# Use a relative path:
-file = "./data/Amazon_sagemaker_Faq.txt"  # Assuming you have a data folder in your project
-
-loader = TextLoader(file_path=file)
-pages = []
-for page in loader.load():
-    pages.append(page)
-
-docs = loader.load()
-
-text_splitter = RecursiveCharacterTextSplitter(
-    chunk_size=500,
-    chunk_overlap=50,
-    add_start_index=True,
-    separators=["\n", "\n\n"]
-)
-
-all_splits = text_splitter.split_documents(docs)
-print(f"Split blog post into {len(all_splits)} sub-documents.")
-
-# Instead of Windows absolute path for persistence:
-# persist_directory = "D:\\Education\\AI\\AI-Agents\\Agentic-RAG"
-
-# Use a relative path:
-persist_directory = "./chroma_db"  # This will create a chroma_db folder in your app's directory
-
-vector_store = Chroma.from_documents(
-    documents=all_splits,
-    collection_name='sagemaker-chroma',
-    persist_directory=persist_directory,
-    embedding=embeddings
+from langchain_community.document_loaders.text import TextLoader
+from langchain_community.vectorstores import Chroma
+from langchain_text_splitters import RecursiveCharacterTextSplitter
+from setup import *
+
+# Use a relative path:
+file = "Amazon_sagemaker_Faq.txt"  # Assuming you have a data folder in your project
+
+loader = TextLoader(file_path=file)
+pages = []
+for page in loader.load():
+    pages.append(page)
+
+docs = loader.load()
+
+text_splitter = RecursiveCharacterTextSplitter(
+    chunk_size=500,
+    chunk_overlap=50,
+    add_start_index=True,
+    separators=["\n", "\n\n"]
+)
+
+all_splits = text_splitter.split_documents(docs)
+print(f"Split blog post into {len(all_splits)} sub-documents.")
+
+# Instead of Windows absolute path for persistence:
+# persist_directory = "D:\\Education\\AI\\AI-Agents\\Agentic-RAG"
+
+# Use a relative path:
+persist_directory = "./chroma_db"  # This will create a chroma_db folder in your app's directory
+
+vector_store = Chroma.from_documents(
+    documents=all_splits,
+    collection_name='sagemaker-chroma',
+    persist_directory=persist_directory,
+    embedding=embeddings
 )