Add index and load index

app.py

@@ -2,33 +2,28 @@ import gradio as gr
 import os
 import openai
 
-from llama_index.core import VectorStoreIndex, SimpleDirectoryReader
+from llama_index.core import VectorStoreIndex, StorageContext, load_index_from_storage
 from llama_index.embeddings.huggingface import HuggingFaceEmbedding
 from llama_index.core import Settings
 
-import logging
-
-# Configure logging
-logging.basicConfig(
-    level=logging.INFO,  # Set the logging level
-    format='%(asctime)s - %(levelname)s - %(message)s',  # Define the log format
-    handlers=[
-        logging.StreamHandler()  # Output logs to the console
-    ]
-)
-
 
 openai.api_key = os.environ['OpenAI_ApiKey']
 Settings.embed_model = HuggingFaceEmbedding(model_name="BAAI/bge-small-en-v1.5")
-logging.info("Start load document.")
 
-documents = SimpleDirectoryReader("data").load_data()
-index = VectorStoreIndex.from_documents(documents)
+
+# documents = SimpleDirectoryReader("data").load_data()
+# index = VectorStoreIndex.from_documents(documents)
+
+persist_dir = "index"
+storage_context = StorageContext.from_defaults(persist_dir=persist_dir)
+index = load_index_from_storage(storage_context)
+
+
 query_engine = index.as_query_engine()
 
 def greet(question):
-    logging.info("execute greet")
-    return question
+
+    return f"Hello, {question} !"
     # return query_engine.query(question)
 
 

index/graph_store.json

@@ -0,0 +1 @@
+{"graph_dict": {}}

index/image__vector_store.json

@@ -0,0 +1 @@
+{"embedding_dict": {}, "text_id_to_ref_doc_id": {}, "metadata_dict": {}}

index/index_store.json

@@ -0,0 +1 @@
+{"index_store/data": {"4e7cd1ca-e62a-4af3-8ea9-6197ea6b3662": {"__type__": "vector_store", "__data__": "{\"index_id\": \"4e7cd1ca-e62a-4af3-8ea9-6197ea6b3662\", \"summary\": null, \"nodes_dict\": {\"3131c6df-2315-4628-83d2-c5347982091d\": \"3131c6df-2315-4628-83d2-c5347982091d\", \"f55ed663-7eba-47c5-9a96-0394fe3b00d7\": \"f55ed663-7eba-47c5-9a96-0394fe3b00d7\", \"ee8342e5-d7ad-43a9-a8ad-964931ab1488\": \"ee8342e5-d7ad-43a9-a8ad-964931ab1488\", \"0b256d01-b2cd-4070-ac36-bf2324094d9d\": \"0b256d01-b2cd-4070-ac36-bf2324094d9d\", \"e0eeb897-ee78-45da-b36e-8ec2a797ed57\": \"e0eeb897-ee78-45da-b36e-8ec2a797ed57\", \"28c3b90b-009b-449f-bae4-007afaa10728\": \"28c3b90b-009b-449f-bae4-007afaa10728\", \"5e97a5f5-989b-4ed6-873e-1946996a913a\": \"5e97a5f5-989b-4ed6-873e-1946996a913a\", \"b5fbe526-cdd0-4cd2-bcbb-b86ffb12f939\": \"b5fbe526-cdd0-4cd2-bcbb-b86ffb12f939\", \"ac2d2cf6-bf7c-466d-9b6e-32015b0429b0\": \"ac2d2cf6-bf7c-466d-9b6e-32015b0429b0\", \"09a4fb1e-0b28-43d0-9c39-a004ebdb044b\": \"09a4fb1e-0b28-43d0-9c39-a004ebdb044b\", \"9f41ebd9-e999-4050-b586-2f1a56890645\": \"9f41ebd9-e999-4050-b586-2f1a56890645\", \"5934fe54-9e96-4dda-885a-a6fdeb384d03\": \"5934fe54-9e96-4dda-885a-a6fdeb384d03\", \"45a736ab-8aab-4eae-a93e-95feb2b194ec\": \"45a736ab-8aab-4eae-a93e-95feb2b194ec\", \"336978fd-5248-4a6b-a9ba-32875908e65f\": \"336978fd-5248-4a6b-a9ba-32875908e65f\", \"f496a636-8bd2-4a21-bfa2-5802876e6c83\": \"f496a636-8bd2-4a21-bfa2-5802876e6c83\", \"22e28c69-7aaa-4f26-b50b-bc365d47c351\": \"22e28c69-7aaa-4f26-b50b-bc365d47c351\", \"c93e8d18-315e-4d14-bdfb-fdca5329642d\": \"c93e8d18-315e-4d14-bdfb-fdca5329642d\", \"848d7e00-67f7-47b0-b3a9-75dd079637b6\": \"848d7e00-67f7-47b0-b3a9-75dd079637b6\", \"af8acf9f-5c05-4b10-bd1f-e31b292c71dc\": \"af8acf9f-5c05-4b10-bd1f-e31b292c71dc\", \"5226d7a0-fe10-4da3-8577-645b953b4be0\": \"5226d7a0-fe10-4da3-8577-645b953b4be0\", \"80696086-4684-44bb-b23c-67bd85d5ad46\": \"80696086-4684-44bb-b23c-67bd85d5ad46\", \"5394d9ec-33fa-4a6a-a23c-18ad921ccbd2\": \"5394d9ec-33fa-4a6a-a23c-18ad921ccbd2\", \"bb25bcad-b90d-472e-8468-c62fd7e36ed3\": \"bb25bcad-b90d-472e-8468-c62fd7e36ed3\", \"4a16a820-13ab-4c70-b352-6892bef6d08f\": \"4a16a820-13ab-4c70-b352-6892bef6d08f\", \"2dad1c5d-7f66-4f45-8815-0a860af8f5d5\": \"2dad1c5d-7f66-4f45-8815-0a860af8f5d5\", \"b08c7f53-814b-4369-9775-71ec94a116b2\": \"b08c7f53-814b-4369-9775-71ec94a116b2\", \"d4c20047-601c-49a1-b080-b33c53454eaf\": \"d4c20047-601c-49a1-b080-b33c53454eaf\", \"c58d008d-37d4-4fac-a8ab-da4a0458f8bb\": \"c58d008d-37d4-4fac-a8ab-da4a0458f8bb\", \"382b55a2-fa12-4dc7-a574-0c52588b2d9c\": \"382b55a2-fa12-4dc7-a574-0c52588b2d9c\", \"9cf12463-1b52-4525-a213-213e62dfd82b\": \"9cf12463-1b52-4525-a213-213e62dfd82b\", \"e93da613-60fa-4f4b-b2d2-006ec09dfdce\": \"e93da613-60fa-4f4b-b2d2-006ec09dfdce\", \"74f5a0b3-1808-440d-b7b2-b2d00427c8a9\": \"74f5a0b3-1808-440d-b7b2-b2d00427c8a9\", \"6f6e2e53-f402-42ee-8ed1-8f0e690c041c\": \"6f6e2e53-f402-42ee-8ed1-8f0e690c041c\", \"81bf4a90-a50d-44c2-b799-2daf80f372b3\": \"81bf4a90-a50d-44c2-b799-2daf80f372b3\", \"da5f3876-f023-4153-86b7-aef735861b0b\": \"da5f3876-f023-4153-86b7-aef735861b0b\", \"392db685-752b-4c56-859c-168e49e3f590\": \"392db685-752b-4c56-859c-168e49e3f590\", \"6eabd896-1ea6-4e16-9a1e-d2d8af9521db\": \"6eabd896-1ea6-4e16-9a1e-d2d8af9521db\", \"8f031c9d-5153-40a4-8acd-798b21a56f3f\": \"8f031c9d-5153-40a4-8acd-798b21a56f3f\", \"b534d3c1-615c-43ce-a4b2-554ed6e0ca05\": \"b534d3c1-615c-43ce-a4b2-554ed6e0ca05\", \"dba581ca-2537-486e-9b4a-8b66a0c79bf7\": \"dba581ca-2537-486e-9b4a-8b66a0c79bf7\", \"898f5a4f-e00f-4f89-82fe-cf17223e65a3\": \"898f5a4f-e00f-4f89-82fe-cf17223e65a3\", \"a72f727d-9fee-402c-86bb-18007efef950\": \"a72f727d-9fee-402c-86bb-18007efef950\", \"9af60375-3bba-482d-a794-a64492da867f\": \"9af60375-3bba-482d-a794-a64492da867f\", \"5a469435-6abf-4b42-89be-df23ceb9a322\": \"5a469435-6abf-4b42-89be-df23ceb9a322\", \"fc0c3388-efa0-46c3-a93c-fbf38e16199c\": \"fc0c3388-efa0-46c3-a93c-fbf38e16199c\", \"0ccf7155-0764-48d9-9f8f-d639902c1f3b\": \"0ccf7155-0764-48d9-9f8f-d639902c1f3b\", \"b3a222f7-243f-4c84-b35d-abf9a1f980c9\": \"b3a222f7-243f-4c84-b35d-abf9a1f980c9\", \"69feea14-fee2-4511-a3e8-857f63d1affd\": \"69feea14-fee2-4511-a3e8-857f63d1affd\", \"fe46efd5-0b1a-4852-933f-b533e9f27406\": \"fe46efd5-0b1a-4852-933f-b533e9f27406\", \"ee9c12da-5548-47ca-b2f2-02cf433d8194\": \"ee9c12da-5548-47ca-b2f2-02cf433d8194\"}, \"doc_id_dict\": {}, \"embeddings_dict\": {}}"}}}