Include pre-built index

Arize-ai · Jan 26, 2024 · 1998dc8 · 1998dc8
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diff --git a/python/examples/llama-index/README.md b/python/examples/llama-index/README.md
@@ -12,14 +12,6 @@ Open [http://localhost:3000](http://localhost:3000) with your browser to see the
 
 ## Getting Started with Docker-Compose
 
-Generate a Llama Index vector store index:
-
-```
-cd ./backend
-python app/engine/generate.py
-cd ..
-```
-
 Ensure that Docker is installed and running. Run the command `docker compose up` to spin up services for the frontend, backend, and Phoenix. Once those services are running, open [http://localhost:3000](http://localhost:3000) to use the chat interface. When you're finished, run `docker compose down` to spin down the services.
 
 Traces can be viewed using the [Phoenix UI](http://localhost:6006).

diff --git a/python/examples/llama-index/backend/.gitignore b/python/examples/llama-index/backend/.gitignore
@@ -1,3 +1,2 @@
 __pycache__
-storage
 .env
diff --git a/python/examples/llama-index/backend/storage/default__vector_store.json b/python/examples/llama-index/backend/storage/default__vector_store.json
diff --git a/python/examples/llama-index/backend/storage/docstore.json b/python/examples/llama-index/backend/storage/docstore.json
diff --git a/python/examples/llama-index/backend/storage/graph_store.json b/python/examples/llama-index/backend/storage/graph_store.json
@@ -0,0 +1 @@
+{"graph_dict": {}}
diff --git a/python/examples/llama-index/backend/storage/image__vector_store.json b/python/examples/llama-index/backend/storage/image__vector_store.json
@@ -0,0 +1 @@
+{"embedding_dict": {}, "text_id_to_ref_doc_id": {}, "metadata_dict": {}}
diff --git a/python/examples/llama-index/backend/storage/index_store.json b/python/examples/llama-index/backend/storage/index_store.json
@@ -0,0 +1 @@
+{"index_store/data": {"9b5c5746-394e-41e2-b776-29b28b1abaac": {"__type__": "vector_store", "__data__": "{\"index_id\": \"9b5c5746-394e-41e2-b776-29b28b1abaac\", \"summary\": null, \"nodes_dict\": {\"24e6e695-c6e3-4199-9560-ee75c4eaa03c\": \"24e6e695-c6e3-4199-9560-ee75c4eaa03c\", \"ab1b5f6f-9fe4-486a-9b5b-6e4963cab437\": \"ab1b5f6f-9fe4-486a-9b5b-6e4963cab437\", \"7433534b-0d0a-4e39-b6fc-20b29fed1895\": \"7433534b-0d0a-4e39-b6fc-20b29fed1895\", \"11952fef-4a9b-422c-8d83-81ae3b0b6385\": \"11952fef-4a9b-422c-8d83-81ae3b0b6385\", \"c5335491-1f31-4fb9-a561-fbf5ca9b4772\": \"c5335491-1f31-4fb9-a561-fbf5ca9b4772\", \"365a56d1-abd3-44c6-a07a-e1486a92642c\": \"365a56d1-abd3-44c6-a07a-e1486a92642c\", \"f29577b7-d551-46d4-9763-c99ab3eef46e\": \"f29577b7-d551-46d4-9763-c99ab3eef46e\", \"f80116a5-dac6-4d23-97fb-8dea02dbfc6e\": \"f80116a5-dac6-4d23-97fb-8dea02dbfc6e\"}, \"doc_id_dict\": {}, \"embeddings_dict\": {}}"}}}
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		@@ -0,0 +1 @@
		{"embedding_dict": {}, "text_id_to_ref_doc_id": {}, "metadata_dict": {}}
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		@@ -0,0 +1 @@
		{"index_store/data": {"9b5c5746-394e-41e2-b776-29b28b1abaac": {"__type__": "vector_store", "__data__": "{\"index_id\": \"9b5c5746-394e-41e2-b776-29b28b1abaac\", \"summary\": null, \"nodes_dict\": {\"24e6e695-c6e3-4199-9560-ee75c4eaa03c\": \"24e6e695-c6e3-4199-9560-ee75c4eaa03c\", \"ab1b5f6f-9fe4-486a-9b5b-6e4963cab437\": \"ab1b5f6f-9fe4-486a-9b5b-6e4963cab437\", \"7433534b-0d0a-4e39-b6fc-20b29fed1895\": \"7433534b-0d0a-4e39-b6fc-20b29fed1895\", \"11952fef-4a9b-422c-8d83-81ae3b0b6385\": \"11952fef-4a9b-422c-8d83-81ae3b0b6385\", \"c5335491-1f31-4fb9-a561-fbf5ca9b4772\": \"c5335491-1f31-4fb9-a561-fbf5ca9b4772\", \"365a56d1-abd3-44c6-a07a-e1486a92642c\": \"365a56d1-abd3-44c6-a07a-e1486a92642c\", \"f29577b7-d551-46d4-9763-c99ab3eef46e\": \"f29577b7-d551-46d4-9763-c99ab3eef46e\", \"f80116a5-dac6-4d23-97fb-8dea02dbfc6e\": \"f80116a5-dac6-4d23-97fb-8dea02dbfc6e\"}, \"doc_id_dict\": {}, \"embeddings_dict\": {}}"}}}