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whatscooking-advisor

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Pash1986 commited on Feb 11

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@@ -18,7 +18,7 @@ It uses OpenAI small text embeddings (256 dimesnsions) to query the database for
 ## How to setup your own
 1. [Create an Atlas cluter](https://www.mongodb.com/docs/atlas/tutorial/deploy-free-tier-cluster/) (free clusters are available)
-2. Load the [dataset](https://huggingface.co/datasets/AIatMongoDB/whatscooking.restaurants) using the `ingest/ingest.py` with your connection string.
 3. Deploy the relevant [Vector Index](https://www.mongodb.com/docs/atlas/atlas-vector-search/vector-search-tutorial/#create-the-atlas-vector-search-index) on `whatscooking.smart_trips` aggregated collection "name" : `vector_index`.
  ```
  {

 ## How to setup your own
 1. [Create an Atlas cluter](https://www.mongodb.com/docs/atlas/tutorial/deploy-free-tier-cluster/) (free clusters are available)
+2. Load the [dataset](https://huggingface.co/datasets/AIatMongoDB/whatscooking.restaurants) using the `ingest.py` [script](https://huggingface.co/datasets/AIatMongoDB/whatscooking.restaurants#ingest-data) with your connection string.
 3. Deploy the relevant [Vector Index](https://www.mongodb.com/docs/atlas/atlas-vector-search/vector-search-tutorial/#create-the-atlas-vector-search-index) on `whatscooking.smart_trips` aggregated collection "name" : `vector_index`.
  ```
  {