[Bugfix] Fixes broken link in README. Improves naming consistency

datastore/factory.py

@@ -68,7 +68,7 @@ async def get_datastore() -> DataStore:
             )
 
             return ElasticsearchDataStore()
-        case "mongodb":
+        case "mongodb-atlas":
             from datastore.providers.mongodb_atlas_datastore import (
                 MongoDBAtlasDataStore,
             )
@@ -77,5 +77,5 @@ async def get_datastore() -> DataStore:
         case _:
             raise ValueError(
                 f"Unsupported vector database: {datastore}. "
-                f"Try one of the following: llama, elasticsearch, pinecone, weaviate, milvus, zilliz, redis, azuresearch, or qdrant"
+                f"Try one of the following: mongodb-atlas, llama, elasticsearch, pinecone, weaviate, milvus, zilliz, redis, azuresearch, or qdrant"
             )

docs/providers/mongodb/setup.md → docs/providers/mongodb_atlas/setup.md

@@ -89,7 +89,7 @@ You can confirm that the required ones have been set like this:  `assert "MONGOD
 | `MONGODB_DATABASE`    | Database name               | SQUAD                                                                            |
 | `MONGODB_COLLECTION`  | Collection name             | Beyonce                                                                          |
 | `MONGODB_INDEX`       | Search index name           | vector_index                                                                     |
-| `DATASTORE`           | Datastore name              | [must be] mongodb                                                                |
+| `DATASTORE`           | Datastore name              | [must be] mongodb-atlas                                                          |
 | `EMBEDDING_MODEL`     | OpenAI Embedding Model      | text-embedding-3-small                                                           |
 | `EMBEDDING_DIMENSION` | Length of Embedding Vectors | 1536                                                                             |
 

examples/providers/mongodb/semantic-search.ipynb → examples/providers/mongodb_atlas/semantic-search.ipynb

@@ -23,7 +23,7 @@
     "    * Create a MongoDB Atlas cluster.\n",
     "    * Add a Vector Index Search to it.<br><br>\n",
     "\n",
-    "    Begin by following the detailed steps in **[setup.md](https://github.com/caseyclements/chatgpt-retrieval-plugin/blob/mongodb/docs/providers/mongodb/setup.md)**.\n",
+    "    Begin by following the detailed steps in **[setup.md](https://github.com/caseyclements/chatgpt-retrieval-plugin/blob/mongodb/docs/providers/mongodb_atlas/setup.md)**.\n",
     "    Once completed, you will have a running Cluster, with a Database, a Collection, and a Vector Search Index attached to it.\n",
     "\n",
     "    You will also have a number of required environment variables. These need to be available to run this example.\n",
@@ -93,7 +93,7 @@
     "import os\n",
     "required_vars = {'BEARER_TOKEN', 'OPENAI_API_KEY', 'DATASTORE', 'EMBEDDING_DIMENSION', 'EMBEDDING_MODEL',\n",
     "                 'MONGODB_COLLECTION', 'MONGODB_DATABASE', 'MONGODB_INDEX', 'MONGODB_URI'}\n",
-    "assert os.environ[\"DATASTORE\"] == 'mongodb'\n",
+    "assert os.environ[\"DATASTORE\"] == 'mongodb-atlas'\n",
     "missing = required_vars - set(os.environ)\n",
     "if missing:\n",
     "    print(f\"It is strongly recommended to set these additional environment variables. {missing}=\")"
@@ -418,7 +418,7 @@
     "\n",
     "Posting an `upsert` request to the ChatGPT Retrieval Plugin API performs two tasks on the backend. First, it inserts into (or updates) your data in the MONGODB_COLLECTION in the MongoDB Cluster that you setup. Second, Atlas asynchronously begins populating a Vector Search Index on the embedding key. \n",
     "\n",
-    "If you have already created the Collection and a Vector Search Index through the Atlas UI while Setting up MongoDB Atlas Cluster in [setup.md](https://github.com/caseyclements/chatgpt-retrieval-plugin/blob/main/docs/providers/mongodb/setup.md), then indexing will begin immediately.\n",
+    "If you have already created the Collection and a Vector Search Index through the Atlas UI while Setting up MongoDB Atlas Cluster in [setup.md](https://github.com/caseyclements/chatgpt-retrieval-plugin/blob/main/docs/providers/mongodb_atlas/setup.md), then indexing will begin immediately.\n",
     "\n",
     "If you haven't set up the Atlas Vector Search yet, no problem. `upsert` will insert the data. To start indexing, simply go back to the Atlas UI and add a Search Index. This will trigger indexing. Once complete, we can begin semantic queries!\n",
     "\n",

tests/datastore/providers/mongodb_atlas/test_integration.py

@@ -1,7 +1,7 @@
 """Integration Tests of ChatGPT Retrieval Plugin
 with MongoDB Atlas Vector Datastore and OPENAI Embedding model.
 
-As described in docs/providers/mongodb/setup.md, to run this, one must
+As described in docs/providers/mongodb_atlas/setup.md, to run this, one must
 have a running MongoDB Atlas Cluster, and
 provide a valid OPENAI_API_KEY.
 """
@@ -104,7 +104,7 @@ def test_required_vars() -> None:
     """Confirm that the environment has all it needs"""
     required_vars = {'BEARER_TOKEN', 'OPENAI_API_KEY', 'DATASTORE', 'EMBEDDING_DIMENSION', 'EMBEDDING_MODEL',
                      'MONGODB_COLLECTION', 'MONGODB_DATABASE', 'MONGODB_INDEX', 'MONGODB_URI'}
-    assert os.environ["DATASTORE"] == 'mongodb'
+    assert os.environ["DATASTORE"] == 'mongodb-atlas'
     missing = required_vars - set(os.environ)
     assert len(missing) == 0
 

tests/datastore/providers/mongodb_atlas/test_mongodb_datastore.py

@@ -2,10 +2,10 @@
 Integration tests of MongoDB Atlas Datastore.
 
 These tests require one to have a running Cluster, Database, Collection and Atlas Search Index
-as described in docs/providers/mongodb/setup.md.
+as described in docs/providers/mongodb_atlas/setup.md.
 
 One will also have to set the same environment variables. Although one CAN
-use we the same collection and index used in examples/providers/mongodb/semantic-search.ipynb,
+use we the same collection and index used in examples/providers/mongodb_atlas/semantic-search.ipynb,
 these tests will make changes to the data, so you may wish to create another collection.
 If you have run the example notebook, you can reuse with the following.