re-add vector provisioning details to readme

README.md

@@ -87,6 +87,56 @@ where:
   which Azure deployment to use in place of each model you wish to be used.
 
 
+### Provisioning vector services
+
+The vector services of the plugin allow certain AI-based features to perform semantic search to improve the responses given by LLMs. Configuration is in roughly three parts:
+
+- 'global' vector settings:
+  - `enabled` - whether to enable or disable vector services overall
+  - `model` - the name of the model to use to calculate embeddings for searches. This must match the model used when storing the data, or the embeddings will be meaningless.
+- 'embedding' vector settings (`embed`):
+  - `type` - the type of embedding service, either `openai` or `grafana/vectorapi` to use Grafana's own vector API.
+  - `openai`, if `type` is `openai`, with keys:
+    - `url` - the URL to the OpenAI instance.
+  - `grafanaVectorAPI` - custom settings for OpenAI embeddings, with keys:
+    - `url` - the URL to the OpenAI instance.
+    - `authType` - the type of authentication to use, either `no-auth` or `basic-auth`.
+    - `basicAuthUser` - the username to use if `authType` is `basic-auth`.
+- 'store' vector settings (`store`):
+  - `type` - the type of vector store to connect to, either `qdrant` to use [Qdrant](https://qdrant.tech) or `grafana/vectorapi` to use Grafana's own vector API.
+  - `qdrant`, if `type` is `qdrant`, with keys:
+    - `address` - the address of the Qdrant server. Note that this uses a gRPC connection.
+    - `secure` - boolean, whether to use a secure connection. If you're using a secure connection you can set the `qdrantApiKey` field in `secureJsonData` to provide an API key with each request.
+  - `grafanaVectorAPI`, if `type` is `grafana/vectorapi`, with keys:
+    - `url` - the URL of the Grafana VectorAPI instance.
+    - `authType` - the type of authentication to use, either `no-auth` or `basic-auth`.
+    - `basicAuthUser` - the username to use if `authType` is `basic-auth`.
+
+**Qdrant example**
+
+```yaml
+apiVersion: 1
+
+apps:
+  - type: 'grafana-llm-app'
+    disabled: false
+    jsonData:
+      vector: 
+        enabled: true
+        model: text-embedding-ada-002
+        embed:
+          type: openai
+        store:
+          type: qdrant
+          qdrant:
+            address: localhost:6334
+            secure: true
+    secureJsonData:
+      openAIKey: $OPENAI_API_KEY
+      vectorStoreBasicAuthPassword: $STORE_PASSWORD
+      vectorEmbedderBasicAuthPassword: $EMBEDDER_PASSWORD 
+```
+
 ## Adding LLM features to your plugin or Grafana core
 
 To make use of this plugin when adding LLM-based features, you can use the helper functions in the `@grafana/experimental` package.