Update appsettings for PostgreSQL

webapi/appsettings.json

@@ -23,7 +23,7 @@
   // Default AI service configuration for generating AI responses and embeddings from the user's input.
   // https://platform.openai.com/docs/guides/chat
   // To use Azure OpenAI as the AI completion service:
-  // - Set "Type" to "AzureOpenAI" 
+  // - Set "Type" to "AzureOpenAI"
   // - Set "Endpoint" to the endpoint of your Azure OpenAI instance (e.g., "https://contoso.openai.azure.com")
   // - Set "Key" using dotnet's user secrets (see above)
   //     (i.e. dotnet user-secrets set "AIService:Key" "MY_AZURE_OPENAI_KEY")
@@ -53,12 +53,12 @@
   // - Set Planner:Type to "Sequential" to enable the multi-step SequentialPlanner
   //     Note: SequentialPlanner works best with `gpt-4`. See the "Enabling Sequential Planner" section in webapi/README.md for configuration instructions.
   // - Set Planner:Type to "Stepwise" to enable MRKL style planning
-  // - Set Planner:RelevancyThreshold to a decimal between 0 and 1.0. 
+  // - Set Planner:RelevancyThreshold to a decimal between 0 and 1.0.
   //
   "Planner": {
     "Type": "Sequential",
     // The minimum relevancy score for a function to be considered.
-    // Set RelevancyThreshold to a value between 0 and 1 if using the SequentialPlanner or Stepwise planner with gpt-3.5-turbo. 
+    // Set RelevancyThreshold to a value between 0 and 1 if using the SequentialPlanner or Stepwise planner with gpt-3.5-turbo.
     // Ignored when Planner:Type is "Action"
     "RelevancyThreshold": "0.25",
     // Whether to allow missing functions in the plan on creation then sanitize output. Functions are considered missing if they're not available in the planner's kernel's context.
@@ -125,12 +125,14 @@
   },
   //
   // Memory stores are used for storing new memories and retrieving semantically similar memories.
-  // - Supported Types are "volatile", "qdrant", "azurecognitivesearch", or "chroma".
+  // - Supported Types are "volatile", "qdrant", "azurecognitivesearch", "postgres", or "chroma".
   // - When using Qdrant or Azure Cognitive Search, see ./README.md for deployment instructions.
   // - Set "MemoryStore:AzureCognitiveSearch:Key" using dotnet's user secrets (see above)
   //     (i.e. dotnet user-secrets set "MemoryStore:AzureCognitiveSearch:Key" "MY_AZCOGSRCH_KEY")
   // - Set "MemoryStore:Qdrant:Key" using dotnet's user secrets (see above) if you are using a Qdrant Cloud instance.
   //     (i.e. dotnet user-secrets set "MemoryStore:Qdrant:Key" "MY_QDRANTCLOUD_KEY")
+  // - Set "MemoryStore:Postgres:ConnectionString" using dotnet's user secrets (see above) if you are using a PostgreSQL database (or CosmosDB for PostgreSQL instance).
+  //     (i.e. dotnet user-secrets set "MemoryStore:Postgres:ConnectionString" "MY_POSTGRES_CONNECTION_STRING")
   //
   "MemoryStore": {
     "Type": "volatile",
@@ -147,6 +149,10 @@
     "Chroma": {
       "Host": "http://localhost",
       "Port": "8000"
+    },
+    "Postgres": {
+      "VectorSize": 1536
+      // "ConnectionString": // dotnet user-secrets set "MemoryStore:Postgres:ConnectionString" "MY_POSTGRES_CONNECTION_STRING"
     }
   },
   //
@@ -170,7 +176,7 @@
   // OCR support is used for allowing end users to upload images containing text in addition to text based documents.
   // - Supported Types are "none", "azureformrecognizer", "tesseract".
   // - When using Tesseract OCR Support (In order to upload image file formats such as png, jpg and tiff)
-  //  - Obtain language data files here: https://github.com/tesseract-ocr/tessdata . 
+  //  - Obtain language data files here: https://github.com/tesseract-ocr/tessdata .
   //  - Add these files to your `data` folder or the path specified in the "FilePath" property and set the "Copy to Output Directory" value to "Copy if newer".
   // - When using Azure Form Recognizer OCR Support
   //  - Set "OcrSupport:AzureFormRecognizer:Key" using dotnet's user secrets (see above)