Update RAG sample flows to use Index Lookup tool (#2237)

* update RAG sample flows

* update tests

* get oid for rbac

* revert

* print client id?

* revert

* spellcheck

* appeasing the spellchecker

* use index provisioned in CI workspace for lookup test

* add chjinche to spellchecker

* json escape parameter overrides

* bump versions

* revert promptflow-ci.py to avoid running into broken tests

assets/promptflow/.cspell.json

@@ -23,6 +23,8 @@
       "openai",
       "pfazure",
       "eastus",
+      "eastus2",
+      "euap",
       "azureai",
       "vectordb",
       "Qdrant",
@@ -66,7 +68,9 @@
       "zelin",
       "embeded",
       "metad",
-      "orignal"
+      "orignal",
+      "mlindex",
+      "chjinche"
     ],
     "ignoreWords": [
       "openmpi",

assets/promptflow/models/bring-your-own-data-chat-qna/model.yaml

@@ -1,7 +1,7 @@
 path:
-  container_name: models
-  container_path: samples/bring_your_own_data_chat_qna/v6/model_folder
-  storage_name: promptflowsamples
+  container_name: gallery-samples
+  container_path: bring_your_own_data_chat_qna
+  storage_name: azuremlragexamples
   type: azureblob
 publish:
   description: description.md

assets/promptflow/models/bring-your-own-data-chat-qna/spec.yaml

@@ -9,4 +9,4 @@ properties:
   azureml.promptflow.description: Create a chatbot that uses LLM and data from your own indexed files to ground multi-round question and answering capabilities in enterprise chat scenarios.
   inference-min-sku-spec: 2|0|14|28
   inference-recommended-sku: Standard_DS3_v2
-version: 6
+version: 7

assets/promptflow/models/bring-your-own-data-qna/model.yaml

@@ -1,7 +1,7 @@
 path:
-  container_name: models
-  container_path: samples/bring_your_own_data_qna/v6/model_folder
-  storage_name: promptflowsamples
+  container_name: gallery-samples
+  container_path: bring_your_own_data_qna
+  storage_name: azuremlragexamples
   type: azureblob
 publish:
   description: description.md

assets/promptflow/models/bring-your-own-data-qna/spec.yaml

@@ -9,4 +9,4 @@ properties:
   azureml.promptflow.description: Use LLM and data from your own indexed files to ground multi-round question and answering capabilities.
   inference-min-sku-spec: 2|0|14|28
   inference-recommended-sku: Standard_DS3_v2
-version: 7
+version: 8

scripts/promptflow-ci/test-configs/bring-your-own-data-chat-qna/test_config.json

@@ -8,10 +8,10 @@
       }
     },
     {
-      "name": "embed_the_question",
+      "name": "lookup",
       "inputs": {
-        "connection": "aoai_connection",
-        "deployment_name": "text-embedding-ada-002"
+        "mlindex_content": "embeddings:\r\n  api_base: https:\/\/promptflow-ci-sweden-central.openai.azure.com\/\r\n  api_type: azure\r\n  api_version: 2023-07-01-preview\r\n  batch_size: '16'\r\n  connection:\r\n    id: \/subscriptions\/96aede12-2f73-41cb-b983-6d11a904839b\/resourceGroups\/promptflow\/providers\/Microsoft.MachineLearningServices\/workspaces\/chjinche-pf-eus\/connections\/chjinche-aoai\r\n  connection_type: workspace_connection\r\n  deployment: text-embedding-ada-002\r\n  dimension: 1536\r\n  file_format_version: '2'\r\n  kind: open_ai\r\n  model: text-embedding-ada-002\r\n  schema_version: '2'\r\nindex:\r\n  engine: langchain.vectorstores.FAISS\r\n  kind: faiss\r\n  method: FlatL2\r\n  path: azureml:\/\/subscriptions\/96aede12-2f73-41cb-b983-6d11a904839b\/resourcegroups\/promptflow\/workspaces\/chjinche-pf-eus\/datastores\/workspaceblobstore\/paths\/azureml\/f6495468-6137-4cb8-8107-9f312e4fc91d\/index\/\r\nself:\r\n  path: \r\n    azureml:\/\/subscriptions\/96aede12-2f73-41cb-b983-6d11a904839b\/resourcegroups\/promptflow\/workspaces\/chjinche-pf-eus\/datastores\/workspaceblobstore\/paths\/azureml\/f6495468-6137-4cb8-8107-9f312e4fc91d\/index\/\r\n  asset_id: \r\n    azureml:\/\/locations\/eastus2euap\/workspaces\/4d49a4bb-8594-4ccd-842e-73a9aeb3fcb1\/data\/azureml-runbook-faiss\/versions\/1",
+        "query_type": "Vector"
       }
     },
     {

scripts/promptflow-ci/test-configs/bring-your-own-data-qna/test_config.json

@@ -1,10 +1,10 @@
 {
   "nodes": [
     {
-      "name": "embed_the_question",
+      "name": "lookup",
       "inputs": {
-        "connection": "aoai_connection",
-        "deployment_name": "text-embedding-ada-002"
+        "mlindex_content": "embeddings:\r\n  api_base: https:\/\/promptflow-ci-sweden-central.openai.azure.com\/\r\n  api_type: azure\r\n  api_version: 2023-07-01-preview\r\n  batch_size: '16'\r\n  connection:\r\n    id: \/subscriptions\/96aede12-2f73-41cb-b983-6d11a904839b\/resourceGroups\/promptflow\/providers\/Microsoft.MachineLearningServices\/workspaces\/chjinche-pf-eus\/connections\/chjinche-aoai\r\n  connection_type: workspace_connection\r\n  deployment: text-embedding-ada-002\r\n  dimension: 1536\r\n  file_format_version: '2'\r\n  kind: open_ai\r\n  model: text-embedding-ada-002\r\n  schema_version: '2'\r\nindex:\r\n  engine: langchain.vectorstores.FAISS\r\n  kind: faiss\r\n  method: FlatL2\r\n  path: azureml:\/\/subscriptions\/96aede12-2f73-41cb-b983-6d11a904839b\/resourcegroups\/promptflow\/workspaces\/chjinche-pf-eus\/datastores\/workspaceblobstore\/paths\/azureml\/f6495468-6137-4cb8-8107-9f312e4fc91d\/index\/\r\nself:\r\n  path: \r\n    azureml:\/\/subscriptions\/96aede12-2f73-41cb-b983-6d11a904839b\/resourcegroups\/promptflow\/workspaces\/chjinche-pf-eus\/datastores\/workspaceblobstore\/paths\/azureml\/f6495468-6137-4cb8-8107-9f312e4fc91d\/index\/\r\n  asset_id: \r\n    azureml:\/\/locations\/eastus2euap\/workspaces\/4d49a4bb-8594-4ccd-842e-73a9aeb3fcb1\/data\/azureml-runbook-faiss\/versions\/1",
+        "query_type": "Vector"
       }
     },
     {