Merge branch 'main' into fetch-metadata-from-id-2

Author: jmsteur

ai/gen-ai-agents/mcp-oci-integration/README.md

@@ -6,6 +6,7 @@ This repository contains code and examples to help in the following tasks:
 * **Integrate** MCP servers with other **OCI resources** (ADB, Select AI, ...)
 * **Integrate** MCP Servers running on OCI with AI Assistants like **ChatGPT**, Claude.ai, MS Copilot
 * **Integrate** MCP Servers with OCI **APM** for **Observability**
+* **how-to** create a **docker** image for your MCP server
 
 ![MCP console](./images/mcp_cli.png)
 
@@ -64,7 +65,7 @@ Using **OCI services** there are several things you can do to get the right leve
 * You can use **OCI IAM** to generate **JWT** tokens
 * You can use OCI network security
 
-More details in a dedicate page.
+More details in a dedicated page.
 
 ## Integrate MCP Semantic Search with ChatGPT
 If you deploy the [MCP Semantic Search](./mcp_semantic_search_with_iam.py) server you can test the integration with **ChatGPT** in **Developer Mode**. It provides a **search** tool, compliant with **OpenAI** specs. 
@@ -81,4 +82,6 @@ In this way you have an option to do full **Text2SQL** search, over your databas
 
 An example is [here](./mcp_selectai.py)
 
+For **Select AI** configuration, see [here](./configure_select_ai.md)
+
 

ai/gen-ai-agents/mcp-oci-integration/config.py

@@ -30,7 +30,7 @@
 AUTH = "API_KEY"
 
 # embeddings
-# added this to distinguish between Cohere end REST NVIDIA models
+# added this to distinguish between Cohere and REST NVIDIA models
 # can be OCI or NVIDIA
 EMBED_MODEL_TYPE = "OCI"
 # EMBED_MODEL_TYPE = "NVIDIA"
@@ -95,7 +95,7 @@
 PORT = 9000
 
 # with this we can toggle JWT token auth
-ENABLE_JWT_TOKEN = False
+ENABLE_JWT_TOKEN = True
 # for JWT token with OCI
 # put your domain URL here
 IAM_BASE_URL = "https://idcs-930d7b2ea2cb46049963ecba3049f509.identity.oraclecloud.com"
@@ -104,4 +104,9 @@
 AUDIENCE = ["urn:opc:lbaas:logicalguid=idcs-930d7b2ea2cb46049963ecba3049f509"]
 
 # for Select AI
+# SELECT_AI_PROFILE = "OCI_GENERATIVE_AI_PROFILE_F1"
+# this one with SH schema
 SELECT_AI_PROFILE = "OCI_GENERATIVE_AI_PROFILE"
+
+# UI
+UI_TITLE = "🛠️ AI Assistant powered by MCP"

ai/gen-ai-agents/mcp-oci-integration/configure_select_ai.md

@@ -0,0 +1,84 @@
+# Select AI Configuration
+
+## Introduction
+**Select AI** is a functionality provided by **Oracle Autonomous Database (ADB)**.
+
+It enables to do easily **Text2SQL**, in other words to translate a request for data, expressed in Natural Language (NL),
+in a SQL statement working in your Database.
+
+Example:
+
+* (NL): List the names of all F1 drivers.
+* (SQL): SELECT DRIVER_NAME from F1USER.F1_DRIVERS
+
+## Configuration
+To use **Select AI** you need an ADB, with the schema where you want to run your SQL statements, and a Large Language Model (LLM).
+You can use a model provided by **OCI Generative AI** service, or a model from another supported provider (see Oracle docs for the list).
+
+In this short note, we will provide information to configure Select AI using OCI Generative AI.
+
+### Store credentials and create a Select AI **Profile**
+Create in your OCI account (enabled to use Generative AI) an API key. Save the keys.
+
+Create and store a **credential**, with a name, inside your DB schema (the schema you're using to execute Select AI, not the data schema). 
+
+Execute the following procedure, with your data
+
+```
+BEGIN
+  DBMS_CLOUD.create_credential(
+    credential_name => 'MY_CREDENTIAL_NAME',
+    user_ocid       => 'ocid1.user.oc1..my_user_oci',
+    tenancy_ocid    => 'ocid1.tenancy.oc1..my_tenancy_ocid',
+    fingerprint     => 'fingerprint of my key',
+    private_key     => 'cut&paste your private key here'
+  );
+END;
+/
+```
+
+Create a **Select AI profile**. Execute the following procedure, again with your data.
+(put the list of the object in the schema you need to make visible to Select AI)
+
+```
+BEGIN
+  DBMS_CLOUD_AI.CREATE_PROFILE(
+      profile_name => 'OCI_GENERATIVE_AI_PROFILE' ,
+      attributes   =>
+      '{
+        "provider": "oci",
+        "region": "us-chicago-1",
+        "oci_compartment_id": "ocid1.compartment.oc1..my compartment ocid",
+        "credential_name": "MY_CREDENTIAL_NAME",
+        "object_list": [
+          {"owner": "SH", "name": "CHANNELS"},
+          {"owner": "SH", "name": "COSTS"},
+          {"owner": "SH", "name": "COUNTRIES"},
+          {"owner": "SH", "name": "CUSTOMERS"},
+          {"owner": "SH", "name": "PRODUCTS"},
+          {"owner": "SH", "name": "PROMOTIONS"},
+          {"owner": "SH", "name": "SALES"},
+          {"owner": "SH", "name": "SUPPLEMENTARY_DEMOGRAPHICS"},
+          {"owner": "SH", "name": "TIMES"}
+        ],
+        "model": "xai.grok-4"
+      }');
+
+END;
+```
+
+## Test Select AI
+You can test that the configuration is correctly working using code like the one in [test select AI](./test_selectai01.py)
+
+The code is using the new library from Oracle: **select-ai**
+To use it, you need also to have installed in your Python environment the library: **oracledb**
+
+```
+pip install select_ai
+pip install oracledb
+```
+
+## References
+For more information, see 
+* [Getting Started with Select AI](https://docs.oracle.com/en-us/iaas/autonomous-database-serverless/doc/select-ai-get-started.html)
+* [How to use Select AI: A step-by-step guide](https://blogs.oracle.com/datawarehousing/post/how-to-use-oracle-select-ai-a-stepbystep-guide-generative-ai)