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----
-title: Specific usage
----
-import { Aside, CardGrid, Card, LinkCard, Steps, Badge } from '@astrojs/starlight/components';
-import { Image } from 'astro:assets';
-
-This Document provides a more in depth tutorial and demo for using the Continue VSCode extension with Db2 for i.
-
-## Getting Started: Continue
-
-
-Continue is the leading open source AI code assistant for VS Code. It provides a wide range of AI features:
-
-* Chat Interface
-* Code Completion
-* Autocomplete
-
-### Install the Continue extension for VS Code
-
-
- 1. Install the Continue extension from the [VS Code Marketplace](https://marketplace.visualstudio.com/items?itemName=Continue.continue).
- 
- 2. Once Installed, there will be a new icon in your VS Code menu (mine is on the top right). Click on the icon to open the chat window.
- 
-
-
-Once you have the extension installed, you can configure the AI provider you want to use. Continue supports multiple AI providers (including [Watsonx](https://docs.continue.dev/customize/model-providers/more/watsonx)!). You can choose the provider you want to use by clicking on the settings icon in the chat window.
-
-For demonstration purposes, we will use the Ollama Provider for hosting LLMs locally on your machine.
-
-
-### Setting up Ollama Provider
-
-Here is a step-by-step guide to setting up the Ollama provider with the IBM Granite models in Continue:
-
-#### 1. Install Ollama
-
-Install Ollama on your machine by following the link below:
-
-
-#### 2. Fetch the IBM Granite 3.0 models
-
-The IBM Granite 3.0 models are available in the Ollama model registry. More information about the IBM Granite models can be found [here](https://ollama.com/blog/ibm-granite).
-
-Using the Ollama CLI, fetch the IBM Granite 3.0 8b model by running the following command:
-```bash
-ollama pull granite3-dense:8b
-```
-
-#### 3. Configure the Ollama provider in Continue
-
-Open the VSCode Command Palette (Press ctrl+shift+p) and search for `Continue: open config.json`. This will open the Continue central config file `$HOME/.continue/config.json` in your editor. To enable the Granite models in Ollama, add the following configuration to the `models` section:
-
-```json title="~/.continue/config.json"
-"models": [
- {
- "title": "Granite Code 8b",
- "provider": "ollama",
- "model": "granite3-dense:8b"
- }
- ],
-```
-
-save this file and select the Granite model in the chat window.
-
-
-
-### Other LLM Providers
-
-You can also use other LLM providers with Continue. Here are some of the available providers:
-- Watsonx
-- Anthropic
-- OpenAI
-- Gemini (Google)
-
-
-
-
-## Examples
-
-Once you have the extension installed and the AI provider configured, you can ask questions about your database using the chat window using the `@db2i` context provider. In Continue, a context provider is very similar to a chat participant in GitHub Copilot. It provides additional context to the AI model to help it generate more accurate SQL queries.
-
-More on context providers can be found [here](https://docs.continue.dev/customize/context-providers/).
-
-### Working with Tables
-
-#### Example 1: Summarize the columns in the `EMPLOYEE` table
-
-
-
-**Notes:**
-- The AI model recognizes the table reference `EMPLOYEE` and provides a summary of the columns in the table.
-- Primary Key and Constraint information is also provided.
-
-
-#### Example 2: Join the `EMPLOYEE` and `DEPARTMENT` tables
-
-
-
-**Notes:**
-- The AI model recognizes the table references `EMPLOYEE` and `DEPARTMENT` and provides a SQL query that joins the two tables.
-- The SQL query is generated based on the context provided by the `@db2i` context provider.
-- The generated SQL query can be copied and run in the SQL editor in VS Code.
-
-
-#### Example 3: More complex queries
-
-
-**Notes:**
-- The AI model recognizes the table references `EMPLOYEE` and `DEPARTMENT` and provides a SQL query that calculates the total, average, and median salary for each department.
-- run the generated SQL query in the SQL editor in VS Code.
-
-We can refine this query further by asking to remove departments that dont have any employees:
-
-
-
-#### Tables context provider:
-
-When you connect to a system and start an SQL Job, we automatically create a default schema contex provider with the tables in that schema. This allows you to ask questions about the tables in the schema without having to reference the schema in your queries.
-
-My defult Library is `SAMPLE`, so `@Db2i-SAMPLE` is the context provider for the tables in the SAMPLE library:
-
-
-Once you select `@Db2i-SAMPLE`, the tables appear in a dopdown list. You can select a table to get a summary of the columns in that table:
-
-
-Example Prompt:
-
-
-Note, you do not need to invoke `@Db2i` in order to use the table context items. One advantage to "tagging" the direct table, is that we only look up information for that table, and dont search the entire library list for the table.
-
-You can add additional table context providers by editing your library list in the SQL Job Manager.
-1. Open the SQL Job Manager
-2. Select New SQL Job, or edit the current Job
-3. Add the library as the first entry in the library list
-4. Save the Job
-
-In the following image, I added `TOYSTORE3` to the library list, and now I can use the `@Db2i-TOYSTORE3` context provider to get information about the tables in the TOYSTORE3 library:
-
-
-
-
-### Working with other references in your Library List
-
-
-#### Example 1: Reference a function in QSYS2
-
-
-**Notes:**
-- The model recognizes the function reference `OBJECT_STATISTICS` in the `QSYS2` library and provides a summary of the function.
-- Information about the `TOYSTORE3` library is also provided.
-- An example of how to use `OBJECT_STATISTICS` is provided.
-
-
-
-
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diff --git a/src/content/docs/extensions/db2i/AI/code-assistant.mdx b/src/content/docs/extensions/db2i/AI/code-assistant.mdx
index 2a3aeb0..d2c2c3d 100644
--- a/src/content/docs/extensions/db2i/AI/code-assistant.mdx
+++ b/src/content/docs/extensions/db2i/AI/code-assistant.mdx
@@ -6,25 +6,21 @@ sidebar:
import { Aside, CardGrid, Card, LinkCard, Steps, Badge } from '@astrojs/starlight/components';
import { Image } from 'astro:assets';
-The Db2 for IBM i extension, as of 1.6.3, has the ability to integrate with specific AI extensions:
+The Db2 for IBM i extension, as of 1.6.3, has the ability to integrate with AI extensions:
-
- ✅ Multiple AI Providers available, including Watsonx!
-
✅ Requires GitHub Copilot licence
-
## Introduction
-The Db2 for i SQL code assistant provides intregrations with AI code assistants such as GitHub Copilot Chat and Continue. These integrations allow you to ask questions about your Db2 for IBM i database, and get help with writing SQL queries. The best part is that you can do this directly from your VS Code editor.
+The Db2 for i SQL code assistant provides integration with GitHub Copilot Chat, allowing you to ask questions about your Db2 for IBM i database, and get help with writing SQL queries. The best part is that you can do this directly from your VS Code editor.
## Use cases
@@ -43,7 +39,7 @@ Common Use cases of the SQL code assistant include:
## How does this work?
-The `@db2i` GitHub Copilot chat participant and the `@Db2i` Continue context provider work in the same way by extracting relevant database information from the user prompt. Here is breakdown of the algorithm:
+The `@db2i` GitHub Copilot chat participant works by extracting relevant database information from the user prompt. Here is a breakdown of the algorithm:
@@ -77,7 +73,7 @@ tell me about the columns in sample.employee
#### Step 4: Add Metadata to Prompt Context
-- Finally, we insert the fetched column metadata into the prompt context using the Continue API
+- Finally, we insert the fetched column metadata into the prompt context
@@ -86,15 +82,15 @@ tell me about the columns in sample.employee
* Since Database metadata is fetched from the SQL Job Manager, it is important to ensure that the SQL Job Manager is connected and configured correctly.
-let's break down the process of how the `@db2i` chat participant and the `@Db2i` context provider work:
+let's break down the process of how the `@db2i` chat participant works:
-### Here’s a breakdown of the process:
+### Here's a breakdown of the process:
-1. **Activate the `@Db2i` Context Provider**
- - Start by typing the "@" symbol in the chat text box to invoke the `@Db2i` context provider.
+1. **Activate the `@db2i` Chat Participant**
+ - Start by typing the "@" symbol in the chat text box to invoke the `@db2i` chat participant.
2. **Enter Your Query**
- Use a prompt like:
```
@@ -109,7 +105,7 @@ By integrating database context directly into our prompts, we make SQL generatio
## What data is shared?
-If you do not want to share your data with any AI services, then do not invoke the functionality through VS Code. For example, we only fetch metadata when the user explicitly requests it through the chat windows. We do not fetch any metadata without the user explicitly using the chat windows in either Copilot Chat or Continue. Simply don't install the extensions, or don't use the `@db2i` context.
+If you do not want to share your data with any AI services, then do not invoke the functionality through VS Code. For example, we only fetch metadata when the user explicitly requests it through the chat windows. We do not fetch any metadata without the user explicitly using the chat windows in Copilot Chat. Simply don't install the extension, or don't use the `@db2i` context.