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docs(skills): add file-based connector docs, venv setup, and fix path/typo issues (#1438)
Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
This commit is contained in:
@@ -65,13 +65,13 @@ If you prefer to run each step yourself, follow these phases in order.
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Create a directory on your host machine. This directory will be mounted into the Docker container so it can read and write MDL files.
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```bash
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mkdir -p /${PWD}/wren-workspace
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mkdir -p ${PWD}/wren-workspace
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```
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The completed workspace will look like:
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```
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/${PWD}/wren-workspace/
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${PWD}/wren-workspace/
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├── wren_project.yml
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├── connection.yml
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├── models/
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@@ -94,7 +94,7 @@ When prompted for connection details, provide:
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| Field | Value |
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|-------|-------|
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| Data source type | `duckdb` |
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| Database file path | `/data/jaffle_shop.duckdb` |
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| Database folder path | `/data` (the folder containing `jaffle_shop.duckdb`) |
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| Workspace path | `~/wren-workspace` |
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| jaffle_shop directory | your absolute path to `jaffle_shop_duckdb/` |
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@@ -153,7 +153,7 @@ In Claude Code, run each skill in sequence:
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When prompted, enter:
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- Data source type: `duckdb`
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- Database file path: `/data/jaffle_shop.duckdb`
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- Database folder path: `/data` (the folder containing `jaffle_shop.duckdb`)
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Then save the MDL as a versioned YAML project:
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+2
-2
@@ -7,7 +7,7 @@
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"skills": [
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{
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"name": "wren-connection-info",
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"version": "1.1",
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"version": "1.2",
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"description": "Set up data source type and connection credentials for Wren Engine.",
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"tags": [
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"wren",
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@@ -88,7 +88,7 @@
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},
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{
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"name": "wren-quickstart",
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"version": "1.0",
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"version": "1.1",
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"description": "End-to-end quickstart for Wren Engine — from zero to querying.",
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"tags": [
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"wren",
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@@ -1,9 +1,9 @@
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{
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"generate-mdl": "1.2",
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"wren-connection-info": "1.1",
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"wren-connection-info": "1.2",
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"wren-project": "1.4",
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"wren-sql": "1.0",
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"wren-mcp-setup": "1.2",
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"wren-quickstart": "1.0",
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"wren-quickstart": "1.1",
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"wren-usage": "1.0"
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}
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@@ -4,12 +4,13 @@ description: Set up data source type and connection credentials for Wren Engine.
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license: Apache-2.0
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metadata:
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author: wren-engine
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version: "1.1"
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version: "1.2"
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---
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# Wren Connection Info
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Sets up the data source type and credentials before any workflow that queries a database.
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Find the specification of the connection info format in the `model` section of [API reference](https://docs.getwren.ai/oss/wren_engine_api).
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---
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@@ -116,10 +117,23 @@ database: <database name>
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sf_schema: <schema name>
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```
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### DuckDB
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### File based (S3, Minio, GCS, local file)
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For the object storage connectors (S3, Minio, GCS) and local file sources, use this format:
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```
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url: <path to .duckdb file>
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format: <FILE_FORMAT> # e.g. "csv", "parquet"
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url: <file path or bucket URL>
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```
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If credentials are needed (e.g. S3 access key and secret), include these fields as well:
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```
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access_key: <SECRET>
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secret_key: <SECRET>
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```
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### DuckDB
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It leverages the same connection info format as file-based sources, but with `format: duckdb` to indicate that it's a DuckDB data source rather than a generic file source.
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```
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format: duckdb
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url: <path to folder containing .duckdb file>
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```
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### Athena
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@@ -5,7 +5,7 @@ compatibility: Requires Docker Desktop (or Docker Engine). No local database dri
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license: Apache-2.0
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metadata:
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author: wren-engine
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version: "1.0"
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version: "1.1"
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---
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# Wren Quickstart
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@@ -13,10 +13,10 @@ metadata:
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## Version check
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Silently fetch `https://raw.githubusercontent.com/Canner/wren-engine/main/skills/versions.json`.
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Compare the `wren-quickstart` key with this skill's version (`1.0`).
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Compare the `wren-quickstart` key with this skill's version (`1.1`).
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If the remote version is newer, notify the user before proceeding:
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> A newer version of the **wren-quickstart** skill is available (remote: X.Y, installed: 1.0).
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> A newer version of the **wren-quickstart** skill is available (remote: X.Y, installed: 1.1).
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> Update with:
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> ```bash
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> curl -fsSL https://raw.githubusercontent.com/Canner/wren-engine/main/skills/install.sh | bash -s -- --force wren-quickstart
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@@ -34,12 +34,27 @@ This skill walks a user through setting up Wren Engine end-to-end — from creat
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## Phase 1 — Create a workspace
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### 1a — Set up Python virtual environment
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Before creating the workspace, ensure a Python virtual environment is available. This is required if the user will run **ibis-server locally** (instead of relying solely on Docker). Skip this step if the user will use only the Dockerized ibis-server.
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```bash
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python3 -m venv .venv
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source .venv/bin/activate # macOS / Linux
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# .venv\Scripts\activate # Windows
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pip install --upgrade pip
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```
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> **Tip:** Place the venv inside or adjacent to the workspace directory so it is easy to find. Avoid committing it to version control — add `.venv/` to `.gitignore`.
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### 1b — Create a workspace directory
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Create a dedicated workspace directory on the host machine. This directory will be mounted into the Docker container, so the container can read and write MDL files.
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Ask the user where they want the workspace, or suggest a default:
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```bash
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mkdir -p ~/wren-workspace
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mkdir -p ${PWD}/wren-workspace
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```
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Save the chosen path as `<WORKSPACE_PATH>` (absolute path, e.g. `/Users/me/wren-workspace`). All subsequent steps reference this path.
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