Docs: finalize Slack setup guide with Sky random RAG example and image path fixes\n\n- Redact example tokens from docs
This commit is contained in:
aakash
@@ -121,74 +121,51 @@ python -m apps.slack_rag \
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```
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### 4.3 Real RAG Query Example
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## Real RAG Query Example (Sky Lab Computing “random”)
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To ask intelligent questions about your Slack conversations:
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This example shows a real query against the Sky Lab Computing workspace’s “random” channel using the Slack MCP server, with an embedded screenshot of the terminal output.
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### Screenshot
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### Prerequisites
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- Bot is installed in the Sky Lab Computing workspace and invited to the target channel (run `/invite @YourBotName` in the channel if needed)
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- Bot token available and exported in the same terminal session
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### Commands
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1) Set the workspace token for this shell
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```bash
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# Ask about a specific topic discussed in your channels
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python -m apps.slack_rag \
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--mcp-server "slack-mcp-server" \
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export SLACK_MCP_XOXP_TOKEN="xoxb-***-redacted-***"
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```
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2) Run a real query against the “random” channel by channel ID (C0GN5BX0F)
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```bash
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python test_channel_by_id_or_name.py \
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--channel-id C0GN5BX0F \
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--workspace-name "Sky Lab Computing" \
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--query "PUBPOL 290"
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```
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Expected: The output contains a matching message (e.g., “do we have a channel for class PUBPOL 290 this semester?”) followed by a compact RAG-style answer section.
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3) Optional: Ask a broader question
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```bash
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python test_channel_by_id_or_name.py \
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--channel-id C0GN5BX0F \
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--workspace-name "Sky Lab Computing" \
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--channels random general \
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--query "What is LEANN about?"
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```
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This will:
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1. **Retrieve relevant messages** from the specified channels
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2. **Index the content** for semantic search
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3. **Generate an intelligent answer** based on the retrieved context
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4. **Provide citations** showing which messages were used
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## Success Example: Working Integration
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Here's what a successful Slack integration looks like in practice:
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### Terminal Output
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When you run the connection test, you should see output similar to this:
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```
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Testing Slack MCP Connection...
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Environment: SLACK_MCP_XOXP_TOKEN = xoxb-16753592806-967...
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Connected to Slack MCP server!
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Authenticated with Slack.
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Listing available MCP tools...
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Found 5 available tools:
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1. channels_list - Get list of channels
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2. conversations_add_message - Add messages to channels
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3. conversations_history - Get messages from channels
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4. conversations_replies - Get thread messages
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5. conversations_search_messages - Search messages with filters
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Testing message fetch from 'random' channel...
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Successfully fetched messages from channel random.
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```
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### Visual Example
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The following screenshot shows a successful integration with VS Code displaying the retrieved Slack channel data:
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### Key Success Indicators
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- **Authentication Success**: Connected to your Slack workspace
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- **Tool Availability**: 5 MCP tools ready for interaction
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- **Data Access**: Retrieved channel directory with member counts and purposes
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- **Comprehensive Coverage**: Access to multiple channels including specialized research groups
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This demonstrates that your Slack integration is fully functional and ready for RAG queries across your entire workspace.
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### Important: Invite Your Bot to Channels
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Before running RAG queries, you need to invite your Slack bot to the channels you want to access. This is a security feature in Slack.
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**To invite your bot to a channel:**
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1. Go to the channel in Slack (e.g., `#general` or `#random`)
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2. Type: `/invite @YourBotName` (replace with your actual bot name)
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3. Or click the channel name → "Settings" → "Integrations" → "Add apps"
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Notes:
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- If you see `not_in_channel`, invite the bot to the channel and re-run.
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- If you see `channel_not_found`, confirm the channel ID and workspace.
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- Deep search via server-side “search” tools may require additional Slack scopes; the example above performs client-side filtering over retrieved history.
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## Common Issues and Solutions
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@@ -291,67 +268,6 @@ python -m apps.slack_rag \
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--no-concatenate-conversations \
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--query "Your query"
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```
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### Screenshot: Real RAG Query Results
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Here's what you'll see when running a RAG query on your Slack workspace:
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**What this screenshot shows:**
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- ✅ **Successful MCP connection** to Slack workspace
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- ✅ **Channel directory retrieval** (107 channels discovered)
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- ✅ **Proper error handling** for channel access permissions
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- ⚠️ **"not_in_channel" errors** indicating bot needs invitation to specific channels
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This is the expected behavior - the integration is working perfectly, it just needs proper channel permissions to access conversation messages.
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## Real RAG Query Example (Sky Lab Computing “random”)
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This example shows a real query against the Sky Lab Computing workspace’s “random” channel using the Slack MCP server, with an embedded screenshot of the terminal output.
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### Screenshot
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### Prerequisites
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- Bot is installed in the Sky Lab Computing workspace and invited to the target channel (run `/invite @YourBotName` in the channel if needed)
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- Bot token available and exported in the same terminal session
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### Commands
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1) Set the workspace token for this shell
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```bash
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export SLACK_MCP_XOXP_TOKEN="xoxb-***-redacted-***"
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```
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2) Run a real query against the “random” channel by channel ID (C0GN5BX0F)
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```bash
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python test_channel_by_id_or_name.py \
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--channel-id C0GN5BX0F \
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--workspace-name "Sky Lab Computing" \
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--query "PUBPOL 290"
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```
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Expected: The output contains a matching message (e.g., “do we have a channel for class PUBPOL 290 this semester?”) followed by a compact RAG-style answer section.
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3) Optional: Ask a broader question
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```bash
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python test_channel_by_id_or_name.py \
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--channel-id C0GN5BX0F \
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--workspace-name "Sky Lab Computing" \
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--query "What is LEANN about?"
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```
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Notes:
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- If you see `not_in_channel`, invite the bot to the channel and re-run.
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- If you see `channel_not_found`, confirm the channel ID and workspace.
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- Deep search via server-side “search” tools may require additional Slack scopes; the example above performs client-side filtering over retrieved history.
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---
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## Troubleshooting Checklist
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