Files
LEANN/apps/slack_rag.py
Aakash Suresh ab251ab751 Fix/twitter bookmarks anchor link (#143)
* fix: Fix Twitter bookmarks anchor link

- Convert Twitter Bookmarks from collapsible details to proper header
- Update internal link to match new anchor format
- Ensures external links to #twitter-bookmarks-your-personal-tweet-library work correctly

Fixes broken link: https://github.com/yichuan-w/LEANN?tab=readme-ov-file#twitter-bookmarks-your-personal-tweet-library

* fix: Fix Slack messages anchor link as well

- Convert Slack Messages from collapsible details to proper header
- Update internal link to match new anchor format
- Ensures external links to #slack-messages-search-your-team-conversations work correctly

Both Twitter and Slack MCP sections now have reliable anchor links.

* fix: Point Slack and Twitter links to main MCP section

- Both Slack and Twitter are subsections under MCP Integration
- Links should point to #mcp-integration-rag-on-live-data-from-any-platform
- Users will land on the MCP section and can find both Slack and Twitter subsections there

This matches the actual document structure where Slack and Twitter are under the MCP Integration section.

* Improve Slack MCP integration with retry logic and comprehensive setup guide

- Add retry mechanism with exponential backoff for cache sync issues
- Handle 'users cache is not ready yet' errors gracefully
- Add max-retries and retry-delay CLI arguments for better control
- Create comprehensive Slack setup guide with troubleshooting
- Update README with link to detailed setup guide
- Improve error messages and user experience

* Fix trailing whitespace in slack setup guide

Pre-commit hooks formatting fixes

* Add comprehensive Slack setup guide with success screenshot

- Create detailed setup guide with step-by-step instructions
- Add troubleshooting section for common issues like cache sync errors
- Include real terminal output example from successful integration
- Add screenshot showing VS Code interface with Slack channel data
- Remove excessive emojis for more professional documentation
- Document retry logic improvements and CLI arguments

* Fix formatting issues in Slack setup guide

- Remove trailing whitespace
- Fix end of file formatting
- Pre-commit hooks formatting fixes

* Add real RAG example showing intelligent Slack query functionality

- Add detailed example of asking 'What is LEANN about?'
- Show retrieved messages from Slack channels
- Demonstrate intelligent answer generation based on context
- Add command example for running real RAG queries
- Explain the 4-step process: retrieve, index, generate, cite

* Update Slack setup guide with bot invitation requirements

- Add important section about inviting bot to channels before RAG queries
- Explain the 'not_in_channel' errors and their meaning
- Provide clear steps for bot invitation process
- Document realistic scenario where bot needs explicit channel access
- Update documentation to be more professional and less cursor-style

* Docs: add real RAG example for Sky Lab #random

- Embed screenshot videos/rag-sky-random.png
- Add step-by-step commands and notes
- Include helper test script tests/test_channel_by_id_or_name.py
- Redact example tokens from docs

* Docs/CI: fix broken image paths and ruff lint\n\n- Move screenshot to docs/videos and update references\n- Remove obsolete rag-query-results image\n- Rename variable to satisfy ruff

* Docs: fix image path for lychee (use videos/ relative under docs/)

* Docs: finalize Slack setup guide with Sky random RAG example and image path fixes\n\n- Redact example tokens from docs

* Fix Slack MCP integration and update documentation

- Fix SlackMCPReader to use conversations_history instead of channels_list
- Add fallback imports for leann.interactive_utils and leann.settings
- Update slack-setup-guide.md with real screenshots and improved text
- Remove old screenshot files

* Add Slack integration screenshots to docs/videos

- Add slack_integration.png showing RAG query results
- Add slack_integration_2.png showing additional demo functionality
- Fixes lychee link checker errors for missing image files

* Update Slack integration screenshot with latest changes

* Remove test_channel_by_id_or_name.py

- Clean up temporary test file that was used for debugging
- Keep only the main slack_rag.py application for production use

* Update Slack RAG example to show LEANN announcement retrieval

- Change query from 'PUBPOL 290' to 'What is LEANN about?' for more challenging retrieval
- Update command to use python -m apps.slack_rag instead of test script
- Add expected response showing Yichuan Wang's LEANN announcement message
- Emphasize this demonstrates ability to find specific announcements in conversation history
- Update description to highlight challenging query capabilities

* Update Slack RAG integration with improved CSV parsing and new screenshots

- Fixed CSV message parsing in slack_mcp_reader.py to properly handle individual messages
- Updated slack_rag.py to filter empty channel strings
- Enhanced slack-setup-guide.md with two new query examples:
  - Advisor Models query: 'train black-box models to adopt to your personal data'
  - Barbarians at the Gate query: 'AI-driven research systems ADRS'
- Replaced old screenshots with four new ones showing both query examples
- Updated documentation to use User OAuth Token (xoxp-) instead of Bot Token (xoxb-)
- Added proper command examples with --no-concatenate-conversations and --force-rebuild flags

* Update Slack RAG documentation with Ollama integration and new screenshots

- Updated slack-setup-guide.md with comprehensive Ollama setup instructions
- Added 6 new screenshots showing complete RAG workflow:
  - Command setup, search results, and LLM responses for both queries
- Removed simulated LLM references, now uses real Ollama with llama3.2:1b
- Enhanced documentation with step-by-step Ollama installation
- Updated troubleshooting checklist to include Ollama-specific checks
- Fixed command syntax and added proper Ollama configuration
- Demonstrates working Slack RAG with real AI-generated responses

* Remove Key Features section from Slack RAG examples

- Simplified documentation by removing the bullet point list
- Keeps the focus on the actual examples and screenshots
2025-10-19 11:47:29 -07:00

228 lines
7.9 KiB
Python

#!/usr/bin/env python3
"""
Slack RAG Application with MCP Support
This application enables RAG (Retrieval-Augmented Generation) on Slack messages
by connecting to Slack MCP servers to fetch live data and index it in LEANN.
Usage:
python -m apps.slack_rag --mcp-server "slack-mcp-server" --query "What did the team discuss about the project?"
"""
import argparse
import asyncio
from apps.base_rag_example import BaseRAGExample
from apps.slack_data.slack_mcp_reader import SlackMCPReader
class SlackMCPRAG(BaseRAGExample):
"""
RAG application for Slack messages via MCP servers.
This class provides a complete RAG pipeline for Slack data, including
MCP server connection, data fetching, indexing, and interactive chat.
"""
def __init__(self):
super().__init__(
name="Slack MCP RAG",
description="RAG application for Slack messages via MCP servers",
default_index_name="slack_messages",
)
def _add_specific_arguments(self, parser: argparse.ArgumentParser):
"""Add Slack MCP-specific arguments."""
parser.add_argument(
"--mcp-server",
type=str,
required=True,
help="Command to start the Slack MCP server (e.g., 'slack-mcp-server' or 'npx slack-mcp-server')",
)
parser.add_argument(
"--workspace-name",
type=str,
help="Slack workspace name for better organization and filtering",
)
parser.add_argument(
"--channels",
nargs="+",
help="Specific Slack channels to index (e.g., general random). If not specified, fetches from all available channels",
)
parser.add_argument(
"--concatenate-conversations",
action="store_true",
default=True,
help="Group messages by channel/thread for better context (default: True)",
)
parser.add_argument(
"--no-concatenate-conversations",
action="store_true",
help="Process individual messages instead of grouping by channel",
)
parser.add_argument(
"--max-messages-per-channel",
type=int,
default=100,
help="Maximum number of messages to include per channel (default: 100)",
)
parser.add_argument(
"--test-connection",
action="store_true",
help="Test MCP server connection and list available tools without indexing",
)
parser.add_argument(
"--max-retries",
type=int,
default=5,
help="Maximum number of retries for failed operations (default: 5)",
)
parser.add_argument(
"--retry-delay",
type=float,
default=2.0,
help="Initial delay between retries in seconds (default: 2.0)",
)
async def test_mcp_connection(self, args) -> bool:
"""Test the MCP server connection and display available tools."""
print(f"Testing connection to MCP server: {args.mcp_server}")
try:
reader = SlackMCPReader(
mcp_server_command=args.mcp_server,
workspace_name=args.workspace_name,
concatenate_conversations=not args.no_concatenate_conversations,
max_messages_per_conversation=args.max_messages_per_channel,
max_retries=args.max_retries,
retry_delay=args.retry_delay,
)
async with reader:
tools = await reader.list_available_tools()
print("Successfully connected to MCP server!")
print(f"Available tools ({len(tools)}):")
for i, tool in enumerate(tools, 1):
name = tool.get("name", "Unknown")
description = tool.get("description", "No description available")
print(f"\n{i}. {name}")
print(
f" Description: {description[:100]}{'...' if len(description) > 100 else ''}"
)
# Show input schema if available
schema = tool.get("inputSchema", {})
if schema.get("properties"):
props = list(schema["properties"].keys())[:3] # Show first 3 properties
print(
f" Parameters: {', '.join(props)}{'...' if len(schema['properties']) > 3 else ''}"
)
return True
except Exception as e:
print(f"Failed to connect to MCP server: {e}")
print("\nTroubleshooting tips:")
print("1. Make sure the MCP server is installed and accessible")
print("2. Check if the server command is correct")
print("3. Ensure you have proper authentication/credentials configured")
print("4. Try running the MCP server command directly to test it")
return False
async def load_data(self, args) -> list[str]:
"""Load Slack messages via MCP server."""
print(f"Connecting to Slack MCP server: {args.mcp_server}")
if args.workspace_name:
print(f"Workspace: {args.workspace_name}")
# Filter out empty strings from channels
channels = [ch for ch in args.channels if ch.strip()] if args.channels else None
if channels:
print(f"Channels: {', '.join(channels)}")
else:
print("Fetching from all available channels")
concatenate = not args.no_concatenate_conversations
print(
f"Processing mode: {'Concatenated conversations' if concatenate else 'Individual messages'}"
)
try:
reader = SlackMCPReader(
mcp_server_command=args.mcp_server,
workspace_name=args.workspace_name,
concatenate_conversations=concatenate,
max_messages_per_conversation=args.max_messages_per_channel,
max_retries=args.max_retries,
retry_delay=args.retry_delay,
)
texts = await reader.read_slack_data(channels=channels)
if not texts:
print("No messages found! This could mean:")
print("- The MCP server couldn't fetch messages")
print("- The specified channels don't exist or are empty")
print("- Authentication issues with the Slack workspace")
return []
print(f"Successfully loaded {len(texts)} text chunks from Slack")
# Show sample of what was loaded
if texts:
sample_text = texts[0][:200] + "..." if len(texts[0]) > 200 else texts[0]
print("\nSample content:")
print("-" * 40)
print(sample_text)
print("-" * 40)
return texts
except Exception as e:
print(f"Error loading Slack data: {e}")
print("\nThis might be due to:")
print("- MCP server connection issues")
print("- Authentication problems")
print("- Network connectivity issues")
print("- Incorrect channel names")
raise
async def run(self):
"""Main entry point with MCP connection testing."""
args = self.parser.parse_args()
# Test connection if requested
if args.test_connection:
success = await self.test_mcp_connection(args)
if not success:
return
print(
"MCP server is working! You can now run without --test-connection to start indexing."
)
return
# Run the standard RAG pipeline
await super().run()
async def main():
"""Main entry point for the Slack MCP RAG application."""
app = SlackMCPRAG()
await app.run()
if __name__ == "__main__":
asyncio.run(main())