DailySum

A CLI tool that uses AI agents to generate daily work summaries from your GitHub activity.

What It Does

Analyzes your GitHub activity and generates daily summaries like this:

Yesterday:
- Merged PR #142: Fix authentication bug in user login flow
- Reviewed PR #138: Add support for OAuth2 integration
- Opened issue #145: Memory leak in background task processor

Today:
- Continue work on OAuth2 integration testing
- Address memory leak issue in background processor
- Review pending PRs from team members

How It Works

This tool uses two Mozilla AI projects:

any-llm

Provides a unified interface to different LLM providers. Switch between OpenAI, Anthropic, Mistral, and other models with a string change.

any-agent

Provides a unified interface for AI agent frameworks. Handles tool orchestration, model interactions, and GitHub API access via Model Context Protocol (MCP).

Together, these handle the complexity of GitHub API interactions and LLM provider differences.

Installation

Requirements

• Python 3.11 or newer
• A GitHub Personal Access Token
• API key for your chosen LLM provider (OpenAI, Anthropic, etc.)

Install from PyPI

pip install dailysum

Install from Source

git clone https://github.com/njbrake/dailysum.git
cd dailysum
pip install -e .

Configuration

Option 1: Interactive Setup (Recommended)

Run the initialization command and follow the prompts:

dailysum init

This will:

• Prompt for your GitHub token
• Let you choose your preferred LLM model
• Optionally set your company name
• Save configuration to ~/.config/dailysum/config.toml

Option 2: Environment Variables

Set these environment variables:

export GITHUB_TOKEN="ghp_your_github_token_here"
export MODEL_ID="openai/gpt-4o-mini"  # Optional, defaults to gpt-4o-mini
export COMPANY="Your Company Name"     # Optional

Then run with the --use-env flag:

dailysum generate --use-env

Getting a GitHub Token

1. Go to GitHub Settings > Developer settings > Personal access tokens
2. Click "Generate new token (classic)"
3. Select scopes: repo, read:user, read:org, notifications
4. Copy the generated token

Supported LLM Providers

• OpenAI: openai/gpt-4o, openai/gpt-4o-mini, openai/gpt-3.5-turbo
• Anthropic: anthropic/claude-3-5-sonnet-20241022, anthropic/claude-3-haiku-20240307
• Mistral: mistral/mistral-large-latest, mistral/mistral-small-latest
• Google: google/gemini-1.5-pro, google/gemini-1.5-flash

See any-llm providers for the complete list.

Usage

Generate Your Daily Summary

dailysum generate

Generate with Quality Evaluation

dailysum generate --evaluate

View Current Configuration

dailysum config

Use Environment Variables Instead of Config File

dailysum generate --use-env

Advanced Usage

Custom Configuration File Location

# Initialize with custom location
dailysum init --config-path /path/to/my/config.toml

# Generate using custom location
dailysum generate --config-path /path/to/my/config.toml

Different Models for Different Purposes

You can easily switch between models by updating your config:

# Use a faster, cheaper model
dailysum init --model-id "openai/gpt-4o-mini"

# Use a more powerful model for complex summaries
dailysum init --model-id "anthropic/claude-3-5-sonnet-20241022"

Development

Setting Up Development Environment

git clone https://github.com/njbrake/dailysum.git
cd dailysum

# Install with development dependencies
pip install -e ".[dev]"

# Set up pre-commit hooks
pre-commit install

Running Tests

pytest

Code Quality

# Format and lint
ruff format .
ruff check . --fix

# Type checking
mypy src/

Contributing

Contributions are welcome. Areas of interest:

• New LLM provider support
• Summary templates and prompts
• Additional GitHub data sources
• CLI improvements
• Tests and documentation

See Contributing Guide for details.

Example Output

📋 Your Daily Summary
┌─────────────────────────────────────────────────────────────┐
│ Yesterday:                                                  │
│ - Merged PR #234: Implement user authentication system     │
│ - Reviewed PR #231: Add Docker configuration               │
│ - Fixed critical bug in payment processing (Issue #189)    │
│ - Updated documentation for API endpoints                  │
│                                                             │
│ Today:                                                      │
│ - Complete integration tests for authentication system     │
│ - Review pending PRs from team members                     │
│ - Start work on user dashboard redesign                    │
│ - Investigate performance issues in search functionality   │
└─────────────────────────────────────────────────────────────┘

Troubleshooting

"Configuration error: GitHub token not found"

Make sure you've either:

• Run dailysum init to set up a config file, or
• Set the GITHUB_TOKEN environment variable

"Unable to import 'any_agent'"

Install the required dependencies:

pip install any-agent any-llm-sdk

Rate Limiting Issues

If you hit GitHub API rate limits:

• Use a GitHub token (provides 5000 requests/hour vs 60 for unauthenticated)
• Consider running the tool less frequently
• The tool automatically respects rate limits and will wait if needed

License

MIT License - see LICENSE for details.

Acknowledgments

• any-llm - Unified LLM provider interface
• any-agent - Unified AI agent framework
• GitHub Copilot MCP - GitHub API access via Model Context Protocol
• Rich - Beautiful terminal output
• Click - Command-line interface framework

Built by Mozilla AI