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https://github.com/tomatyss/pymailai
PyMailAI is a Python package that enables AI agents to use email as an input/output interface.
https://github.com/tomatyss/pymailai
agent anthropic email llm ollama openai
Last synced: 4 days ago
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PyMailAI is a Python package that enables AI agents to use email as an input/output interface.
- Host: GitHub
- URL: https://github.com/tomatyss/pymailai
- Owner: tomatyss
- License: mit
- Created: 2024-12-20T13:58:03.000Z (17 days ago)
- Default Branch: main
- Last Pushed: 2024-12-29T21:53:49.000Z (8 days ago)
- Last Synced: 2024-12-29T22:17:13.844Z (8 days ago)
- Topics: agent, anthropic, email, llm, ollama, openai
- Language: Python
- Homepage: https://tomatyss.github.io/PyMailAI/
- Size: 117 KB
- Stars: 2
- Watchers: 2
- Forks: 0
- Open Issues: 2
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# 📧 PyMailAI
[](https://tomatyss.github.io/PyMailAI/)
[](https://badge.fury.io/py/pymailai)
[](https://pypi.org/project/pymailai/)
[](https://github.com/tomatyss/PyMailAI/actions/workflows/tests.yml)
[](https://codecov.io/gh/tomatyss/PyMailAI)
[](https://github.com/psf/black)
[](https://opensource.org/licenses/MIT)
[](https://pepy.tech/project/pymailai)
PyMailAI is a Python package that enables AI agents to use email as an input/output interface. It provides simple wrappers to:
1. Get prompts from incoming emails
2. Process them with your LLM of choice
3. Send the responses back via email
## Installation
```bash
pip install pymailai
```
## Quick Start
### Basic OpenAI Example
Here's how to use PyMailAI with OpenAI's API to create an email-based AI assistant:
```python
import os
import asyncio
import openai
from pymailai import EmailAgent, EmailConfig
from pymailai.message import EmailData
# Configure OpenAI
openai.api_key = os.getenv("OPENAI_API_KEY")
async def process_with_openai(message: EmailData):
"""Process email content using OpenAI."""
try:
# Send email content to OpenAI
completion = await openai.ChatCompletion.acreate(
model="gpt-3.5-turbo",
messages=[
{"role": "user", "content": message.body_text}
]
)
# Get AI response
ai_response = completion.choices[0].message.content
# Send response back via email
return EmailData(
message_id="", # Will be generated by email server
subject=f"Re: {message.subject}",
from_address=message.to_addresses[0],
to_addresses=[message.from_address],
cc_addresses=[],
body_text=ai_response,
body_html=None,
timestamp=message.timestamp,
in_reply_to=message.message_id,
references=[message.message_id]
)
except Exception as e:
print(f"Error: {e}")
return None
# Configure email settings
config = EmailConfig(
imap_server="imap.gmail.com",
smtp_server="smtp.gmail.com",
email=os.getenv("EMAIL_ADDRESS"),
password=os.getenv("EMAIL_PASSWORD")
)
# Create and run the agent
async with EmailAgent(config, message_handler=process_with_openai) as agent:
print(f"AI Email Agent started. Monitoring {config.email}")
try:
while True:
await asyncio.sleep(1)
except KeyboardInterrupt:
print("Stopping...")
```
### Anthropic Computer-Use Agent
PyMailAI can be used with Anthropic's computer-use agent to create an email interface for interacting with the computer. Here's how to set it up:
1. First, install the required dependencies:
```bash
pip install "pymailai[anthropic]"
```
2. Set up your environment variables:
```bash
# Email settings
export EMAIL_ADDRESS="[email protected]"
export EMAIL_PASSWORD="your-app-password"
export EMAIL_IMAP_SERVER="imap.gmail.com"
export EMAIL_SMTP_SERVER="smtp.gmail.com"
# Anthropic API key
export ANTHROPIC_API_KEY="your-anthropic-key"
```
3. Run the computer-use agent example:
```bash
python examples/anthropic_computer_agent.py
```
This will start an email agent that:
- Monitors your inbox for new emails
- Processes them using Anthropic's computer-use agent
- Sends back the results via email
- Supports all computer-use capabilities (bash commands, file editing, etc.)
Example usage:
1. Send an email to your configured email address
2. The agent will process your request using Anthropic's computer-use capabilities
3. Results will be sent back as email replies
4. The agent maintains conversation context between emails
### Using with Any LLM Code
PyMailAI can wrap any existing LLM code. Just use the email body as your prompt:
```python
async def your_llm_handler(message: EmailData):
"""Use any LLM code here."""
# Get prompt from email
prompt = message.body_text
# Process with your LLM code
response = your_llm_function(prompt) # Your existing LLM code
# Send result back via email
return EmailData(
message_id="",
subject=f"Re: {message.subject}",
from_address=message.to_addresses[0],
to_addresses=[message.from_address],
cc_addresses=[],
body_text=response,
body_html=None,
timestamp=message.timestamp,
in_reply_to=message.message_id,
references=[message.message_id]
)
```
## Configuration
The package uses environment variables for configuration:
```bash
# Email settings
export EMAIL_ADDRESS="[email protected]"
export EMAIL_PASSWORD="your-app-password"
export EMAIL_IMAP_SERVER="imap.gmail.com" # Optional, default: imap.gmail.com
export EMAIL_SMTP_SERVER="smtp.gmail.com" # Optional, default: smtp.gmail.com
# Your LLM API keys
export OPENAI_API_KEY="your-openai-key"
export ANTHROPIC_API_KEY="your-anthropic-key"
# ... other API keys as needed
```
## Documentation
Full documentation is available at [https://tomatyss.github.io/PyMailAI/](https://tomatyss.github.io/PyMailAI/)
## More Examples
Check the `examples/` directory for more examples:
- `openai_completion.py`: Basic OpenAI integration
- `anthropic_computer_agent.py`: Anthropic computer-use agent
- `ollama_completion.py`: Local LLM integration with Ollama
- `simple_ai_agent.py`: Template for custom agents
### Ollama Integration
To use PyMailAI with Ollama's local LLM models:
1. Install the required dependencies:
```bash
pip install "pymailai[ollama]"
```
2. Install and start Ollama from https://ollama.ai, then pull the model:
```bash
ollama pull llama3.2
```
3. Set up your environment variables:
```bash
export EMAIL_ADDRESS="[email protected]"
export EMAIL_PASSWORD="your-email-password"
export EMAIL_IMAP_SERVER="your-imap-server"
export EMAIL_SMTP_SERVER="your-smtp-server"
export EMAIL_IMAP_PORT="993"
export EMAIL_SMTP_PORT="465"
```
4. Run the Ollama example:
```bash
python examples/ollama_completion.py
```
## Contributing
### Development Setup
1. Install development dependencies:
```bash
make install
```
This will install all dev dependencies and set up pre-commit hooks.
### Code Quality
We use pre-commit hooks to ensure code quality. The hooks run automatically on commit and include:
- black (code formatting)
- isort (import sorting)
- flake8 (linting)
- mypy (type checking)
To manually install the pre-commit hooks:
```bash
make install-hooks
```
### Building Documentation
To build the documentation locally:
```bash
# Install Sphinx and theme
pip install sphinx sphinx-rtd-theme
# Build the docs
cd docs
make html
# View the docs (macOS)
open build/html/index.html
```
## License
MIT License