flamepy 0.6.0rc1

Python SDK for Flame, a distributed system for Agentic AI

Flame Python SDK

Python SDK for the Flame, a distributed system for Agentic AI.

For the user guide, see Flame Python SDK. For the detailed API surface, see API.md.

Installation

pip install flamepy

Quick Start

import flamepy

def main():
    # Create a session with the application, e.g. Agent
    session = flamepy.create_session("flmping")
    
    # Create and run a task
    resp = session.invoke(b"task input data")

    # Handle the output of task
    print(resp)

    # Close session
    session.close()

if __name__ == "__main__":
    main()

Verify A Runner Cluster

After configuring ~/.flame/flame.yaml for a running cluster with session manager, object cache, executor manager, and the flmrun template application, run:

python -m flamepy.runner.e2e

Installed wheels also provide:

flamepy-runner-e2e

The check packages a tiny temporary project and verifies Runner function calls, ObjectFuture chaining, and a stateful instance service. Use --json for machine-readable output and --python-version 3.12 to verify a specific executor Python runtime.

API Reference

Session

Represents a computing session with application, e.g. Agent, Tools.

# Create a session
session = flamepy.create_session("my-app")

# Close a session
session.close()

Task

Represents individual computing tasks within a session.

from concurrent.futures import wait

# Run a task synchronously (blocks until complete)
result = session.invoke(b"input data")

# Run a task asynchronously (returns Future immediately)
future = session.run(b"input data")
result = future.result()  # Wait for completion

# Run multiple tasks in parallel
futures = [session.run(f"input {i}".encode()) for i in range(10)]
wait(futures)  # Wait for all tasks to complete
results = [f.result() for f in futures]

# Create a task and get task object
task = session.create_task(b"input data")

# Get task status
task = session.get_task(task.id)

# Watch task progress
for update in session.watch_task(task.id):
    print(f"Task state: {update.state}")
    if update.is_completed():
        break

Error Handling

The SDK provides custom exception types for different error scenarios:

from flamepy import FlameError, FlameErrorCode

try:
    session = flamepy.create_session("flmping")
except FlameError as e:
    if e.code == FlameErrorCode.INVALID_CONFIG:
        print("Configuration error:", e.message)
    elif e.code == FlameErrorCode.INVALID_STATE:
        print("State error:", e.message)

Development

To set up the development environment:

# Clone the repository
git clone https://github.com/xflops/flame.git
cd flame/sdk/python

# Install in development mode
# Note: Use --no-build-isolation if you have setuptools>=61.0 installed
python3 -m pip install -e . --user --no-build-isolation

# Or build and install the wheel
python3 -m build --wheel --no-isolation
python3 -m pip install dist/flamepy-0.6.0rc1-py3-none-any.whl --user

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

# Run tests
pytest

# Format code
ruff format

# Type checking
mypy flamepy/

Requirements

• Python >= 3.9
• setuptools >= 61.0 (for building from source)

Troubleshooting

If you encounter issues with the package name showing as "UNKNOWN":

1. Make sure you have setuptools>=61.0 installed:

   python3 -m pip install --user --upgrade "setuptools>=61.0"
   

2. Clean any stale build artifacts:

   rm -rf dist build src/flamepy.egg-info *.egg-info
   

3. Use --no-build-isolation flag when installing:

   python3 -m pip install . --user --no-build-isolation