waldiez 0.1.11

waldiez

Waldiez

Translate a Waldiez flow:

To a python script or a jupyter notebook with the corresponding ag2 agents and chats.

Features

• Export .waldiez flows to .py or .ipynb
• Run a .waldiez flow
• Include a logs folder with the logs of the flow in csv format
• Provide a custom IOSStream to handle input and output.

Installation

On PyPI:

python -m pip install waldiez

From the repository:

python -m pip install git+https://github.com/waldiez/waldiez.git

Usage

CLI

# Export a Waldiez flow to a python script or a jupyter notebook
waldiez --export /path/to/a/flow.waldiez --output /path/to/an/output/flow[.py|.ipynb]
# Export and run the script, optionally force generation if the output file already exists
waldiez /path/to/a/flow.waldiez --output /path/to/an/output/flow[.py] [--force]

Using docker/podman

CONTAINER_COMMAND=docker # or podman
# pull the image
$CONTAINER_COMMAND pull waldiez/waldiez
# Export a Waldiez flow to a python script or a jupyter notebook
$CONTAINER_COMMAND run \
  --rm \
  -v /path/to/a/flow.waldiez:/flow.waldiez \
  -v /path/to/an/output:/output \
  waldiez/waldiez --export /flow.waldiez --output /output/flow[.py|.ipynb]

# with selinux and/or podman, you might get permission (or file not found) errors, so you can try:
$CONTAINER_COMMAND run \
  --rm \
  -v /path/to/a/flow.waldiez:/flow.waldiez \
  -v /path/to/an/output:/output \
  --userns=keep-id \
  --security-opt label=disable \
  waldiez/waldiez --export /flow.waldiez --output /output/flow[.py|.ipynb]

# Export and run the script
$CONTAINER_COMMAND run --rm -v /path/to/a/flow.waldiez:/flow.waldiez -v /path/to/an/output:/output waldiez/waldiez /flow.waldiez --output /output/output[.py]

As a library

Export a flow

# Export a Waldiez flow to a python script or a jupyter notebook
from waldiez import WaldiezExporter
flow_path = "/path/to/a/flow.waldiez"
output_path = "/path/to/an/output.py"  # or .ipynb
exporter = WaldiezExporter.load(flow_path)
exporter.export(output_path)

Run a flow

# Run a flow
from waldiez import WaldiezRunner
flow_path = "/path/to/a/flow.waldiez"
output_path = "/path/to/an/output.py"
runner = WaldiezRunner.load(flow_path)
runner.run(output_path=output_path)

Run a flow with a custom IOStream

# Run the flow with a custom IOStream
# In case the standard 'input' and 'print' functions cannot be used
import time
import threading

from typing import Any

from waldiez import WaldiezRunner
from waldiez.io import WaldiezIOStream

flow_path = "/path/to/a/flow.waldiez"
output_path = "/path/to/an/output.py"


def custom_print_function(*args: Any, sep: str = " ", **kwargs: Any) -> None:
    """Custom print function."""
    print(*args, sep=sep, **kwargs)


# Custom input handler
class InputProcessorWrapper:
    """Wrapper input processor.
    
    To manage the interaction between the custom input processor and IOStream.
    """

    def __init__(self):
        self.stream = None  # Placeholder for the WaldiezIOStream instance
        self.lock = threading.Lock()  # Ensure thread-safe operations

    def custom_input_processor(self, prompt: str) -> None:
        """Simulate external input and send it back to the IOStream."""
        def external_input_simulation():
            with self.lock:  # Ensure thread-safe access
                time.sleep(2)  # Simulate delay for network input
                if self.stream:
                    self.stream.set_input("Simulated external input")
                else:
                    raise RuntimeError("Stream reference not set!")

        threading.Thread(target=external_input_simulation, daemon=True).start()

    def set_stream(self, stream: "WaldiezIOStream"):
        """Set the WaldiezIOStream instance."""
        with self.lock:  # Ensure thread-safe setting of the stream
            self.stream = stream

processor_wrapper = InputProcessorWrapper()

stream = WaldiezIOStream(
    input_timeout=30,
    print_function=
    on_prompt_input=processor_wrapper.custom_input_processor,
)

# Link the processor wrapper to the WaldiezIOStream instance
processor_wrapper.set_stream(custom_stream)

with WaldiezIOStream.set_default(io_stream):
    runner = WaldiezRunner.load(flow_path)
    runner.run(stream=io_stream, output_path=output_path)

Tools

• ag2 (formerly AutoGen)
• juptytext
• pydantic

Known Conflicts

• autogen-agentchat: This package conflicts with ag2. Ensure that autogen-agentchat is uninstalled before installing waldiez. If you have already installed autogen-agentchat, you can uninstall it with the following command:

  pip uninstall autogen-agentchat -y
  

  If already installed waldiez you might need to reinstall it after uninstalling autogen-agentchat:

  pip install --force --no-cache waldiez
  

License

This project is licensed under the MIT License - see the LICENSE file for details.