Zack
1 year ago
commit
e9b2800815
@ -0,0 +1,19 @@
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---
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name: Docker Image CI
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on: # yamllint disable-line rule:truthy
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push:
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branches: ["master"]
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pull_request:
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branches: ["master"]
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jobs:
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build:
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runs-on: ubuntu-latest
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name: Build Docker image
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steps:
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- uses: actions/checkout@v4
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- name: Build the Docker image
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run: docker build . --file Dockerfile --tag my-image-name:$(date +%s)
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@ -0,0 +1,98 @@
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name: Docker
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# This workflow uses actions that are not certified by GitHub.
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# They are provided by a third-party and are governed by
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# separate terms of service, privacy policy, and support
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# documentation.
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on:
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schedule:
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- cron: '31 19 * * *'
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push:
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branches: [ "master" ]
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# Publish semver tags as releases.
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tags: [ 'v*.*.*' ]
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pull_request:
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branches: [ "master" ]
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env:
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# Use docker.io for Docker Hub if empty
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REGISTRY: ghcr.io
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# github.repository as <account>/<repo>
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IMAGE_NAME: ${{ github.repository }}
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jobs:
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build:
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runs-on: ubuntu-latest
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permissions:
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contents: read
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packages: write
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# This is used to complete the identity challenge
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# with sigstore/fulcio when running outside of PRs.
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id-token: write
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steps:
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- name: Checkout repository
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uses: actions/checkout@v4
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# Install the cosign tool except on PR
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# https://github.com/sigstore/cosign-installer
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- name: Install cosign
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if: github.event_name != 'pull_request'
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uses: sigstore/cosign-installer@1fc5bd396d372bee37d608f955b336615edf79c8 #v3.2.0
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with:
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cosign-release: 'v2.1.1'
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# Set up BuildKit Docker container builder to be able to build
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# multi-platform images and export cache
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# https://github.com/docker/setup-buildx-action
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- name: Set up Docker Buildx
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uses: docker/setup-buildx-action@f95db51fddba0c2d1ec667646a06c2ce06100226 # v3.0.0
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# Login against a Docker registry except on PR
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# https://github.com/docker/login-action
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- name: Log into registry ${{ env.REGISTRY }}
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if: github.event_name != 'pull_request'
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uses: docker/login-action@343f7c4344506bcbf9b4de18042ae17996df046d # v3.0.0
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with:
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registry: ${{ env.REGISTRY }}
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username: ${{ github.actor }}
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password: ${{ secrets.GITHUB_TOKEN }}
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# Extract metadata (tags, labels) for Docker
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# https://github.com/docker/metadata-action
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- name: Extract Docker metadata
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id: meta
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uses: docker/metadata-action@31cebacef4805868f9ce9a0cb03ee36c32df2ac4 # v5.3.0
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with:
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images: ${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}
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# Build and push Docker image with Buildx (don't push on PR)
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# https://github.com/docker/build-push-action
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- name: Build and push Docker image
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id: build-and-push
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uses: docker/build-push-action@4a13e500e55cf31b7a5d59a38ab2040ab0f42f56 # v5.1.0
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with:
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context: .
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push: ${{ github.event_name != 'pull_request' }}
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tags: ${{ steps.meta.outputs.tags }}
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labels: ${{ steps.meta.outputs.labels }}
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cache-from: type=gha
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cache-to: type=gha,mode=max
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# Sign the resulting Docker image digest except on PRs.
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# This will only write to the public Rekor transparency log when the Docker
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# repository is public to avoid leaking data. If you would like to publish
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# transparency data even for private images, pass --force to cosign below.
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# https://github.com/sigstore/cosign
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- name: Sign the published Docker image
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if: ${{ github.event_name != 'pull_request' }}
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env:
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# https://docs.github.com/en/actions/security-guides/security-hardening-for-github-actions#using-an-intermediate-environment-variable
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TAGS: ${{ steps.meta.outputs.tags }}
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DIGEST: ${{ steps.build-and-push.outputs.digest }}
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# This step uses the identity token to provision an ephemeral certificate
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# against the sigstore community Fulcio instance.
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run: echo "${TAGS}" | xargs -I {} cosign sign --yes {}@${DIGEST}
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@ -0,0 +1,34 @@
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name: Python Package using Conda
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on: [push]
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jobs:
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build-linux:
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runs-on: ubuntu-latest
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strategy:
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max-parallel: 5
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steps:
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- uses: actions/checkout@v4
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- name: Set up Python 3.10
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uses: actions/setup-python@v5
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with:
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python-version: '3.10'
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- name: Add conda to system path
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run: |
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# $CONDA is an environment variable pointing to the root of the miniconda directory
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echo $CONDA/bin >> $GITHUB_PATH
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- name: Install dependencies
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run: |
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conda env update --file environment.yml --name base
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- name: Lint with flake8
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run: |
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conda install flake8
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# stop the build if there are Python syntax errors or undefined names
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flake8 . --count --select=E9,F63,F7,F82 --show-source --statistics
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# exit-zero treats all errors as warnings. The GitHub editor is 127 chars wide
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flake8 . --count --exit-zero --max-complexity=10 --max-line-length=127 --statistics
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- name: Test with pytest
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run: |
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conda install pytest
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pytest
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@ -1,18 +1,14 @@
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import os
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from dotenv import load_dotenv
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from swarms.models.gemini import Gemini
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load_dotenv()
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api_key = os.environ["GEMINI_API_KEY"]
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# Initialize the model
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model = Gemini(gemini_api_key=api_key)
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model = Gemini(
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gemini_api_key="A",
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)
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# Establish the prompt and image
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task = "What is your name"
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img = "images/github-banner-swarms.png"
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# Run the model
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out = model.run("What is your name?", img=img)
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out = model.run("What is your name?", img)
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print(out)
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@ -0,0 +1 @@
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27dcfa74d334bc871f3234de431e71c6eeba5dd6
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@ -0,0 +1 @@
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../../blobs/2d74da6615135c58cf3cf9ad4cb11e7c613ff9e55fe658a47ab83b6c8d1174a9
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@ -1,78 +1,132 @@
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from dataclasses import dataclass, field
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from typing import (
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Any,
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Callable,
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Dict,
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List,
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Union,
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)
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from dataclass import dataclass, field
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from swarms.structs.agent import Agent
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from typing import Optional
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from typing import List, Dict, Any, Sequence
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# Define a generic Task that can handle different types of callable objects
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@dataclass
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class Task:
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"""
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Task class for running a task in a sequential workflow.
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Task is a unit of work that can be executed by a set of agents.
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A task is defined by a task name and a set of agents that can execute the task.
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The task can also have a set of dependencies, which are the names of other tasks
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that must be executed before this task can be executed.
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Args:
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description (str): The description of the task.
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agent (Union[Callable, Agent]): The model or agent to execute the task.
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args (List[Any]): Additional arguments to pass to the task execution.
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kwargs (Dict[str, Any]): Additional keyword arguments to pass to the task execution.
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result (Any): The result of the task execution.
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history (List[Any]): The history of the task execution.
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id (str): The name of the task.
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description (Optional[str]): A description of the task.
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task (str): The name of the task.
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result (Any): The result of the task.
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agents (Sequence[Agent]): A list of agents that can execute the task.
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dependencies (List[str], optional): A list of task names that must be executed before this task can be executed. Defaults to [].
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args (List[Any], optional): A list of arguments to pass to the agents. Defaults to field(default_factory=list).
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kwargs (List[Any], optional): A list of keyword arguments to pass to the agents. Defaults to field(default_factory=list).
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Methods:
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execute: Execute the task.
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execute: Executes the task by passing the results of the parent tasks to the agents.
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Examples:
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>>> from swarms.structs import Task, Agent
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>>> from swarms.models import OpenAIChat
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>>> agent = Agent(llm=OpenAIChat(openai_api_key=""), max_loops=1, dashboard=False)
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>>> task = Task(description="What's the weather in miami", agent=agent)
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>>> task.execute()
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>>> task.result
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import os
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from swarms.models import OpenAIChat
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from swarms.structs import Agent
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from swarms.structs.sequential_workflow import SequentialWorkflow
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from dotenv import load_dotenv
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"""
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load_dotenv()
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# Load the environment variables
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api_key = os.getenv("OPENAI_API_KEY")
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# Initialize the language agent
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llm = OpenAIChat(
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openai_api_key=api_key,
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temperature=0.5,
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max_tokens=3000,
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)
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# Initialize the agent with the language agent
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agent1 = Agent(llm=llm, max_loops=1)
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description: str
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agent: Union[Callable, Agent]
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args: List[Any] = field(default_factory=list)
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kwargs: Dict[str, Any] = field(default_factory=dict)
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result: Any = None
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history: List[Any] = field(default_factory=list)
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# logger = logging.getLogger(__name__)
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# Create another agent for a different task
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agent2 = Agent(llm=llm, max_loops=1)
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# Create the workflow
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workflow = SequentialWorkflow(max_loops=1)
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# Add tasks to the workflow
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workflow.add(
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agent1, "Generate a 10,000 word blog on health and wellness.",
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)
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# Suppose the next task takes the output of the first task as input
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workflow.add(
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agent2, "Summarize the generated blog",
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)
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# Run the workflow
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workflow.run()
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# Output the results
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for task in workflow.tasks:
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print(f"Task: {task.description}, Result: {task.result}")
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def execute(self):
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"""
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Execute the task.
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Raises:
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ValueError: If a Agent instance is used as a task and the 'task' argument is not provided.
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def __init__(
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self,
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id: str,
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description: Optional[str],
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task: str,
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result: Any,
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agents: Sequence[Agent],
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dependencies: List[str] = [],
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args: List[Any] = field(default_factory=list),
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kwargs: List[Any] = field(default_factory=list),
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):
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self.id = id
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self.description = description
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self.task = task
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self.result = result
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self.agents = agents
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self.dependencies = dependencies
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self.results = []
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self.args = args
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self.kwargs = kwargs
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||||
def execute(self, parent_results: Dict[str, Any]):
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"""Executes the task by passing the results of the parent tasks to the agents.
|
||||
|
||||
Args:
|
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parent_results (Dict[str, Any]): A dictionary of task names and their results.
|
||||
|
||||
Examples:
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||||
"""
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||||
if isinstance(self.agent, Agent):
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# Add a prompt to notify the Agent of the sequential workflow
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||||
args = [parent_results[dep] for dep in self.dependencies]
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for agent in self.agents:
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if isinstance(agent, Agent):
|
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if "prompt" in self.kwargs:
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self.kwargs["prompt"] += (
|
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f"\n\nPrevious output: {self.result}"
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||||
if self.result
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||||
f"\n\nPrevious output: {self.results[-1]}"
|
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if self.results
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||||
else ""
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||||
)
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else:
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self.kwargs["prompt"] = (
|
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f"Main task: {self.description}"
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+ (
|
||||
f"\n\nPrevious output: {self.result}"
|
||||
if self.result
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||||
f"\n\nPrevious output: {self.results[-1]}"
|
||||
if self.results
|
||||
else ""
|
||||
)
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||||
)
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self.result = self.agent.run(*self.args, **self.kwargs)
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result = agent.run(
|
||||
self.description, *args, **self.kwargs
|
||||
)
|
||||
else:
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||||
self.result = self.agent(*self.args, **self.kwargs)
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||||
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||||
self.history.append(self.result)
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||||
result = agent(self.description, *args, **self.kwargs)
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self.results.append(result)
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args = [result]
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self.history.append(result)
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@ -0,0 +1,86 @@
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import uuid
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||||
|
||||
from swarms.telemetry.user_utils import (
|
||||
generate_unique_identifier,
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||||
generate_user_id,
|
||||
get_machine_id,
|
||||
get_system_info,
|
||||
)
|
||||
|
||||
# Helper functions tests
|
||||
def test_generate_user_id():
|
||||
# Generate user IDs and ensure they are UUID strings
|
||||
user_id = generate_user_id()
|
||||
assert isinstance(user_id, str)
|
||||
assert uuid.UUID(user_id, version=4)
|
||||
|
||||
|
||||
def test_get_machine_id():
|
||||
# Get machine ID and ensure it's a valid SHA-256 hash
|
||||
machine_id = get_machine_id()
|
||||
assert isinstance(machine_id, str)
|
||||
assert len(machine_id) == 64
|
||||
assert all(char in "0123456789abcdef" for char in machine_id)
|
||||
|
||||
|
||||
def test_get_system_info():
|
||||
# Get system information and ensure it's a dictionary with expected keys
|
||||
system_info = get_system_info()
|
||||
assert isinstance(system_info, dict)
|
||||
expected_keys = [
|
||||
"platform",
|
||||
"platform_release",
|
||||
"platform_version",
|
||||
"architecture",
|
||||
"hostname",
|
||||
"ip_address",
|
||||
"mac_address",
|
||||
"processor",
|
||||
"python_version",
|
||||
]
|
||||
assert all(key in system_info for key in expected_keys)
|
||||
|
||||
|
||||
def test_generate_unique_identifier():
|
||||
# Generate unique identifiers and ensure they are valid UUID strings
|
||||
unique_id = generate_unique_identifier()
|
||||
assert isinstance(unique_id, str)
|
||||
assert uuid.UUID(
|
||||
unique_id, version=5, namespace=uuid.NAMESPACE_DNS
|
||||
)
|
||||
|
||||
|
||||
def test_generate_user_id_edge_case():
|
||||
# Test generate_user_id with multiple calls
|
||||
user_ids = set()
|
||||
for _ in range(100):
|
||||
user_id = generate_user_id()
|
||||
user_ids.add(user_id)
|
||||
assert len(user_ids) == 100 # Ensure generated IDs are unique
|
||||
|
||||
|
||||
def test_get_machine_id_edge_case():
|
||||
# Test get_machine_id with multiple calls
|
||||
machine_ids = set()
|
||||
for _ in range(100):
|
||||
machine_id = get_machine_id()
|
||||
machine_ids.add(machine_id)
|
||||
assert len(machine_ids) == 100 # Ensure generated IDs are unique
|
||||
|
||||
|
||||
def test_get_system_info_edge_case():
|
||||
# Test get_system_info for consistency
|
||||
system_info1 = get_system_info()
|
||||
system_info2 = get_system_info()
|
||||
assert (
|
||||
system_info1 == system_info2
|
||||
) # Ensure system info remains the same
|
||||
|
||||
|
||||
def test_generate_unique_identifier_edge_case():
|
||||
# Test generate_unique_identifier for uniqueness
|
||||
unique_ids = set()
|
||||
for _ in range(100):
|
||||
unique_id = generate_unique_identifier()
|
||||
unique_ids.add(unique_id)
|
||||
assert len(unique_ids) == 100 # Ensure generated IDs are unique
|
||||
Loading…
Reference in new issue