Merge pull request #1 from lmnr-ai:flow

Flow

.github/workflows/publish.yml

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+name: Publish Python Package
+
+on:
+  push:
+    branches: ["main"]
+
+permissions:
+  contents: read
+
+jobs:
+  publish:
+    runs-on: ubuntu-latest
+    steps:
+    - uses: actions/checkout@v4
+    - name: Install uv
+      uses: astral-sh/setup-uv@v4
+    - name: Set up Python
+      uses: actions/setup-python@v5
+      with:
+        python-version: '3.10'
+    - name: Install the project
+      run: uv sync --all-extras --dev
+    - name: Build package
+      run: uv build
+    - name: Publish package
+      uses: pypa/gh-action-pypi-publish@release/v1

.gitignore

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+.DS_Store
+
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+cover/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+.pybuilder/
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+#   For a library or package, you might want to ignore these files since the code is
+#   intended to run in multiple environments; otherwise, check them in:
+# .python-version
+
+# pipenv
+#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+#   However, in case of collaboration, if having platform-specific dependencies or dependencies
+#   having no cross-platform support, pipenv may install dependencies that don't work, or not
+#   install all needed dependencies.
+#Pipfile.lock
+
+# poetry
+#   Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
+#   This is especially recommended for binary packages to ensure reproducibility, and is more
+#   commonly ignored for libraries.
+#   https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
+#poetry.lock
+
+# pdm
+#   Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
+#pdm.lock
+#   pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
+#   in version control.
+#   https://pdm.fming.dev/latest/usage/project/#working-with-version-control
+.pdm.toml
+.pdm-python
+.pdm-build/
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
+
+# pytype static type analyzer
+.pytype/
+
+# Cython debug symbols
+cython_debug/
+
+# PyCharm
+#  JetBrains specific template is maintained in a separate JetBrains.gitignore that can
+#  be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
+#  and can be added to the global gitignore or merged into this file.  For a more nuclear
+#  option (not recommended) you can uncomment the following to ignore the entire idea folder.
+#.idea/

.vscode/settings.json

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+{
+  "[python]": {
+    "editor.codeActionsOnSave": {
+      "source.fixAll": "explicit",
+      "source.organizeImports": "explicit"
+    },
+    "editor.defaultFormatter": "charliermarsh.ruff"
+  }
+}

README.md

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+# Laminar Flow
+
+A lightweight task engine for building AI agents that prioritizes simplicity and flexibility.
+
+## Core Concept
+
+Unlike traditional node-based workflows, Laminar Flow uses a dynamic task queue system built on three simple principles:
+
+1. **Concurrent Execution** - Tasks run in parallel automatically
+2. **Dynamic Scheduling** - Tasks can schedule new tasks at runtime
+3. **Smart Dependencies** - Tasks can await results from previous operations
+
+Results of all tasks are stored in a thread-safe `Context`.
+
+This task-based architecture makes complex workflows surprisingly simple:
+
+✨ **What's Possible:**
+- [x] Parallel task execution without explicit threading code
+- [x] Self-modifying dynamic workflows and cycles
+- [x] Conditional branching and control flow
+- [x] Streaming of tasks execution
+- [x] Automatic state management and persistence
+
+Flow is extremely lightweight, clearly written and has not external dependencies for the engine.
+
+## Getting started
+
+### Basic Usage
+```python
+from concurrent.futures import ThreadPoolExecutor
+from lmnr_flow import Flow, TaskOutput
+
+flow = Flow(thread_pool_executor=ThreadPoolExecutor(max_workers=4))
+
+# Simple task that returns a result
+def my_task(context: Context) -> TaskOutput:
+    return TaskOutput(output="Hello World!", next=None)
+
+flow.add_task("greet", my_task)
+result = flow.run("greet")  # Returns {"greet": "Hello World!"}
+```
+
+### Task Chaining
+```python
+# Tasks can trigger other tasks
+def task1(context: Context) -> TaskOutput:
+    return TaskOutput(output="result1", next=["task2"])
+
+def task2(context: Context) -> TaskOutput:
+    # Access results from previous tasks
+    t1_result = context.get("task1")  # Gets "result1"
+    return TaskOutput(output="result2", next=None)
+
+flow.add_task("task1", task1)
+flow.add_task("task2", task2)
+flow.run("task1")  # Returns {"task2": "result2"}
+```
+
+### Parallel Execution
+```python
+def starter(context: Context) -> TaskOutput:
+    # Launch multiple tasks in parallel
+    return TaskOutput(output="started", next=["slow_task1", "slow_task2"])
+
+def slow_task1(context: Context) -> TaskOutput:
+    time.sleep(1)
+    return TaskOutput(output="result1", next=None)
+
+def slow_task2(context: Context) -> TaskOutput:
+    time.sleep(1)
+    return TaskOutput(output="result2", next=None)
+
+# Both slow_tasks execute in parallel, taking ~1 second total
+flow.add_task("starter", starter)
+flow.add_task("slow_task1", slow_task1)
+flow.add_task("slow_task2", slow_task2)
+flow.run("starter")
+```
+
+### Streaming Results
+```python
+def streaming_task(context: Context) -> TaskOutput:
+    # Stream intermediate results
+    stream = context.get_stream()
+    for i in range(3):
+        stream.put(("streaming_task", f"interim_{i}"))
+    return TaskOutput(output="final", next=None)
+
+flow.add_task("streaming_task", streaming_task)
+
+# Get results as they arrive
+for task_id, output in flow.stream("streaming_task"):
+    print(f"{task_id}: {output}")
+    # Prints:
+    # streaming_task: interim_0
+    # streaming_task: interim_1
+    # streaming_task: interim_2
+    # streaming_task: final
+```
+
+### Dynamic Workflows
+```python
+def conditional_task(context: Context) -> TaskOutput:
+    count = context.get("count", 0)
+
+    if count >= 3:
+        return TaskOutput(output="done", next=["finish"])
+
+    context.set("count", count + 1)
+    return TaskOutput(output=f"iteration_{count}", next=["conditional_task"])
+
+# Task will loop 3 times before finishing
+flow.add_task("conditional_task", conditional_task)
+flow.add_task("finish", lambda ctx: TaskOutput("completed", None))
+flow.run("conditional_task")
+```
+
+### Input Parameters
+```python
+def parameterized_task(context: Context) -> TaskOutput:
+    name = context.get("user_name")
+    return TaskOutput(output=f"Hello {name}!", next=None)
+
+flow.add_task("greet", parameterized_task)
+result = flow.run("greet", inputs={"user_name": "Alice"})
+# Returns {"greet": "Hello Alice!"}
+```
+
+## Advanced Features
+
+- **Context Sharing**: All tasks share the same context, allowing for complex data flows
+- **Error Handling**: Exceptions in tasks are properly propagated
+- **Thread Safety**: All operations are thread-safe
+- **Minimal Dependencies**: Core engine has zero external dependencies
+
+## Roadmap
+- [ ] Add async
+- [ ] Serverless deployment
+- [ ] Timetravel UI

pyproject.toml

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+[build-system]
+requires = ["hatchling"]
+build-backend = "hatchling.build"
+
+[project]
+name = "lmnr-flow"
+version = "0.1.0b1"
+description = "Lightweight task engine for building AI agents"
+readme = "README.md"
+requires-python = ">=3.10"
+
+dependencies = [
+    "lmnr>=0.4.43",
+    "pytest>=8.3.3",
+]
+
+[project.urls]
+"Homepage" = "https://github.com/lmnr-ai/flow"
+"Bug Tracker" = "https://github.com/lmnr-ai/flow/issues"
+
+[project.license]
+file = "LICENSE"

src/lmnr_flow/__init__.py

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+from .context import Context
+from .flow import Flow, TaskOutput
+from .state import State