Metadata-Version: 2.1
Name: langgraph-codegen
Version: 0.1.26
Summary: Generate graph code from DSL for LangGraph framework
Home-page: https://github.com/jojohannsen/langgraph-codegen
Author: Johannes Johannsen
Author-email: johannes.johannsen@gmail.com
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: colorama>=0.4.6
Requires-Dist: rich>=13.3.1

# langgraph-codegen
##### Quick Start

To generate a graph from text:

```bash
# View available example graphs, 'plan_and_execute' is one of the examples
lgcodegen --list

# View contents of a graph file
lgcodegen plan_and_execute

# Generate different components
lgcodegen --graph plan_and_execute    # Generate graph code
lgcodegen --nodes plan_and_execute    # Generate node code
lgcodegen --conditions plan_and_execute    # Generate condition code
lgcodegen --state plan_and_execute    # Generate state code

# complete running graph with mocked nodes, state, conditions
# Runnable code in: plan_and_execute/plan_and_execute.py
lgcodegen plan_and_execute --code
python plan_and_execute/plan_and_execute.py
```

##### How to use gen_graph function

Generates python code for parts of langgraph

```python
from langgraph_codegen import gen_graph

graph_spec = """
# required: start with StateClass and first_node
START(StateClass) => first_node

first_node
  should_go_to_second => second_node
  => third_node

second_node => third_node

third_node => END
"""

graph_code = gen_graph("my_graph", graph_spec)
print(graph_code)
```

Output is:
```python
# GENERATED code, creates compiled graph: my_graph
my_graph = StateGraph(StateClass)
my_graph.add_node('first_node', first_node)
my_graph.add_node('should_go_to_second', should_go_to_second)
my_graph.add_node('second_node', second_node)
my_graph.add_node('third_node', third_node)
my_graph.add_edge(START, 'first_node')
my_graph.add_edge('should_go_to_second', 'second_node')
my_graph.add_edge('should_go_to_second', 'third_node')
my_graph.add_edge('second_node', 'third_node')
my_graph.add_edge('third_node', END)

my_graph = my_graph.compile()
```

#### Syntax

```START(StateClass) => first_node``` required

```# anything after pound sign is ignored```

```node_1 => node_2``` unconditional edge

```python
node_X
  condition_A => node_Y
  condition_B => node_Z
  => END  # unconditional if all above conditions fail
```

```node_1 => node_2, node_3``` ok to transition to multiple nodes.

##### Why This DSL Was Made

The main thing I want to do is condense larger patterns into the DSL, to make it easier to experiment with and evaluate graph architectures.

The thing I like about the code with the DSL is that both Nodes and Conditional Edges are represented by functions that take the Graph State as a parameter.  The second thing I like about it is that Nodes have a single name, it's in the text graph, and there's a function with that name.

The langgraph graph GraphBuilder is way more flexible, but in many cases an equivalent DSL version is easier to understand and easier to modify, and easier to experiment with different graph architectures.
