Files
langgraph/libs/cli/generate_schema.py
T
51f6cee1b1 chore: uv lock resolution (#7342)
## Summary

Adds native uv workspace/lockfile support to the LangGraph CLI's Docker
build pipeline. Instead of listing dependencies manually, users can
point at their existing `uv.lock` and the CLI will:

1. Discover workspace packages and their dependency graph
2. Export locked requirements via `uv export --package <name> --frozen`
3. Copy only the necessary workspace closure into the container
4. Install packages in dependency order with `--no-deps` for
reproducibility
5. Rewrite all import paths (graphs, auth, encryption, etc.) to
container paths

### New config field: `source`

Rather than using `pip` or `uv pip`, we add a new `uv_lock` installer.
The previous installers should still remain unchanged.

To avoid ambiguity, we discriminate by "source" field and **do not
permit** other arbitrary "dependencies". In this mode, we will treat the
provided root (defaults to the current directory) as the source of
truth.

This also would natively support uv workspaces, so you can specify the
target package within a larger workspace.

**Simple single-package project:**
```json
{
  "python_version": "3.11",
  "graphs": {
    "agent": "./agent.py:graph"
  },
  "source": {
    "kind": "uv"
  }
}
```

**Multi-package workspace with explicit package:**
```json
{
  "python_version": "3.11",
  "graphs": {
    "agent": "../../apps/agent/src/agent/graph.py:graph"
  },
  "source": {
    "kind": "uv",
    "root": "../..",
    "package": "agent"
  }
}
```

**Traditional pip deployment (unchanged):**
```json
{
  "python_version": "3.11",
  "dependencies": ["langgraph", "my-package"],
  "graphs": {
    "agent": "./agent.py:graph"
  }
}
```

Config validation enforces mutual exclusivity. you must use either
`dependencies` or `source`, not both.

---------

Co-authored-by: Will Fu-Hinthorn <will@langchain.dev>
2026-04-07 17:17:54 -07:00

297 lines
10 KiB
Python

#!/usr/bin/env python3
"""
Script to generate a JSON schema for the langgraph-cli Config class.
This script creates a schema.json file that can be referenced in langgraph.json files
to provide IDE autocompletion and validation.
"""
import inspect
import json
import textwrap
from pathlib import Path
import msgspec
from langgraph_cli.schemas import (
AuthConfig,
CacheConfig,
CheckpointerConfig,
Config,
ConfigurableHeaderConfig,
CorsConfig,
GraphDef,
HttpConfig,
IndexConfig,
SecurityConfig,
SerdeConfig,
StoreConfig,
ThreadTTLConfig,
TTLConfig,
WebhooksConfig,
WebhookUrlPolicy,
)
def add_descriptions_to_schema(schema, cls):
"""Add docstring descriptions to the schema properties."""
if schema.get("description"):
schema["description"] = inspect.cleandoc(schema["description"])
elif class_doc := inspect.getdoc(cls):
schema["description"] = inspect.cleandoc(class_doc)
# Get attribute docstrings from the class
attr_docs = {}
# Also check class annotations for docstrings
source_lines = inspect.getsourcelines(cls)[0]
current_attr = None
docstring_lines = []
for line in source_lines:
line = line.strip()
# Check for attribute definition (TypedDict style)
if ":" in line and not line.startswith("#") and not line.startswith('"""'):
parts = line.split(":", 1)
if len(parts) == 2 and parts[0].strip().isidentifier():
# If we were collecting a docstring, save it for the previous attribute
if current_attr and docstring_lines:
attr_docs[current_attr] = "\n".join(docstring_lines).strip('"')
docstring_lines = []
current_attr = parts[0].strip()
# Check for docstring after attribute
elif line.startswith('"""') and current_attr:
# Start or end of a docstring
if len(line) > 3 and line.endswith('"""'):
# Single line docstring
attr_docs[current_attr] = line.strip('"')
current_attr = None
elif docstring_lines:
# End of multi-line docstring
docstring_lines.append(line.rstrip('"'))
attr_docs[current_attr] = "\n".join(docstring_lines).strip('"')
docstring_lines = []
current_attr = None
else:
# Start of multi-line docstring
docstring_lines.append(line.lstrip('"'))
# Continue multi-line docstring
elif docstring_lines and current_attr:
docstring_lines.append(line.strip('"'))
# Add the last docstring if there is one
if current_attr and docstring_lines:
attr_docs[current_attr] = "\n".join(docstring_lines).strip('"')
# Add descriptions to properties
if "properties" in schema:
for prop_name, prop_schema in schema["properties"].items():
# First try to get from attribute docstrings
if prop_name in attr_docs and "description" not in prop_schema:
prop_schema["description"] = textwrap.dedent(attr_docs[prop_name])
# Fall back to class docstring parsing
elif class_doc:
for line in class_doc.split("\n"):
if line.strip().startswith(
f"{prop_name}:"
) or line.strip().startswith(f'"{prop_name}"'):
description = line.split(":", 1)[1].strip()
if description and "description" not in prop_schema:
prop_schema["description"] = description
break
# Recursively process nested definitions
if "$defs" in schema:
for def_name, def_schema in schema["$defs"].items():
# Find the class that corresponds to this definition
for potential_cls in [
Config,
GraphDef,
StoreConfig,
IndexConfig,
AuthConfig,
SecurityConfig,
HttpConfig,
CorsConfig,
CacheConfig,
ThreadTTLConfig,
CheckpointerConfig,
SerdeConfig,
TTLConfig,
ConfigurableHeaderConfig,
WebhooksConfig,
WebhookUrlPolicy,
]:
if potential_cls.__name__ == def_name:
add_descriptions_to_schema(def_schema, potential_cls)
break
return schema
def generate_schema():
"""Generate a JSON schema for the Config class using msgspec."""
# Generate the basic schema
schema = msgspec.json.schema(Config)
# Add title and description
schema["title"] = "LangGraph CLI Configuration"
schema["description"] = "Configuration schema for langgraph-cli"
# Add docstring descriptions
schema = add_descriptions_to_schema(schema, Config)
# Add constraint that only one of python_version or node_version should be specified
config_schema = schema["$defs"]["Config"]
# Create two subschemas: one with python_version and one with node_version
# Define properties specific to Python projects
python_specific_props = ["python_version", "pip_config_file"]
# Define properties specific to Node.js projects
node_specific_props = ["node_version"]
# Define properties common to both project types
common_props = [
k
for k in config_schema["properties"]
if k not in python_specific_props and k not in node_specific_props
]
# Create legacy Python schema with python_version and pip_config_file
legacy_python_schema = {
"type": "object",
"properties": {
# Include Python-specific properties
**{k: config_schema["properties"][k].copy() for k in python_specific_props},
# Include common properties
**{k: config_schema["properties"][k].copy() for k in common_props},
},
"required": ["dependencies", "graphs"],
}
legacy_python_schema["properties"]["pip_installer"] = {
"anyOf": [
{"type": "string", "enum": ["auto", "pip", "uv"]},
{"type": "null"},
]
}
uv_source_python_schema = {
"type": "object",
"properties": {
**{
k: config_schema["properties"][k].copy()
for k in python_specific_props + common_props
},
},
"required": ["graphs", "source"],
}
# source must be a UvSource object (not null)
uv_source_python_schema["properties"]["source"] = {"$ref": "#/$defs/UvSource"}
uv_source_python_schema["properties"]["pip_installer"] = {
"anyOf": [
{"type": "string", "enum": ["auto", "pip", "uv"]},
{"type": "null"},
]
}
# Add enum constraint for python_version
if "python_version" in legacy_python_schema["properties"]:
legacy_python_schema["properties"]["python_version"]["enum"] = [
"3.11",
"3.12",
"3.13",
]
if "python_version" in uv_source_python_schema["properties"]:
uv_source_python_schema["properties"]["python_version"]["enum"] = [
"3.11",
"3.12",
"3.13",
]
# Create Node.js schema with node_version
node_schema = {
"type": "object",
"properties": {
# Include Node-specific properties
**{k: config_schema["properties"][k].copy() for k in node_specific_props},
# Include common properties
**{k: config_schema["properties"][k].copy() for k in common_props},
},
"required": ["node_version", "graphs"],
}
node_schema["properties"]["pip_installer"] = {
"anyOf": [
{"type": "string", "enum": ["auto", "pip", "uv"]},
{"type": "null"},
]
}
# Add enum constraint for node_version
if "node_version" in node_schema["properties"]:
node_schema["properties"]["node_version"]["anyOf"] = [
{"type": "string", "enum": ["20"]},
{"type": "null"},
]
# Add enum constraint for image_distro
if "image_distro" in node_schema["properties"]:
node_schema["properties"]["image_distro"]["anyOf"] = [
{"type": "string", "enum": ["debian", "wolfi"]},
{"type": "null"},
]
# Replace the Config schema with a oneOf constraint
config_schema["oneOf"] = [
legacy_python_schema,
uv_source_python_schema,
node_schema,
]
# Remove the properties field as it's now defined in the oneOf subschemas
if "properties" in config_schema:
del config_schema["properties"]
return schema
def main():
"""Generate the schema and write it to a file."""
schema = generate_schema()
# Add versioning to the schema
import importlib.metadata
try:
version = importlib.metadata.version("langgraph_cli").split(".")
schema_version = f"v{version[0]}"
except importlib.metadata.PackageNotFoundError:
schema_version = "v1"
# Add version to schema
schema["version"] = schema_version
config_dir = Path(__file__).parent / "schemas"
# Create versioned schema file
versioned_path = config_dir / f"schema.{schema_version}.json"
with open(versioned_path, "w") as f:
json.dump(schema, f, indent=2)
# Also create a latest version
latest_path = config_dir / "schema.json"
with open(latest_path, "w") as f:
json.dump(schema, f, indent=2)
print(f"Schema written to {versioned_path} and {latest_path}")
print(
f"You can now add '$schema: https://raw.githubusercontent.com/langchain-ai/langgraph/refs/heads/main/libs/cli/schemas/schema.json'"
f" or '$schema: https://raw.githubusercontent.com/langchain-ai/langgraph/refs/heads/main/libs/cli/schemas/schema.{schema_version}.json'"
" to your langgraph.json files"
)
if __name__ == "__main__":
main()