docs: Update langgraph-api/cloud version constraints

This commit is contained in:
Nuno Campos
2024-08-26 08:25:24 -07:00
parent a2cfe694f1
commit 0d9c0732d4
2 changed files with 32 additions and 24 deletions
+22 -16
View File
@@ -1,15 +1,14 @@
# How to Set Up a LangGraph Application for Deployment
A LangGraph application must be configured with a [LangGraph API configuration file](../reference/cli.md#configuration-file) in order to be deployed to LangGraph Cloud (or to be self-hosted). This how-to guide discusses the basic steps to setup a LangGraph application for deployment using `requirements.txt` to specify project dependencies.
A LangGraph application must be configured with a [LangGraph API configuration file](../reference/cli.md#configuration-file) in order to be deployed to LangGraph Cloud (or to be self-hosted). This how-to guide discusses the basic steps to setup a LangGraph application for deployment using `requirements.txt` to specify project dependencies.
This walkthrough is based on [this repository](https://github.com/langchain-ai/langgraph-example), which you can play around with to learn more about how to setup your LangGraph application for deployment.
!!! tip "Setup with pyproject.toml"
If you prefer using poetry for dependency management, check out [this how-to guide](./setup_pyproject.md) on using `pyproject.toml` for LangGraph Cloud.
If you prefer using poetry for dependency management, check out [this how-to guide](./setup_pyproject.md) on using `pyproject.toml` for LangGraph Cloud.
!!! tip "Setup with a Monorepo"
If you are interested in deploying a graph located inside a monorepo, take a look at [this](https://github.com/langchain-ai/langgraph-example-monorepo) repository for an example of how to do so.
If you are interested in deploying a graph located inside a monorepo, take a look at [this](https://github.com/langchain-ai/langgraph-example-monorepo) repository for an example of how to do so.
The final repo structure will look something like this:
@@ -35,23 +34,27 @@ After each step, an example file directory is provided to demonstrate how code c
Dependencies can optionally be specified in one of the following files: `pyproject.toml`, `setup.py`, or `requirements.txt`. If none of these files is created, then dependencies can be specified later in the [LangGraph API configuration file](#create-langgraph-api-config).
The dependencies below will be included in the image, you can also use them in your code, as long as with a compatible version range:
```
langgraph>=0.2.0,<0.3.0
langgraph>=0.2.7,<0.3.0
langgraph-checkpoint>=1.0.4
langchain-core>=0.2.27,<0.3.0
langsmith>=0.1.63
orjson>=3.10.1
httpx>=0.27.0
tenacity>=8.3.0
uvicorn>=0.29.0
orjson>=3.9.7
httpx>=0.25.0
tenacity>=8.0.0
uvicorn>=0.26.0
sse-starlette>=2.1.0
uvloop>=0.19.0
httptools>=0.6.1
jsonschema-rs>=0.18.0
uvloop>=0.18.0
httptools>=0.5.0
jsonschema-rs>=0.16.3
croniter>=1.0.1
structlog>=24.4.0
structlog>=23.1.0
redis>=5.0.0,<6.0.0
```
Example `requirements.txt` file:
```
langgraph
langchain_anthropic
@@ -62,6 +65,7 @@ langchain_openai
```
Example file directory:
```bash
my-app/
├── my_agent # all project code lies within here
@@ -73,6 +77,7 @@ my-app/
Environment variables can optionally be specified in a file (e.g. `.env`). See the [Environment Variables reference](../reference/env_var.md) to configure additional variables for a deployment.
Example `.env` file:
```
MY_ENV_VAR_1=foo
MY_ENV_VAR_2=bar
@@ -94,7 +99,6 @@ Implement your graphs! Graphs can be defined in a single file or multiple files.
Example `agent.py` file, which shows how to import from other modules you define (code for the modules is not shown here, please see [this repo](https://github.com/langchain-ai/langgraph-example) to see their implementation):
```python
# my_agent/agent.py
from typing import TypedDict, Literal
@@ -125,9 +129,10 @@ graph = workflow.compile()
```
!!! warning "Assign `CompiledGraph` to Variable"
The build process for LangGraph Cloud requires that the `CompiledGraph` object be assigned to a variable at the top-level of a Python module (alternatively, you can provide [a function that creates a graph](./graph_rebuild.md)).
The build process for LangGraph Cloud requires that the `CompiledGraph` object be assigned to a variable at the top-level of a Python module (alternatively, you can provide [a function that creates a graph](./graph_rebuild.md)).
Example file directory:
```bash
my-app/
├── my_agent # all project code lies within here
@@ -147,6 +152,7 @@ my-app/
Create a [LangGraph API configuration file](../reference/cli.md#configuration-file) called `langgraph.json`. See the [LangGraph CLI reference](../reference/cli.md#configuration-file) for detailed explanations of each key in the JSON object of the configuration file.
Example `langgraph.json` file:
```json
{
"dependencies": ["./my_agent"],
@@ -160,7 +166,7 @@ Example `langgraph.json` file:
Note that the variable name of the `CompiledGraph` appears at the end of the value of each subkey in the top-level `graphs` key (i.e. `:<variable_name>`).
!!! warning "Configuration Location"
The LangGraph API configuration file must be placed in a directory that is at the same level or higher than the Python files that contain compiled graphs and associated dependencies.
The LangGraph API configuration file must be placed in a directory that is at the same level or higher than the Python files that contain compiled graphs and associated dependencies.
Example file directory: