README.md

langchain-gradient

This package contains the LangChain integration with DigitalOcean Gradient Serverless Inference.

Migrating to 1.0.0

1.0.0 replaces the deprecated gradient SDK with pydo (Gradient SDK retires 2026-08-15).

• Reinstall so you pick up pydo: pip install -U "langchain-gradient>=1.0.0"
• Exception types now come from azure-core/pydo (not gradient.*)
• timeout must be a positive int (default 120); it is an HTTP connect/read idle timeout, not a total generation budget
• See CHANGELOG for the full breaking-change list

Installation

pip install -U langchain-gradient

And you should configure credentials by setting the DIGITALOCEAN_INFERENCE_KEY environment variable:

1. Log in to the DigitalOcean Cloud console
2. Go to the Gradient Platform and navigate to Serverless Inference.
3. Click on Create model access key, enter a name, and create the key.
4. Use the generated key as your DIGITALOCEAN_INFERENCE_KEY:

Create .env file with your access key:
DIGITALOCEAN_INFERENCE_KEY=your_access_key_here

Chat Models

ChatGradient class exposes chat models from langchain-gradient.

Invoke

import os
from dotenv import load_dotenv
from langchain_gradient import ChatGradient

load_dotenv()

llm = ChatGradient(
    model="llama3.3-70b-instruct",
    api_key=os.getenv("DIGITALOCEAN_INFERENCE_KEY")
)

result = llm.invoke("What is the capital of France?.")
print(result)

Stream

import os
from dotenv import load_dotenv
from langchain_gradient import ChatGradient

load_dotenv()

llm = ChatGradient(
    model="llama3.3-70b-instruct",
    api_key=os.getenv("DIGITALOCEAN_INFERENCE_KEY")
)

for chunk in llm.stream("Tell me what happened to the Dinosaurs?"):
    print(chunk.content, end="", flush=True)

More features coming soon.