Framework Integrations

Use Till scoped API keys with frameworks that accept a custom API key and base URL.

🦜

LangChain

Python and JavaScript agent framework

LangChain makes it easy to build agents that call LLMs. With Till, you can give each agent run a scoped key with an activation cap and conservatively reserved token or spend budgets.

Python

from langchain_openai import ChatOpenAI

# Create a Till scoped key first (via dashboard or API)
# till_sk_abc123... with $5 spend limit

llm = ChatOpenAI(
    model="gpt-4",
    api_key="till_sk_abc123...",  # Your Till scoped key
    base_url="https://api.till.ac/v1"
)

# Use normally - Till enforces limits automatically
response = llm.invoke("Hello, world!")

JavaScript/TypeScript

import { ChatOpenAI } from "@langchain/openai";

const llm = new ChatOpenAI({
  model: "gpt-4",
  apiKey: "till_sk_abc123...",
  configuration: {
    baseURL: "https://api.till.ac/v1"
  }
});

const response = await llm.invoke("Hello, world!");

With Anthropic

from langchain_anthropic import ChatAnthropic

llm = ChatAnthropic(
    model="claude-3-opus-20240229",
    api_key="till_sk_xyz789...",
    base_url="https://api.till.ac"
)

🤖

AutoGPT / Agent-GPT

Autonomous AI agent frameworks

AutoGPT can burn through API credits quickly due to its autonomous nature. Till can cap activations and conservatively reserve spend for known-priced models, subject to the accounting boundaries in the documentation.

Configuration

Set these environment variables in your .env file:

# Replace your OpenAI key with a Till scoped key
OPENAI_API_KEY=till_sk_abc123...

# Point to Till's proxy
OPENAI_API_BASE=https://api.till.ac/v1

# The scoped key has built-in limits:
# - 100 activations max
# - $10 spend cap
# - Whichever hits first stops the agent

Why this matters

AutoGPT's agent loop can make hundreds of API calls. Without limits, a single stuck agent could cost hundreds of dollars. With Till:

Set a $10 spend limit per agent run
Agent hits the limit and stops cleanly
You review results, create a new key if needed
Inspect Till usage alongside the upstream provider bill

👥

CrewAI

Multi-agent orchestration framework

CrewAI orchestrates multiple agents working together. Give each crew a separate Till key to attribute estimated spend and set independent activation caps.

from crewai import Agent, Task, Crew
from langchain_openai import ChatOpenAI

# Each crew gets its own scoped key with budget
research_llm = ChatOpenAI(
    api_key="till_sk_research_team...",  # $20 budget
    base_url="https://api.till.ac/v1"
)

writing_llm = ChatOpenAI(
    api_key="till_sk_writing_team...",  # $15 budget
    base_url="https://api.till.ac/v1"
)

researcher = Agent(
    role="Research Analyst",
    llm=research_llm,
    # ...
)

writer = Agent(
    role="Content Writer",
    llm=writing_llm,
    # ...
)

⬡

OpenAI SDK (Direct)

Official Python and Node.js SDKs

Use Till with the official OpenAI SDK by setting the base URL.

Python

from openai import OpenAI

client = OpenAI(
    api_key="till_sk_abc123...",
    base_url="https://api.till.ac/v1"
)

response = client.chat.completions.create(
    model="gpt-4",
    messages=[{"role": "user", "content": "Hello!"}]
)

Node.js

import OpenAI from "openai";

const client = new OpenAI({
  apiKey: "till_sk_abc123...",
  baseURL: "https://api.till.ac/v1"
});

const response = await client.chat.completions.create({
  model: "gpt-4",
  messages: [{ role: "user", content: "Hello!" }]
});

Framework Integrations

LangChain

Python

JavaScript/TypeScript

With Anthropic

AutoGPT / Agent-GPT

Configuration

Why this matters

CrewAI

OpenAI SDK (Direct)

Python

Node.js

Works with any framework