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After you configure provider access in Metorial, you can connect those tools to an LLM like ChatGPT. In this guide, you’ll learn how to build a chat-enabled app that automatically handles tool calls from your Metorial providers.
What you’ll learn:
  • How to use a Metorial provider
  • How to use the Metorial SDKs
Before you start:
  • Create a Metorial project
  • Configure at least one provider or integration
  • Create an API key
1

1. Install the SDKs

Run the installer for your language of choice:
npm install metorial @metorial/openai openai

pip install metorial openai
2

2. Configure Clients

Instantiate both clients with your API keys and your provider deployment ID.
import { Metorial } from 'metorial';
import { metorialOpenAI } from '@metorial/openai';
import OpenAI from 'openai';

let metorial = new Metorial({
  apiKey: '$$SECRET_TOKEN$$'
});

let openai = new OpenAI({
  apiKey: '...your-openai-api-key...'
});

from metorial import Metorial, metorial_openai
from openai import AsyncOpenAI

metorial = Metorial(api_key="$$SECRET_TOKEN$$")
openai = AsyncOpenAI(api_key="...your-openai-api-key...")
3

3. Fetch Your Provider Tools

Create a session that exposes your deployed provider tools.
let session = await metorial.connect({
	adapter: metorialOpenAI.chatCompletions(),
	providers: [
		{ providerDeploymentId: '...your-provider-deployment-id...' }
	]
});

let tools = session.tools();

session = await metorial.connect(
    adapter=metorial_openai(),
    providers=[{"provider_deployment_id": "...your-provider-deployment-id..."}],
)
tools = session.tools()
4

4. Send Your First Prompt

Kick off the loop by sending an initial message.
let messages = [
  { role: "user", content: "Summarize the README.md file of the metorial/websocket-explorer repository on GitHub." }
];

messages = [
  {"role": "user", "content": "Summarize the README.md file of the metorial/websocket-explorer repository on GitHub."}
]
5

5. Loop & Handle Tool Calls

  1. Send messages to OpenAI, passing the tools.
  2. If the assistant response contains tool_calls, invoke it:
let response = await openai.chat.completions.create({
  model: 'gpt-4o',
  messages,
  tools
});
let choice = response.choices[0]!;
let toolCalls = choice.message.tool_calls;
let toolResults = await session.callTools(toolCalls);

response = await openai.chat.completions.create(
  model="gpt-4o",
  messages=messages,
  tools=session.tools(),
)
choice = response.choices[0]
tool_calls = choice.message.tool_calls
tool_results = await session.call_tools(tool_calls)
  1. Append both the tool call requests and their results to messages.
  2. Repeat until the assistant’s response has no more tool_calls.
6

6. Display the Final Output

Once there are no more tool calls, your assistant’s final reply is in:
console.log(choice.message.content);

print(choice.message.content)

​
What’s Next?

You are set up to use Metorial provider tools in an application. Next, review the observability tooling available for sessions, connections, and tool calls.

Next Up: How to monitor your provider and tool calls

Learn how to use the observability & logging features.