Using your first provider

Learn how to connect your provider to an LLM and build a chat-enabled app

Now that you’ve deployed your first provider and confirmed it’s working, you can connect it 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:

• Complete the Introduction guide
• Complete the Deploying your first provider guide
• Complete the Testing your first provider guide

1. 1. Install the SDKs

   Run the installer for your language of choice:

   TypeScript

   npm install metorial @metorial/openai openai
   
2. 2. Configure Clients

   Instantiate both clients with your API keys and your provider deployment ID.

   TypeScript

   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...'
   });
   
3. 3. Fetch Your Provider Tools

   Create a session that exposes your deployed provider tools.

   TypeScript

   let session = await metorial.connect({
   	adapter: metorialOpenAI.chatCompletions(),
   	providers: [
   		{ providerDeploymentId: '...your-provider-deployment-id...' }
   	]
   });
   
   let tools = session.tools();
   
4. 4. Send Your First Prompt

   Kick off the loop by sending an initial message.

   TypeScript

   let 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:

   TypeScript

   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);
   

   3. Append both the tool call requests and their results to messages.
   4. 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:

   TypeScript

   console.log(choice.message.content);
   

What’s Next?

You are all set on having a production-ready provider to use in your AI apps. Next, you will learn about all the observability tooling available.

Next Up: How to monitor your provider and tool calls

Learn how to use the observability & logging features.