Feature: Make create-onchain-agent templates LLM provider-agnostic

[0xshae]

Language Implementation

• Python
• TypeScript

Feature Type

• Action Provider Template
• Wallet Provider Template
• Framework Extension
• Core Requirements
• Other

🚀 The feature, motivation and pitch

The create-onchain-agent templates currently hardcode OpenAI as the LLM provider. The generated create-agent.ts uses import { openai } from "@ai-sdk/openai" and calls openai.chat("gpt-4o-mini") directly, and the generated .env.local only includes OPENAI_API_KEY=.

This means a developer using any other provider (Anthropic, Google, OpenRouter, Groq, Ollama, etc.) has to open create-agent.ts and rewrite the model initialization before they can even run the agent.

This is unnecessary because @ai-sdk/openai and @langchain/openai — the packages already installed in the template — natively support connecting to any OpenAI-compatible API via their baseURL option. And all major LLM providers now expose OpenAI-compatible endpoints (Anthropic, Google Gemini, OpenRouter, Groq, Together AI, Ollama).

Proposal: Replace the hardcoded openai("gpt-4o-mini") singleton with createOpenAI({ apiKey, baseURL }) configured via environment variables:

• AI_API_KEY — API key for any provider (falls back to OPENAI_API_KEY)
• AI_BASE_URL — provider's endpoint (optional, defaults to OpenAI)
• AI_MODEL — model identifier (optional, defaults to gpt-4o-mini)

The generated .env.local would include inline examples for all major providers, so a developer with an Anthropic key can just set two env vars and run npm run dev — no code changes needed.

This change:

• Adds zero new dependencies (uses createOpenAI/ChatOpenAI already installed)
• Is fully backward-compatible (falls back to OPENAI_API_KEY if AI_API_KEY is not set)
• Matches how the core @coinbase/agentkit library already works: fully LLM-agnostic

Alternatives

Let developers manually edit create-agent.ts after scaffolding. This is the current approach but creates friction for anyone not using OpenAI.

Additional context

The core @coinbase/agentkit library and all framework extensions (agentkit-langchain, agentkit-vercel-ai-sdk) are already fully LLM-agnostic. The OpenAI lock-in exists only in the scaffolding layer. The Python create-onchain-agent has the same issue.