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Examples

This directory contains examples demonstrating how to use the Helicone AI SDK Provider with the Vercel AI SDK.

Setup

  1. Install dependencies:
npm install
  1. Create a .env file in the root directory with your Helicone API key:
HELICONE_API_KEY=your_api_key_here

Running Examples

You can run any example using tsx:

npx tsx examples/basic.ts
npx tsx examples/streaming.ts
npx tsx examples/advanced-tracking.ts
npx tsx examples/multiple-providers.ts
npx tsx examples/tool-calling.ts
npx tsx examples/stream-tool-calling.ts
npx tsx examples/streamText-tools-properties.ts
npx tsx examples/prompts.ts
npx tsx examples/agent-tools.ts
npx tsx examples/agents-json.ts
npx tsx examples/agents-zod.ts
npx tsx examples/validate-ui-messages.ts

Available Examples

basic.ts

Simple text generation example showing basic usage of the Helicone provider.

streaming.ts

Demonstrates streaming responses from the model.

advanced-tracking.ts

Shows how to use advanced tracking features like session IDs, user IDs, custom properties, tags, and caching.

multiple-providers.ts

Example of using multiple AI providers (OpenAI and Anthropic) through Helicone.

tool-calling.ts

Comprehensive example demonstrating how to use tool calling (function calling) with generateText.

Note: generateText returns tool call requests but does not execute them automatically. For automatic tool execution, see stream-tool-calling.ts.

stream-tool-calling.ts

Demonstrates streaming with tool calling using streamText. Shows how to handle tool calls and results in a streaming context, including processing fullStream chunks for text deltas, tool calls, and tool results. Includes weather and calculation tools with automatic execution.

streamText-tools-properties.ts

Example showing tool calling with streamText and how to access tool properties in the streaming response. Useful for debugging and monitoring tool execution in real-time.

prompts.ts

Comprehensive examples of Helicone prompts integration, including:

  • Basic prompt usage with inputs
  • Streaming with prompts
  • Multiple environment configurations (development, staging, production)
  • Prompts combined with tools
  • Regular messages (without prompts) for comparison

agent-tools.ts

Demonstrates using the experimental Agent class with Helicone, showing a customer support agent with multiple tools.

Includes detailed step-by-step execution tracking and tool call/result logging.

agents-json.ts

Agent demo using jsonSchema(...) helpers to define tool schemas. Shows how to structure agent tools using JSON Schema format.

agents-zod.ts

Agent demo using raw Zod schemas to define tool schemas. Functionally similar to agents-json.ts but demonstrates the Zod schema approach.

Both agents-json.ts and agents-zod.ts send the same tool definitions; any behavioral differences stem from model choice or prompt/tool-choice settings (e.g., forcing toolChoice: { type: 'required' }).

validate-ui-messages.ts

Example demonstrating how to use validateUIMessages with Helicone provider, commonly used in API routes. Shows how to handle AI SDK v6 UI message format with parts array, including:

  • Message validation
  • Conversation history handling
  • Edge cases and different message types
  • Integration with the Agent class

Notes

  • Make sure you have a valid Helicone API key from helicone.ai
  • Some examples may require specific model access (e.g., GPT-4, Claude)
  • All requests are tracked in your Helicone dashboard