Practical code examples for common integration patterns.
Send a message and receive a complete model response.
curl https://gateway.hkting.com/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer sk-your-api-key" \
-d '{
"model": "gpt-4o",
"messages": [
{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": "Explain quantum computing in simple terms."}
],
"temperature": 0.7,
"max_tokens": 500
}'{
"id": "chatcmpl-xxx",
"object": "chat.completion",
"created": 1734567890,
"model": "gpt-4o",
"choices": [
{
"index": 0,
"message": {
"role": "assistant",
"content": "Quantum computing uses qubits instead of bits..."
},
"finish_reason": "stop"
}
],
"usage": {
"prompt_tokens": 18,
"completion_tokens": 142,
"total_tokens": 160
}
}Receive responses incrementally via Server-Sent Events (SSE) for real-time applications.
curl https://gateway.hkting.com/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer sk-your-api-key" \
-d '{
"model": "gpt-4o",
"messages": [
{"role": "user", "content": "Write a short poem about AI."}
],
"stream": true
}'Let the model call functions defined in your request to fetch data or take actions.
curl https://gateway.hkting.com/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer sk-your-api-key" \
-d '{
"model": "gpt-4o",
"messages": [
{"role": "user", "content": "What'''s the weather like in Paris today?"}
],
"tools": [
{
"type": "function",
"function": {
"name": "get_weather",
"description": "Get the current weather for a city",
"parameters": {
"type": "object",
"properties": {
"location": {
"type": "string",
"description": "City name"
}
},
"required": ["location"]
}
}
}
],
"tool_choice": "auto"
}'{
"id": "chatcmpl-xxx",
"object": "chat.completion",
"choices": [
{
"index": 0,
"message": {
"role": "assistant",
"content": null,
"tool_calls": [
{
"id": "call_abc123",
"type": "function",
"function": {
"name": "get_weather",
"arguments": "{\"location\":\"Paris\"}"
}
}
]
},
"finish_reason": "tool_calls"
}
]
}The model decides when to call a tool. If it does, the response includes a tool_calls field instead of content. You then send the tool result back to continue the conversation.
Generate vector embeddings for text input using supported embedding models.
curl https://gateway.hkting.com/v1/embeddings \
-H "Content-Type: application/json" \
-H "Authorization: Bearer sk-your-api-key" \
-d '{
"model": "text-embedding-ada-002",
"input": "The quick brown fox jumps over the lazy dog"
}'Configure AI coding agents and assistants to use HuiLink as their API backend.
# Configure Claude Code to use Token Gateway
export ANTHROPIC_BASE_URL=https://gateway.hkting.com
export ANTHROPIC_API_KEY=sk-your-api-key
# Start a Claude Code session
claudeClaude Code uses Anthropic's Messages API format. HuiLink provides protocol conversion between OpenAI and Anthropic formats, enabling seamless integration with both ecosystems.