@countly/ai-sdk-core

Shared transport, data model, cost calculation, and event builders for the Countly AI SDK.

This is the foundation package. You usually don't install it directly — every adapter pulls it in automatically:

• @countly/ai-sdk-openai
• @countly/ai-sdk-anthropic
• @countly/ai-sdk-mastra
• @countly/ai-sdk-vercel
• @countly/ai-sdk-google-genai
• @countly/ai-sdk-langchain
• @countly/ai-sdk-cohere
• @countly/ai-sdk-llamaindex

What it provides

• Unified data model (RawExtractionResult) — OpenTelemetry GenAI-aligned schema produced by every adapter
• HTTP transport — buffered POST /i with per-event device_id, retry with exponential backoff, dead-letter buffer (max 1000), 429 Retry-After support
• Cost calculation — built-in pricing for 30+ models (OpenAI, Anthropic, Google, Cohere) with per-model override
• Event builders — [CLY]_llm_interaction, [CLY]_llm_tool_used, [CLY]_llm_tool_usage_parameter, [CLY]_llm_interaction_feedback
• Finish reason normalization — maps provider-specific values to canonical stop | length | tool_calls | content_filter | error | other
• Error categorization — rate_limit | context_length | content_filter | timeout | auth_error | api_error

Direct usage

If you're building a custom integration not covered by an existing adapter:

import {
  resolveConfig,
  createTransport,
  buildAllEvents,
  generatePromptId,
} from "@countly/ai-sdk-core";

const config = resolveConfig({
  appKey: "YOUR_APP_KEY",
  url: "https://your-countly-server.com",
});
const transport = createTransport(config);

const raw = {
  provider: "my-llm",
  model: "my-model",
  usage_input: 100,
  usage_output: 50,
  usage_total: 150,
  latency_total: 1200,
  status: "success" as const,
};

const events = buildAllEvents(raw, config, {
  prompt_id: generatePromptId(),
  sdk_adapter: "custom",
});
transport.enqueue(events);

Feedback events

Feedback is not auto-collected — wire it from your UI's thumbs-up/down handler:

import { buildFeedbackEvent, createTransport, resolveConfig } from "@countly/ai-sdk-core";

const config = resolveConfig({ appKey: "...", url: "..." });
const transport = createTransport(config);

function onFeedback(promptId: string, rating: string, userId: string) {
  const event = buildFeedbackEvent({ prompt_id: promptId, rating });
  event.deviceId = userId;
  transport.enqueue([event]);
}

The prompt_id links back to the [CLY]_llm_interaction event. Store it in your chat UI and read it back when the user clicks feedback.

Full documentation

See the Countly AI SDK repository for the unified data model, observability levels (0/1/2), per-user attribution via AsyncLocalStorage, cost calculation, privacy controls, and Countly plugin integration (Drill, Funnels, Cohorts, APM, Crash Analytics).

License

MIT