AI Decision System
Replayable, offline-verifiable records for AI-assisted go/no-go decisions: experiment promotions, typed model answers and human-approved actions.
翻译准备中
Track LLM application performance and manage prompts for engineering teams
翻译准备中
AI 摘要 · README
开发工具Python · TypeScriptGitHub @respanai自行安装运营者未确认
试用过了吗? 点一下就好,无需登录。
尚未检测到更新。GitHub 发布版本后会显示在这里。
个人 GitHub 账号下公开仓库的所有者可以登录并验证所有权,自行管理介绍,无需管理员批准。
登录并生成验证文件,在 30 分钟内将其提交到此仓库的默认分支。其他分支或分叉仓库中的文件无效。然后在下方检查文件,即可无需管理员批准直接管理项目。请保留文件以维持管理权限。
如需登录,将前往登录页面。登录后请回到此处,再次点击所选的验证按钮。
安装型项目无需部署域名也可验证。个人仓库可通过 GitHub 登录验证,组织仓库可使用上方的仓库验证文件。
正在加载完整 README。 以下为已保存的摘录。
Observability, prompt management, and evals for LLM engineering teams.
Respan's library for sending telemetries of LLM applications in OpenLLMetry format.
Replace openai with the provider SDK your application uses. The facade supplies the eligible first-party instrumentation adapters; TypeScript users should not install with --omit=optional because those adapters are optional dependencies of @respan/respan.查看完整 README ↗Respan's library for sending telemetries of LLM applications in OpenLLMetry format.
pip install respan-ai openai
npm install @respan/respan openai
Replace openai with the provider SDK your application uses. The facade supplies the eligible first-party instrumentation adapters; TypeScript users should not install with --omit=optional because those adapters are optional dependencies of @respan/respan.
| Variable | Required | Description |
|---|---|---|
RESPAN_API_KEY | Yes | Your Respan API key. Authenticates both proxy and tracing. Get it from the platform. |
RESPAN_BASE_URL | No | Defaults to https://api.respan.ai/api. |
The quickstart below routes OpenAI through the Respan gateway, so RESPAN_API_KEY authenticates both inference and telemetry export. When calling a provider directly, configure that provider's credentials and endpoint normally; Respan still uses RESPAN_API_KEY for telemetry.
import os
from openai import OpenAI
from respan import Respan
# Omit `instrumentations` to auto-discover the matching bundled adapter.
respan = Respan()
# Respan API key authenticates both proxy and tracing
respan_api_key = os.environ["RESPAN_API_KEY"]
respan_base_url = os.getenv("RESPAN_BASE_URL", "https://api.respan.ai/api")
client = OpenAI(api_key=respan_api_key, base_url=respan_base_url)
response = client.chat.completions.create(
model="gpt-4.1-nano",
messages=[{"role": "user", "content": "Say hello in three languages."}],
)
print(response.choices[0].message.content)
respan.shutdown()
import OpenAI from "openai";
import { Respan } from "@respan/respan";
const respanBaseURL =
process.env.RESPAN_BASE_URL ?? "https://api.respan.ai/api";
// Omit `instrumentations` to auto-discover the matching bundled adapter.
const respan = new Respan({
apiKey: process.env.RESPAN_API_KEY,
baseURL: respanBaseURL,
});
await respan.initialize();
const client = new OpenAI({
apiKey: process.env.RESPAN_API_KEY,
baseURL: respanBaseURL,
});
const response = await client.chat.completions.create({
model: "gpt-4.1-nano",
messages: [{ role: "user", content: "Say hello in three languages." }],
});
console.log(response.choices[0].message.content);
await respan.shutdown();
See your traces in the Respan platform.
Install the facade and the provider SDK, omit the instrumentations option, and initialize Respan before the first provider call. Missing provider SDKs are skipped without failing startup and are visible through the instrumentation status API.
| Provider | Python SDK | TypeScript SDK |
|---|---|---|
| OpenAI | openai | openai |
| Azure OpenAI | openai | openai |
| Anthropic | anthropic | @anthropic-ai/sdk |
| Vertex AI | google-cloud-aiplatform | @google-cloud/vertexai |
| Google GenAI | google-genai | — |
| AWS Bedrock | boto3 | @aws-sdk/client-bedrock-runtime |
| Cohere | — | cohere-ai |
| Together AI | together | together-ai |
| OpenRouter | — | @openrouter/sdk |
| Writer | — | writer-sdk |
| Ollama | ollama | — |
respan-ai bundles the seven eligible Python adapters. A normal @respan/respan install includes the nine TypeScript adapters as optional dependencies.
Inspect the result after construction in Python with respan.get_auto_instrumentation_status(), or after await respan.initialize() in TypeScript with respan.getInstrumentationStatus().
LLM wrappers, agent frameworks, application frameworks, protocol/tooling integrations, observability bridges, and vector databases remain explicit opt-ins to prevent duplicate spans. Supplying instrumentations selects explicit mode and disables automatic discovery by default.
Python can intentionally combine explicit plugins with direct-SDK automatic discovery by setting is_auto_instrument=True. Use Respan(is_auto_instrument=False) to disable automatic discovery entirely.
In TypeScript, use disabledInstrumentations: ["openrouter"] to disable one automatic adapter, or instrumentations: [] to disable all automatic discovery. TypeScript explicit mode is currently exclusive and cannot be combined with automatic discovery.
Structure traces with @workflow / @task (Python) or withWorkflow / withTask (TypeScript). See the decorators example for details.
Attach customer_identifier, thread_identifier, and metadata to all spans in scope. See the attributes example.
The SDKs batch spans in memory and retry, but never write to disk, so spans still queued during a long outage or a process crash are lost. For long-running agents that must not lose spans, run the packaged Respan Collector next to the application — the upstream OpenTelemetry Collector with a persistent, bounded queue — and point RESPAN_BASE_URL at it (respan collector start or docker compose -f collector/docker-compose.yaml up -d).
Please star us if you found this helpful!