Developer-friendly & type-safe Typescript SDK specifically catered to leverage opperai API.
Welcome to the OpperAI python SDK
Opper is a task completion platform for building reliable AI integrations. The Opper platform builds a happy path for declarative programming with AI models, combined with in context reinforcement learning, observability and cost tracking all in one platform - for reliable results in no time!
This SDK is generated using Speakeasy — check out our detailed documentation with guides and examples:
The SDK can be installed with either npm, pnpm, bun or yarn package managers.
npm add opperaipnpm add opperaibun add opperaiyarn add opperai
# Note that Yarn does not install peer dependencies automatically. Run
# `yarn add zod@^3.23.8` as well if you haven't already.Important
This SDK currently supports Zod v3.x. Ensure your project installs zod@^3.23.8 (or another 3.x release) and avoids Zod v4 releases.
Note
This package is published with CommonJS and ES Modules (ESM) support.
This SDK is also an installable MCP server where the various SDK methods are exposed as tools that can be invoked by AI applications.
Node.js v20 or greater is required to run the MCP server from npm.
Claude installation steps
Add the following server definition to your claude_desktop_config.json file:
{
"mcpServers": {
"Opper": {
"command": "npx",
"args": [
"-y", "--package", "opperai",
"--",
"mcp", "start",
"--http-bearer", "..."
]
}
}
}Cursor installation steps
Create a .cursor/mcp.json file in your project root with the following content:
{
"mcpServers": {
"Opper": {
"command": "npx",
"args": [
"-y", "--package", "opperai",
"--",
"mcp", "start",
"--http-bearer", "..."
]
}
}
}MCP standalone Binary
You can also run MCP servers as a standalone binary with no additional dependencies. You must pull these binaries from available Github releases:curl -L -o mcp-server \
https://github.com/{org}/{repo}/releases/download/{tag}/mcp-server-bun-darwin-arm64 && \
chmod +x mcp-serverIf the repo is a private repo you must add your Github PAT to download a release -H "Authorization: Bearer {GITHUB_PAT}".
{
"mcpServers": {
"Todos": {
"command": "./DOWNLOAD/PATH/mcp-server",
"args": [
"start"
]
}
}
}For a full list of server arguments, run:
npx -y --package opperai -- mcp start --helpFor supported JavaScript runtimes, please consult RUNTIMES.md.
Log in at opper and create your own API key in the top right menu. Each api key is associated with a project, you will have all calls, functions, indexes and traces associated with this project. There is a default project for each organization but it is recommended to create a new project to better being able to separate the different applications and environments.
There are plenty of guides and example code in our examples
import { Opper } from "opperai";
const opper = new Opper({
httpBearer: process.env["OPPER_HTTP_BEARER"] ?? "",
});
// Define the output structure (JSON Schema instead of Pydantic)
const roomDescriptionSchema = {
type: "object",
properties: {
room_count: { type: "number" },
view: { type: "string" },
bed_size: { type: "string" },
hotel_name: { type: "string" },
},
required: ["room_count", "view", "bed_size", "hotel_name"],
};
async function main() {
// Complete a task
const completion = await opper.call({
name: "extractRoom",
instructions: "Extract details about the room from the provided text",
input: "The Grand Hotel offers a luxurious suite with 3 spacious rooms, each providing a breathtaking view of the ocean. The suite includes a king-sized bed, an en-suite bathroom, and a private balcony for an unforgettable stay.",
outputSchema: roomDescriptionSchema,
});
console.log(completion.jsonPayload);
// Expected: { room_count: 3, view: 'ocean', bed_size: 'king-sized', hotel_name: 'The Grand Hotel' }
}
main();More advanced example
import { Opper } from "opperai";
const opper = new Opper({
httpBearer: process.env["OPPER_HTTP_BEARER"] ?? "",
});
async function run() {
const result = await opper.call({
name: "add_numbers",
instructions: "Calculate the sum of two numbers",
inputSchema: {
"properties": {
"x": {
"title": "X",
"type": "integer",
},
"y": {
"title": "Y",
"type": "integer",
},
},
"required": [
"x",
"y",
],
"title": "OpperInputExample",
"type": "object",
},
outputSchema: {
"properties": {
"sum": {
"title": "Sum",
"type": "integer",
},
},
"required": [
"sum",
],
"title": "OpperOutputExample",
"type": "object",
},
input: {
"x": 4,
"y": 5,
},
examples: [
{
input: {
"x": 1,
"y": 3,
},
output: {
"sum": 4,
},
comment: "Adds two numbers",
},
],
parentSpanId: "123e4567-e89b-12d3-a456-426614174000", // Pass the id you need
tags: {
"project": "project_456",
"user": "company_123",
},
configuration: {},
});
console.log(result);
}
run();This SDK supports the following security scheme globally:
| Name | Type | Scheme | Environment Variable |
|---|---|---|---|
httpBearer |
http | HTTP Bearer | OPPER_HTTP_BEARER |
To authenticate with the API the httpBearer parameter must be set when initializing the SDK client instance. For example:
import { Opper } from "opperai";
const opper = new Opper({
httpBearer: process.env["OPPER_HTTP_BEARER"] ?? "",
});Available methods
- getUsage - Usage
- createEntry - Create Dataset Entry
- listEntries - List Dataset Entries
- getEntry - Get Dataset Entry
- deleteEntry - Delete Dataset Entry
- queryEntries - Query Dataset Entries
- update - Update Dataset Entry
- create - Create Embedding
- create - Create Function
- list - List Functions
- get - Get Function
- update - Update Function
- delete - Delete Function
- getByName - Get Function By Name
- getByRevision - Get Function By Revision
- call - Call Function
- stream - Stream Function
- callRevision - Call Function Revision
- streamRevision - Stream Function Revision
- list - List Function Revisions
- create - Create Knowledge Base
- list - List Knowledge Bases
- get - Get Knowledge Base
- delete - Delete Knowledge Base
- getByName - Get Knowledge Base By Name
- getUploadUrl - Get Upload Url
- registerFileUpload - Register File Upload
- deleteFile - Delete File From Knowledge Base
- query - Query Knowledge Base
- add - Add
- list - List Models
- registerCustom - Register Custom Model
- listCustom - List Custom Models
- getCustom - Get Custom Model
- updateCustom - Update Custom Model
- deleteCustom - Delete Custom Model
- getCustomByName - Get Custom Model By Name
- createMetric - Create Metric
- list - List Metrics
- get - Get Metric
- updateMetric - Update Metric
- delete - Delete Metric
- create - Create Span
- get - Get Span
- update - Update Span
- delete - Delete Span
- saveExamples - Save To Dataset
All the methods listed above are available as standalone functions. These functions are ideal for use in applications running in the browser, serverless runtimes or other environments where application bundle size is a primary concern. When using a bundler to build your application, all unused functionality will be either excluded from the final bundle or tree-shaken away.
To read more about standalone functions, check FUNCTIONS.md.
Available standalone functions
analyticsGetUsage- Usagecall- Function CalldatasetsCreateEntry- Create Dataset EntrydatasetsDeleteEntry- Delete Dataset EntrydatasetsEntriesUpdate- Update Dataset EntrydatasetsGetEntry- Get Dataset EntrydatasetsListEntries- List Dataset EntriesdatasetsQueryEntries- Query Dataset EntriesembeddingsCreate- Create EmbeddingfunctionsCall- Call FunctionfunctionsCallRevision- Call Function RevisionfunctionsCreate- Create FunctionfunctionsDelete- Delete FunctionfunctionsGet- Get FunctionfunctionsGetByName- Get Function By NamefunctionsGetByRevision- Get Function By RevisionfunctionsList- List FunctionsfunctionsRevisionsList- List Function RevisionsfunctionsStream- Stream FunctionfunctionsStreamRevision- Stream Function RevisionfunctionsUpdate- Update FunctionknowledgeAdd- AddknowledgeCreate- Create Knowledge BaseknowledgeDelete- Delete Knowledge BaseknowledgeDeleteFile- Delete File From Knowledge BaseknowledgeGet- Get Knowledge BaseknowledgeGetByName- Get Knowledge Base By NameknowledgeGetUploadUrl- Get Upload UrlknowledgeList- List Knowledge BasesknowledgeQuery- Query Knowledge BaseknowledgeRegisterFileUpload- Register File UploadlanguageModelsDeleteCustom- Delete Custom ModellanguageModelsGetCustom- Get Custom ModellanguageModelsGetCustomByName- Get Custom Model By NamelanguageModelsList- List ModelslanguageModelsListCustom- List Custom ModelslanguageModelsRegisterCustom- Register Custom ModellanguageModelsUpdateCustom- Update Custom ModelopenaiCreateChatCompletion- Chat CompletionsspanMetricsCreateMetric- Create MetricspanMetricsDelete- Delete MetricspanMetricsGet- Get MetricspanMetricsList- List MetricsspanMetricsUpdateMetric- Update MetricspansCreate- Create SpanspansDelete- Delete SpanspansGet- Get SpanspansSaveExamples- Save To DatasetspansUpdate- Update Spanstream- Function StreamtracesGet- Get TracetracesList- List Traces
Server-sent events are used to stream content from certain
operations. These operations will expose the stream as an async iterable that
can be consumed using a for await...of loop. The loop will
terminate when the server no longer has any events to send and closes the
underlying connection.
import { Opper } from "opperai";
const opper = new Opper({
httpBearer: process.env["OPPER_HTTP_BEARER"] ?? "",
});
async function run() {
const result = await opper.stream({
name: "add_numbers",
instructions: "Calculate the sum of two numbers",
inputSchema: {
"properties": {
"x": {
"title": "X",
"type": "integer",
},
"y": {
"title": "Y",
"type": "integer",
},
},
"required": [
"x",
"y",
],
"title": "OpperInputExample",
"type": "object",
},
outputSchema: {
"properties": {
"sum": {
"title": "Sum",
"type": "integer",
},
},
"required": [
"sum",
],
"title": "OpperOutputExample",
"type": "object",
},
input: {
"x": 4,
"y": 5,
},
examples: [
{
input: {
"x": 1,
"y": 3,
},
output: {
"sum": 4,
},
comment: "Adds two numbers",
},
],
parentSpanId: "123e4567-e89b-12d3-a456-426614174000",
tags: {
"project": "project_456",
"user": "company_123",
},
});
for await (const event of result) {
// Handle the event
console.log(event);
}
}
run();Some of the endpoints in this SDK support retries. If you use the SDK without any configuration, it will fall back to the default retry strategy provided by the API. However, the default retry strategy can be overridden on a per-operation basis, or across the entire SDK.
Change Retry Strategy
To change the default retry strategy for a single API call, simply provide a retryConfig object to the call: ```typescript import { Opper } from "opperai";const opper = new Opper({ httpBearer: process.env["OPPER_HTTP_BEARER"] ?? "", });
async function run() { const result = await opper.call({ name: "add_numbers", instructions: "Calculate the sum of two numbers", inputSchema: { "properties": { "x": { "title": "X", "type": "integer", }, "y": { "title": "Y", "type": "integer", }, }, "required": [ "x", "y", ], "title": "OpperInputExample", "type": "object", }, outputSchema: { "properties": { "sum": { "title": "Sum", "type": "integer", }, }, "required": [ "sum", ], "title": "OpperOutputExample", "type": "object", }, input: { "x": 4, "y": 5, }, examples: [ { input: { "x": 1, "y": 3, }, output: { "sum": 4, }, comment: "Adds two numbers", }, ], parentSpanId: "123e4567-e89b-12d3-a456-426614174000", tags: { "project": "project_456", "user": "company_123", }, configuration: {}, }, { retries: { strategy: "backoff", backoff: { initialInterval: 1, maxInterval: 50, exponent: 1.1, maxElapsedTime: 100, }, retryConnectionErrors: false, }, });
console.log(result); }
run();
If you'd like to override the default retry strategy for all operations that support retries, you can provide a retryConfig at SDK initialization:
```typescript
import { Opper } from "opperai";
const opper = new Opper({
retryConfig: {
strategy: "backoff",
backoff: {
initialInterval: 1,
maxInterval: 50,
exponent: 1.1,
maxElapsedTime: 100,
},
retryConnectionErrors: false,
},
httpBearer: process.env["OPPER_HTTP_BEARER"] ?? "",
});
async function run() {
const result = await opper.call({
name: "add_numbers",
instructions: "Calculate the sum of two numbers",
inputSchema: {
"properties": {
"x": {
"title": "X",
"type": "integer",
},
"y": {
"title": "Y",
"type": "integer",
},
},
"required": [
"x",
"y",
],
"title": "OpperInputExample",
"type": "object",
},
outputSchema: {
"properties": {
"sum": {
"title": "Sum",
"type": "integer",
},
},
"required": [
"sum",
],
"title": "OpperOutputExample",
"type": "object",
},
input: {
"x": 4,
"y": 5,
},
examples: [
{
input: {
"x": 1,
"y": 3,
},
output: {
"sum": 4,
},
comment: "Adds two numbers",
},
],
parentSpanId: "123e4567-e89b-12d3-a456-426614174000",
tags: {
"project": "project_456",
"user": "company_123",
},
configuration: {},
});
console.log(result);
}
run();
Check our detailed docs for error handling
OpperError is the base class for all HTTP error responses. It has the following properties:
| Property | Type | Description |
|---|---|---|
error.message |
string |
Error message |
error.statusCode |
number |
HTTP response status code eg 404 |
error.headers |
Headers |
HTTP response headers |
error.body |
string |
HTTP body. Can be empty string if no body is returned. |
error.rawResponse |
Response |
Raw HTTP response |
error.data$ |
Optional. Some errors may contain structured data. See Error Classes. |
Example Error Handling
import { Opper } from "opperai";
import * as errors from "opperai/models/errors";
const opper = new Opper({
httpBearer: process.env["OPPER_HTTP_BEARER"] ?? "",
});
async function run() {
try {
const result = await opper.call({
name: "add_numbers",
instructions: "Calculate the sum of two numbers",
inputSchema: {
"properties": {
"x": {
"title": "X",
"type": "integer",
},
"y": {
"title": "Y",
"type": "integer",
},
},
"required": [
"x",
"y",
],
"title": "OpperInputExample",
"type": "object",
},
outputSchema: {
"properties": {
"sum": {
"title": "Sum",
"type": "integer",
},
},
"required": [
"sum",
],
"title": "OpperOutputExample",
"type": "object",
},
input: {
"x": 4,
"y": 5,
},
examples: [
{
input: {
"x": 1,
"y": 3,
},
output: {
"sum": 4,
},
comment: "Adds two numbers",
},
],
parentSpanId: "123e4567-e89b-12d3-a456-426614174000",
tags: {
"project": "project_456",
"user": "company_123",
},
configuration: {},
});
console.log(result);
} catch (error) {
// The base class for HTTP error responses
if (error instanceof errors.OpperError) {
console.log(error.message);
console.log(error.statusCode);
console.log(error.body);
console.log(error.headers);
// Depending on the method different errors may be thrown
if (error instanceof errors.BadRequestError) {
console.log(error.data$.type); // string
console.log(error.data$.message); // string
console.log(error.data$.detail); // any
}
}
}
}
run();Primary errors:
OpperError: The base class for HTTP error responses.BadRequestError: Bad Request. Status code400.UnauthorizedError: Unauthorized. Status code401.NotFoundError: Not Found. Status code404.RequestValidationError: Request Validation Error. Status code422. *
Less common errors (8)
Network errors:
ConnectionError: HTTP client was unable to make a request to a server.RequestTimeoutError: HTTP request timed out due to an AbortSignal signal.RequestAbortedError: HTTP request was aborted by the client.InvalidRequestError: Any input used to create a request is invalid.UnexpectedClientError: Unrecognised or unexpected error.
Inherit from OpperError:
ConflictError: Conflict. Status code409. Applicable to 3 of 52 methods.*ErrorT: Request validation error. Applicable to 1 of 52 methods.*ResponseValidationError: Type mismatch between the data returned from the server and the structure expected by the SDK. Seeerror.rawValuefor the raw value anderror.pretty()for a nicely formatted multi-line string.
* Check the method documentation to see if the error is applicable.
Server Selection
### Override Server URL Per-ClientThe default server can be overridden globally by passing a URL to the serverURL: string optional parameter when initializing the SDK client instance. For example:
import { Opper } from "opperai";
const opper = new Opper({
serverURL: "https://api.opper.ai/v2",
httpBearer: process.env["OPPER_HTTP_BEARER"] ?? "",
});
async function run() {
const result = await opper.call({
name: "add_numbers",
instructions: "Calculate the sum of two numbers",
inputSchema: {
"properties": {
"x": {
"title": "X",
"type": "integer",
},
"y": {
"title": "Y",
"type": "integer",
},
},
"required": [
"x",
"y",
],
"title": "OpperInputExample",
"type": "object",
},
outputSchema: {
"properties": {
"sum": {
"title": "Sum",
"type": "integer",
},
},
"required": [
"sum",
],
"title": "OpperOutputExample",
"type": "object",
},
input: {
"x": 4,
"y": 5,
},
examples: [
{
input: {
"x": 1,
"y": 3,
},
output: {
"sum": 4,
},
comment: "Adds two numbers",
},
],
parentSpanId: "123e4567-e89b-12d3-a456-426614174000",
tags: {
"project": "project_456",
"user": "company_123",
},
configuration: {},
});
console.log(result);
}
run();Custom HTTP Client
The TypeScript SDK makes API calls using an HTTPClient that wraps the native
Fetch API. This
client is a thin wrapper around fetch and provides the ability to attach hooks
around the request lifecycle that can be used to modify the request or handle
errors and response.
The HTTPClient constructor takes an optional fetcher argument that can be
used to integrate a third-party HTTP client or when writing tests to mock out
the HTTP client and feed in fixtures.
The following example shows how to use the "beforeRequest" hook to to add a
custom header and a timeout to requests and how to use the "requestError" hook
to log errors:
import { Opper } from "opperai";
import { HTTPClient } from "opperai/lib/http";
const httpClient = new HTTPClient({
// fetcher takes a function that has the same signature as native `fetch`.
fetcher: (request) => {
return fetch(request);
}
});
httpClient.addHook("beforeRequest", (request) => {
const nextRequest = new Request(request, {
signal: request.signal || AbortSignal.timeout(5000)
});
nextRequest.headers.set("x-custom-header", "custom value");
return nextRequest;
});
httpClient.addHook("requestError", (error, request) => {
console.group("Request Error");
console.log("Reason:", `${error}`);
console.log("Endpoint:", `${request.method} ${request.url}`);
console.groupEnd();
});
const sdk = new Opper({ httpClient });You can setup your SDK to emit debug logs for SDK requests and responses.
You can pass a logger that matches console's interface as an SDK option.
Warning
Beware that debug logging will reveal secrets, like API tokens in headers, in log messages printed to a console or files. It's recommended to use this feature only during local development and not in production.
import { Opper } from "opperai";
const sdk = new Opper({ debugLogger: console });You can also enable a default debug logger by setting an environment variable OPPER_DEBUG to true.
This SDK is in beta, and there may be breaking changes between versions without a major version update. Therefore, we recommend pinning usage to a specific package version. This way, you can install the same version each time without breaking changes unless you are intentionally looking for the latest version.
While we value open-source contributions to this SDK, this library is generated programmatically. Any manual changes added to internal files will be overwritten on the next generation. We look forward to hearing your feedback. Feel free to open a PR or an issue with a proof of concept and we'll do our best to include it in a future release.