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492 lines
16 KiB
Markdown
492 lines
16 KiB
Markdown
---
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sidebar_label: Custom Javascript
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description: Configure custom JavaScript providers to integrate any API or service with promptfoo's testing framework using TypeScript, CommonJS, or ESM modules
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---
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# Javascript Provider
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Custom Javascript providers let you create providers in JavaScript or TypeScript to integrate with any API or service not already built into promptfoo.
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## Supported File Formats and Examples
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promptfoo supports multiple JavaScript module formats. Complete working examples are available on GitHub:
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- [CommonJS Provider](https://github.com/promptfoo/promptfoo/tree/main/examples/provider-custom/basic) - (`.js`, `.cjs`) - Uses `module.exports` and `require()`
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- [ESM Provider](https://github.com/promptfoo/promptfoo/tree/main/examples/provider-custom/mjs) - (`.mjs`, `.js` with `"type": "module"`) - Uses `import`/`export`
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- [TypeScript Provider](https://github.com/promptfoo/promptfoo/tree/main/examples/provider-custom/typescript) - (`.ts`) - Provides type safety with interfaces
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- [Embeddings Provider](https://github.com/promptfoo/promptfoo/tree/main/examples/provider-custom/embeddings) (commonjs)
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## Provider Interface
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At minimum, a custom provider must implement an `id` method and a `callApi` method.
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```javascript title="echoProvider.mjs"
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// Save as echoProvider.mjs for ES6 syntax, or echoProvider.js for CommonJS
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export default class EchoProvider {
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id = () => 'echo';
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callApi = async (prompt, context, options) => {
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return {
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output: `Echo: ${prompt}`,
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};
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};
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}
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```
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You can optionally use a constructor to initialize the provider, for example:
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```javascript title="openaiProvider.js"
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const promptfoo = require('promptfoo').default;
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module.exports = class OpenAIProvider {
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constructor(options) {
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this.providerId = options.id || 'openai-custom';
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this.config = options.config;
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}
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id() {
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return this.providerId;
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}
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async callApi(prompt, context, options) {
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const { data } = await promptfoo.cache.fetchWithCache(
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'https://api.openai.com/v1/chat/completions',
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{
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method: 'POST',
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headers: {
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'Content-Type': 'application/json',
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Authorization: `Bearer ${process.env.OPENAI_API_KEY}`,
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},
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body: JSON.stringify({
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model: this.config?.model || 'gpt-5-mini',
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messages: [{ role: 'user', content: prompt }],
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max_completion_tokens: this.config?.max_tokens || 1024,
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temperature: this.config?.temperature || 1,
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}),
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},
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);
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return {
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output: data.choices[0].message.content,
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tokenUsage: data.usage,
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};
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}
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};
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```
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`callApi` returns a `ProviderResponse` object. The `ProviderResponse` object format:
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```javascript
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{
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// main response shown to users
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output: "Model response - can be text or structured data",
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error: "Error message if applicable",
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prompt: "The actual prompt sent to the LLM", // Optional: reported prompt
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tokenUsage: {
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total: 100,
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prompt: 50,
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completion: 50,
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},
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cost: 0.002,
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cached: false,
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conversationEnded: false, // Optional: set true to stop multi-turn redteam gracefully
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conversationEndReason: 'thread_closed', // Optional reason when conversationEnded=true
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metadata: {}, // Additional data
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...
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}
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```
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### Context Parameter
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The `context` parameter provides test case information and utility objects:
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```javascript
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{
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vars: {}, // Test case variables
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prompt: {}, // Prompt template (raw, label, config)
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test: { // Full test case object
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vars: {},
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metadata: {
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pluginId: '...', // Redteam plugin (e.g. "promptfoo:redteam:harmful:hate")
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strategyId: '...', // Redteam strategy (e.g. "jailbreak", "jailbreak-templates")
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},
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},
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originalProvider: {}, // Original provider when overridden
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logger: {}, // Winston logger instance
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}
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```
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For redteam evals, use `context.test.metadata.pluginId` and `context.test.metadata.strategyId` to identify which plugin and strategy generated the test case.
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### Reporting the Actual Prompt
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If your provider dynamically generates or modifies prompts, you can report the actual prompt sent to the LLM using the `prompt` field in your response. This is useful for:
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- Frameworks like GenAIScript that generate prompts dynamically
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- Agent frameworks that build multi-turn conversations
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- Providers that add system instructions or modify the prompt
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```javascript title="dynamicPromptProvider.mjs"
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export default class DynamicPromptProvider {
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id = () => 'dynamic-prompt';
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callApi = async (prompt, context) => {
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// Generate a different prompt dynamically
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const generatedPrompt = `System: You are helpful.\nUser: ${prompt}`;
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// Call the LLM with the generated prompt
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const response = await callLLM(generatedPrompt);
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return {
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output: response,
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prompt: generatedPrompt, // Report what was actually sent
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};
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};
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}
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```
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The reported prompt is used for:
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- **Display**: Shown as "Actual Prompt Sent" in the web UI
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- **Assertions**: Prompt-based assertions like `moderation` check this value
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- **Debugging**: Helps understand what was actually sent to the LLM
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See the [vercel-ai-sdk example](https://github.com/promptfoo/promptfoo/tree/main/examples/integration-vercel/ai-sdk) for a complete working example.
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### Two-Stage Provider
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```javascript title="twoStageProvider.js"
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const promptfoo = require('promptfoo').default;
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module.exports = class TwoStageProvider {
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constructor(options) {
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this.providerId = options.id || 'two-stage';
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this.config = options.config;
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}
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id() {
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return this.providerId;
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}
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async callApi(prompt) {
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// First stage: fetch additional data
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const secretData = await this.fetchSecret(this.config.secretKey);
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// Second stage: call LLM with enriched prompt
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const enrichedPrompt = `${prompt}\nContext: ${secretData}`;
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const llmResponse = await this.callLLM(enrichedPrompt);
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return {
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output: llmResponse.output,
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metadata: { secretUsed: true },
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};
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}
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async fetchSecret(key) {
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// Fetch some external data needed for processing
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return `Secret information for ${key}`;
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}
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async callLLM(prompt) {
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const { data } = await promptfoo.cache.fetchWithCache(
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'https://api.openai.com/v1/chat/completions',
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{
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method: 'POST',
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headers: {
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'Content-Type': 'application/json',
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Authorization: `Bearer ${process.env.OPENAI_API_KEY}`,
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},
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body: JSON.stringify({
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model: 'gpt-5-mini',
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messages: [{ role: 'user', content: prompt }],
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}),
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},
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);
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return {
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output: data.choices[0].message.content,
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};
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}
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};
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```
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### TypeScript Implementation
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```typescript title="typedProvider.ts"
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import promptfoo from 'promptfoo';
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import type {
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ApiProvider,
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ProviderOptions,
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ProviderResponse,
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CallApiContextParams,
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} from 'promptfoo';
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export default class TypedProvider implements ApiProvider {
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protected providerId: string;
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public config: Record<string, any>;
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constructor(options: ProviderOptions) {
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this.providerId = options.id || 'typed-provider';
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this.config = options.config || {};
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}
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id(): string {
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return this.providerId;
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}
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async callApi(prompt: string, context?: CallApiContextParams): Promise<ProviderResponse> {
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const username = (context?.vars?.username as string) || 'anonymous';
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return {
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output: `Hello, ${username}! You said: "${prompt}"`,
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tokenUsage: {
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total: prompt.length,
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prompt: prompt.length,
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completion: 0,
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},
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};
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}
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}
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```
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### TypeScript Providers in Frontend Projects
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Promptfoo loads TypeScript providers in Node.js, not through your frontend bundler. If your provider imports app code from a Vite, Next.js, or Webpack project, make sure the imports are also valid from Node.
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For path aliases such as `@/utils`, define the alias in `tsconfig.json`:
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```json
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{
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"compilerOptions": {
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"baseUrl": ".",
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"paths": {
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"@/*": ["src/*"]
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}
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}
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}
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```
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Run `promptfoo eval` from the project root so the TypeScript loader can find that `tsconfig.json`.
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If your provider depends on bundler-only aliases, browser-only globals, CSS imports, or frontend plugins, compile or bundle the provider to JavaScript first and reference the built file:
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```yaml
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providers:
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- file://dist/promptfoo-provider.js
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```
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## Additional Capabilities
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### Embeddings API
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```javascript title="embeddingProvider.js"
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async callEmbeddingApi(text) {
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const response = await fetch('https://api.openai.com/v1/embeddings', {
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method: 'POST',
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headers: {
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'Content-Type': 'application/json',
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Authorization: `Bearer ${process.env.OPENAI_API_KEY}`,
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},
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body: JSON.stringify({
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model: 'text-embedding-3-small',
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input: text,
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}),
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});
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const data = await response.json();
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return {
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embedding: data.data[0].embedding,
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tokenUsage: {
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total: data.usage.total_tokens,
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prompt: data.usage.prompt_tokens,
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completion: 0,
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},
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};
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}
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```
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### Classification API
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```javascript title="classificationProvider.js"
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async callClassificationApi(text) {
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return {
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classification: {
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positive: 0.75,
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neutral: 0.20,
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negative: 0.05,
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},
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};
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}
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```
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### Handling Multimodal Content
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Custom providers handle multimodal content the same way whether the media comes from a standard eval or a red team strategy: read the media variable from `context.vars` and translate it into the target API's expected payload shape.
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For standard evals, provide the media value through `tests[].vars`, `defaultTest.vars`, a dataset column, or a dynamic variable:
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```yaml title="promptfooconfig.yaml"
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prompts:
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- '{{image}} {{question}}'
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tests:
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- vars:
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image: 'data:image/png;base64,iVBORw0KGgo...'
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question: Describe this image.
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```
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In this case, `context.vars.image` contains the configured value. It may be raw base64, a `data:` URL, an external URL, or another representation your provider knows how to forward.
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For red team runs, [image](/docs/red-team/strategies/image), [audio](/docs/red-team/strategies/audio), and [video](/docs/red-team/strategies/video) strategies generate media and store it in the template variable named by `redteam.injectVar`. The rendered `prompt` also contains the media value, but `context.vars` is safer because it preserves variable boundaries and avoids parsing a very long prompt.
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| Red team strategy | `context.vars[redteam.injectVar]` | Extra context | Forwarding notes |
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| ----------------- | -------------------------------------------------------- | --------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
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| `image` | Raw PNG base64, no `data:` prefix | `context.vars.image_text`, `context.test.metadata.originalText` | Wrap as `data:image/png;base64,...` for APIs that expect data URLs. |
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| `audio` | Raw MP3 base64 from remote generation, no `data:` prefix | `context.test.metadata.originalText` | Requires remote generation. Forward with MIME type `audio/mpeg` or your provider's equivalent audio format. |
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| `video` | Raw MP4 base64 when local FFmpeg generation succeeds | `context.vars.video_text`, `context.test.metadata.originalText` | Install FFmpeg and set `PROMPTFOO_DISABLE_REMOTE_GENERATION=true` or `PROMPTFOO_DISABLE_REDTEAM_REMOTE_GENERATION=true` for real MP4 bytes. If generation falls back, the value may decode to the original text instead of an MP4. |
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Audio and video have opposite generation requirements today: audio requires remote generation, while real MP4 video requires the local FFmpeg path. Run separate scans if you need to verify both remote audio and local MP4 handling.
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```javascript title="multimodalProvider.js"
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module.exports = class MultimodalProvider {
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id() {
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return 'multimodal-provider';
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}
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async callApi(prompt, context) {
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const apiKey = process.env.OPENAI_API_KEY;
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if (!apiKey) {
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return { error: 'OPENAI_API_KEY is required' };
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}
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const imageBase64 = context.vars.image || '';
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const question = context.vars.question || 'Describe this image';
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// Red team image runs provide raw PNG base64. Eval vars may already provide a URL.
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const imageUrl = /^(data:|https?:\/\/)/.test(imageBase64)
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? imageBase64
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: `data:image/png;base64,${imageBase64}`;
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const response = await fetch('https://api.openai.com/v1/chat/completions', {
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method: 'POST',
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headers: {
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Authorization: `Bearer ${apiKey}`,
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'Content-Type': 'application/json',
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},
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body: JSON.stringify({
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model: 'gpt-5',
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messages: [
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{
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role: 'user',
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content: [
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{ type: 'image_url', image_url: { url: imageUrl } },
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{ type: 'text', text: question },
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],
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},
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],
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}),
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});
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if (!response.ok) {
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return { error: `OpenAI API error ${response.status}: ${await response.text()}` };
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}
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const result = await response.json();
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const output = result.choices?.[0]?.message?.content;
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return output
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? { output }
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: { error: `OpenAI API returned no output: ${JSON.stringify(result)}` };
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}
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};
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```
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:::note
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`injectVar` defaults to the **last** template variable in your prompt. With `{{image}} {{question}}`, it defaults to `question` — not `image`. Always set `injectVar` explicitly when using media strategies.
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:::
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Avoid logging full media strings; screenshots, audio, and video can be large or sensitive. For debugging, log length, detected MIME type, a hash, or the first few bytes after decoding instead of the full base64 payload.
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See the [Python provider multimodal docs](/docs/providers/python#handling-multimodal-content) for a Python example.
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## Cache System
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The built-in caching system helps avoid redundant API calls:
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```javascript title="cacheExample.js"
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// Get the cache instance
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const cache = promptfoo.cache.getCache();
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// Store and retrieve data
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await cache.set('my-key', 'cached-value', { ttl: 3600 }); // TTL in seconds
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const value = await cache.get('my-key');
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// Fetch with cache wrapper
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const { data, cached } = await promptfoo.cache.fetchWithCache(
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'https://api.example.com/endpoint',
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{
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method: 'POST',
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body: JSON.stringify({ query: 'data' }),
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},
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5000, // timeout in ms
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);
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```
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## Configuration
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### Provider Configuration
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```yaml title="promptfooconfig.yaml"
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providers:
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- id: file://./myProvider.mjs # ES6 modules
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label: 'My Custom API' # Display name in UI
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config:
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model: 'gpt-5'
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temperature: 0.7
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max_tokens: 2000
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custom_parameter: 'custom value'
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# - id: file://./myProvider.js # CommonJS modules
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```
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### Link to Cloud Target
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:::info Promptfoo Cloud Feature
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Available in [Promptfoo Cloud](/docs/enterprise) deployments.
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:::
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Link your local provider configuration to a cloud target using `linkedTargetId`:
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```yaml
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providers:
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- id: file://./myProvider.mjs
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config:
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linkedTargetId: 'promptfoo://provider/12345678-1234-1234-1234-123456789abc'
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```
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See [Linking Local Targets to Cloud](/docs/red-team/troubleshooting/linking-targets/) for setup instructions.
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### Multiple Instances
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|
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```yaml title="multiple-providers.yaml"
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providers:
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- id: file:///path/to/provider.js
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label: high-temperature
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config:
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temperature: 0.9
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- id: file:///path/to/provider.js
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label: low-temperature
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config:
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temperature: 0.1
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```
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## See Also
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|
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- [Browser Provider](/docs/providers/browser/)
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- [Custom Provider Examples](https://github.com/promptfoo/promptfoo/tree/main/examples)
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- [Custom Script Provider](/docs/providers/custom-script/)
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- [Go Provider](/docs/providers/go/)
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- [HTTP Provider](/docs/providers/http/)
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- [Python Provider](/docs/providers/python/)
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