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229 lines
8.5 KiB
Markdown
229 lines
8.5 KiB
Markdown
---
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sidebar_label: Replicate
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description: "Deploy and run open-source AI models in the cloud using Replicate's scalable API for image, text, and audio generation"
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---
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# Replicate
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Replicate is an API for machine learning models. It currently hosts models like [Llama v2](https://replicate.com/replicate/llama70b-v2-chat), [Gemma](https://replicate.com/google-deepmind/gemma-7b-it), and [Mistral/Mixtral](https://replicate.com/mistralai/mixtral-8x7b-instruct-v0.1).
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:::info
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The Replicate provider in promptfoo uses direct HTTP requests to the Replicate API, so no additional SDK installation is required.
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:::
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To run a model, specify the Replicate model name and optionally the version:
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```
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# With specific version (recommended for consistency)
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replicate:replicate/llama70b-v2-chat:e951f18578850b652510200860fc4ea62b3b16fac280f83ff32282f87bbd2e48
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# Without version (uses latest)
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replicate:meta/meta-llama-3-8b-instruct
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```
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:::tip
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For production use, always specify the version to ensure consistent results. You can find version IDs on the model's page on Replicate.
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:::
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## Examples
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Here's an example of using Llama on Replicate. In the case of Llama, the version hash and everything under `config` is optional:
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```yaml
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providers:
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- id: replicate:meta/llama-2-7b-chat
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config:
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temperature: 0.01
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max_length: 1024
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prompt:
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prefix: '[INST] '
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suffix: ' [/INST]'
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```
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Here's an example of using Gemma on Replicate. Note that unlike Llama, it does not have a default version, so we specify the model version:
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```yaml
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providers:
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- id: replicate:google-deepmind/gemma-7b-it:2790a695e5dcae15506138cc4718d1106d0d475e6dca4b1d43f42414647993d5
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config:
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temperature: 0.01
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max_new_tokens: 1024
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prompt:
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prefix: "<start_of_turn>user\n"
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suffix: "<end_of_turn>\n<start_of_turn>model"
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```
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## Configuration
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The Replicate provider supports several [configuration options](https://github.com/promptfoo/promptfoo/blob/main/src/providers/replicate.ts#L24) that can be used to customize the behavior of the models, like so:
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| Parameter | Description |
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| -------------------- | ------------------------------------------------------------- |
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| `temperature` | Controls randomness in the generation process. |
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| `max_length` | Specifies the maximum length of the generated text. |
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| `max_new_tokens` | Limits the number of new tokens to generate. |
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| `top_p` | Nucleus sampling: a float between 0 and 1. |
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| `top_k` | Top-k sampling: number of highest probability tokens to keep. |
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| `repetition_penalty` | Penalizes repetition of words in the generated text. |
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| `system_prompt` | Sets a system-level prompt for all requests. |
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| `stop_sequences` | Specifies stopping sequences that halt the generation. |
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| `seed` | Sets a seed for reproducible results. |
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:::warning
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Not every model supports every completion parameter. Be sure to review the API provided by the model beforehand.
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:::
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These parameters are supported for all models:
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| Parameter | Description |
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| --------------- | ------------------------------------------------------------------------ |
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| `apiKey` | The API key for authentication with Replicate. |
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| `prompt.prefix` | String added before each prompt. Useful for instruction/chat formatting. |
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| `prompt.suffix` | String added after each prompt. Useful for instruction/chat formatting. |
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Supported environment variables:
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- `REPLICATE_API_TOKEN` - Your Replicate API key.
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- `REPLICATE_API_KEY` - An alternative to `REPLICATE_API_TOKEN` for your API key.
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- `REPLICATE_MAX_LENGTH` - Specifies the maximum length of the generated text.
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- `REPLICATE_TEMPERATURE` - Controls randomness in the generation process.
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- `REPLICATE_REPETITION_PENALTY` - Penalizes repetition of words in the generated text.
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- `REPLICATE_TOP_P` - Controls the nucleus sampling: a float between 0 and 1.
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- `REPLICATE_TOP_K` - Controls the top-k sampling: the number of highest probability vocabulary tokens to keep for top-k-filtering.
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- `REPLICATE_SEED` - Sets a seed for reproducible results.
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- `REPLICATE_STOP_SEQUENCES` - Specifies stopping sequences that halt the generation.
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- `REPLICATE_SYSTEM_PROMPT` - Sets a system-level prompt for all requests.
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## Images
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Image generators such as SDXL can be used like so:
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```yaml
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prompts:
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- 'Generate an image: {{subject}}'
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providers:
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- id: replicate:image:stability-ai/sdxl:7762fd07cf82c948538e41f63f77d685e02b063e37e496e96eefd46c929f9bdc
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config:
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width: 768
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height: 768
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num_inference_steps: 50
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tests:
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- vars:
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subject: fruit loops
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```
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## Supported Parameters for Images
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These parameters are supported for image generation models:
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| Parameter | Description |
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| --------------------- | ------------------------------------------------------------- |
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| `width` | The width of the generated image. |
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| `height` | The height of the generated image. |
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| `refine` | Which refine style to use |
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| `apply_watermark` | Apply a watermark to the generated image. |
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| `num_inference_steps` | The number of inference steps to use during image generation. |
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:::warning
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Not every model supports every image parameter. Be sure to review the API provided by the model beforehand.
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:::
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Supported environment variables for images:
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- `REPLICATE_API_TOKEN` - Your Replicate API key.
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- `REPLICATE_API_KEY` - An alternative to `REPLICATE_API_TOKEN` for your API key.
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:::warning
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**Important:** Replicate image URLs are temporary and typically expire after 24 hours. If you need to preserve generated images, download them immediately or use the automated download hook described below.
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:::
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## Downloading Generated Images
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Since Replicate image URLs expire, you may want to automatically download and save images during evaluation. You can use an `afterEach` hook for this purpose:
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Create a file `save-images.js`:
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```javascript
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const fs = require('fs');
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const path = require('path');
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// For Node >= 20, fetch is available globally
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const { fetch } = globalThis;
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/**
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* Downloads and saves Replicate generated images after each test
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*/
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module.exports = {
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async hook(hookName, context) {
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// Only run for afterEach hook and when we have an output
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if (hookName !== 'afterEach') {
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return;
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}
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// Extract URL from markdown image format
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const output = context.result?.response?.output;
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if (!output || typeof output !== 'string') {
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return;
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}
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const match = output.match(/!\[.*?\]\((.*?)\)/);
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const imageUrl = match?.[1];
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if (!imageUrl || !imageUrl.includes('replicate.delivery')) {
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return;
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}
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try {
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// Create images directory if it doesn't exist
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const imagesDir = path.join(__dirname, 'images');
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await fs.promises.mkdir(imagesDir, { recursive: true });
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// Generate filename from test description and timestamp
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const testDesc = context.test.description || 'unnamed';
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const timestamp = new Date().toISOString().replace(/[:.]/g, '-');
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const sanitizedName = testDesc
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.replace(/[^a-z0-9\s-]/gi, '')
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.trim()
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.replace(/\s+/g, '-')
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.toLowerCase();
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const filename = `${sanitizedName}-${timestamp}.png`;
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const filepath = path.join(imagesDir, filename);
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// Download and save the image
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const response = await fetch(imageUrl);
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if (!response.ok) {
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throw new Error(`HTTP error: ${response.status}`);
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}
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const buffer = await response.arrayBuffer();
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await fs.promises.writeFile(filepath, Buffer.from(buffer));
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console.log(`✓ Saved image: ${filename}`);
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} catch (error) {
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console.error(`❌ Failed to save image: ${error.message}`);
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}
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},
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};
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```
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Then reference it in your promptfoo configuration:
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```yaml
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# yaml-language-server: $schema=https://promptfoo.dev/config-schema.json
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extensions:
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- file://save-images.js:hook
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prompts:
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- 'Generate an image: {{subject}}'
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providers:
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- replicate:image:black-forest-labs/flux-dev
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tests:
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- vars:
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subject: a beautiful sunset over mountains
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```
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This hook will automatically download all generated images to an `images/` directory with descriptive filenames based on the test description and timestamp.
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