data
Replicate Lua API for KosmoKrator Agents
Agent-facing Lua documentation and function reference for the Replicate KosmoKrator integration.Lua Namespace
Agents call this integration through app.integrations.replicate.*.
Use lua_read_doc("integrations.replicate") inside KosmoKrator to discover the same reference at runtime.
Call Lua from the Headless CLI
Use kosmo integrations:lua when a shell script, CI job, cron job, or another coding CLI should run a deterministic
Replicate workflow without starting an interactive agent session.
kosmo integrations:lua --eval 'dump(app.integrations.replicate.cancel_prediction({}))' --json kosmo integrations:lua --eval 'print(docs.read("replicate"))' --json
kosmo integrations:lua --eval 'print(docs.read("replicate.cancel_prediction"))' --json Workflow file
Put repeatable logic in a Lua file, then execute it with JSON output for the calling process.
local replicate = app.integrations.replicate
local result = replicate.cancel_prediction({})
dump(result) kosmo integrations:lua workflow.lua --json
kosmo integrations:lua workflow.lua --force --json integrations:lua exposes app.integrations.replicate, app.mcp.*, docs.*, json.*, and regex.*. Use app.integrations.replicate.default.* or app.integrations.replicate.work.* when you configured named credential accounts.
MCP-only Lua
If the script only needs configured MCP servers and does not need Replicate, use the narrower mcp:lua command.
# Use mcp:lua for MCP-only scripts; use integrations:lua for this integration namespace.
kosmo mcp:lua --eval 'dump(mcp.servers())' --json Agent-Facing Lua Docs
This is the rendered version of the full Lua documentation exposed to agents when they inspect the integration namespace.
Replicate Lua Reference
Namespace: replicate
This integration covers Replicate’s official HTTP API OpenAPI schema from https://api.replicate.com/openapi.json. Tools map directly to documented operations for account, collections, deployments, files, hardware, models, predictions, search, trainings, and webhook signing secrets.
All tools return Replicate’s JSON response directly. File downloads return { body, content_type } when Replicate responds with non-JSON content.
Common Patterns
Read account details:
local account = app.integrations.replicate.get_account({})
Create a prediction by version:
local prediction = app.integrations.replicate.create_prediction({
version = "replicate-version-id",
input = { prompt = "a quiet forest trail" }
})
Create a prediction using an official model:
local prediction = app.integrations.replicate.create_model_prediction({
model_owner = "black-forest-labs",
model_name = "flux-schnell",
input = { prompt = "a quiet forest trail" }
})
Create a prediction using a deployment:
local prediction = app.integrations.replicate.create_deployment_prediction({
deployment_owner = "example-org",
deployment_name = "image-worker",
input = { prompt = "a quiet forest trail" }
})
Cancel a prediction:
app.integrations.replicate.cancel_prediction({
prediction_id = "prediction-id"
})
Search public models:
local result = app.integrations.replicate.search_models({
body = "image generation"
})
Upload a file:
local file = app.integrations.replicate.create_file({
body = {
content = "/tmp/example.png",
filename = "example.png",
type = "image/png",
metadata = { source = "agent" }
}
})
Tool Families
- Account:
get_account - Collections:
list_collections,get_collection - Deployments:
list_deployments,create_deployment,get_deployment,update_deployment,delete_deployment,create_deployment_prediction - Files:
list_files,create_file,get_file,delete_file,download_file - Hardware:
list_hardware - Models:
list_models,create_model,search_models,get_model,update_model,delete_model,list_model_examples,create_model_prediction,get_model_readme,list_model_versions,get_model_version,delete_model_version - Predictions:
list_predictions,create_prediction,get_prediction,cancel_prediction - Search:
search - Trainings:
list_trainings,create_training,get_training,cancel_training - Webhooks:
get_default_webhook_secret
For operations with a request body, pass either body = { ... } or pass body fields directly when there is no ambiguity. Headers from the OpenAPI schema, such as Prefer and Cancel-After, can be passed by their exact name or snake_case form.
Raw agent markdown
# Replicate Lua Reference
Namespace: `replicate`
This integration covers Replicate's official HTTP API OpenAPI schema from `https://api.replicate.com/openapi.json`. Tools map directly to documented operations for account, collections, deployments, files, hardware, models, predictions, search, trainings, and webhook signing secrets.
All tools return Replicate's JSON response directly. File downloads return `{ body, content_type }` when Replicate responds with non-JSON content.
## Common Patterns
Read account details:
```lua
local account = app.integrations.replicate.get_account({})
```
Create a prediction by version:
```lua
local prediction = app.integrations.replicate.create_prediction({
version = "replicate-version-id",
input = { prompt = "a quiet forest trail" }
})
```
Create a prediction using an official model:
```lua
local prediction = app.integrations.replicate.create_model_prediction({
model_owner = "black-forest-labs",
model_name = "flux-schnell",
input = { prompt = "a quiet forest trail" }
})
```
Create a prediction using a deployment:
```lua
local prediction = app.integrations.replicate.create_deployment_prediction({
deployment_owner = "example-org",
deployment_name = "image-worker",
input = { prompt = "a quiet forest trail" }
})
```
Cancel a prediction:
```lua
app.integrations.replicate.cancel_prediction({
prediction_id = "prediction-id"
})
```
Search public models:
```lua
local result = app.integrations.replicate.search_models({
body = "image generation"
})
```
Upload a file:
```lua
local file = app.integrations.replicate.create_file({
body = {
content = "/tmp/example.png",
filename = "example.png",
type = "image/png",
metadata = { source = "agent" }
}
})
```
## Tool Families
- Account: `get_account`
- Collections: `list_collections`, `get_collection`
- Deployments: `list_deployments`, `create_deployment`, `get_deployment`, `update_deployment`, `delete_deployment`, `create_deployment_prediction`
- Files: `list_files`, `create_file`, `get_file`, `delete_file`, `download_file`
- Hardware: `list_hardware`
- Models: `list_models`, `create_model`, `search_models`, `get_model`, `update_model`, `delete_model`, `list_model_examples`, `create_model_prediction`, `get_model_readme`, `list_model_versions`, `get_model_version`, `delete_model_version`
- Predictions: `list_predictions`, `create_prediction`, `get_prediction`, `cancel_prediction`
- Search: `search`
- Trainings: `list_trainings`, `create_training`, `get_training`, `cancel_training`
- Webhooks: `get_default_webhook_secret`
For operations with a request body, pass either `body = { ... }` or pass body fields directly when there is no ambiguity. Headers from the OpenAPI schema, such as `Prefer` and `Cancel-After`, can be passed by their exact name or snake_case form. local result = app.integrations.replicate.cancel_prediction({})
print(result) Functions
cancel_prediction Write
Cancel a prediction that is currently running. Example cURL request that creates a prediction and then cancels it: ```console # First, create a prediction PREDICTION_ID=$(curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -d '{ "input": { "prompt": "a video that may take a while to generate" } }' \ https://api.replicate.com/v1/models/minimax/video-01/predictions | jq -r '.id') # Echo the prediction ID echo "Created prediction with ID: $PREDICTION_ID" # Cancel the prediction curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ https://api.replicate.com/v1/predictions/$PREDICTION_ID/cancel ```
- Lua path
app.integrations.replicate.cancel_prediction- Full name
replicate.replicate_cancel_prediction
| Parameter | Type | Required | Description |
|---|---|---|---|
| No parameters. | |||
cancel_training Write
Cancel a training
- Lua path
app.integrations.replicate.cancel_training- Full name
replicate.replicate_cancel_training
| Parameter | Type | Required | Description |
|---|---|---|---|
| No parameters. | |||
create_deployment Write
Create a new deployment: Example cURL request: ```console curl -s \ -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -d '{ "name": "my-app-image-generator", "model": "stability-ai/sdxl", "version": "da77bc59ee60423279fd632efb4795ab731d9e3ca9705ef3341091fb989b7eaf", "hardware": "gpu-t4", "min_instances": 0, "max_instances": 3 }' \ https://api.replicate.com/v1/deployments ``` The response will be a JSON object describing the deployment: ```json { "owner": "acme", "name": "my-app-image-generator", "current_release": { "number": 1, "model": "stability-ai/sdxl", "version": "da77bc59ee60423279fd632efb4795ab731d9e3ca9705ef3341091fb989b7eaf", "created_at": "2024-02-15T16:32:57.018467Z", "created_by": { "type": "organization", "username": "acme", "name": "Acme Corp, Inc.", "avatar_url": "https://cdn.replicate.com/avatars/acme.png", "github_url": "https://github.com/acme" }, "configuration": { "hardware": "gpu-t4", "min_instances": 1, "max_instances": 5 } } } ```
- Lua path
app.integrations.replicate.create_deployment- Full name
replicate.replicate_create_deployment
| Parameter | Type | Required | Description |
|---|---|---|---|
| No parameters. | |||
create_prediction_using_deployment Write
Create a prediction for the deployment and inputs you provide. Example cURL request: ```console curl -s -X POST -H 'Prefer: wait' \ -d '{"input": {"prompt": "A photo of a bear riding a bicycle over the moon"}}' \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H 'Content-Type: application/json' \ https://api.replicate.com/v1/deployments/acme/my-app-image-generator/predictions ``` The request will wait up to 60 seconds for the model to run. If this time is exceeded the prediction will be returned in a `"starting"` state and need to be retrieved using the `predictions.get` endpoint. For a complete overview of the `deployments.predictions.create` API check out our documentation on [creating a prediction](https://replicate.com/docs/topics/predictions/create-a-prediction) which covers a variety of use cases.
- Lua path
app.integrations.replicate.create_prediction_using_deployment- Full name
replicate.replicate_create_deployment_prediction
| Parameter | Type | Required | Description |
|---|---|---|---|
| No parameters. | |||
create_file Write
Create a file by uploading its content and optional metadata. Example cURL request: ```console curl -X POST https://api.replicate.com/v1/files \ -H "Authorization: Token $REPLICATE_API_TOKEN" \ -H 'Content-Type: multipart/form-data' \ -F 'content=@/path/to/archive.zip;type=application/zip;filename=example.zip' \ -F 'metadata={"customer_reference_id": 123};type=application/json' ``` The request must include: - `content`: The file content (required) - `type`: The content / MIME type for the file (defaults to `application/octet-stream`) - `filename`: The filename (required, 255 bytes, valid UTF-8) - `metadata`: User-provided metadata associated with the file (defaults to `{}`, must be valid JSON)
- Lua path
app.integrations.replicate.create_file- Full name
replicate.replicate_create_file
| Parameter | Type | Required | Description |
|---|---|---|---|
| No parameters. | |||
create_model Write
Create a model. Example cURL request: ```console curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H 'Content-Type: application/json' \ -d '{"owner": "alice", "name": "hot-dog-detector", "description": "Detect hot dogs in images", "visibility": "public", "hardware": "cpu"}' \ https://api.replicate.com/v1/models ``` The response will be a model object in the following format: ```json { "url": "https://replicate.com/alice/hot-dog-detector", "owner": "alice", "name": "hot-dog-detector", "description": "Detect hot dogs in images", "visibility": "public", "github_url": null, "paper_url": null, "license_url": null, "run_count": 0, "cover_image_url": null, "default_example": null, "latest_version": null, } ``` Note that there is a limit of 1,000 models per account. For most purposes, we recommend using a single model and pushing new [versions](https://replicate.com/docs/how-does-replicate-work#versions) of the model as you make changes to it.
- Lua path
app.integrations.replicate.create_model- Full name
replicate.replicate_create_model
| Parameter | Type | Required | Description |
|---|---|---|---|
| No parameters. | |||
create_prediction_using_official_model Write
Create a prediction using an [official model](https://replicate.com/changelog/2025-01-29-official-models). If you're _not_ running an official model, use the [`predictions.create`](#predictions.create) operation instead. Example cURL request: ```console curl -s -X POST -H 'Prefer: wait' \ -d '{"input": {"prompt": "Write a short poem about the weather."}}' \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H 'Content-Type: application/json' \ https://api.replicate.com/v1/models/meta/meta-llama-3-70b-instruct/predictions ``` The request will wait up to 60 seconds for the model to run. If this time is exceeded the prediction will be returned in a `"starting"` state and need to be retrieved using the `predictions.get` endpoint. For a complete overview of the `deployments.predictions.create` API check out our documentation on [creating a prediction](https://replicate.com/docs/topics/predictions/create-a-prediction) which covers a variety of use cases.
- Lua path
app.integrations.replicate.create_prediction_using_official_model- Full name
replicate.replicate_create_model_prediction
| Parameter | Type | Required | Description |
|---|---|---|---|
| No parameters. | |||
create_prediction Write
Create a prediction for the model version and inputs you provide. Example cURL request: ```console curl -s -X POST -H 'Prefer: wait' \ -d '{"version": "replicate/hello-world:5c7d5dc6dd8bf75c1acaa8565735e7986bc5b66206b55cca93cb72c9bf15ccaa", "input": {"text": "Alice"}}' \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H 'Content-Type: application/json' \ https://api.replicate.com/v1/predictions ``` The request will wait up to 60 seconds for the model to run. If this time is exceeded the prediction will be returned in a `"starting"` state and need to be retrieved using the `predictions.get` endpoint. For a complete overview of the `predictions.create` API check out our documentation on [creating a prediction](https://replicate.com/docs/topics/predictions/create-a-prediction) which covers a variety of use cases.
- Lua path
app.integrations.replicate.create_prediction- Full name
replicate.replicate_create_prediction
| Parameter | Type | Required | Description |
|---|---|---|---|
| No parameters. | |||
create_training Write
Start a new training of the model version you specify. Example request body: ```json { "destination": "{new_owner}/{new_name}", "input": { "train_data": "https://example.com/my-input-images.zip", }, "webhook": "https://example.com/my-webhook", } ``` Example cURL request: ```console curl -s -X POST \ -d '{"destination": "{new_owner}/{new_name}", "input": {"input_images": "https://example.com/my-input-images.zip"}}' \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H 'Content-Type: application/json' \ https://api.replicate.com/v1/models/stability-ai/sdxl/versions/da77bc59ee60423279fd632efb4795ab731d9e3ca9705ef3341091fb989b7eaf/trainings ``` The response will be the training object: ```json { "id": "zz4ibbonubfz7carwiefibzgga", "model": "stability-ai/sdxl", "version": "da77bc59ee60423279fd632efb4795ab731d9e3ca9705ef3341091fb989b7eaf", "input": { "input_images": "https://example.com/my-input-images.zip" }, "logs": "", "error": null, "status": "starting", "created_at": "2023-09-08T16:32:56.990893084Z", "urls": { "web": "https://replicate.com/p/zz4ibbonubfz7carwiefibzgga", "get": "https://api.replicate.com/v1/predictions/zz4ibbonubfz7carwiefibzgga", "cancel": "https://api.replicate.com/v1/predictions/zz4ibbonubfz7carwiefibzgga/cancel" } } ``` As models can take several minutes or more to train, the result will not be available immediately. To get the final result of the training you should either provide a `webhook` HTTPS URL for us to call when the results are ready, or poll the [get a training](#trainings.get) endpoint until it has finished. When a training completes, it creates a new [version](https://replicate.com/docs/how-does-replicate-work#terminology) of the model at the specified destination. To find some models to train on, check out the [trainable language models collection](https://replicate.com/collections/trainable-language-models).
- Lua path
app.integrations.replicate.create_training- Full name
replicate.replicate_create_training
| Parameter | Type | Required | Description |
|---|---|---|---|
| No parameters. | |||
delete_deployment Write
Delete a deployment Deployment deletion has some restrictions: - You can only delete deployments that have been offline and unused for at least 15 minutes. Example cURL request: ```command curl -s -X DELETE \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ https://api.replicate.com/v1/deployments/acme/my-app-image-generator ``` The response will be an empty 204, indicating the deployment has been deleted.
- Lua path
app.integrations.replicate.delete_deployment- Full name
replicate.replicate_delete_deployment
| Parameter | Type | Required | Description |
|---|---|---|---|
| No parameters. | |||
delete_file Write
Delete a file. Once a file has been deleted, subsequent requests to the file resource return 404 Not found. Example cURL request: ```console curl -X DELETE \ -H "Authorization: Token $REPLICATE_API_TOKEN" \ https://api.replicate.com/v1/files/cneqzikepnug6xezperrr4z55o ```
- Lua path
app.integrations.replicate.delete_file- Full name
replicate.replicate_delete_file
| Parameter | Type | Required | Description |
|---|---|---|---|
| No parameters. | |||
delete_model Write
Delete a model Model deletion has some restrictions: - You can only delete models you own. - You can only delete private models. - You can only delete models that have no versions associated with them. Currently you'll need to [delete the model's versions](#models.versions.delete) before you can delete the model itself. Example cURL request: ```command curl -s -X DELETE \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ https://api.replicate.com/v1/models/replicate/hello-world ``` The response will be an empty 204, indicating the model has been deleted.
- Lua path
app.integrations.replicate.delete_model- Full name
replicate.replicate_delete_model
| Parameter | Type | Required | Description |
|---|---|---|---|
| No parameters. | |||
delete_model_version Write
Delete a model version and all associated predictions, including all output files. Model version deletion has some restrictions: - You can only delete versions from models you own. - You can only delete versions from private models. - You cannot delete a version if someone other than you has run predictions with it. - You cannot delete a version if it is being used as the base model for a fine tune/training. - You cannot delete a version if it has an associated deployment. - You cannot delete a version if another model version is overridden to use it. Example cURL request: ```command curl -s -X DELETE \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ https://api.replicate.com/v1/models/replicate/hello-world/versions/5c7d5dc6dd8bf75c1acaa8565735e7986bc5b66206b55cca93cb72c9bf15ccaa ``` The response will be an empty 202, indicating the deletion request has been accepted. It might take a few minutes to be processed.
- Lua path
app.integrations.replicate.delete_model_version- Full name
replicate.replicate_delete_model_version
| Parameter | Type | Required | Description |
|---|---|---|---|
| No parameters. | |||
download_file Read
Download a file by providing the file owner, access expiry, and a valid signature. Example cURL request: ```console curl -X GET "https://api.replicate.com/v1/files/cneqzikepnug6xezperrr4z55o/download?expiry=1708515345&owner=mattt&signature=zuoghqlrcnw8YHywkpaXQlHsVhWen%2FDZ4aal76dLiOo%3D" ```
- Lua path
app.integrations.replicate.download_file- Full name
replicate.replicate_download_file
| Parameter | Type | Required | Description |
|---|---|---|---|
| No parameters. | |||
get_authenticated_account Read
Returns information about the user or organization associated with the provided API token. Example cURL request: ```console curl -s \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ https://api.replicate.com/v1/account ``` The response will be a JSON object describing the account: ```json { "type": "organization", "username": "acme", "name": "Acme Corp, Inc.", "github_url": "https://github.com/acme", } ```
- Lua path
app.integrations.replicate.get_authenticated_account- Full name
replicate.replicate_get_account
| Parameter | Type | Required | Description |
|---|---|---|---|
| No parameters. | |||
get_collection_models Read
Example cURL request: ```console curl -s \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ https://api.replicate.com/v1/collections/super-resolution ``` The response will be a collection object with a nested list of the models in that collection: ```json { "name": "Super resolution", "slug": "super-resolution", "description": "Upscaling models that create high-quality images from low-quality images.", "full_description": "## Overview\n\nThese models generate high-quality images from low-quality images. Many of these models are based on **advanced upscaling techniques**.\n\n### Key Features\n\n- Enhance image resolution\n- Restore fine details\n- Improve overall image quality", "models": [...] } ```
- Lua path
app.integrations.replicate.get_collection_models- Full name
replicate.replicate_get_collection
| Parameter | Type | Required | Description |
|---|---|---|---|
| No parameters. | |||
get_signing_secret_default_webhook Read
Get the signing secret for the default webhook endpoint. This is used to verify that webhook requests are coming from Replicate. Example cURL request: ```console curl -s \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ https://api.replicate.com/v1/webhooks/default/secret ``` The response will be a JSON object with a `key` property: ```json { "key": "..." } ```
- Lua path
app.integrations.replicate.get_signing_secret_default_webhook- Full name
replicate.replicate_get_default_webhook_secret
| Parameter | Type | Required | Description |
|---|---|---|---|
| No parameters. | |||
get_deployment Read
Get information about a deployment by name including the current release. Example cURL request: ```console curl -s \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ https://api.replicate.com/v1/deployments/replicate/my-app-image-generator ``` The response will be a JSON object describing the deployment: ```json { "owner": "acme", "name": "my-app-image-generator", "current_release": { "number": 1, "model": "stability-ai/sdxl", "version": "da77bc59ee60423279fd632efb4795ab731d9e3ca9705ef3341091fb989b7eaf", "created_at": "2024-02-15T16:32:57.018467Z", "created_by": { "type": "organization", "username": "acme", "name": "Acme Corp, Inc.", "avatar_url": "https://cdn.replicate.com/avatars/acme.png", "github_url": "https://github.com/acme" }, "configuration": { "hardware": "gpu-t4", "min_instances": 1, "max_instances": 5 } } } ```
- Lua path
app.integrations.replicate.get_deployment- Full name
replicate.replicate_get_deployment
| Parameter | Type | Required | Description |
|---|---|---|---|
| No parameters. | |||
get_file Read
Get the details of a file. Example cURL request: ```console curl -s \ -H "Authorization: Token $REPLICATE_API_TOKEN" \ https://api.replicate.com/v1/files/cneqzikepnug6xezperrr4z55o ```
- Lua path
app.integrations.replicate.get_file- Full name
replicate.replicate_get_file
| Parameter | Type | Required | Description |
|---|---|---|---|
| No parameters. | |||
get_model Read
Example cURL request: ```console curl -s \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ https://api.replicate.com/v1/models/replicate/hello-world ``` The response will be a model object in the following format: ```json { "url": "https://replicate.com/replicate/hello-world", "owner": "replicate", "name": "hello-world", "description": "A tiny model that says hello", "visibility": "public", "github_url": "https://github.com/replicate/cog-examples", "paper_url": null, "license_url": null, "run_count": 5681081, "cover_image_url": "...", "default_example": {...}, "latest_version": {...}, } ``` The model object includes the [input and output schema](https://replicate.com/docs/reference/openapi#model-schemas) for the latest version of the model. Here's an example showing how to fetch the model with cURL and display its input schema with [jq](https://stedolan.github.io/jq/): ```console curl -s \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ https://api.replicate.com/v1/models/replicate/hello-world \ | jq ".latest_version.openapi_schema.components.schemas.Input" ``` This will return the following JSON object: ```json { "type": "object", "title": "Input", "required": [ "text" ], "properties": { "text": { "type": "string", "title": "Text", "x-order": 0, "description": "Text to prefix with 'hello '" } } } ``` The `cover_image_url` string is an HTTPS URL for an image file. This can be: - An image uploaded by the model author. - The output file of the example prediction, if the model author has not set a cover image. - The input file of the example prediction, if the model author has not set a cover image and the example prediction has no output file. - A generic fallback image. The `default_example` object is a [prediction](#predictions.get) created with this model. The `latest_version` object is the model's most recently pushed [version](#models.versions.get).
- Lua path
app.integrations.replicate.get_model- Full name
replicate.replicate_get_model
| Parameter | Type | Required | Description |
|---|---|---|---|
| No parameters. | |||
get_model_readme Read
Get the README content for a model. Example cURL request: ```console curl -s \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ https://api.replicate.com/v1/models/replicate/hello-world/readme ``` The response will be the README content as plain text in Markdown format: ``` # Hello World Model This is an example model that... ```
- Lua path
app.integrations.replicate.get_model_readme- Full name
replicate.replicate_get_model_readme
| Parameter | Type | Required | Description |
|---|---|---|---|
| No parameters. | |||
get_model_version Read
Example cURL request: ```console curl -s \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ https://api.replicate.com/v1/models/replicate/hello-world/versions/5c7d5dc6dd8bf75c1acaa8565735e7986bc5b66206b55cca93cb72c9bf15ccaa ``` The response will be the version object: ```json { "id": "5c7d5dc6dd8bf75c1acaa8565735e7986bc5b66206b55cca93cb72c9bf15ccaa", "created_at": "2022-04-26T19:29:04.418669Z", "cog_version": "0.3.0", "openapi_schema": {...} } ``` Every model describes its inputs and outputs with [OpenAPI Schema Objects](https://spec.openapis.org/oas/latest.html#schemaObject) in the `openapi_schema` property. The `openapi_schema.components.schemas.Input` property for the [replicate/hello-world](https://replicate.com/replicate/hello-world) model looks like this: ```json { "type": "object", "title": "Input", "required": [ "text" ], "properties": { "text": { "x-order": 0, "type": "string", "title": "Text", "description": "Text to prefix with 'hello '" } } } ``` The `openapi_schema.components.schemas.Output` property for the [replicate/hello-world](https://replicate.com/replicate/hello-world) model looks like this: ```json { "type": "string", "title": "Output" } ``` For more details, see the docs on [Cog's supported input and output types](https://github.com/replicate/cog/blob/75b7802219e7cd4cee845e34c4c22139558615d4/docs/python.md#input-and-output-types)
- Lua path
app.integrations.replicate.get_model_version- Full name
replicate.replicate_get_model_version
| Parameter | Type | Required | Description |
|---|---|---|---|
| No parameters. | |||
get_prediction Read
Get the current state of a prediction. Example cURL request: ```console curl -s \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ https://api.replicate.com/v1/predictions/gm3qorzdhgbfurvjtvhg6dckhu ``` The response will be the prediction object: ```json { "id": "gm3qorzdhgbfurvjtvhg6dckhu", "model": "replicate/hello-world", "version": "5c7d5dc6dd8bf75c1acaa8565735e7986bc5b66206b55cca93cb72c9bf15ccaa", "input": { "text": "Alice" }, "logs": "", "output": "hello Alice", "error": null, "status": "succeeded", "created_at": "2023-09-08T16:19:34.765994Z", "source": "api", "data_removed": false, "started_at": "2023-09-08T16:19:34.779176Z", "completed_at": "2023-09-08T16:19:34.791859Z", "metrics": { "predict_time": 0.012683 }, "urls": { "web": "https://replicate.com/p/gm3qorzdhgbfurvjtvhg6dckhu", "get": "https://api.replicate.com/v1/predictions/gm3qorzdhgbfurvjtvhg6dckhu", "cancel": "https://api.replicate.com/v1/predictions/gm3qorzdhgbfurvjtvhg6dckhu/cancel" } } ``` `source` will indicate how the prediction was created. Possible values are `web` or `api`. `status` will be one of: - `starting`: the prediction is starting up. If this status lasts longer than a few seconds, then it's typically because a new worker is being started to run the prediction. - `processing`: the `predict()` method of the model is currently running. - `succeeded`: the prediction completed successfully. - `failed`: the prediction encountered an error during processing. - `canceled`: the prediction was canceled by its creator. In the case of success, `output` will be an object containing the output of the model. Any files will be represented as HTTPS URLs. You'll need to pass the `Authorization` header to request them. In the case of failure, `error` will contain the error encountered during the prediction. Terminated predictions (with a status of `succeeded`, `failed`, or `canceled`) will include a `metrics` object with a `predict_time` property showing the amount of CPU or GPU time, in seconds, that the prediction used while running. It won't include time waiting for the prediction to start. The `metrics` object will also include a `total_time` property showing the total time, in seconds, that the prediction took to complete. All input parameters, output values, and logs are automatically removed after an hour, by default, for predictions created through the API. You must save a copy of any data or files in the output if you'd like to continue using them. The `output` key will still be present, but it's value will be `null` after the output has been removed. Output files are served by `replicate.delivery` and its subdomains. If you use an allow list of external domains for your assets, add `replicate.delivery` and `*.replicate.delivery` to it.
- Lua path
app.integrations.replicate.get_prediction- Full name
replicate.replicate_get_prediction
| Parameter | Type | Required | Description |
|---|---|---|---|
| No parameters. | |||
get_training Read
Get the current state of a training. Example cURL request: ```console curl -s \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ https://api.replicate.com/v1/trainings/zz4ibbonubfz7carwiefibzgga ``` The response will be the training object: ```json { "completed_at": "2023-09-08T16:41:19.826523Z", "created_at": "2023-09-08T16:32:57.018467Z", "error": null, "id": "zz4ibbonubfz7carwiefibzgga", "input": { "input_images": "https://example.com/my-input-images.zip" }, "logs": "...", "metrics": { "predict_time": 502.713876 }, "output": { "version": "...", "weights": "..." }, "started_at": "2023-09-08T16:32:57.112647Z", "status": "succeeded", "urls": { "web": "https://replicate.com/p/zz4ibbonubfz7carwiefibzgga", "get": "https://api.replicate.com/v1/trainings/zz4ibbonubfz7carwiefibzgga", "cancel": "https://api.replicate.com/v1/trainings/zz4ibbonubfz7carwiefibzgga/cancel" }, "model": "stability-ai/sdxl", "version": "da77bc59ee60423279fd632efb4795ab731d9e3ca9705ef3341091fb989b7eaf", } ``` `status` will be one of: - `starting`: the training is starting up. If this status lasts longer than a few seconds, then it's typically because a new worker is being started to run the training. - `processing`: the `train()` method of the model is currently running. - `succeeded`: the training completed successfully. - `failed`: the training encountered an error during processing. - `canceled`: the training was canceled by its creator. In the case of success, `output` will be an object containing the output of the model. Any files will be represented as HTTPS URLs. You'll need to pass the `Authorization` header to request them. In the case of failure, `error` will contain the error encountered during the training. Terminated trainings (with a status of `succeeded`, `failed`, or `canceled`) will include a `metrics` object with a `predict_time` property showing the amount of CPU or GPU time, in seconds, that the training used while running. It won't include time waiting for the training to start. The `metrics` object will also include a `total_time` property showing the total time, in seconds, that the training took to complete.
- Lua path
app.integrations.replicate.get_training- Full name
replicate.replicate_get_training
| Parameter | Type | Required | Description |
|---|---|---|---|
| No parameters. | |||
list_collections_models Read
Example cURL request: ```console curl -s \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ https://api.replicate.com/v1/collections ``` The response will be a paginated JSON list of collection objects: ```json { "next": "null", "previous": null, "results": [ { "name": "Super resolution", "slug": "super-resolution", "description": "Upscaling models that create high-quality images from low-quality images." } ] } ```
- Lua path
app.integrations.replicate.list_collections_models- Full name
replicate.replicate_list_collections
| Parameter | Type | Required | Description |
|---|---|---|---|
| No parameters. | |||
list_deployments Read
Get a list of deployments associated with the current account, including the latest release configuration for each deployment. Example cURL request: ```console curl -s \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ https://api.replicate.com/v1/deployments ``` The response will be a paginated JSON array of deployment objects, sorted with the most recent deployment first: ```json { "next": "http://api.replicate.com/v1/deployments?cursor=cD0yMDIzLTA2LTA2KzIzJTNBNDAlM0EwOC45NjMwMDAlMkIwMCUzQTAw", "previous": null, "results": [ { "owner": "replicate", "name": "my-app-image-generator", "current_release": { "number": 1, "model": "stability-ai/sdxl", "version": "da77bc59ee60423279fd632efb4795ab731d9e3ca9705ef3341091fb989b7eaf", "created_at": "2024-02-15T16:32:57.018467Z", "created_by": { "type": "organization", "username": "acme", "name": "Acme Corp, Inc.", "avatar_url": "https://cdn.replicate.com/avatars/acme.png", "github_url": "https://github.com/acme" }, "configuration": { "hardware": "gpu-t4", "min_instances": 1, "max_instances": 5 } } } ] } ```
- Lua path
app.integrations.replicate.list_deployments- Full name
replicate.replicate_list_deployments
| Parameter | Type | Required | Description |
|---|---|---|---|
| No parameters. | |||
list_files Read
Get a paginated list of all files created by the user or organization associated with the provided API token. Example cURL request: ```console curl -s \ -H "Authorization: Token $REPLICATE_API_TOKEN" \ https://api.replicate.com/v1/files ``` The response will be a paginated JSON array of file objects, sorted with the most recent file first.
- Lua path
app.integrations.replicate.list_files- Full name
replicate.replicate_list_files
| Parameter | Type | Required | Description |
|---|---|---|---|
| No parameters. | |||
list_available_hardware_models Read
Example cURL request: ```console curl -s \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ https://api.replicate.com/v1/hardware ``` The response will be a JSON array of hardware objects: ```json [ {"name": "CPU", "sku": "cpu"}, {"name": "Nvidia T4 GPU", "sku": "gpu-t4"}, {"name": "Nvidia A40 GPU", "sku": "gpu-a40-small"}, {"name": "Nvidia A40 (Large) GPU", "sku": "gpu-a40-large"}, ] ```
- Lua path
app.integrations.replicate.list_available_hardware_models- Full name
replicate.replicate_list_hardware
| Parameter | Type | Required | Description |
|---|---|---|---|
| No parameters. | |||
list_examples_model Read
List [example predictions](https://replicate.com/docs/topics/models/publish-a-model#what-are-examples) made using the model. These are predictions that were saved by the model author as illustrative examples of the model's capabilities. If you want all the examples for a model, use this operation. If you just want the model's default example, you can use the [`models.get`](#models.get) operation instead, which includes a `default_example` object. Example cURL request: ```console curl -s \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ https://api.replicate.com/v1/models/replicate/hello-world/examples ``` The response will be a pagination object containing a list of example predictions: ```json { "next": "https://api.replicate.com/v1/models/replicate/hello-world/examples?cursor=...", "previous": "https://api.replicate.com/v1/models/replicate/hello-world/examples?cursor=...", "results": [...] } ``` Each item in the `results` list is a [prediction object](#predictions.get).
- Lua path
app.integrations.replicate.list_examples_model- Full name
replicate.replicate_list_model_examples
| Parameter | Type | Required | Description |
|---|---|---|---|
| No parameters. | |||
list_model_versions Read
Example cURL request: ```console curl -s \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ https://api.replicate.com/v1/models/replicate/hello-world/versions ``` The response will be a JSON array of model version objects, sorted with the most recent version first: ```json { "next": null, "previous": null, "results": [ { "id": "5c7d5dc6dd8bf75c1acaa8565735e7986bc5b66206b55cca93cb72c9bf15ccaa", "created_at": "2022-04-26T19:29:04.418669Z", "cog_version": "0.3.0", "openapi_schema": {...} } ] } ```
- Lua path
app.integrations.replicate.list_model_versions- Full name
replicate.replicate_list_model_versions
| Parameter | Type | Required | Description |
|---|---|---|---|
| No parameters. | |||
list_public_models Read
Get a paginated list of public models. Example cURL request: ```console curl -s \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ https://api.replicate.com/v1/models ``` The response will be a pagination object containing a list of model objects. See the [`models.get`](#models.get) docs for more details about the model object. ## Sorting You can sort the results using the `sort_by` and `sort_direction` query parameters. For example, to get the most recently created models: ```console curl -s \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ "https://api.replicate.com/v1/models?sort_by=model_created_at&sort_direction=desc" ``` Available sorting options: - `model_created_at`: Sort by when the model was first created - `latest_version_created_at`: Sort by when the model's latest version was created (default) Sort direction can be `asc` (ascending) or `desc` (descending, default).
- Lua path
app.integrations.replicate.list_public_models- Full name
replicate.replicate_list_models
| Parameter | Type | Required | Description |
|---|---|---|---|
| No parameters. | |||
list_predictions Read
Get a paginated list of all predictions created by the user or organization associated with the provided API token. This will include predictions created from the API and the website. It will return 100 records per page. Example cURL request: ```console curl -s \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ https://api.replicate.com/v1/predictions ``` The response will be a paginated JSON array of prediction objects, sorted with the most recent prediction first: ```json { "next": null, "previous": null, "results": [ { "completed_at": "2023-09-08T16:19:34.791859Z", "created_at": "2023-09-08T16:19:34.907244Z", "data_removed": false, "error": null, "id": "gm3qorzdhgbfurvjtvhg6dckhu", "input": { "text": "Alice" }, "metrics": { "predict_time": 0.012683 }, "output": "hello Alice", "started_at": "2023-09-08T16:19:34.779176Z", "source": "api", "status": "succeeded", "urls": { "web": "https://replicate.com/p/gm3qorzdhgbfurvjtvhg6dckhu", "get": "https://api.replicate.com/v1/predictions/gm3qorzdhgbfurvjtvhg6dckhu", "cancel": "https://api.replicate.com/v1/predictions/gm3qorzdhgbfurvjtvhg6dckhu/cancel" }, "model": "replicate/hello-world", "version": "5c7d5dc6dd8bf75c1acaa8565735e7986bc5b66206b55cca93cb72c9bf15ccaa", } ] } ``` `id` will be the unique ID of the prediction. `source` will indicate how the prediction was created. Possible values are `web` or `api`. `status` will be the status of the prediction. Refer to [get a single prediction](#predictions.get) for possible values. `urls` will be a convenience object that can be used to construct new API requests for the given prediction. If the requested model version supports streaming, this will have a `stream` entry with an HTTPS URL that you can use to construct an [`EventSource`](https://developer.mozilla.org/en-US/docs/Web/API/EventSource). `model` will be the model identifier string in the format of `{model_owner}/{model_name}`. `version` will be the unique ID of model version used to create the prediction. `data_removed` will be `true` if the input and output data has been deleted.
- Lua path
app.integrations.replicate.list_predictions- Full name
replicate.replicate_list_predictions
| Parameter | Type | Required | Description |
|---|---|---|---|
| No parameters. | |||
list_trainings Read
Get a paginated list of all trainings created by the user or organization associated with the provided API token. This will include trainings created from the API and the website. It will return 100 records per page. Example cURL request: ```console curl -s \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ https://api.replicate.com/v1/trainings ``` The response will be a paginated JSON array of training objects, sorted with the most recent training first: ```json { "next": null, "previous": null, "results": [ { "completed_at": "2023-09-08T16:41:19.826523Z", "created_at": "2023-09-08T16:32:57.018467Z", "error": null, "id": "zz4ibbonubfz7carwiefibzgga", "input": { "input_images": "https://example.com/my-input-images.zip" }, "metrics": { "predict_time": 502.713876 }, "output": { "version": "...", "weights": "..." }, "started_at": "2023-09-08T16:32:57.112647Z", "source": "api", "status": "succeeded", "urls": { "web": "https://replicate.com/p/zz4ibbonubfz7carwiefibzgga", "get": "https://api.replicate.com/v1/trainings/zz4ibbonubfz7carwiefibzgga", "cancel": "https://api.replicate.com/v1/trainings/zz4ibbonubfz7carwiefibzgga/cancel" }, "model": "stability-ai/sdxl", "version": "da77bc59ee60423279fd632efb4795ab731d9e3ca9705ef3341091fb989b7eaf", } ] } ``` `id` will be the unique ID of the training. `source` will indicate how the training was created. Possible values are `web` or `api`. `status` will be the status of the training. Refer to [get a single training](#trainings.get) for possible values. `urls` will be a convenience object that can be used to construct new API requests for the given training. `version` will be the unique ID of model version used to create the training.
- Lua path
app.integrations.replicate.list_trainings- Full name
replicate.replicate_list_trainings
| Parameter | Type | Required | Description |
|---|---|---|---|
| No parameters. | |||
search_models_collections_and_docs_beta Read
Search for public models, collections, and docs using a text query. For models, the response includes all model data, plus a new `metadata` object with the following fields: - `generated_description`: A longer and more detailed AI-generated description of the model - `tags`: An array of tags for the model - `score`: A score for the model's relevance to the search query Example cURL request: ```console curl -s \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ "https://api.replicate.com/v1/search?query=nano+banana" ``` Note: This search API is currently in beta and may change in future versions.
- Lua path
app.integrations.replicate.search_models_collections_and_docs_beta- Full name
replicate.replicate_search
| Parameter | Type | Required | Description |
|---|---|---|---|
| No parameters. | |||
search_public_models Read
Get a list of public models matching a search query. Example cURL request: ```console curl -s -X QUERY \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: text/plain" \ -d "hello" \ https://api.replicate.com/v1/models ``` The response will be a paginated JSON object containing an array of model objects. See the [`models.get`](#models.get) docs for more details about the model object.
- Lua path
app.integrations.replicate.search_public_models- Full name
replicate.replicate_search_models
| Parameter | Type | Required | Description |
|---|---|---|---|
| No parameters. | |||
update_deployment Write
Update properties of an existing deployment, including hardware, min/max instances, and the deployment's underlying model [version](https://replicate.com/docs/how-does-replicate-work#versions). Example cURL request: ```console curl -s \ -X PATCH \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -d '{"min_instances": 3, "max_instances": 10}' \ https://api.replicate.com/v1/deployments/acme/my-app-image-generator ``` The response will be a JSON object describing the deployment: ```json { "owner": "acme", "name": "my-app-image-generator", "current_release": { "number": 2, "model": "stability-ai/sdxl", "version": "da77bc59ee60423279fd632efb4795ab731d9e3ca9705ef3341091fb989b7eaf", "created_at": "2024-02-15T16:32:57.018467Z", "created_by": { "type": "organization", "username": "acme", "name": "Acme Corp, Inc.", "avatar_url": "https://cdn.replicate.com/avatars/acme.png", "github_url": "https://github.com/acme" }, "configuration": { "hardware": "gpu-t4", "min_instances": 3, "max_instances": 10 } } } ``` Updating any deployment properties will increment the `number` field of the `current_release`.
- Lua path
app.integrations.replicate.update_deployment- Full name
replicate.replicate_update_deployment
| Parameter | Type | Required | Description |
|---|---|---|---|
| No parameters. | |||
update_metadata_model Write
Update select properties of an existing model. You can update the following properties: - `description` - Model description - `readme` - Model README content - `github_url` - GitHub repository URL - `paper_url` - Research paper URL - `weights_url` - Model weights URL - `license_url` - License URL Example cURL request: ```console curl -X PATCH \ https://api.replicate.com/v1/models/your-username/your-model-name \ -H "Authorization: Token $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -d '{ "description": "Detect hot dogs in images", "readme": "# Hot Dog Detector\n\n Ketchup, mustard, and onions...", "github_url": "https://github.com/alice/hot-dog-detector", "paper_url": "https://arxiv.org/abs/2504.17639", "weights_url": "https://huggingface.co/alice/hot-dog-detector", "license_url": "https://choosealicense.com/licenses/mit/" }' ``` The response will be the updated model object with all of its properties.
- Lua path
app.integrations.replicate.update_metadata_model- Full name
replicate.replicate_update_model
| Parameter | Type | Required | Description |
|---|---|---|---|
| No parameters. | |||