Cancel Prediction
Tool to cancel a prediction that is still running. Use when you need to stop an in-progress prediction to free up resources or halt execution.
Replicate allows users to run AI models via a cloud API without managing infrastructure.
Tool to cancel a prediction that is still running. Use when you need to stop an in-progress prediction to free up resources or halt execution.
Tool to cancel an ongoing training operation in Replicate. Use when you need to stop a training job that is in progress.
Tool to create a new deployment with specified model, version, hardware, and scaling parameters. Use when you need to deploy a model for production use with auto-scaling.
Tool to create or upload a file to Replicate. Use when you need to upload file content with optional metadata.
Tool to create a new Replicate model with specified owner, name, visibility, and hardware. Use when you need to create a destination model before launching LoRA/fine-tune training.
Tool to create a prediction using an official Replicate model. Use when you need to run inference with a specific model using its owner and name. Supports synchronous waiting (up to 60 seconds) and webhooks for async notifications.
Create a prediction for a Replicate Deployment using model inputs. Supports webhook notifications and an optional wait of up to 60 seconds for completion.
Tool to create a prediction to run a model by version ID. Use when you have a specific model version identifier and need to run inference with provided inputs. Supports synchronous waiting and webhook notifications.
Tool to create a training job for a specific model version. Use when you need to fine-tune a model with custom training data. Supports webhook notifications for training status updates.
Tool to delete a deployment from your account. Use when you need to remove a deployment. Deployments must be offline and unused for at least 15 minutes before deletion.
Delete a file by its ID. Returns a success message, including when the file is already absent.
Download a stored file using Replicate's signed download fields. Replicate documents a limit of 3,000 requests per minute for non-prediction endpoints. Accounts with low credit balances can be throttled more aggressively.
Tool to get authenticated account information. Use when you need to retrieve details about the account associated with the API token.
Tool to get deployment details by owner and name. Use when you need information about a specific deployment including its release configuration and hardware settings.
Tool to get details of a file by its ID. Use when you need to inspect uploaded file information before further operations. Returned URLs may be short-lived; download or persist needed files promptly after retrieval.
Tool to get a specific collection of models by its slug. Use when you need detailed information about a collection and its models.
Get details of a specific model by owner and name. The latest version and its input/output schema may be included when available.
Tool to get the README content for a model in Markdown format. Consult alongside REPLICATE_MODELS_EXAMPLES_LIST before calling REPLICATE_CREATE_PREDICTION — Replicate enforces strict JSON schemas on model inputs and returns 422 errors for incorrect keys or types. Use after retrieving model details when you want to view its documentation.
Tool to get a specific version of a model. Use when you need details about a particular model version including its schema and metadata.
Tool to get the status and output of a prediction by its ID. Use when you need to check on a running prediction or retrieve the results of a completed prediction.
Get a training's current state, output, logs, and runtime metrics by ID. Replicate documents a limit of 3,000 requests per minute for non-prediction endpoints and may throttle low-credit accounts more aggressively.
Tool to get the signing secret for the default webhook. Use when you need to retrieve the secret key used to verify webhook authenticity.
Tool to list all predictions for the authenticated user or organization with pagination. Use when you need to retrieve prediction history or filter predictions by creation date.
Tool to list available hardware SKUs for models and deployments. Use when you need to see what hardware options are available on the Replicate platform.
List deployments associated with the account, including their latest release configurations. Results are paginated; use the next-page cursor to retrieve additional deployments.
Tool to retrieve a paginated list of uploaded files. Use to view all files created by the authenticated user or organization. Files are sorted with most recent first. Pagination is cursor-based: follow the next cursor until empty to retrieve all files. Limit requests to 1–2/second to avoid 429 Too Many Requests errors. Use to validate current file_ids before passing to prediction tools, as stale file_ids cause runtime errors.
Tool to list all collections of models. Use when you need to retrieve available model collections. Collections are curated groupings of related models. Response includes only collection metadata (name, slug, description), not individual models within each collection; use REPLICATE_MODELS_GET for per-model details. Response may include a non-null `next` field indicating additional pages; follow it to enumerate all collections.
List example predictions for a specific model, with cursor-based pagination. Example input or output may be absent if data has been removed.
List versions of a specific model, newest first, with cursor-based pagination.
Tool to list public models with pagination and sorting. Use when you need to browse available models or find models sorted by creation date.
Tool to list all training jobs for the authenticated user or organization with pagination. Use when you need to retrieve training history or check the status of training jobs.
Tool to search for models, collections, and docs using text queries (beta). Use when you need to find relevant models or collections based on keywords or descriptions.
Update a model's metadata, including its description, README, and associated URLs.
The Replicate integration connects your Dench AI CRM directly to Replicate, so agents can read and act on your Replicate data as part of everyday work — answering questions in chat, keeping your CRM in sync, and running automations without anyone copying data between tools.
33 actions are available for agents to invoke on your behalf. Every call runs through Replicate's own authorization, scoped to the account you connect.
Sign in to your Dench workspace and open Integrations.
Find Replicate and click Connect — you'll authorize access through Replicate's own sign-in flow. No API keys or code required.
Ask an agent to use Replicate in chat, or call it from an automation.
Manage or disconnect the connection any time from workspace settings.
The Dench Replicate integration connects your AI CRM to Replicate, so AI agents can work with your Replicate data as part of chats, automations, and CRM workflows. You connect your account once, and every agent in your workspace can use it — governed by your workspace permissions.
The Replicate integration currently exposes 33 actions, including Cancel Prediction, Cancel Training, Create Deployment, Create File, Create Model, and Create Model Prediction. Agents invoke them on your behalf from chat or from automations.
No. You connect Replicate from your Dench workspace using Replicate's own sign-in and authorization flow — no API keys to copy, no glue code to maintain.
Connections are authorized through Replicate's own authentication flow, and Dench stores only the authorization needed to act on your behalf. You can review and disconnect the Replicate connection from your workspace settings at any time.