Replicate

Learn how to use Replicate with Composio

Overview

SLUG: REPLICATE

Description

Replicate allows users to run AI models via a cloud API without managing infrastructure.

Authentication Details

bearer_token
stringRequired

Connecting to Replicate

Create an auth config

Use the dashboard to create an auth config for the Replicate toolkit. This allows you to connect multiple Replicate accounts to Composio for agents to use.

1

Select App

Navigate to Replicate.

2

Configure Auth Config Settings

Select among the supported auth schemes of and configure them here.

3

Create and Get auth config ID

Click “Create Replicate Auth Config”. After creation, copy the displayed ID starting with ac_. This is your auth config ID. This is not a sensitive ID — you can save it in environment variables or a database. This ID will be used to create connections to the toolkit for a given user.

Connect Your Account

Using API Key

1from composio import Composio
2
3# Replace these with your actual values
4replicate_auth_config_id = "ac_YOUR_REPLICATE_CONFIG_ID" # Auth config ID created above
5user_id = "0000-0000-0000" # UUID from database/app
6
7composio = Composio()
8
9def authenticate_toolkit(user_id: str, auth_config_id: str):
10 # Replace this with a method to retrieve an API key from the user.
11 # Or supply your own.
12 user_api_key = input("[!] Enter API key")
13
14 connection_request = composio.connected_accounts.initiate(
15 user_id=user_id,
16 auth_config_id=auth_config_id,
17 config={"auth_scheme": "API_KEY", "val": user_api_key}
18 )
19
20 # API Key authentication is immediate - no redirect needed
21 print(f"Successfully connected Replicate for user {user_id}")
22 print(f"Connection status: {connection_request.status}")
23
24 return connection_request.id
25
26
27connection_id = authenticate_toolkit(user_id, replicate_auth_config_id)
28
29# You can verify the connection using:
30connected_account = composio.connected_accounts.get(connection_id)
31print(f"Connected account: {connected_account}")

Tools

Executing tools

To prototype you can execute some tools to see the responses and working on the Replicate toolkit’s playground

Python
1from composio import Composio
2from openai import OpenAI
3import json
4
5openai = OpenAI()
6composio = Composio()
7
8# User ID must be a valid UUID format
9user_id = "0000-0000-0000" # Replace with actual user UUID from your database
10
11tools = composio.tools.get(user_id=user_id, toolkits=["REPLICATE"])
12
13print("[!] Tools:")
14print(json.dumps(tools))
15
16def invoke_llm(task = "What can you do?"):
17 completion = openai.chat.completions.create(
18 model="gpt-4o",
19 messages=[
20 {
21 "role": "user",
22 "content": task, # Your task here!
23 },
24 ],
25 tools=tools,
26 )
27
28 # Handle Result from tool call
29 result = composio.provider.handle_tool_calls(user_id=user_id, response=completion)
30 print(f"[!] Completion: {completion}")
31 print(f"[!] Tool call result: {result}")
32
33invoke_llm()

Tool List

Tool Name: Get File Details

Description

Tool to get details of a file by its id. use when you need to inspect uploaded file information before further operations.

Action Parameters

file_id
stringRequired

Action Response

data
objectRequired
error
string
successful
booleanRequired

Tool Name: List Files

Description

Tool to list all files created by the user or organization. use after authenticating to fetch files list.

Action Parameters

Action Response

data
objectRequired
error
string
successful
booleanRequired

Tool Name: Get Model Details

Description

Tool to get details of a specific model by owner and name. use when you need model metadata (schema, urls) before running predictions.

Action Parameters

model_name
stringRequired
model_owner
stringRequired

Action Response

data
objectRequired
error
string
successful
booleanRequired

Tool Name: Get Model README

Description

Tool to get the readme content for a model in markdown format. use after retrieving model details when you want to view its documentation.

Action Parameters

model_name
stringRequired
model_owner
stringRequired

Action Response

data
objectRequired
error
string
successful
booleanRequired

Tool Name: List model collections

Description

Tool to list all collections of models. use when you need to retrieve available model collections.

Action Parameters

Action Response

data
objectRequired
error
string
successful
booleanRequired

Tool Name: Create file

Description

Tool to create a file by uploading content. use when you need to upload and store a file for later reference.

Action Parameters

content
stringRequired
filename
stringRequired
metadata
object
type
stringDefaults to application/octet-stream

Action Response

data
objectRequired
error
string
successful
booleanRequired

Tool Name: Create Prediction

Description

Tool to create a prediction for a given deployment. use when you need to run model inference with specified inputs. use 'wait for' to wait until the prediction completes.

Action Parameters

deployment_name
stringRequired
deployment_owner
stringRequired
input
objectRequired
wait_for
integer
webhook
string
webhook_events_filter
array

Action Response

data
objectRequired
error
string
successful
booleanRequired

Tool Name: List model examples

Description

Tool to list example predictions for a specific model. use when you want to retrieve author-provided illustrative examples after identifying the model.

Action Parameters

model_name
stringRequired
model_owner
stringRequired

Action Response

data
objectRequired
error
string
successful
booleanRequired