Manus

Use Manus AI agents through LiteLLM's OpenAI-compatible Responses API.

Property	Details
Description	Manus is an AI agent platform for complex reasoning tasks, document analysis, and multi-step workflows with asynchronous task execution.
Provider Route on LiteLLM	manus/{agent_profile}
Supported Operations	/responses (Responses API)
Provider Doc	Manus API ↗

Model Format

manus/{agent_profile}

Examples:

• manus/manus-1.6 - General purpose agent
• manus/manus-1.6-lite - Lightweight agent for simple tasks
• manus/manus-1.6-max - Advanced agent for complex analysis

LiteLLM Python SDK

Basic Usage

import litellm
import os
import time

# Set API key
os.environ["MANUS_API_KEY"] = "your-manus-api-key"

# Create task
response = litellm.responses(
    model="manus/manus-1.6",
    input="What's the capital of France?",
)

print(f"Task ID: {response.id}")
print(f"Status: {response.status}")  # "running"

# Poll until complete
task_id = response.id
while response.status == "running":
    time.sleep(5)
    response = litellm.get_response(
        response_id=task_id,
        custom_llm_provider="manus",
    )
    print(f"Status: {response.status}")

# Get results
if response.status == "completed":
    for message in response.output:
        if message.role == "assistant":
            print(message.content[0].text)

LiteLLM AI Gateway

Setup

config.yaml

model_list:
  - model_name: manus-agent
    litellm_params:
      model: manus/manus-1.6
      api_key: os.environ/MANUS_API_KEY

Start Proxy

litellm --config config.yaml

Usage

cURL

Create Task

# Create task
curl -X POST http://localhost:4000/responses \
  -H "Authorization: Bearer your-proxy-key" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "manus-agent",
    "input": "What is the capital of France?"
  }'

# Response
{
  "id": "task_abc123",
  "status": "running",
  "metadata": {
    "task_url": "https://manus.im/app/task_abc123"
  }
}

Poll for Completion

# Check status (repeat until status is "completed")
curl http://localhost:4000/responses/task_abc123 \
  -H "Authorization: Bearer your-proxy-key"

# When completed
{
  "id": "task_abc123",
  "status": "completed",
  "output": [
    {
      "role": "user",
      "content": [{"text": "What is the capital of France?"}]
    },
    {
      "role": "assistant",
      "content": [{"text": "The capital of France is Paris."}]
    }
  ]
}

OpenAI SDK

Create Task and Poll

import openai
import time

client = openai.OpenAI(
    base_url="http://localhost:4000",
    api_key="your-proxy-key"
)

# Create task
response = client.responses.create(
    model="manus-agent",
    input="What is the capital of France?"
)

print(f"Task ID: {response.id}")
print(f"Status: {response.status}")  # "running"

# Poll until complete
task_id = response.id
while response.status == "running":
    time.sleep(5)
    response = client.responses.retrieve(response_id=task_id)
    print(f"Status: {response.status}")

# Get results
if response.status == "completed":
    for message in response.output:
        if message.role == "assistant":
            print(message.content[0].text)

How It Works

Manus operates as an asynchronous agent API:

1. Create Task: When you call litellm.responses(), Manus creates a task and returns immediately with status: "running"
2. Task Executes: The agent works on your request in the background
3. Poll for Completion: You must repeatedly call litellm.get_response() or client.responses.retrieve() until the status changes to "completed"
4. Get Results: Once completed, the output field contains the full conversation

Task Statuses:

• running - Agent is actively working
• pending - Agent is waiting for input
• completed - Task finished successfully
• error - Task failed

Production Usage

For production applications, use webhooks instead of polling to get notified when tasks complete.

Supported Parameters

Parameter	Supported	Notes
input	✅	Text, images, or structured content
stream	✅	Fake streaming (task runs async)
max_output_tokens	✅	Limits response length
previous_response_id	✅	For multi-turn conversations

Related Documentation

• LiteLLM Responses API
• Manus OpenAI Compatibility