Manus

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

# 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

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

litellm --config config.yaml

Usage

# 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"
  }
}

# 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."}]
    }
  ]
}

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

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

Supported Parameters

Files API

Manus supports file uploads for document analysis and processing. Files can be uploaded and then referenced in Responses API calls.

LiteLLM Python SDK

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

# Upload file
file_content = b"This is a document for analysis."
created_file = await litellm.acreate_file(
    file=("document.txt", file_content),
    purpose="assistants",
    custom_llm_provider="manus",
)
print(f"Uploaded file: {created_file.id}")

# Use file with Responses API
response = await litellm.aresponses(
    model="manus/manus-1.6",
    input=[
        {
            "role": "user",
            "content": [
                {"type": "input_text", "text": "Summarize this document."},
                {"type": "input_file", "file_id": created_file.id},
            ],
        },
    ],
    extra_body={"task_mode": "agent", "agent_profile": "manus-1.6-agent"},
)
print(f"Response: {response.id}")

# Retrieve file
retrieved_file = await litellm.afile_retrieve(
    file_id=created_file.id,
    custom_llm_provider="manus",
)
print(f"File details: {retrieved_file.filename}, {retrieved_file.bytes} bytes")

# Delete file
deleted_file = await litellm.afile_delete(
    file_id=created_file.id,
    custom_llm_provider="manus",
)
print(f"Deleted: {deleted_file.deleted}")

LiteLLM AI Gateway

# Upload file
curl -X POST http://localhost:4000/v1/files \\
  -H "Authorization: Bearer your-proxy-key" \\
  -F "file=@document.txt" \\
  -F "purpose=assistants" \\
  -F "custom_llm_provider=manus"

# Response
{
  "id": "file_abc123",
  "object": "file",
  "bytes": 1024,
  "created_at": 1234567890,
  "filename": "document.txt",
  "purpose": "assistants",
  "status": "uploaded"
}

# Create response with file
curl -X POST http://localhost:4000/responses \\
  -H "Authorization: Bearer your-proxy-key" \\
  -H "Content-Type: application/json" \\
  -d '{
    "model": "manus-agent",
    "input": [
      {
        "role": "user",
        "content": [
          {"type": "input_text", "text": "Summarize this document."},
          {"type": "input_file", "file_id": "file_abc123"}
        ]
      }
    ]
  }'

# Get file details
curl http://localhost:4000/v1/files/file_abc123 \\
  -H "Authorization: Bearer your-proxy-key"

# Response
{
  "id": "file_abc123",
  "object": "file",
  "bytes": 1024,
  "created_at": 1234567890,
  "filename": "document.txt",
  "purpose": "assistants",
  "status": "uploaded"
}

# Delete file
curl -X DELETE http://localhost:4000/v1/files/file_abc123 \\
  -H "Authorization: Bearer your-proxy-key"

# Response
{
  "id": "file_abc123",
  "object": "file",
  "deleted": true
}

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

# Upload file
with open("document.txt", "rb") as f:
    created_file = client.files.create(
        file=f,
        purpose="assistants",
        extra_body={"custom_llm_provider": "manus"}
    )
print(f"Uploaded file: {created_file.id}")

# Use file with Responses API
response = client.responses.create(
    model="manus-agent",
    input=[
        {
            "role": "user",
            "content": [
                {"type": "input_text", "text": "Summarize this document."},
                {"type": "input_file", "file_id": created_file.id}
            ]
        }
    ]
)
print(f"Response: {response.id}")

# Retrieve file
retrieved_file = client.files.retrieve(created_file.id)
print(f"File: {retrieved_file.filename}, {retrieved_file.bytes} bytes")

# Delete file
deleted_file = client.files.delete(created_file.id)
print(f"Deleted: {deleted_file.deleted}")

Related Documentation

• LiteLLM Responses API
• LiteLLM Files API
• Manus OpenAI Compatibility