---
title: "Manus"
description: "import Tabs from '@theme/Tabs'; import TabItem from '@theme/TabItem';"
type: skill
canonical_url: https://claudary.paisolsolutions.com/skills/manus
source: "Claudary"
difficulty: intermediate
author: "Claude Code Knowledge Pack"
date: 2026-07-10T11:30:46.645Z
license: CC-BY-4.0
attribution: "Manus — Claudary (https://claudary.paisolsolutions.com/skills/manus)"
---

# Manus
import Tabs from '@theme/Tabs'; import TabItem from '@theme/TabItem';

## Overview

import Tabs from '@theme/Tabs';
import TabItem from '@theme/TabItem';

# 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), `/files` (Files API) |
| Provider Doc | [Manus API ↗](https://open.manus.im/docs/openai-compatibility) |

## Model Format

```shell
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

```python showLineNumbers title="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

```yaml showLineNumbers title="config.yaml"
model_list:
  - model_name: manus-agent
    litellm_params:
      model: manus/manus-1.6
      api_key: os.environ/MANUS_API_KEY
```

```bash title="Start Proxy"
litellm --config config.yaml
```

### Usage

<Tabs>
<TabItem value="curl" label="cURL">

```bash showLineNumbers title="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"
  }
}
```

```bash showLineNumbers title="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."}]
    }
  ]
}
```

</TabItem>
<TabItem value="openai" label="OpenAI SDK">

```python showLineNumbers title="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)
```

</TabItem>
</Tabs>

## 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](https://open.manus.im/docs/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 |

## 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

```python showLineNumbers title="Upload, Use, Retrieve, and Delete Files"
import litellm
import os

# 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

<Tabs>
<TabItem value="curl" label="cURL">

```bash showLineNumbers title="Upload File"
# 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"
}
```

```bash showLineNumbers title="Use File with Responses API"
# 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"}
        ]
      }
    ]
  }'
```

```bash showLineNumbers title="Retrieve File"
# 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"
}
```

```bash showLineNumbers title="Delete File"
# 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
}
```

</TabItem>
<TabItem value="openai" label="OpenAI SDK">

```python showLineNumbers title="Upload, Use, Retrieve, and Delete Files"
import openai

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}")
```

</TabItem>
</Tabs>

## Related Documentation

- [LiteLLM Responses API](/docs/response_api)
- [LiteLLM Files API](/docs/proxy/litellm_managed_files)
- [Manus OpenAI Compatibility](https://open.manus.im/docs/openai-compatibility)

---

Source: [Claudary](https://claudary.paisolsolutions.com/skills/manus) · https://claudary.paisolsolutions.com