MANUS docs

docs/my-website/docs/providers/manus.md

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+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) |
+| 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 |
+
+## Related Documentation
+
+- [LiteLLM Responses API](/docs/response_api)
+- [Manus OpenAI Compatibility](https://open.manus.im/docs/openai-compatibility)

docs/my-website/sidebars.js

@@ -710,6 +710,7 @@ const sidebars = {
         "providers/llamafile",
         "providers/llamagate",
         "providers/lm_studio",
+        "providers/manus",
         "providers/meta_llama",
         "providers/milvus_vector_stores",
         "providers/mistral",