Raw Input Content

Raw input content is the starting point of memory production. You can provide chat text, images, business documents, tool call records, and other raw content directly. MemOS extracts information with long-term value and turns it into retrievable memories.

1. Text

Raw text, chats, event information, or any string content.

{
  "user_id": "memos_user_123",
  "conversation_id": "0910",
  "messages": [
    {
      "role": "user",
      "content": "I am Wang, and I like spicy food."
    }
  ]
}

Best for: chat messages, user preferences, behavior events, and structured data.

2. Images

MemOS can extract visual information from images and combine it with the text context sent alongside the image.

{
  "role": "user",
  "content": [
    { "type": "text", "text": "This is the MemOS image I am studying." },
    { "type": "image_url", "image_url": { "url": "https://cdn.memtensor.com.cn/img/1758706201390_iluj1c_compressed.png" } }
  ]
}

For local images, replace url with a Base64 data URL:

{
  "type": "image_url",
  "image_url": {
    "url": "data:image/jpeg;base64,{base64_image}"
  }
}

Best for: capturing operation states from screenshots, key information from receipts, design details from mockups, or conclusions from charts.

3. Documents

MemOS can read PDF, Word, Markdown, JSON, XML, TXT, and other file formats, and combine document content with the text context sent alongside the file.

{
  "role": "user",
  "content": [
    { "type": "file", "file": { "file_data": "https://cdn.memtensor.com.cn/file/MemOS 2.pdf" } }
  ]
}

For local documents, set file_data to a Base64 string.

Best for: extracting conclusions from reports, constraints from requirement documents, rules from policy materials, or key settings from configuration files.

4. Tool Calls

Agent tool decisions and tool results. MemOS generates tool memories so the Agent can call tools more reliably later.

{
  "messages": [
    {
      "role": "assistant",
      "tool_calls": [{ "id": "call_123", "type": "function", "function": { "name": "get_weather", "arguments": "{\"location\":\"Beijing\"}" } }]
    },
    {
      "role": "tool",
      "tool_call_id": "call_123",
      "content": [{ "type": "text", "text": "{\"temperature\":\"7°C\"}" }]
    }
  ]
}

Best for: recording tool selection, parameters, and returned results to improve future tool call success. See Tool Memory.

5. Natural Language Feedback

Corrections and supplements from users about answers, memories, or knowledge. You can pass the feedback text directly without locating a specific memory.

{
  "user_id": "memos_user_123",
  "feedback_content": "The purchase limit for office software is 600 yuan, not 800 yuan.",
  "allow_knowledgebase_ids": ["kb_xxx"]
}

Best for: correcting wrong memories, updating outdated information, and filling missing details. See Add Feedback.

6. Knowledge Bases and Skills

Project-level knowledge documents or Agent skill packages. These are managed separately from user memories.

{
  "knowledgebase_id": "kb_xxx",
  "file": [
    { "type": "document", "content": "https://cdn.memtensor.com.cn/file/MemOS 2.pdf" },
    { "type": "skill", "name": "return_process.md", "content": "data:text/markdown;base64,{base64_skill}" }
  ]
}

Best for: importing product documentation, policies, SOPs, FAQs, or Agent skill packages. See Knowledge Base and Skill.

7. Content Limits

8. API Overview

9. Explore Different APIs