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Markdown files are useful for README files, API docs, project notes, meeting notes, knowledge base entries, and changelogs. Moxus AI supports .md and .markdown uploads in Conversation. For API calls, read the Markdown content and place it in the message text.

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Supported paths

Conversation upload

Upload a .md or .markdown file in Conversation. The file is read as text and sent with the current message.

API call

Read the Markdown file in your backend and append its content to messages.content.

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File rules

FieldDetails
Formats.md, .markdown
Content typetext/markdown
Single file sizeAbout 20MB for Conversation uploads
BillingBilled by the text tokens included in the request
Best model typeChat or reasoning models with enough context length
Markdown files are not sent as image_url parts like images, and they are not sent as file objects like PDFs. They are read as text and appended to the user message.

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Use in Conversation

1

Open Conversation

Sign in, open Conversation, and choose a model that can handle long text.
2

Upload a Markdown file

Click the attachment button in the input box and choose a .md or .markdown file. The file appears in the attachment area.
3

Describe the task

Tell the model what to do, such as summarize the document, extract API sections, review a changelog, or rewrite the content.
4

Send and review

The Markdown content is sent with your message. After the request, open Usage to review the call and cost.

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API example

For API calls, read the Markdown file in your program and include its content in messages.content: 
MARKDOWN_CONTENT="$(cat README.md)"

curl https://moxus.ai/v1/chat/completions \
  -H "Authorization: Bearer sk-your-key" \
  -H "Content-Type: application/json" \
  -d "$(jq -n --arg content "$MARKDOWN_CONTENT" '{
    model: "gpt-4o",
    messages: [
      {
        role: "user",
        content: "Summarize this Markdown file and list the key features:\n\nMarkdown file: README.md\n\n\($content)"
      }
    ]
  }')"

from openai import OpenAI

client = OpenAI(
    api_key="sk-your-key",
    base_url="https://moxus.ai/v1",
)

with open("README.md", "r", encoding="utf-8") as file:
    markdown = file.read()

response = client.chat.completions.create(
    model="gpt-4o",
    messages=[
        {
            "role": "user",
            "content": f"Summarize this Markdown file and list the key features:\n\nMarkdown file: README.md\n\n{markdown}",
        }
    ],
)

print(response.choices[0].message.content)

import OpenAI from "openai";
import { readFileSync } from "node:fs";

const client = new OpenAI({
  apiKey: "sk-your-key",
  baseURL: "https://moxus.ai/v1",
});

const markdown = readFileSync("README.md", "utf8");

const response = await client.chat.completions.create({
  model: "gpt-4o",
  messages: [
    {
      role: "user",
      content: `Summarize this Markdown file and list the key features:\n\nMarkdown file: README.md\n\n${markdown}`,
    },
  ],
});

console.log(response.choices[0].message.content);

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Recommendations

  • Remove unrelated logs, repeated tables of contents, and generated content before sending long files.
  • Keep headings, section names, and list numbers when you need traceable answers.
  • Use Structured output when you need JSON or predictable fields.
  • If you send images, PDFs, and Markdown together, describe the role of each attachment in your prompt.
Markdown files may contain internal links, example keys, config snippets, or private code. Remove sensitive content before uploading or sending it through the API.

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Next steps