Connect Curl & HTTP to Unsloth

Guide to hitting Unsloth's API with curl (or any HTTP client), complete with copy-pasteable recipes for every endpoint and feature..

Unsloth exposes three OpenAI/Anthropic-compatible wire formats at the same base URL on the port Unsloth started on. All of them take an Authorization: Bearer sk-unsloth-… header and return either JSON or SSE, depending on whether you set stream. This page groups the recipes by endpoint (/v1/chat/completions, /v1/messages, /v1/responses, /v1/models) and ends with a shared section on Unsloth's built-in server-side tools, which work across all the chat endpoints.

If you're not sure what URL / key / model name to use, read the API overview first. It walks you through starting Unsloth, loading a model, and creating an sk-unsloth-… key.

🔑 Authentication

Every request needs an Authorization header:

Authorization: Bearer sk-unsloth-xxxxxxxxxxxx

To keep keys out of your shell history, export the key once and reference the env var:

export UNSLOTH_STUDIO_AUTH_TOKEN=sk-unsloth-xxxxxxxxxxxx

The snippets below inline the key as sk-unsloth-xxxxxxxxxxxx for clarity. In practice, substitute $UNSLOTH_STUDIO_API_KEY.

📋 List loaded models

curl http://localhost:8888/v1/models \
  -H "Authorization: Bearer sk-unsloth-xxxxxxxxxxxx"

Response:

{
  "object": "list",
  "data": [
    {"id": "unsloth/gemma-3-27b-it-GGUF", "object": "model", "owned_by": "local"}
  ]
}

Use the id field whenever a request needs a "model" value (or when a client like opencode asks for a Model ID).

💬 Chat Completions (/v1/chat/completions)

The OpenAI Chat Completions dialect. The broadest compatibility surface. Works with the OpenAI SDK, opencode, Cursor, Continue, Cline, Open WebUI, SillyTavern, and most OpenAI-compatible tools.

Basic request

curl http://localhost:8888/v1/chat/completions \
  -H "Authorization: Bearer sk-unsloth-xxxxxxxxxxxx" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "default",
    "messages": [{"role": "user", "content": "Hello"}]
  }'

Streaming

Add "stream": true and the response switches to Server-Sent Events (text/event-stream). Tell curl to flush as bytes arrive with --no-buffer (-N):

curl -N http://localhost:8888/v1/chat/completions \
  -H "Authorization: Bearer sk-unsloth-xxxxxxxxxxxx" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "qwen-local",
    "messages": [{"role": "user", "content": "Write a haiku about locally-run LLMs."}],
    "stream": true
  }'

Each line of the response looks like data: {"choices":[{"delta":{"content":"..."}}]}, ending with data: [DONE].

Images (vision)

Attach an image as an image_url content part in the user message. The URL can be HTTPS or a base64 data: URI:

# Embed a local file as base64 (trimmed for brevity)
IMG=$(base64 -w 0 test.jpg)

cat > /tmp/request.json <<EOF
{
  "model":"default",
  "messages":[{"role":"user","content":[
    {"type":"text","text":"Describe the image."},
    {"type":"image_url","image_url":{"url":"data:image/jpeg;base64,$IMG"}}
  ]}],
  "max_tokens":200,
  "stream":false
}
EOF

curl http://localhost:8888/v1/chat/completions \
  -H "Authorization: Bearer sk-unsloth-xxxxxxxxxxxx" \
  -H "Content-Type: application/json" \
  -d @/tmp/request.json

The loaded model must be multimodal. If you load a text-only model the request succeeds structurally but the model won't process the image.

Function calling (OpenAI tools)

Pass OpenAI-style tools and (optionally) tool_choice. Your client runs each tool call and returns the result on the next turn.

curl http://localhost:8888/v1/chat/completions \
  -H "Authorization: Bearer sk-unsloth-xxxxxxxxxxxx" \
  -H "Content-Type: application/json" \
  -d '{
    "model":"default",
    "input":[{"role":"user","content":"What is the weather in Paris?"}],
    "tools":[{
      "type":"function",
      "name":"get_weather",
      "description":"Get current weather for a city.",
      "parameters":{
        "type":"object",
        "properties":{"city":{"type":"string"}},
        "required":["city"]
      }
    }],
    "tool_choice":"required"
  }' | jq '.output, .usage'

📨 Anthropic Messages (/v1/messages)

Unsloth's Anthropic-compatible dialect used by Claude Code, the Anthropic SDK, OpenClaw, and any client that speaks the Messages API.

Basic request

curl http://localhost:8888/v1/messages \
  -H "Authorization: Bearer sk-unsloth-xxxxxxxxxxxx" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "default",
    "max_tokens": 1024,
    "messages": [{"role": "user", "content": "Hello"}]
  }'

max_tokens is required on /v1/messages (it's optional on /v1/chat/completions).

Streaming

curl -N http://localhost:8888/v1/messages \
  -H "Authorization: Bearer sk-unsloth-xxxxxxxxxxxx" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "qwen-local",
    "max_tokens": 1024,
    "messages": [{"role": "user", "content": "Explain LoRA in two sentences."}],
    "stream": true
  }'

Events follow Anthropic's SSE shape: message_start, content_block_start, content_block_delta, content_block_stop, message_delta, message_stop, plus Unsloth's custom tool_result event for server-side tool output.

Images (vision)

Anthropic-style image content uses a source block with base64 data:

IMG=$(base64 -w 0 test.jpg)

cat > /tmp/request.json <<EOF
{
  "messages":[{"role":"user","content":[
    {"type":"text","text":"Describe the image."},
    {"type":"image","source":{"type":"base64","media_type":"image/jpeg","data":"$IMG"}}
  ]}],
  "max_tokens":200,
  "stream":true
}
EOF

curl -s http://3.128.175.236:8888/v1/messages \
  -H "Authorization: Bearer sk-unsloth-xxxxxxxx" \
  -H "Content-Type: application/json" \
  -d @/tmp/request.json

Tool calling (Anthropic tools)

curl http://localhost:8888/v1/messages \
  -H "Authorization: Bearer sk-unsloth-xxxxxxxxxx" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "qwen-local",
    "max_tokens": 1024,
    "messages": [{"role": "user", "content": "Whats the weather in Tokyo?"}],
    "tools": [
      {
        "name": "get_weather",
        "description": "Get the current weather for a city",
        "input_schema": {
          "type": "object",
          "properties": {
            "city": {"type": "string"}
          },
          "required": ["city"]
        }
      }
    ],
    "tool_choice": {"type": "auto"}
  }'

tool_choice values map as follows to the OpenAI dialect: Anthropic auto → OpenAI auto, Anthropic any → OpenAI required, Anthropic {type: "tool", name: "x"} → OpenAI {type: "function", function: {name: "x"}}, Anthropic none → OpenAI none.

🧬 Responses (/v1/responses)

Unsloth also speaks the newer OpenAI Responses API, the protocol Codex and other recent OpenAI clients have moved to.

curl http://localhost:8888/v1/responses \
  -H "Authorization: Bearer sk-unsloth-xxxxxxxxxxxx" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "qwen-local",
    "input": "Write a one-sentence greeting."
  }'

Streaming works the same way as Chat Completions. Add "stream": true and pipe with -N.

🧰 Unsloth server-side tools (shorthand)

In addition to client-side function calling, Unsloth can execute Python, bash, and web search server-side and stream the results back as custom tool_result events. This is the feature that makes Unsloth feel like a "real" agent out of the box, no round-tripping tool calls through your client.

Opt in by passing these extra fields to either /v1/chat/completions or /v1/messages:

Field	Type	Notes
enable_thinking	boolean	false to disable thinking. true by default
enable_tools	boolean	true to enable server-side tool execution.
enabled_tools	array<string>	Which tools the model can call. Supports python, bash, web_search.
session_id	string	Optional. Persists tool state (e.g. Python kernel) across calls.

Thinking mode

Thinking mode is enabled by default.

curl http://localhost:8888/v1/chat/completions \
  -H "Authorization: Bearer sk-unsloth-xxxxxxxxxxxx" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "default",
    "messages": [{"role": "user", "content": "summarize quantum tunneling in one sentence"}],
    "stream": false,
  }'

The model will think before providing an answer.

To disable thinking pass enable_thinking: false in your request. The model will provide an answer without thinking first.

Python execution

curl http://localhost:8888/v1/chat/completions \
  -H "Authorization: Bearer sk-unsloth-xxxxxxxxxxxx" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "qwen-local",
    "messages": [{"role": "user", "content": "What is 123 * 456? Use code to compute it."}],
    "stream": false,
    "enable_tools": true,
    "enabled_tools": ["python"],
    "session_id": "my-session"
  }'

Web search + Python (streaming)

curl http://localhost:8888/v1/chat/completions \
  -H "Authorization: Bearer sk-unsloth-xxxxxx" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "qwen-local",
    "messages": [{"role": "user", "content": "Search for Python 3.13 features"}],
    "stream": true,
    "enable_tools": true,
    "enabled_tools": ["web_search", "python"],
    "session_id": "my-session"
  }'

On /v1/messages

The same shorthand works against the Anthropic Messages endpoint:

curl http://localhost:8888/v1/messages \
  -H "Authorization: Bearer sk-unsloth-xxxxxxxxxxx" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "qwen-local",
    "max_tokens": 1024,
    "messages": [{"role": "user", "content": "Search for Python 3.13 features"}],
    "stream": true,
    "enable_tools": true,
    "enabled_tools": ["web_search", "python"],
    "session_id": "my-session"
  }'

Unsloth streams its own tool_result SSE events in addition to the standard Anthropic / OpenAI event types, The model sees each tool's output on its next turn.

❔ Troubleshooting

401 Unauthorized - The Authorization header is missing or the key is wrong. Double-check: Authorization: Bearer sk-unsloth-….

curl hangs on streaming requests - Add -N (same as --no-buffer). Without it, curl buffers the SSE stream and you see nothing until the end.

Base64 encoding differs between OSes - Linux's base64 defaults to wrapping lines, macOS / BSD does not. Use base64 -w 0 on Linux, base64 on macOS, or pipe the output through tr -d '\n'.

JSON escaping in shells - Heredocs (-d @file.json) are cleaner than inline strings once the body gets complex. Example: curl ... -d @body.json.

max_tokens errors on /v1/messages - The Anthropic dialect requires it. Add "max_tokens": 1024 (or whatever limit you want).

For endpoint-level issues (model not loading, connection dropped, wrong port) see the API overview page.