likhonsheikhdev/docker-model-runner

pip install anthropic
export ANTHROPIC_BASE_URL=https://likhonsheikhdev-docker-model-runner.hf.space
export ANTHROPIC_API_KEY=any-key

import anthropic

client = anthropic.Anthropic()

message = client.messages.create(
    model="MiniMax-M2",
    max_tokens=1000,
    system="You are a helpful assistant.",
    messages=[{"role": "user", "content": "Hi, how are you?"}]
)

for block in message.content:
    if block.type == "thinking":
        print(f"Thinking:\n{block.thinking}\n")
    elif block.type == "text":
        print(f"Text:\n{block.text}\n")

import anthropic

client = anthropic.Anthropic(
    base_url="https://likhonsheikhdev-docker-model-runner.hf.space"
)

message = client.messages.create(
    model="MiniMax-M2",
    max_tokens=1024,
    thinking={
        "type": "enabled",
        "budget_tokens": 200
    },
    messages=[{"role": "user", "content": "Explain quantum computing"}]
)

# Response contains interleaved thinking and text blocks
for block in message.content:
    if block.type == "thinking":
        print(f"💭 Thinking: {block.thinking}")
    elif block.type == "text":
        print(f"📝 Response: {block.text}")

import anthropic

client = anthropic.Anthropic(
    base_url="https://likhonsheikhdev-docker-model-runner.hf.space"
)

with client.messages.stream(
    model="MiniMax-M2",
    max_tokens=1024,
    thinking={"type": "enabled", "budget_tokens": 100},
    messages=[{"role": "user", "content": "Hello!"}]
) as stream:
    for event in stream:
        if hasattr(event, 'type'):
            if event.type == 'content_block_start':
                print(f"\n[{event.content_block.type}]", end=" ")
            elif event.type == 'content_block_delta':
                if hasattr(event.delta, 'thinking'):
                    print(event.delta.thinking, end="")
                elif hasattr(event.delta, 'text'):
                    print(event.delta.text, end="")

import anthropic

client = anthropic.Anthropic(
    base_url="https://likhonsheikhdev-docker-model-runner.hf.space"
)

messages = [{"role": "user", "content": "What is 2+2?"}]

# First turn
response = client.messages.create(
    model="MiniMax-M2",
    max_tokens=1024,
    thinking={"type": "enabled", "budget_tokens": 100},
    messages=messages
)

# Append full response (including thinking) to history
messages.append({
    "role": "assistant",
    "content": response.content  # Includes both thinking and text blocks
})

# Second turn
messages.append({"role": "user", "content": "Now multiply that by 3"})

response2 = client.messages.create(
    model="MiniMax-M2",
    max_tokens=1024,
    thinking={"type": "enabled", "budget_tokens": 100},
    messages=messages
)

curl -X POST https://likhonsheikhdev-docker-model-runner.hf.space/v1/messages \
  -H "Content-Type: application/json" \
  -H "x-api-key: any-key" \
  -d '{
    "model": "MiniMax-M2",
    "max_tokens": 1024,
    "thinking": {"type": "enabled", "budget_tokens": 100},
    "messages": [
      {"role": "user", "content": "Explain AI briefly"}
    ]
  }'