Ling-3.0-flash-VL

from openai import OpenAI

client = OpenAI(base_url="http://localhost:30000/v1", api_key="EMPTY")
resp = client.chat.completions.create(
    model="inclusionAI/Ling-3.0-flash-VL",
    messages=[{
        "role": "user",
        "content": [
            {"type": "image_url", "image_url": {"url": "https://raw.githubusercontent.com/sgl-project/sglang/main/examples/assets/example_image.png"}},
            {"type": "text", "text": "Describe this image in one sentence."},
        ],
    }],
    max_tokens=2048,
)
msg = resp.choices[0].message
print("Reasoning:", getattr(msg, "reasoning_content", None))
print("Content:", msg.content)

Reasoning: The user wants a one-sentence description of this image. Let me look at the image carefully.

The image shows a man wearing a yellow shirt (with some kind of text on it, probably "Sudsy" or similar) standing behind a yellow taxi SUV, ironing clothes on a portable ironing board set up at the rear of the vehicle. On the left side, another yellow taxi (sedan) is passing by on the street. The background is an urban streetscape with buildings lined up.

I need to write this in one sentence. For example: "A man wearing a yellow shirt irons clothes on a portable ironing board attached to the back of a yellow taxi on a city street, while another taxi passes by."

Let me make it concise yet descriptive. One sentence.

"On a city street, a man in a yellow sweatshirt irons clothes on a portable ironing board mounted on the back of a yellow taxi SUV, while another yellow taxi drives past."

This works. I'll return only the answer.
Content: A man in a yellow shirt irons clothes on a portable ironing board set up at the back of a yellow taxi on a city street, while another yellow cab drives past.

from openai import OpenAI

client = OpenAI(base_url="http://localhost:30000/v1", api_key="EMPTY", timeout=900)
resp = client.chat.completions.create(
    model="inclusionAI/Ling-3.0-flash-VL",
    messages=[{
        "role": "user",
        "content": [
            {"type": "video_url", "video_url": {"url": "https://github.com/sgl-project/sgl-test-files/raw/refs/heads/main/videos/jobs_presenting_ipod.mp4"}},
            {"type": "text", "text": "What is happening in this video? Answer in two sentences."},
        ],
    }],
    max_tokens=2048,
)
msg = resp.choices[0].message
print("Reasoning:", getattr(msg, "reasoning_content", None))
print("Content:", msg.content)

Reasoning: The user wants me to describe what is happening in this video in two sentences.

Looking at the video, I can see:
- A man on stage (appears to be Steve Jobs) presenting something
- He's wearing a black shirt and jeans
- There's a large screen behind him showing a close-up of a hand reaching toward a pocket on blue jeans
- Text appears on screen asking "Anyone know what this pocket is for?"
- He pulls out a small white device (iPod Nano) from his pocket
- The text says "I've always wondered that" and "well now we know" and "is the new iPod Nano"
- He holds up the white iPod Nano device

This is clearly Steve Jobs presenting the new iPod Nano at an Apple event. The small white device is the iPod Nano.

I need to summarize this in exactly two sentences.
Content: A presenter on stage pulls a small white device from his pocket while a large screen behind him displays a close-up image of a hand reaching toward a jeans pocket. He holds the device up to reveal it is the new iPod Nano, answering the on-screen text that questioned what the small pocket was designed for.

from openai import OpenAI

client = OpenAI(base_url="http://localhost:30000/v1", api_key="EMPTY")
resp = client.chat.completions.create(
    model="inclusionAI/Ling-3.0-flash-VL",
    messages=[{
        "role": "user",
        "content": [
            {"type": "image_url", "image_url": {"url": "https://raw.githubusercontent.com/sgl-project/sglang/main/examples/assets/example_image.png"}},
            {"type": "text", "text": "Describe this image in one sentence."},
        ],
    }],
    max_tokens=512,
    extra_body={"chat_template_kwargs": {"enable_thinking": False}},
)
msg = resp.choices[0].message
print("Reasoning:", getattr(msg, "reasoning_content", None))
print("Content:", msg.content)

Reasoning: None
Content: A man in a yellow sweatshirt irons a blue shirt on a folding board attached to the back of a parked yellow taxi SUV, while another yellow cab drives past on a city street.

import json
from openai import OpenAI

client = OpenAI(base_url="http://localhost:30000/v1", api_key="EMPTY")
tools = [{
    "type": "function",
    "function": {
        "name": "get_weather",
        "description": "Get the current weather for a city",
        "parameters": {
            "type": "object",
            "properties": {"city": {"type": "string", "description": "City name"}},
            "required": ["city"],
        },
    },
}]
messages = [{"role": "user", "content": "What's the weather like in Paris today?"}]

resp = client.chat.completions.create(
    model="inclusionAI/Ling-3.0-flash-VL",
    messages=messages,
    tools=tools,
    tool_choice="auto",
    max_tokens=2048,
)
msg = resp.choices[0].message
print("finish_reason:", resp.choices[0].finish_reason)
print("Reasoning:", getattr(msg, "reasoning_content", None))
print("Content:", msg.content)
for call in msg.tool_calls:
    print("Tool call:", call.function.name, call.function.arguments)

messages.append({
    "role": "assistant",
    "content": msg.content or "",
    "tool_calls": [{"id": c.id, "type": "function",
                    "function": {"name": c.function.name, "arguments": c.function.arguments}}
                   for c in msg.tool_calls],
})
messages.append({
    "role": "tool",
    "tool_call_id": msg.tool_calls[0].id,
    "content": json.dumps({"city": "Paris", "temperature_c": 18, "condition": "light rain"}),
})
resp = client.chat.completions.create(
    model="inclusionAI/Ling-3.0-flash-VL",
    messages=messages,
    tools=tools,
    max_tokens=2048,
)
msg = resp.choices[0].message
print("finish_reason:", resp.choices[0].finish_reason)
print("Reasoning:", getattr(msg, "reasoning_content", None))
print("Content:", msg.content)

finish_reason: tool_calls
Reasoning: The user wants to know the current weather in Paris. I'll call the get_weather function with the city "Paris".
Content: Let me check the weather in Paris for you right away!
Tool call: get_weather {"city": "Paris"}
finish_reason: stop
Reasoning: None
Content: Here's the current weather in Paris:

- 🌡️ **Temperature:** 18°C
- 🌧️ **Condition:** Light rain

It looks like a mild day with some light rain. You might want to bring an umbrella if you're heading out! ☂️