Azure AI Foundry

pip install obiguard

from obiguard import Obiguard

client = Obiguard(
  obiguard_api_key="ak***",  # Your Obiguard access key
)

response = client.chat.completions.create(
  model="DeepSeek-V3-0324", # Replace with your deployed model name
  messages=[
    {"role": "system", "content": "You are a helpful assistant."},
    {"role": "user", "content": "Tell me about cloud computing"}
  ]
)

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

tools = [{
    "type": "function",
    "function": {
        "name": "getWeather",
        "description": "Get the current weather",
        "parameters": {
            "type": "object",
            "properties": {
                "location": {"type": "string", "description": "City and state"},
                "unit": {"type": "string", "enum": ["celsius", "fahrenheit"]}
            },
            "required": ["location"]
        }
    }
}]

response = client.chat.completions.create(
    model="DeepSeek-V3-0324", # Use a model that supports function calling
    messages=[
        {"role": "system", "content": "You are a helpful assistant."},
        {"role": "user", "content": "What's the weather like in Delhi?"}
    ],
    tools=tools,
    tool_choice="auto"
)

print(response.choices[0])

response = client.chat.completions.create(
    model="Llama-4-Scout-17B-16E", # Use a model that supports vision
    messages=[
        {
            "role": "user",
            "content": [
                {"type": "text", "text": "What's in this image?"},
                {
                    "type": "image_url",
                    "image_url": "https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg",
                },
            ],
        }
    ],
    max_tokens=500,
)

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

response = client.chat.completions.create(
    model="cohere-command-a", # Use a model that supports response formats
    messages=[
        {"role": "system", "content": "You are a helpful assistant."},
        {"role": "user", "content": "List the top 3 cloud providers with their main services"}
    ],
    response_format={"type": "json_object"},
    temperature=0
)

import json
print(json.loads(response.choices[0].message.content))