Google Vertex AI

completion = client.chat.completions.create(
  messages=[
    {
      "role": "system",
      "content": "You are a helpful assistant"
    },
    {
      "role": "user",
      "content": [
        {
          "type": "image_url",
          "image_url": {
            "url": "gs://cloud-samples-data/generative-ai/image/scones.jpg"
          }
        },
        {
          "type": "text",
          "text": "Describe the image"
        }
      ]
    }
  ],
  model='gemini-1.5-pro-001',
  max_tokens=200
)
print(completion)

from obiguard import Obiguard

client = Obiguard(
  obiguard_api_key="OBIGUARD_API_KEY",  # Your Obiguard API key
  strict_open_ai_compliance=False
)

# Create the request
response = client.chat.completions.create(
  model="anthropic.claude-3-7-sonnet@20250219",
  max_tokens=3000,
  thinking={
    "type": "enabled",
    "budget_tokens": 2030
  },
  stream=True,
  messages=[
    {
      "role": "user",
      "content": [
        {
          "type": "text",
          "text": "when does the flight from new york to bengaluru land tomorrow, what time, what is its flight number, and what is its baggage belt?"
        }
      ]
   }
  ]
)
print(response)
# in case of streaming responses you'd have to parse the response_chunk.choices[0].delta.content_blocks array
# response = client.chat.completions.create(
#   ...same config as above but with stream: true
# )
# for chunk in response:
#     if chunk.choices[0].delta:
#         content_blocks = chunk.choices[0].delta.get("content_blocks")
#         if content_blocks is not None:
#             for content_block in content_blocks:
#                 print(content_block)

from obiguard import Obiguard

client = Obiguard(
  obiguard_api_key="OBIGUARD_API_KEY",  # Your Obiguard API key
  virtual_key="VIRTUAL_KEY",   # Add your provider's virtual key
  strict_open_ai_compliance=False
)

response = client.chat.completions.create(
  model="anthropic.claude-3-7-sonnet@20250219",
  max_tokens=3000,
  thinking={
    "type": "enabled",
    "budget_tokens": 2030
  },
  stream=True,
  messages=[
    {
      "role": "user",
      "content": [
        {
          "type": "text",
          "text": "when does the flight from baroda to bangalore land tomorrow, what time, what is its flight number, and what is its baggage belt?"
        }
      ]
    },
    {
      "role": "assistant",
      "content": [
        {
          "type": "thinking",
          "thinking": "The user is asking several questions about a flight from Baroda (also known as Vadodara) to Bangalore:\n1. When does the flight land tomorrow\n2. What time does it land\n3. What is the flight number\n4. What is the baggage belt number at the arrival airport\n\nTo properly answer these questions, I would need access to airline flight schedules and airport information systems. However, I don't have:\n- Real-time or scheduled flight information\n- Access to airport baggage claim allocation systems\n- Information about specific flights between these cities\n- The ability to look up tomorrow's specific flight schedules\n\nThis question requires current, specific flight information that I don't have access to. Instead of guessing or providing potentially incorrect information, I should explain this limitation and suggest ways the user could find this information.",
          "signature": "EqoBCkgIARABGAIiQBVA7FBNLRtWarDSy9TAjwtOpcTSYHJ+2GYEoaorq3V+d3eapde04bvEfykD/66xZXjJ5yyqogJ8DEkNMotspRsSDKzuUJ9FKhSNt/3PdxoMaFZuH+1z1aLF8OeQIjCrA1+T2lsErrbgrve6eDWeMvP+1sqVqv/JcIn1jOmuzrPi2tNz5M0oqkOO9txJf7QqEPPw6RG3JLO2h7nV1BMN6wE="
        }
      ]
    },
    {
      "role": "user",
      "content": "thanks that's good to know, how about to chennai?"
    }
  ]
)
print(response)

from obiguard import Obiguard

client = Obiguard(
 obiguard_api_key="OBIGUARD_API_KEY",  # Your Obiguard API key
)

client.images.generate(
  prompt = "Cat flying to mars from moon",
  model = "imagen-3.0-generate-001"
)