Use the gateway

1
from openai import OpenAI
2
3
client = OpenAI(
4
    base_url="https://api.respan.ai/api/",
5
    api_key="YOUR_RESPAN_API_KEY",
6
)
7
8
response = client.chat.completions.create(
9
    model="gpt-5.4",
10
    messages=[{"role": "user", "content": "Hello"}],
11
    stream=True,
12
)
13
14
for chunk in response:
15
    print(chunk)

1
from openai import OpenAI
2
client = OpenAI(
3
    base_url="https://api.respan.ai/api/",
4
    api_key="YOUR_RESPAN_API_KEY",
5
)
6
7
tools = [
8
  {
9
    "type": "function",
10
    "function": {
11
      "name": "get_current_weather",
12
      "description": "Get the current weather in a given location",
13
      "parameters": {
14
        "type": "object",
15
        "properties": {
16
          "location": {
17
            "type": "string",
18
            "description": "The city and state, e.g. San Francisco, CA",
19
          },
20
          "unit": {"type": "string", "enum": ["celsius", "fahrenheit"]},
21
        },
22
        "required": ["location"],
23
      },
24
    }
25
  }
26
]
27
messages = [{"role": "user", "content": "What's the weather like in Boston today?"}]
28
completion = client.chat.completions.create(
29
  model="gpt-5.4",
30
  messages=messages,
31
  tools=tools,
32
  tool_choice="auto"
33
)
34
print(completion)

1
payload = {
2
    "model": "claude-sonnet-4-20250514",
3
    "max_tokens": 16000,
4
    "thinking": {
5
        "type": "enabled",
6
        "budget_tokens": 10000
7
    },
8
    "messages": [
9
        {
10
            "role": "user",
11
            "content": "Are there an infinite number of prime numbers such that n mod 4 == 3?"
12
        }
13
    ]
14
}

1
import os
2
import base64
3
import requests
4
from openai import OpenAI
5
6
openai_client = OpenAI()
7
pdf_url = "https://www.w3.org/WAI/ER/tests/xhtml/testfiles/resources/pdf/dummy.pdf"
8
response = requests.get(pdf_url)
9
file_data = response.content
10
file = openai_client.files.create(file=file_data, purpose="user_data")
11
12
client = OpenAI(
13
    base_url="https://api.respan.ai/api",
14
    api_key=os.getenv("RESPAN_API_KEY"),
15
)
16
17
file_content = [
18
    {"type": "text", "text": "What's this file about?"},
19
    {
20
        "type": "file",
21
        "file": {
22
            "file_id": file.id,
23
        },
24
    }
25
]
26
27
response = client.chat.completions.create(
28
    model="gpt-5.4",
29
    messages=[
30
        {
31
            "role": "user",
32
            "content": file_content,
33
        }
34
    ],
35
)

1
from openai import OpenAI
2
3
client = OpenAI(
4
    base_url="https://api.respan.ai/api/",
5
    api_key="YOUR_RESPAN_API_KEY",
6
)
7
8
response = client.chat.completions.create(
9
    model="gpt-5.4",
10
    messages=[{"role": "user", "content": [
11
        {"type": "text", "text": "What do you see?"},
12
        {"type": "image_url", "image_url": {"url": "https://example.com/image.png"}}
13
    ]}],
14
)

1
import anthropic
2
3
client = anthropic.Anthropic(
4
    base_url="https://api.respan.ai/api/anthropic/",
5
    api_key="YOUR_RESPAN_API_KEY",
6
)
7
8
message = client.messages.create(
9
    model="claude-sonnet-4-20250514",
10
    system=[
11
      {
12
        "type": "text",
13
        "text": "You are an AI assistant tasked with analyzing literary works.",
14
      },
15
      {
16
        "type": "text",
17
        "text": "<the entire contents of 'Pride and Prejudice'>",
18
        "cache_control": {"type": "ephemeral"}
19
      }
20
    ],
21
    messages=[{"role": "user", "content": "Analyze the major themes."}]
22
)