Native SDK Support

from openai import OpenAI

client = OpenAI(
    api_key="your_truefoundry_api_key",
    base_url="{GATEWAY_BASE_URL}"
)

response = client.chat.completions.create(
    model="openai-main/gpt-4o-mini", # tfy model name
    messages=[{"role": "user", "content": "Hello, how are you?"}]
)

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

from google import genai
from google.genai import types

client = genai.Client(
    api_key="TFY_API_KEY",
    http_options=types.HttpOptions(
        base_url="{GATEWAY_BASE_URL}/gemini/{providerAccountName}/proxy"
    )
)

response = client.models.generate_content(
    model="gemini-2.5-flash",  # actual model id
    contents="How does AI work?",
)

print(response.text)

from anthropic import Anthropic

BASE_URL = "{GATEWAY_BASE_URL}"
API_KEY = "your-truefoundry-api-key"

client = Anthropic(
    api_key=API_KEY,
    base_url=BASE_URL,
    default_headers={
        "Authorization": f"Bearer {API_KEY}"
    }
)

def generate_response():
    response = client.messages.create(
        model="anthropic/claude-3-5",  # tfy model name
        max_tokens=1024,
        messages=[
            {
                "role": "user",
                "content": "Hello, Claude! Please explain quantum computing in simple terms."
            }
        ]
    )

    print(response.content)

generate_response()

import boto3
import os

os.environ["AWS_BEARER_TOKEN_BEDROCK"] = "your_truefoundry_api_key"

bedrock_runtime = boto3.client(
    service_name="bedrock-runtime",
    region_name=os.environ.get("AWS_REGION", "dummy"),
    endpoint_url="{GATEWAY_BASE_URL}/bedrock/proxy",
)

response = bedrock_runtime.converse(
    modelId="tfy-ai-bedrock/global-anthropic-claude-opus-4-5-20251101-v1-0",  # tfy model name
    messages=[
        {"role": "user", "content": [{"text": "Hello, how are you?"}]},
    ],
    inferenceConfig={"maxTokens": 256, "temperature": 0.7},
)

for block in response["output"]["message"]["content"]:
    if "text" in block:
        print(block["text"], end="")

import json

response = bedrock_runtime.invoke_model(
    modelId="tfy-ai-bedrock/global-anthropic-claude-opus-4-5-20251101-v1-0",
    contentType="application/json",
    accept="application/json",
    body=json.dumps({
        "anthropic_version": "bedrock-2023-05-31",
        "max_tokens": 256,
        "messages": [
            {
                "role": "user",
                "content": [{"type": "text", "text": "Hello, how are you?"}],
            }
        ],
    }),
)

from langchain_aws import ChatBedrockConverse

llm = ChatBedrockConverse(
    model="tfy-ai-bedrock/global-anthropic-claude-opus-4-5-20251101-v1-0",  # tfy model name
    region_name="dummy",
    endpoint_url="{GATEWAY_BASE_URL}/bedrock/proxy",
    api_key="your_truefoundry_api_key",
    temperature=0.2,
    max_tokens=256,
)

response = llm.invoke([("human", "Hello, how are you?")])
print(response.content)