OpenAI & Other SDKs

from openai import OpenAI
 
client = OpenAI()  # reads OPENAI_API_KEY
response = client.chat.completions.create(
    model="gpt-4o-mini",
    messages=[{"role": "user", "content": "Hello"}],
)
print(response.choices[0].message.content)

"""openai_sdks.py - chat, embeddings, tools, and LiteLLM fallback."""
from __future__ import annotations
 
import json
import os
from openai import OpenAI, AsyncOpenAI
 
client = OpenAI()
 
# Chat completion
chat = client.chat.completions.create(
    model="gpt-4o-mini",
    messages=[
        {"role": "system", "content": "You are a helpful assistant."},
        {"role": "user", "content": "What is FastAPI?"},
    ],
    temperature=0.2,
)
print(chat.choices[0].message.content)
 
# Embeddings
emb = client.embeddings.create(
    model="text-embedding-3-small",
    input=["Python data pipelines", "Machine learning basics"],
)
print("embedding dim:", len(emb.data[0].embedding))
 
# Function calling
tools = [{
    "type": "function",
    "function": {
        "name": "search_docs",
        "description": "Search internal documentation",
        "parameters": {
            "type": "object",
            "properties": {"query": {"type": "string"}},
            "required": ["query"],
        },
    },
}]
tool_resp = client.chat.completions.create(
    model="gpt-4o-mini",
    messages=[{"role": "user", "content": "Find docs about pydantic validators"}],
    tools=tools,
)
msg = tool_resp.choices[0].message
if msg.tool_calls:
    call = msg.tool_calls[0]
    print(f"tool: {call.function.name}({call.function.arguments})")
 
# LiteLLM multi-provider
try:
    import litellm
    response = litellm.completion(
        model="gpt-4o-mini",
        messages=[{"role": "user", "content": "Hi"}],
    )
    print("litellm:", response.choices[0].message.content[:50])
except ImportError:
    print("litellm not installed - skip")

# Custom base URL (Azure OpenAI, local proxy)
client = OpenAI(base_url=os.environ["OPENAI_BASE_URL"], api_key=os.environ["OPENAI_API_KEY"])
 
# Async usage in FastAPI
async def ask(question: str) -> str:
    client = AsyncOpenAI()
    resp = await client.chat.completions.create(
        model="gpt-4o-mini",
        messages=[{"role": "user", "content": question}],
    )
    return resp.choices[0].message.content or ""