legacyllm 0.1.0

Automatic model routing and deprecation handling for OpenAI, Anthropic, and Google Gemini

legacyllm

Stop updating model names manually. legacyllm automatically detects deprecated AI models and routes them to their current replacements — across OpenAI, Anthropic, and Google Gemini.

import legacyllm

# claude-3-opus is retired — legacyllm swaps it automatically
response = legacyllm.chat(
    model="claude-3-opus-20240229",
    messages=[{"role": "user", "content": "Say hi"}]
)

# [legacyllm] 'claude-3-opus-20240229' is deprecated, switching to 'claude-opus-4-8'
print(response["text"])        # Hi!
print(response["model_used"])  # claude-opus-4-8
print(response["was_swapped"]) # True
print(response["usage"])       # {"input_tokens": 10, "output_tokens": 4, "total_tokens": 14}

---

Install

pip install legacyllm

Set your API keys in a .env file:

OPENAI_API_KEY=...
ANTHROPIC_API_KEY=...
GEMINI_API_KEY=...

---

Usage

Basic

import legacyllm

response = legacyllm.chat(
    model="claude-opus-4-6",
    messages=[{"role": "user", "content": "Hello"}]
)

print(response["text"])

With parameters

response = legacyllm.chat(
    model="gpt-4o",
    messages=[{"role": "user", "content": "Hello"}],
    max_tokens=512,
    temperature=0.7,
    system="You are a helpful assistant."
)

Conversation history

response = legacyllm.chat(
    model="claude-opus-4-6",
    messages=[
        {"role": "user", "content": "My name is John"},
        {"role": "assistant", "content": "Hi John!"},
        {"role": "user", "content": "What's my name?"}
    ]
)

Streaming

for chunk in legacyllm.chat(
    model="gpt-4o",
    messages=[{"role": "user", "content": "Tell me a story"}],
    stream=True
):
    print(chunk, end="", flush=True)

Async

import asyncio
import legacyllm

async def main():
    response = await legacyllm.async_chat(
        model="gemini-2.5-flash",
        messages=[{"role": "user", "content": "Hello"}]
    )
    print(response["text"])

asyncio.run(main())

Tools / function calling

response = legacyllm.chat(
    model="gpt-4o",
    messages=[{"role": "user", "content": "What's the weather in NYC?"}],
    tools=[{
        "type": "function",
        "name": "get_weather",
        "description": "Get weather for a location",
        "parameters": {
            "type": "object",
            "properties": {
                "location": {"type": "string"}
            },
            "required": ["location"]
        }
    }]
)

---

Response

Every response returns the same shape regardless of provider:

{
    "text":           str,   # the response text
    "model_used":     str,   # actual model used (may differ if swapped)
    "was_swapped":    bool,  # True if model was deprecated and swapped
    "original_model": str,   # the model name you passed in
    "usage": {
        "input_tokens":  int,
        "output_tokens": int,
        "total_tokens":  int
    }
}

---

Supported providers

Provider	Models
OpenAI	gpt-*, o1, o3, o4
Anthropic	claude-*
Google	gemini-*

---

Helper commands

# see available parameters for a provider
legacyllm.params("openai")
legacyllm.params("anthropic")
legacyllm.params("google")

# list all current models
legacyllm.models()
legacyllm.models("openai")

# from the terminal
python -m legacyllm params openai
python -m legacyllm models
python -m legacyllm update

---

Keeping models up to date

legacyllm ships with a built-in deprecation index. To refresh it:

python -m legacyllm update

This fetches the latest models from all 3 providers, updates legacyllm/data/current_models.json, and flags any models that have disappeared so you can update the deprecation index.

---

Contributing

The deprecation index (legacyllm/data/depricated.json) needs ongoing maintenance as providers release and retire models. If you notice a missing deprecation:

1. Fork the repo
2. Add the entry to legacyllm/data/depricated.json with replacement and deprecated_on
3. Run pytest to validate
4. Submit a pull request

---

License

MIT