wraipperz 0.1.10

Simple wrappers for various AI APIs including LLMs, ASR, and TTS

wraipperz (WIP - agent generated)

Simple wrappers for various AI APIs including LLMs, ASR, and TTS.

Installation

pip install wraipperz
uv add wraipperz

Features

• LLM API Wrappers: Unified interface for OpenAI, Anthropic, Google, and other LLM providers
• ASR (Automatic Speech Recognition): Convert speech to text
• TTS (Text-to-Speech): Convert text to speech
• Async Support: Asynchronous API calls for improved performance

Quick Start

LLM

import os
from wraipperz import call_ai, MessageBuilder

os.environ["OPENAI_API_KEY"] = "your_openai_key" # if not defined in environment variables
messages = MessageBuilder().add_system("You are a helpful assistant.").add_user("What's 1+1?")

# Call an LLM with a simple interface
response, cost = call_ai(
    model="openai/gpt-4o",
    messages=messages
)

Parsing LLM output to pydantic object.

from pydantic import BaseModel, Field
from wraipperz import pydantic_to_yaml_example, find_yaml, MessageBuilder, call_ai
import yaml


class User(BaseModel):
    name: str = Field(json_schema_extra={"example": "Bob", "comment": "The name of the character."})
    age: int = Field(json_schema_extra={"example": 12, "comment": "The age of the character."})


template = pydantic_to_yaml_example(User)
prompt = f"""Extract the user's name and age from the unstructured text provided below and output your answer following the provided example.
Text: "John is a well respected 31 years old pirate who really likes mooncakes."
Exampe output:
\`\`\`yaml
{template}
\`\`\`
"""
messages = MessageBuilder().add_system(prompt).build()
response, cost = call_ai(model="openai/gpt-4o-mini", messages=messages)

yaml_content = find_yaml(response)
user = User(**yaml.safe_load(yaml_content))
print(user)  # prints name='John' age=31

TTS

from wraipperz.api.tts import create_tts_manager

tts_manager = create_tts_manager()

# Generate speech using OpenAI Realtime TTS
response = tts_manager.generate_speech(
    "openai_realtime",
    text="This is a demonstration of my voice capabilities!",
    output_path="realtime_output.mp3",
    voice="ballad",
    context="Speak in a extremelly calm, soft, and relaxed voice.",
    return_alignment=True,
    speed=1.1,
)

# Convert speech using ElevenLabs
# TODO add example

Environment Variables

Set up your API keys in environment variables to enable providers.

OPENAI_API_KEY=your_openai_key
ANTHROPIC_API_KEY=your_anthropic_key
GOOGLE_API_KEY=your_google_key
# ...  todo add all

License

MIT

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.