axcent 0.3.1

The easiest way to build AI agents in Python

Axcent

The easiest way to build AI agents in Python.

Axcent is a lightweight framework designed to let you build powerful AI agents with tool calling, context caching, and multi-backend support in just a few lines of code.

Installation

pip install axcent

To use Gemini models:

pip install axcent[gemini]

Quick Start (OpenAI)

import os
from axcent import Agent

# Set your API Key
os.environ["OPENAI_API_KEY"] = "sk-..."

# Initialize Agent
agent = Agent(system_prompt="You are a helpful assistant.")

# Register a Tool
@agent.tool
def get_weather(city: str) -> str:
    """Returns weather info for a city."""
    return f"The weather in {city} is sunny!"

# Ask away!
response = agent.ask("What is the weather in Tokyo?")
print(response)

Features

• Simple Tool Registration: Just use @agent.tool.
• Automatic Context Caching: Optimizes token usage by enforcing stable prompt structures.
• Token Monitoring: Track prompt, completion, and cached tokens via agent.get_total_usage().
• Multimodal Support: Process images and audio with the Transcriber class.
• Backend Agnostic:
  • OpenAI: First-class support with vision.
  • Google Gemini: Support for all latest models including multimodal.
  • OpenRouter: Use any model via OpenRouter API compatibility.

Multimodal: Images & Audio

Axcent v0.3.0 introduces multimodal capabilities. Use the Transcriber class to let your agent "see" images and "hear" audio.

from axcent import Agent, Transcriber
from axcent.llm import GeminiBackend

agent = Agent(system_prompt="You are a helpful assistant.")

@agent.tool
def see_media(path: str) -> str:
    """Analyze an image or audio file."""
    transcriber = Transcriber(
        system_prompt="Describe this media briefly.",
        backend=GeminiBackend()
    )
    return transcriber.transcribe_file(path)

# Now the agent can understand media files!
response = agent.ask("What's in /path/to/image.jpg?")

You can also send images/audio directly with ask():

from axcent import Agent, Image

agent = Agent(model="gpt-4o")  # Vision-capable model
img = Image(url="https://example.com/photo.jpg")
response = agent.ask("What's in this image?", media=[img])

Multi-Backend Usage

Google Gemini

from axcent import Agent, GeminiBackend
import os

# Set API Key (or GOOGLE_API_KEY)
os.environ["GEMINI_API_KEY"] = "AIza..."

# Use Gemini Backend (uses google-genai V2 SDK)
backend = GeminiBackend(model="gemini-3-flash")
agent = Agent(system_prompt="You are a helper.", backend=backend)

OpenRouter

import os
from axcent import Agent

os.environ["OPENAI_API_KEY"] = "sk-or-..."
os.environ["OPENAI_BASE_URL"] = "https://openrouter.ai/api/v1"

agent = Agent(system_prompt="You are a helper.")

License

MIT