AutoChat

AutoChat is an assistant library, to make it easy to create interactive agents. It supports OpenAI/Anthropic and can run on top of any other LLM.

• Autochat Class: Conversation wrapper to store instruction, context and messages histories.
• Message Class: Message wrapper to handle format/parsing automatically.
• Function Calls: Capability to handle function calls within the conversation, allowing complex interactions and responses.
• Template System: A straightforward text-based template system for defining the behavior of the chatbot, making it easy to customize its responses and actions.

Installation

To install the package, you can use pip:

pip install autochat

Please note that this package requires Python 3.6 or later.

Function Calls

The library supports function calls, handling the back-and-forth between the system and the assistant.

from autochat import Autochat, Message
import requests

def search_top_result(query: str):
    response = requests.get(f"https://google.com/search?q={query}")
    return response.text

classifierGPT = Autochat(instruction="You are a helpful assistant that can search the web for information")
classifierGPT.add_function(search_top_result)

text = "since when is the lastest iphone available?"
for message in classifierGPT.run_conversation(text):
    print(message.to_markdown())

# > ## assistant
# > search_top_result(query=next iphone release date)
# > ## function
# > (html content)
# > ## assistant
# > The latest iPhone models, iPhone 14, iPhone 14 Plus, iPhone 14 Pro, and iPhone 14 Pro Max, were released on September 16, 2022.

Simple Example

> from autochat import Autochat
> chat = Autochat(instruction="You are a parot")
> chat.ask('Hi my name is Bob')
# Message(role=assistant, content="Hi my name is Bob, hi my name is Bob!")
> chat.ask('Can you tell me my name?')
# Message(role=assistant, content="Your name is Bob, your name is Bob!")

Template System

We provide a simple template system for defining the behavior of the chatbot, using markdown-like syntax.

## system
You are a parrot

## user
Hi my name is Bob

## assistant
Hi my name is Bob, hi my name is Bob!

## user
Can you tell me my name?

## assistant
Your name is Bob, your name is Bob!

You can then load the template file using the from_template method:

parrotGPT = Autochat.from_template("./parrot_template.txt")

The template system also supports function calls. Check out the examples/demo_label.py for a complete example.

Use different API providers (only anthropic and openai are supported for now)

Default provider is openai.

Anthropic:

chat = Autochat(provider="anthropic")

Environment Variables

The AUTOCHAT_MODEL environment variable specifies the model to use. If not set, it defaults to "gpt-4-turbo".

export AUTOCHAT_MODEL="gpt-4-turbo"
export OPENAI_API_KEY=<your-key>

or with anthropic

export AUTOCHAT_MODEL="claude-3-opus"
export ANTHROPIC_API_KEY=<your-key>

Use AUTOCHAT_HOST to use alternative provider (openai, anthropic, openpipe, llama_cpp, ...)

Support

If you encounter any issues or have questions, please file an issue on the GitHub project page.

License

This project is licensed under the terms of the MIT license.