Create programs that think, using LLMs.
Project description
Think
Think is a Python package for creating thinking programs.
It provides simple but powerful primitives for robust integration of Large Language Models (LLMs) into your Python programs.
Examples
Using AI as an ordinary function:
from think.llm.openai import ChatGPT
from think.ai import ai
@ai
def haiku(topic: str) -> str:
"""
Write a haiku about {{ topic }}
"""
llm = ChatGPT()
print(haiku(llm, topic="computers"))
Allowing AI to use tools:
from datetime import date
from think.llm.openai import ChatGPT
from think.chat import Chat
from think.tool import tool
@tool
def current_date() -> str:
"""
Get the current date.
:returns: current date in YYYY-MM-DD format
"""
return date.today().isoformat()
llm = ChatGPT()
chat = Chat("You are a helpful assistant.")
chat.user("How old are you (in days since your knowledge cutoff)?")
print(llm(chat, tools=[current_date]))
Parsing AI output:
import json
from pydantic import BaseModel
from think.llm.openai import ChatGPT
from think.chat import Chat
from think.parser import JSONParser
class CityInfo(BaseModel):
name: str
country: str
population: int
latitude: float
longitude: float
llm = ChatGPT()
parser = JSONParser(spec=CityInfo)
chat = Chat(
"You are a hepful assistant. Your task is to answer questions about cities, "
"to the best of your knowledge. Your output must be a valid JSON conforming to "
"this JSON schema:\n" + json.dumps(parser.schema)
).user(city)
answer = llm(chat, parser=parser)
print(f"{answer.name} is a city in {answer.country} with {answer.population} inhabitants.")
print(f"It is located at {answer.latitude} latitude and {answer.longitude} longitude.")
Quickstart
Install via pip
:
pip install think-llm
Note that the package name is think-llm
, not think
.
Set up your LLM credentials (OpenAI or Anthropic, depending on the LLM you want to use):
export OPENAI_API_KEY=<your-openai-key>
export ANTHROPIC_API_KEY=<your-anthropic-key>
And you're ready to go:
from think.llm.openai import ChatGPT
from think.chat import Chat
llm = ChatGPT()
chat = Chat("You are a helpful assistant.").user("Tell me a funny joke.")
print(llm(chat))
Explore the examples directory for more usage examples, and the source code for documentation on how to use the library (until we build proper docs! if you want to help out with that, please see below).
Roadmap
Features and capabilities that are planned for the near future:
- documentation
- full support for Anthropic (tools, parsers, AI functions)
- support for other LLM APIs via LiteLLM or similar
- support for local LLMs via HuggingFace
- more examples
If you want to help with any of these, please look at the open issues, join the conversation and submit a PR. Please read the Contributing section below.
Contributing
Contributions are welcome!
To ensure that your contribution is accepted, please follow these guidelines:
- open an issue to discuss your idea before you start working on it, or if there's already an issue for your idea, join the conversation there and explain how you plan to implement it
- make sure that your code is well documented (docstrings, type annotations, comments, etc.) and tested (test coverage should only go up)
- make sure that your code is formatted and type-checked with
ruff
(default settings)
Copyright
Copyright (C) 2023-2024. Senko Rasic and Think contributors. You may use and/or distribute this project under the terms of MIT license. See the LICENSE file for more details.
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