pytypingchat 0.0.1

Description:

pytypingchat 0.0.1

typingchat
A python style implementation of Typechat
Useage
pip3 install pytypingchat

local install
pip3 install .

demo
Custom dataclass
from typingchat.core import TypeChat,OpenAIChat
from pydantic import BaseModel,Field
from typing import Literal

class Customer(BaseModel):
name: str = Field(description="Specify the customer's name")

class CoffeeDrink(BaseModel):
type: Literal["CoffeeDrink"] = Field(default="CoffeeDrink", description="Specify the type of coffee drink")
name: Literal["cappuccino", "flat white", "latte", "latte macchiato", "mocha", "chai latte"] = Field(None, description="Specify the name of the coffee drink")
count: int = Field(1, description="Specify the selected drink quantity")

def add_sugar(self, customer: Customer):
"""
add some sugar to coffee

Returns:

"""
return "add sugar success"

OPENAI_API_KEY = "sk-xxx"
OPENAI_MODEL = "gpt-3.5-turbo-0125"

chat = OpenAIChat(api_key=OPENAI_API_KEY,model=OPENAI_MODEL)
typechat = TypeChat(chat=chat)
coffee: CoffeeDrink = typechat.translate( #type: ignore
message="I want a mocha.",
obj=CoffeeDrink
)

coffee.model_dump() # {'type': 'CoffeeDrink', 'name': 'mocha', 'count': 1})


output
{'type': 'CoffeeDrink', 'name': 'mocha', 'count': 1})

use as function call
chat = OpenAIChat(api_key=OPENAI_API_KEY, model=OPENAI_MODEL)
typechat = TypeChat(chat=chat)
product = typechat.translate(
message="I want a flat white",
obj=CoffeeDrink
)
filter = lambda name: True if name in [product.add_sugar.__name__] else False
reply_messsage = typechat.operate(product, message="Add a little sugar to Tom's coffee", func_filter=filter,extra_dataclass=[Customer])

reply_message.content # The sugar has been successfully added to Tom's coffee.

References

https://github.com/microsoft/TypeChat