UnifiedAI 1.5.5

A python package that simplifies and unifies the usage of multiple AI APIs

UnifiedAI

UnifiedAI is a Python package that simplifies the usage of multiple AI APIs by providing a single, unified API. Currently, it supports OpenAI, Anthropic, Google, and Ollama AI APIs.

Features

• Single API for multiple AI providers.
• Easy switching between different AI models.
• Simplified authentication and API key management.

Installation

pip install UnifiedAI

Usage

Creating an AI instance

API = AI(instance_name,api_provider,api_key,model_name)

Usage and methods of using one AI instance

from UnifiedAI import *

API = AI("gpt4","openai","OPENAI_API_KEY","gpt-4o")


#default is "You are a helpful assistant"
API.set_instructions("You are a sarcastically helpful assistant.")


#default is 512
API.set_max_tokens(100)


# add context without an api call
API.add_context("My Name is John.")


print(API.get_response("what is my name?"))

    
#history is a list object of all the user messages and assistant responses. 
print(API.history)


#print the input token usage of the model
print(API.usage.input_tokens)

#print the output token usage of the model
print(API.usage.output_tokens)


    

Use multiple AI instances at once using a Batch instance.

    
from UnifiedAI import *
import json

gpt = AI("gpt","openai","OPENAI_API_KEY","gpt-4o")
claude = AI("claude","anthropic","ANTHROPIC_API_KEY","claude-3-5-sonnet-latest")
gemini = AI("gemini","google","GEMINI_API_KEY","gemini-1.5-pro")
llama = AI("llama","ollama",None,"llama3.2") 


models  = Batch([gpt, claude, gemini,llama])

models.set_instructions("You are a sarcastically helpful assistant.")

models.set_max_tokens(100)

models.add_context("My name is John.")

# get_response returns a dictionary object with
# the model names and their responses
print(json.dumps(models.get_response("what is my name?"),indent=4))

# print the output token usage of each model
print(models.usage["gpt"].output_tokens)
print(models.usage["claude"].output_tokens)
print(models.usage["gemini"].output_tokens)
print(models.usage["llama"].output_tokens)

Compare responses with different system instructions.

from UnifiedAI import *
import json

angry = AI("angry","openai","OPENAI_API_KEY","gpt-4o")
sarcastic = AI("sarcastic","openai","OPENAI_API_KEY","gpt-4o")
sad = AI("sad","openai","OPENAI_API_KEY","gpt-4o")

angry.set_instructions("Answer in a angry way.")
sarcastic.set_instructions("Answer in a sarcastic way.")
sad.set_instructions("Answer in a sad way.")


emotions = Batch([angry,sarcastic,sad])


emotions.set_max_tokens(100)


print(json.dumps(emotions.get_response("what is 1 + 1?"),indent=4))


print(emotions.usage["angry"].output_tokens)
print(emotions.usage["sarcastic"].output_tokens)
print(emotions.usage["sad"].output_tokens)