Generate human-like text responses using state-of-the-art language models. Kelly AI provides access to multiple LLMs including ChatGPT, Google Gemini, Gemma, and custom KellyAI models.
Generate text
Use the llm() method to generate text responses from AI language models.
Import and initialize
from kellyapi import KellyAPI
kelly = KellyAPI(api_key="your_api_key")
Send your prompt
response = await kelly.llm(
prompt="Explain quantum computing in simple terms",
model="chatgpt",
character="KellyAI"
)
Parameters
Your question or instruction for the language model.
The language model to use. Available options include chatgpt, gemini, gemma, and other models.
The character or personality the AI should adopt when responding.
Available models
Retrieve the list of available language models:
models = await kelly.llm_models()
print(models)
Complete example
import asyncio
from kellyapi import KellyAPI
async def chat():
kelly = KellyAPI(api_key="your_api_key")
# Get available models
models = await kelly.llm_models()
print("Available models:", models)
# Generate a response
response = await kelly.llm(
prompt="Write a short poem about artificial intelligence",
model="chatgpt",
character="KellyAI"
)
print("\nAI Response:")
print(response)
# Run the async function
asyncio.run(chat())
Use cases
Question answering
Get informative answers to your questions:
response = await kelly.llm(
prompt="What are the benefits of renewable energy?",
model="chatgpt"
)
print(response)
Content generation
Create original content:
response = await kelly.llm(
prompt="Write a product description for eco-friendly water bottles",
model="gemini"
)
print(response)
Code assistance
Get help with programming:
response = await kelly.llm(
prompt="Explain how to implement a binary search algorithm in Python",
model="chatgpt"
)
print(response)
Text summarization
Summarize long texts:
long_text = """[Your long article or document here]"""
response = await kelly.llm(
prompt=f"Summarize the following text in 3 bullet points:\n\n{long_text}",
model="chatgpt"
)
print(response)
Creative writing
Generate creative content:
response = await kelly.llm(
prompt="Write a short story about a robot learning to paint",
model="gemini",
character="Creative Writer"
)
print(response)
Translation assistance
Translate text between languages:
response = await kelly.llm(
prompt="Translate 'Hello, how are you?' to Spanish, French, and German",
model="chatgpt"
)
print(response)
Conversational AI
Build interactive chatbots:
import asyncio
from kellyapi import KellyAPI
async def chatbot():
kelly = KellyAPI(api_key="your_api_key")
print("Chatbot started. Type 'exit' to quit.")
while True:
user_input = input("\nYou: ")
if user_input.lower() == "exit":
break
response = await kelly.llm(
prompt=user_input,
model="chatgpt",
character="Helpful Assistant"
)
print(f"\nAI: {response}")
asyncio.run(chatbot())
The llm() method returns the text response as a string. Different models may have different response styles and capabilities.
For best results, be specific in your prompts. Include context, desired format, and any constraints. For example: “Write a 100-word summary” or “Explain in simple terms for beginners.”