Seamless integration and composability for large language model apps.
Project description
chaincrafter
Seamless integration and composability for large language model apps.
Features
- Composable prompts and chains
- Use multiple models to run one chain and then use that as input for a different chain and model
- Customizable prompt and response formatting
- Add modifiers to prompts to change the style, length, and format of the response
- Extract data from the response to use in the next prompt
- Add custom functions to process the response
- Add custom functions to process the input variables
- Integration with OpenAI API (llama.cpp in progress)
- Async calls to models
- Load Prompts and Chains from YAML using Catalogs
- Makes it easier to share prompts and chains between projects
- Build up a prompts library
Installation
pip install chaincrafter
Usage
- Define your prompts and the variables that they expect
- The input variables can be of any type, and can be processed by a function
- The prompt message is treated as an f-string
- Define your chain of prompts
- The chain is a list of tuples, where each tuple contains a prompt and the output key to store the response in
- The output key is used to access the response in the next prompt
- Set up the models that you want to use
- Run the chain using the models
from chaincrafter import Chain, Prompt
from chaincrafter.models import OpenAiChat
chat_model = OpenAiChat(temperature=0.65, model_name="gpt-3.5-turbo")
system_prompt = Prompt("You are a helpful assistant who responds to questions about the world")
hello_prompt = Prompt("Hello, what is the capital of France? Answer only with the city name.")
followup_prompt = Prompt("{city} sounds like a nice place to visit. What is the population of {city}?")
chain = Chain(
system_prompt,
(hello_prompt, "city"),
(followup_prompt, "followup_response"),
)
messages = chain.run(chat_model)
for message in messages:
print(f"{message['role']}: {message['content']}")
Running the examples
source venv/bin/activate
export OPENAI_API_KEY="..."
python -m examples.interesting_facts
python -m examples.interesting_facts_catalog
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