Me, myself and I geenet

Minimal Prompt Chainables

Sequential prompt chaining in one method with context and output back-referencing.

Files

main.py - start here - full example using MinimalChainable from chain.py to build a sequential prompt chain
chain.py - contains zero library minimal prompt chain class
chain_test.py - tests for chain.py, you can ignore this
requirements.py - python requirements

Setup

Prompt Chaining with QwQ, Qwen, o1-mini, Ollama, and LLM

Here we explore prompt chaining with local reasoning models in combination with base models. With shockingly powerful local models like QwQ and Qwen, we can build some powerful prompt chains that let us tap into their capabilities in a immediately useful, local, private, AND free way.

Explore the idea of building prompt chains where the first is a powerful reasoning model that generates a response, and then use a base model to extract the response.

Play with the prompts and models to see what works best for your use cases. Use the o1 series to see how qwq compares.

Setup

Bun (to run bun run chain.ts ...)

Prompt Chaining with QwQ, Qwen, o1-mini, Ollama, and LLM

Here we explore prompt chaining with local reasoning models in combination with base models. With shockingly powerful local models like QwQ and Qwen, we can build some powerful prompt chains that let us tap into their capabilities in a immediately useful, local, private, AND free way.

Explore the idea of building prompt chains where the first is a powerful reasoning model that generates a response, and then use a base model to extract the response.

Play with the prompts and models to see what works best for your use cases. Use the o1 series to see how qwq compares.

Setup

Bun (to run bun run chain.ts ...)


	import logging
	from distutils import log

	logging.basicConfig(level=logging.DEBUG)

	log.set_verbosity(log.DEBUG)


	from cffi import FFI

	"""
	Simple demonstration of how to implement Server-sent events (SSE) in Python
	using Bottle micro web-framework.

	SSE require asynchronous request handling, but it's tricky with WSGI. One way
	to achieve that is to use gevent library as shown here.

	Usage: just start the script and open http://localhost:8080/ in your browser.

	Based on:

	-- show running queries (pre 9.2)
	SELECT procpid, age(query_start, clock_timestamp()), usename, current_query
	FROM pg_stat_activity
	WHERE current_query != '<IDLE>' AND current_query NOT ILIKE '%pg_stat_activity%'
	ORDER BY query_start desc;

	-- show running queries (9.2)
	SELECT pid, age(query_start, clock_timestamp()), usename, query
	FROM pg_stat_activity
	WHERE query != '<IDLE>' AND query NOT ILIKE '%pg_stat_activity%'