Comment on Selkie – Opinionated TUI Framework for RakuparentComments−antononcube4moThere is a set of Raku modules that leverage LLMs for different tasks (mostly code generation) using different techniques:- https://raku.land/zef:antononcube/LLM::Resources : Uses agentic LLM-graphs with asynchronous execution- https://raku.land/zef:antononcube/ML::FindTextualAnswer : Finds answers to questions over provided texts (e.g. natural language code generation commands)- https://raku.land/zef:antononcube/ML::NLPTemplateEngine : Fills-in predefined code templates based on natural language code descriptions/commands- https://raku.land/zef:antononcube/DSL::Examples : Example translations of natural language commands to executable code−apogeeOP4moI've got a few LLM modules too, mostly for handling context management:- https://raku.land/zef:apogee/LLM::Character implements CCv3 which is a standard for managing characters (system prompts) and lorebooks (injected snippets)- https://raku.land/zef:apogee/LLM::Chat handles context shifting for long contexts, sampler settings, templating for text completion & inferencing with or without streaming using supply/tap- https://raku.land/zef:apogee/LLM::Data::Inference adds retries, JSON parsing & multi-model route handling to LLM::Chat- https://raku.land/zef:apogee/LLM::Data::Pipeline allows you to declaratively build multi-step pipelines (simple agentic LLM use)- https://raku.land/zef:apogee/HuggingFace::API is a partial wrapper around HF API for grabbing tokenizers.json & tokenizer_config.json- https://raku.land/zef:apogee/Template::Jinja2 is a near-complete impl of Jinja2 for parsing LLM text completion templates (can be used for anything you'd use Jinja2 for)- https://raku.land/zef:apogee/Tokenizers is a thin wrapper around HF tokenizers, for token counting mostly
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There is a set of Raku modules that leverage LLMs for different tasks (mostly code generation) using different techniques:
- https://raku.land/zef:antononcube/LLM::Resources : Uses agentic LLM-graphs with asynchronous execution
- https://raku.land/zef:antononcube/ML::FindTextualAnswer : Finds answers to questions over provided texts (e.g. natural language code generation commands)
- https://raku.land/zef:antononcube/ML::NLPTemplateEngine : Fills-in predefined code templates based on natural language code descriptions/commands
- https://raku.land/zef:antononcube/DSL::Examples : Example translations of natural language commands to executable code
I've got a few LLM modules too, mostly for handling context management:
- https://raku.land/zef:apogee/LLM::Character implements CCv3 which is a standard for managing characters (system prompts) and lorebooks (injected snippets)
- https://raku.land/zef:apogee/LLM::Chat handles context shifting for long contexts, sampler settings, templating for text completion & inferencing with or without streaming using supply/tap
- https://raku.land/zef:apogee/LLM::Data::Inference adds retries, JSON parsing & multi-model route handling to LLM::Chat
- https://raku.land/zef:apogee/LLM::Data::Pipeline allows you to declaratively build multi-step pipelines (simple agentic LLM use)
- https://raku.land/zef:apogee/HuggingFace::API is a partial wrapper around HF API for grabbing tokenizers.json & tokenizer_config.json
- https://raku.land/zef:apogee/Template::Jinja2 is a near-complete impl of Jinja2 for parsing LLM text completion templates (can be used for anything you'd use Jinja2 for)
- https://raku.land/zef:apogee/Tokenizers is a thin wrapper around HF tokenizers, for token counting mostly