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TODOs (in priority order)
- [ ] Use custom `click` argument types to support the `configlib` for functions.
ai agent llm prompt
View sourceTODOs (in priority order)
- Use custom
clickargument types to support theconfiglibfor functions. - Design a module for benchmark building pipelines
- Use reflection for automated logger configuration for the log module
- Implement
log.watchdog - Figure out how to strictly separate
load_configandload_envforconfigurableclasses - Simplify the usage pattern of
load_configandload_env - Add error messages if using a configuration setting before it is loaded
- Develop a standard operating procedure (sop) for redacting the identity information for anonymous artifact submission in paper reviewing
- Refine the ergonomics of
prompt - Add format specifiers to
prompt - Add a
py-tree-sitterwrapper module - Move in the LLM pricing tracker
- Develop a sop to integrate Python code with native language code (such as Rust and Zig) to accommodate memory/time critical scenarios
-
We should implementDeferred: The current status of Zig toolchains is immatureIntervalTreein thealgmodule in Zig, as the Python implementation consumes too much memory -
subshellsometimes misses outputs, especially whenPHDKIT_SIMPLE_SUBSHELLis on -
Consider how to useconfiglibfor the context manager protocol - Explore how to handle optional settings in
configlib - Add
postloadfunctionalities forconfiglib - Add docs for default setting values in
configlib - Implement the
subshellfunctionality of therichwrapper module - Make
infix_fntype-safe - Audit this whole "vibe-coding" interval tree implementation for correctness and performance
- Consider how to handle configurations of base classes in
configlib -
Implement theAlready supported bydyntqdmfunctionality of therichwrapper modulerich - Test whether
configlibhandles arrays in TOML correctly - Add a flag to
subshellto switch it to a simple interface when interacting with coding agents
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