llama.cpp/requirements/requirements-all.txt

-r ../examples/llava/requirements.txt
-r ../examples/server/bench/requirements.txt
-r ../examples/server/tests/requirements.txt

-r ./requirements-compare-llama-bench.txt
-r ./requirements-pydantic.txt
-r ./requirements-test-tokenizer-random.txt

-r ./requirements-convert_hf_to_gguf.txt
-r ./requirements-convert_hf_to_gguf_update.txt
-r ./requirements-convert_legacy_llama.txt
-r ./requirements-convert_llama_ggml_to_gguf.txt
py : type-check all Python scripts with Pyright (#8341) * py : type-check all Python scripts with Pyright * server-tests : use trailing slash in openai base_url * server-tests : add more type annotations * server-tests : strip "chat" from base_url in oai_chat_completions * server-tests : model metadata is a dict * ci : disable pip cache in type-check workflow The cache is not shared between branches, and it's 250MB in size, so it would become quite a big part of the 10GB cache limit of the repo. * py : fix new type errors from master branch * tests : fix test-tokenizer-random.py Apparently, gcc applies optimisations even when pre-processing, which confuses pycparser. * ci : only show warnings and errors in python type-check The "information" level otherwise has entries from 'examples/pydantic_models_to_grammar.py', which could be confusing for someone trying to figure out what failed, considering that these messages can safely be ignored even though they look like errors. 2024-07-07 19:04:39 +00:00			`-r ../examples/llava/requirements.txt`
			`-r ../examples/server/bench/requirements.txt`
			`-r ../examples/server/tests/requirements.txt`

			`-r ./requirements-compare-llama-bench.txt`
			`-r ./requirements-pydantic.txt`
			`-r ./requirements-test-tokenizer-random.txt`

			`-r ./requirements-convert_hf_to_gguf.txt`
			`-r ./requirements-convert_hf_to_gguf_update.txt`
			`-r ./requirements-convert_legacy_llama.txt`
			`-r ./requirements-convert_llama_ggml_to_gguf.txt`