* server: Retrieve prompt template in /props

This PR adds the following:
- Expose the model's Jinja2 prompt template from the model in the /props endpoint.
- Change log-level from Error to Warning for warning about template mismatch.

The front-end stands a better chance of actually executing the Jinja template format correctly. Server is currently just guessing it.

Ideally this should have been inside a JSON block that expose the same key/value pairs as listed during startup in "llm_load_print_meta" function.

* Make string buffer dynamic

* Add doc and better string handling

* Using chat_template naming convention

* Use intermediate vector for string assignment

This patch replaces an old commad "main" with "llama-cli"
in finetune.sh.
The part that I fixed is comment, so it doesn't change
the script.

Signed-off-by: Masanari Iida <standby24x7@gmail.com>

Rename an old command name "finetune" to "llama-finetune"
in README.md

Signed-off-by: Masanari Iida <standby24x7@gmail.com>

ggml-ci

* add chatglm3-6b model support huggingface model:
 https://hf-mirror.com/THUDM/chatglm3-6b

Signed-off-by: XingXing Qiao <qiaoxx@dingdao.com>

* remove .rotary_pos_emb.inv_freq and unuse code for chatglm3 model

Signed-off-by: XingXing Qiao <qiaoxx@dingdao.com>

* fix lint error

Signed-off-by: XingXing Qiao <qiaoxx@dingdao.com>

* optimize convert-hf-to-gguf.py for chatglm model

Signed-off-by: XingXing Qiao <qiaoxx@dingdao.com>

* support glm-4-9b-chat

Signed-off-by: XingXing Qiao <qiaoxx@dingdao.com>

* fix eos tokens to glm4

* remove unused log

* add preprocess to chatglm3 and chatglm4

* add eos_id_list to llama.cpp

* fix code style

* fix code style

* fix conflicts

* fix conflicts

* Revert "add eos_id_list to llama.cpp"

This reverts commit 3a4d579.

* set <|endoftext|> as eos and <|user|> as eot

* fix chat template bug

* add comment to glm prefix and suffix

* fix conflicts and add rope_ratio & ChatGLMForConditionalGeneration

* fix chat template bug

* fix codestyle

* fix conflicts

* modified the general name of glm model

* fix conflicts

* remove prefix and suffix

* use normal glm4 chattempalte & use LLM_FFN_SWIGLU in phi3

* fix: resolve Flake8 errors in `convert-hf-to-gguf.py`

- Fix E302 by adding two blank lines before top-level function definitions
- Replace print statements to fix NP100
- Fix E303 by ensuring only one blank line between lines of code

* fix rope ratio to solve incorrect answers

* fix by comments

---------

Signed-off-by: XingXing Qiao <qiaoxx@dingdao.com>
Co-authored-by: XingXing Qiao <qiaoxx@dingdao.com>
Co-authored-by: Umpire2018 <138990495+Umpire2018@users.noreply.github.com>

…8048)

CLI to hash GGUF files to detect difference on a per model and per tensor level

The hash type we support is:

- `--xxh64`: use xhash 64bit hash mode (default)
- `--sha1`: use sha1
- `--uuid`: use uuid
- `--sha256`: use sha256

While most POSIX systems already have hash checking programs like sha256sum, it
is designed to check entire files. This is not ideal for our purpose if we want
to check for consistency of the tensor data even if the metadata content of the
gguf KV store has been updated.

This program is designed to hash a gguf tensor payload on a 'per tensor layer'
in addition to a 'entire tensor model' hash. The intent is that the entire
tensor layer can be checked first but if there is any detected inconsistencies,
then the per tensor hash can be used to narrow down the specific tensor layer
that has inconsistencies.

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>

* adding guile_llama_cpp  to binding list

* fix formatting

* fix formatting

* Added checks for cmake,make and ctest

* Removed erroneous whitespace

* Update README.md

* Update README.md

* Update README.md

fixed llama-cli/main, templates on some cmds added chat template sections and fixed typos in some areas

* Update README.md

* Update README.md

* Update README.md

* 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.

Only used in _set_vocab_gpt2() for now.

This makes Gemma and Gemma-2 tokenize pretty much EVERYTHING correctly,
including HTML tags and consecutive spaces,
but it unfortunately requires model re-conversion.

There seems to be a weird behavior of the HF tokenizer for Gemma,
which prefers to use the 16-space token over more lengthy space tokens,
while using the SentencePiece tokenizer does not do this.
(the implementation in llama.cpp has the same behavior as SentencePiece)

* llama : fix wrong pre-tokenization of byte tokens