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# What does this PR do?
Update guidance docs to reflect grammar support in API. The previous
wording was vague and made it sound like openai API supported the
grammar parameter.


https://github.com/huggingface/text-generation-inference/blob/main/router/src/server.rs#L654
confirms that support for grammar is TGI only at this time.

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This PR adds support for `do_sample` to chat to enable greedy sampling

---------
Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>

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This PR resolves an issue with the penalty processors during batched
generation where extra padding tokens incorrectly impact the penalty
scores.

generation is impacted in the case where at least one item in the batch
includes a `frequency_penalty`

reproduction script below
```python
import requests
from concurrent import futures
import time

headers = {
    "Content-Type": "application/json",
}

json_data = {
    "inputs": "[INST] Whats the capitol of France? [/INST]",
    "parameters": {
        "max_new_tokens": 100,
        "seed": 20,
        "do_sample": False,
    },
}


json_data2 = {
    "inputs": "<s>[INST]Write a mind bending story: I saw a puppy a cat a rat and a raccoon during my bike ride in the park[/INST]",
    "parameters": {
        "max_new_tokens": 100,
        "seed": 2,
        "do_sample": False,
        # OFFENDING LINE
        "frequency_penalty": 1.05,
    },
}

base_url = "http://localhost:3000/generate

"


def req():
    response = requests.post(base_url, headers=headers, json=json_data)
    print("[req ]", response.json())


def req2():
    response = requests.post(base_url, headers=headers, json=json_data2)
    print("[req2]", response.json())


n = 1

for i in range(0, 3):
    print(f"- {n} threads -")
    with futures.ThreadPoolExecutor(max_workers=n) as executor:
        executor.submit(req)
        for i in range(3):
            executor.submit(req2)

    n += 1

# - 1 threads -
# [req ] {'generated_text': ' The capital of France is Paris.'}
# [req2] {'generated_text': " As you were riding your bicycle through Central Park, enjoying some fresh air on an otherwise gloomy day. You couldn't help but notice that it was eerily quiet for this time of year - usually there would be hordes"}
# [req2] {'generated_text': " As you were riding your bicycle through Central Park, enjoying some fresh air on an otherwise gloomy day. You couldn't help but notice that it was eerily quiet for this time of year - usually there would be hordes"}
# [req2] {'generated_text': " As you were riding your bicycle through Central Park, enjoying some fresh air on an otherwise gloomy day. You couldn't help but notice that it was eerily quiet for this time of year - usually there would be hordes"}
# - 2 threads -
# [req ] {'generated_text': ' The capital city'}
# [req2] {'generated_text': ' As""%\n================'}
# [req2] {'generated_text': ' As""%%$\n================'}
# [req2] {'generated_text': " As you were riding your bicycle through Central Park, enjoying some fresh air on an otherwise gloomy day. You couldn't help but notice that it was eerily quiet for this time of year - usually there would be hordes"}

# output with this PR's changes:
# - 1 threads -
# [req ] {'generated_text': ' The capital of France is Paris.'}
# [req2] {'generated_text': " As you were riding your bicycle through Central Park, enjoying some fresh air on an otherwise gloomy day. You couldn't help but notice that it was eerily quiet for this time of year - usually there would be hordes"}
# [req2] {'generated_text': " As you were riding your bicycle through Central Park, enjoying some fresh air on an otherwise gloomy day. You couldn't help but notice that it was eerily quiet for this time of year - usually there would be hordes"}
# [req2] {'generated_text': " As you were riding your bicycle through Central Park, enjoying some fresh air on an otherwise gloomy day. You couldn't help but notice that it was eerily quiet for this time of year - usually there would be hordes"}
# - 2 threads -
# [req ] {'generated_text': ' The capital city'}
# [req2] {'generated_text': " As you were riding your bicycle through Central Park, enjoying some fresh air on an otherwise gloomy day. You couldn't help but notice that it was eerily quiet for this time of year - usually there would be hordes"}
# [req2] {'generated_text': " As you were riding your bicycle through Central Park, enjoying some fresh air on an otherwise gloomy day. You couldn't help but notice that it was eerily quiet for this time of year - usually there would be hordes"}
# [req2] {'generated_text': " As you were riding your bicycle through Central Park, enjoying some fresh air on an otherwise gloomy day. You couldn't help but notice that it was eerily quiet for this time of year - usually there would be hordes"}

```

**divergence from expected generation is easier to reproduce with
batched grammar requests as they are more sensitive to unexpected
outputs.

this PR resolves the issue by setting the penalty score to 0 where input
ids are padding tokens (0).

---------
Co-authored-by: OlivierDehaene <olivier@huggingface.co>

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This PR resolves an issue loading in tokenizer_configs where the eos or
bos token is null as in:
[Qwen/Qwen1.5-72B-Chat](https://huggingface.co/Qwen/Qwen1.5-72B-Chat/blob/main/tokenizer_config.json)

resolves:
https://github.com/huggingface/text-generation-inference/issues/1545 and
related to https://github.com/QwenLM/Qwen1.5/issues/162

Once https://github.com/huggingface/huggingface.js/pull/629 gets merged,
we will rely on TGI's specs to generate jsonschema types for
`text_generation` and `chat_completion`.

This PR adds some documentation for `GenerationParameters`'s properties
so that they get documented in the downstream tools (TGI docs but also
`huggingface.js`/`huggingface_hub` inference clients). I mostly took
inspiration from [the python
client](https://github.com/huggingface/text-generation-inference/blob/main/clients/python/text_generation/types.py)
for the descriptions.

# What does this PR do?

Fix some small typos in the docs; add minor clarifications; add guidance
to features on landing page

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## Who can review?

@OlivierDehaene

This was ignored up to now, even with `--cuda-graphs 0`.

With this fix, `--cuda-graphs` is obeyed to.

This PR allows the `CompletionRequest.prompt` to be sent as a string or
array of strings. When an array is sent the first value will be used if
it's a string; otherwise the according error will be thrown

Fixes:
https://github.com/huggingface/text-generation-inference/issues/1690
Similar to: https://github.com/vllm-project/vllm/pull/323/files

This PR bumps the client tests from `google/flan-t5-xxl` to
`meta-llama/Llama-2-7b-chat-hf` to resolve issues when calling the
endpoint and `google/flan-t5-xxl` is not available

run with
```bash
make python-client-tests

clients/python/tests/test_client.py ..............     [ 43%]
clients/python/tests/test_errors.py ..........         [ 75%]
clients/python/tests/test_inference_api.py ......      [ 93%]
clients/python/tests/test_types.py ..                  [100%]
```

**note `google/flan-t5-xxl` function is currently unused but still
included in the `conftest.py`

`/v1/chat/completions` and `/v1/completions` have different output types
depending on the `stream` parameter. This PR aims at fixing the
inconsistency in the auto-generated
[openapi.json](https://huggingface.github.io/text-generation-inference/openapi.json)
specs.

cc @OlivierDehaene @drbh I reused what had been done for the `/`
endpoint but haven't tested anything myself. Could you confirm this is
the correct way of handling things?

Also, should I update the openapi.json file manually? If yes, how can I
do it?

This PR makes tool calling aware of the name of the function selected. 

Fixes:
https://github.com/huggingface/text-generation-inference/issues/1657

Thank you @puppetm4st3r for the helpful snippets, large parts of this PR
are simply refactors of the code shared 🙏

**opening draft PR because small tweaks are needed before merging

# What does this PR do?

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# What does this PR do?

compliation -> compilation


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# What does this PR do?

- Renamed `max_input_length` into `max_input_tokens` for consistency
(backward compatible change, will yell if both are set.)
- Will now use the config for `max_input_tokens` `max_total_token` and
`max_batch_total_tokens`.
- Capping the values to 16k in order to save VRAM on behalf of users
(overriddable by simply setting the values).

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# What does this PR do?

I have suggested similar changes over at
https://github.com/huggingface/text-embeddings-inference/pull/201.

Here being my additional question, why `debug` is enabled during release
building? (hence I didn't add the flag to script things)

Applying the following optimizations:
- `lto` (link time optimizations) over all code (including dependencies)
- Using a single `codegen-unit` to apply optimizations within 1 code
unit at build time


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---------
Co-authored-by: Dong Shin <d0104.shin@gmail.com>

wrap text-generation-launcher in docker image
mask ldconfig failures to user (no need in most cases anyway)

---------
Signed-off-by: Raphael Glon <oOraph@users.noreply.github.com>
Co-authored-by: Raphael Glon <oOraph@users.noreply.github.com>

This reverts commit b83aab9b.

Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>

@Narsil @drbh this will update flash attention v2 and vllm.
You will need to re-install them.

# What does this PR do?

- Changed all models to extract `embed_tokens` in order to enable llava
to separately call the embeddings and the core model layers.
- Added VlmCausalLM to inherit from FlashMistral in order to be
maximally supported. The only added logics sits on top and parses images
into pixel values, preallocates input_ids space for the image
embeddings, and passes them for the model.
- Added Clip for the vision tower.
- Didn't add flash for the vision tower since there's no padding anyway.
- Added heuristic (potentially incomplete) to calculate number of
features *before* calculating the clip patches (allows for easier logic
reuse of the LLM under the hood).


Still needs to be done:

- [x] Implement the image parsing in the controller side, to avoid
downloading n times per TP shard and also refusing requests too large
early and avoid issues where the truncation actually truncates the
image.
- [ ] Make sure it works with quantization properly.
- [x] Make sure it works with TP>1



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Reverts huggingface/text-generation-inference#725

---------
Co-authored-by: Julien Chaumond <julien@huggingface.co>

fixes
https://github.com/huggingface/text-generation-inference/issues/1711

Signed-off-by: Raphael Glon <oOraph@users.noreply.github.com>
Co-authored-by: Raphael Glon <oOraph@users.noreply.github.com>

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