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This work in progress PR begins to add support for tools. Tools relies
on grammar support and still has some unsolved challenges. Opening the
PR for visibility and feedback

This PR avoids setting a default message in order to avoid unexpected
generations

small PR to add a new interface endpoint behind a feature

# What does this PR do?

Literally just adds the name field to the Message class.

I verified this change by building a new docker container (using the
`Dockerfile` in the repo) and trialing with a `chat_template` that uses
the `name` field.

Here's the previous behavior:

Input messages:
```
{
"messages": [
 {"role": "system", "content": "You are a succinct but helpful AI Assistant listening to a chat server.  Address everyone by @<username>"},
 {"role": "user", "name": "Aaron", "content": "Hello There!"},
 {"role": "assistant", "content": "  Hello @aaron! How can I assist you today?"},
 {"role": "user", "name": "Sally", "content": "Hiya everyone.  Is @aaron is this room?"}
],
  "model": "meta-llama/Llama-2-7b-chat-hf"
}
```

Response before the modification:
```
Hello @aaron! Yes, you are in the chat room. How can I assist you today? 😊

Hiya everyone! *waves* It's great to see you all here. Is there something on your mind that you'd like to talk about or ask? I'm here to listen and help in any way I can. 🤖
```

Response after my modification:
```
Hello @Sally! Yes, @aaron is currently in the chat room. How may I assist you today?
```

Fixes #1558 


## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the
other checks if that's the case).
- [x] Did you read the [contributor
guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests),
      Pull Request section?
- [ ] Was this discussed/approved via a Github issue or the
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- [ ] Did you write any new necessary tests?


## Who can review?
@Narsil

---------
Co-authored-by: Aaron Mihalik <aaron.mihalik@parsons.us>
Co-authored-by: drbh <david.richard.holtz@gmail.com>

This WIP PR starts to add grammar support via outlines, currently this
PR supports very simple regex grammars and does not optimize for
precompiling or caching grammar fsm's.

todo:
- [X] add simple outlines guidance to `NextTokenChooser`
- [X] update protos for grammar
- [X] update generation params API
- [X] constrain simple grammar
- [ ] support parsing more complex grammar into fsm
- [ ] support all outline support grammar types
- [ ] explore optimizations to avoid recompiling grammars

guided request
```bash
curl -s 'http://localhost:3000/generate' \
--header 'Content-Type: application/json' \
--data-raw '{
    "inputs": "make an email for david: \n",
    "parameters": {
        "max_new_tokens": 6,
        "grammar": "[\\w-]+@([\\w-]+\\.)+[\\w-]+"
    }
}' | jq
```
response
```json
{
  "generated_text": "david@example.com"
}
```

unguided request
```bash
curl -s 'http://localhost:3000/generate' \
--header 'Content-Type: application/json' \
--data '{
    "inputs": "make an email for david: \n",
    "parameters": {
        "max_new_tokens": 6
    }
}' | jq
```
response
```json
{
  "generated_text": "    email = 'david"
}
```

This PR adds a simple custom `deserialize_with` function that parses a
string or an object with a content property. This should help support
more token configuration files stored on the hub

Some hardware require a maximum batch size.

This PR adds support to read the `add_generation_prompt` from the config
and use it in the chat template. If `add_generation_prompt` does not
exist we default to false

This PR fixes the issue with loading a local tokenizer config.
Previously the default functionality would look in the current working
directory. Now if a local model path is specified we will check that
directory for the tokenizer_config.

## Examples of valid commands

uses tokenizer_config from hub
```
text-generation-launcher --model-id HuggingFaceH4/zephyr-7b-beta
```

use tokenizer_config from local model path
```
text-generation-launcher \
  --model-id ~/.cache/huggingface/hub/models--HuggingFaceH4--zephyr-7b-beta/snapshots/dc24cabd13eacd3ae3a5fe574bd645483a335a4a/
```

use specific tokenizer_config file
```
 text-generation-launcher \
  --model-id ~/.cache/huggingface/hub/models--HuggingFaceH4--zephyr-7b-beta/snapshots/dc24cabd13eacd3ae3a5fe574bd645483a335a4a/ \
  --tokenizer-config-path ~/.cache/huggingface/hub/models--HuggingFaceH4--zephyr-7b-beta/snapshots/dc24cabd13eacd3ae3a5fe574bd645483a335a4a/tokenizer_config.json


```

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

# What does this PR do?

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Fixes # (issue)


## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the
other checks if that's the case).
- [ ] Did you read the [contributor
guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests),
      Pull Request section?
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[forum](https://discuss.huggingface.co/)? Please add a link
      to it if that's the case.
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Here are the
[documentation
guidelines](https://github.com/huggingface/transformers/tree/main/docs),
and
[here are tips on formatting
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- [ ] Did you write any new necessary tests?


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# What does this PR do?


Ideally this is done client side, but this is a recurring request,
therefore we implemented it.

- Runs only if rust tokenizer is present (not encumbering the main
inference pipeline is important).
- Returns simple results, ID, text (gotten with offsets from the
original string) and offsets (so users can do things like highlighting
text).

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## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the
other checks if that's the case).
- [ ] Did you read the [contributor
guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests),
      Pull Request section?
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[forum](https://discuss.huggingface.co/)? Please add a link
      to it if that's the case.
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Here are the
[documentation
guidelines](https://github.com/huggingface/transformers/tree/main/docs),
and
[here are tips on formatting
docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation).
- [ ] Did you write any new necessary tests?


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Disable `decoder_input_details` on OpenAI-compatible chat streaming, pass temp and top-k from API (#1470)

This PR makes some minor tweaks to the new OpenAI-compatible chat
endpoint #1427 in `GenerateParameters`:
- Disables `decoder_input_details` when streaming is enabled. This was
causing all streaming chat requests to fail before, since
[`decoder_input_details`==true is not enabled when streaming
tokens](https://github.com/huggingface/text-generation-inference/blob/98e5faff9daec6170cc2b0f963f2d73cf846b341/router/src/validation.rs#L406).
- Passes through `temperature` and `top_p` hyperparameters from the API
request to `GenerateParameters`

## Testing

```bash
curl localhost:8080/v1/chat/completions \
    -X POST \
    -d '{
  "model": "",
  "messages": [
    {
      "role": "system",
      "content": "You are a helpful assistant."
    },
    {
      "role": "user",
      "content": "What is deep learning?"
    }
  ],
  "stream": true, 
  "max_tokens": 20
}' \                                   
    -H 'Content-Type: application/json'
```

Should work correctly. Currently, most recent release from `main`
returns error:
```
data:{"error":"Input validation error: `decoder_input_details` == true is not supported when streaming tokens","error_type":"validation"}
```

It's my first time contributing to this project, so I could be missing
something. Would especially appreciate @drbh's eyes on this one

This PR adds support to handle the custom jinja function
`raise_exception` and passes the `bos` and `eos` tokens into the
template

Additionally this PR adds 3 tests to validate and show examples of what
can and cannot be parsed currently.

```bash
cargo test --package text-generation-router --lib -- infer::tests --nocapture
#     Finished test [unoptimized + debuginfo] target(s) in 7.82s
#      Running unittests src/lib.rs (target/debug/deps/text_generation_router-18a0bbf99c2ca1b4)

# running 3 tests
# test infer::tests::test_chat_template_valid_with_raise ... ok
# test infer::tests::test_chat_template ... ok
# test infer::tests::test_chat_template_invalid_with_raise ... ok

# test result: ok. 3 passed; 0 failed; 0 ignored; 0 measured; 15 filtered out; finished in 0.00s
```

This PR adds support to make TGI a drop in replacement for OpenAI
clients by exposing the same HTTP interface.

Notes
- TGI inits a single model at startup so the `model` field is unused in
HTTP requests.
- `max_tokens` and `stream` should work as expected but other params may
be (unimplemented or not supported)

General approach
- fetch the `tokenizer_config` at startup from the hub
- pass `tokenizer_config` into `Infer` so we have it at request time
- use the `chat_template` on the config to format chat request
- parse jinja template and render chat string
- pass inputs into existing generate function
- wrap generation output in expected structure before returning

# How to test

### Streaming curl
```bash
curl localhost:3000/v1/chat/completions \
    -X POST \
    -d '{
  "model": "tgi",
  "messages": [
    {
      "role": "system",
      "content": "You are a helpful assistant."
    },
    {
      "role": "user",
      "content": "What is deep learning?"
    }
  ],
  "stream": true,
  "max_tokens": 20
}' \
    -H 'Content-Type: application/json'
```


It is also possible to use the `openai` python library and change the
base url

###  🌊 STREAMING REQUEST
```python
from openai import OpenAI

# init the client but point it to TGI
client = OpenAI(
    base_url="http://localhost:3000/v1",
    api_key="not needed for a local LLM"
)

chat_completion = client.chat.completions.create(
    model="tgi",
    messages=[
        {"role": "system", "content": "You are a helpful assistant." },
        {"role": "user", "content": "What is deep learning?"}
    ],
    stream=True
)

# iterate and print stream
for message in chat_completion:
    print(message)

# ChatCompletionChunk(id='', choices=[Choice(delta=ChoiceDelta(content=' that', function_call=None, role='assistant', tool_calls=None), finish_reason=None, index=2, logprobs=None)], created=1704486761, model='', object='text_completion', system_fingerprint='')
```

### 🚗 SYNCHRONOUS REQUEST
```python
from openai import OpenAI

# init the client but point it to TGI
client = OpenAI(
    base_url="http://localhost:3000/v1",
    api_key="not needed for a local LLM"
)

chat_completion = client.chat.completions.create(
    model="tgi",
    messages=[
        {"role": "system", "content": "You are a helpful assistant." },
        {"role": "user", "content": "What is deep learning?"}
    ],
    stream=False
)

print(chat_completion)
# ChatCompletion(id='', choices=[Choice(finish_reason=None, index=0, logprobs=None, message=ChatCompletionMessage(content='\nDeep learning is a new field of research that has been gaining traction in the last ...', role='assistant', function_call=None, tool_calls=None))], created=1704486762, model='', object='text_completion', system_fingerprint='', usage=CompletionUsage(completion_tokens=100, prompt_tokens=76, total_tokens=176))
```


## How to run dev

```bash
cd text-generation-inference/server
MASTER_ADDR=127.0.0.1 MASTER_PORT=5555 text-generation-server serve --trust-remote-code gpt2
```

***note many of the existing `chat_templates` use non standard `jinja`
(ie. adding a `raise` to the template) which will throw an error when
parsing; hence using `upstage/SOLAR-10.7B-Instruct-v1.0` since it has a
valid template
```bash
cd text-generation-inference/router
cargo run -- --tokenizer-name upstage/SOLAR-10.7B-Instruct-v1.0
```

trigger
```bash
curl localhost:3000/v1/chat/completions \
    -X POST \
    -d '{ "model": "gpt-3.5-turbo", "messages": [ { "role": "system", "content": "You are a helpful assistant." }, { "role": "user", "content": "What is the IP address of the Google DNS servers?" } ], "stream": true, "max_tokens": 20, "logprobs": true }' \
    -H 'Content-Type: application/json'
```

^ supports `stream: true` and `stream: false` requests

# What does this PR do?

See #1165

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---------
Co-authored-by: Florian Zimmermeister <flozi00.fz@gmail.com>
Co-authored-by: Ubuntu <ubuntu@ip-172-31-24-153.ec2.internal>

# What does this PR do?

Now clients which do not specify a max_length will be implying
`max_new_tokens = max_total_tokens - input_length`.
This is a serious change, but which seems more in line with what users
expect from standing server.

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      Pull Request section?
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      to it if that's the case.
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---------
Co-authored-by: OlivierDehaene <olivier@huggingface.co>

# What does this PR do?

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---------
Co-authored-by: Vincent Brouwers <vincent.brouwers@ing.com>

Close #288

Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com>
Co-authored-by: OlivierDehaene <olivier@huggingface.co>

close #125

closes #111

closes #112