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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>

# What does this PR do?

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# What does this PR do?

```
text-generation-launcher --model-id XXX # Uses cuda graphs by default
text-generation-launcher --model-id XXX --cuda-graphs "1,2"  #Restrict the number of cuda graphs which saves VRAM
text-generation-launcher --model-id XXX --cuda-graphs "0"  # Disabling it entirely
```
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Close #1679

This PR correctly handles batches with a mixture of constrained and non
constrained generations.

Currently if batch contains mixed generations the generation will throw
an error because it will incorrectly attempt to constrain a request with
an empty grammar.

We now handled `None` grammars and only apply the mask if needed

Fixes:
https://github.com/huggingface/text-generation-inference/issues/1643

This PR fixes a bug with `ChatCompletionLogprobs` where if
`top_tokens.len() == 0` empty results were returned.

```bash
 curl http://localhost:3000/v1/chat/completions \
    -X POST \
    -H 'Content-Type: application/json' \
    -d '{
  "model": "tgi",
  "logprobs": true,
  "messages": [
    {
      "role": "user",
      "content": "What is deep learning?"
    }
  ],
  "stream": false,
  "max_tokens": 20
}'
```

response


```json
{"id":"","object":"text_completion","created":1711588522,"model":"google/gemma-2b-it","system_fingerprint":"1.4.4-native","choices":[{"index":0,"message":{"role":"assistant","content":"**Deep learning** is a subset of machine learning (ML) that emphasizes the creation of **artificial"},"logprobs":{"content":[{"token":"**","logprob":-0.22558594,"top_logprobs":[]},{"token":"Deep","logprob":-0.0014877319,"top_logprobs":[]},{"token":" learning","logprob":-0.12695312,"top_logprobs":[]},{"token":"**","logprob":-0.055664062,"top_logprobs":[]},{"token":" is","logprob":-0.00090026855,"top_logprobs":[]},{"token":" a","logprob":-0.006072998,"top_logprobs":[]},{"token":" subset","logprob":-2.25,"top_logprobs":[]},{"token":" of","logprob":-0.00031089783,"top_logprobs":[]},{"token":" machine","logprob":-0.091308594,"top_logprobs":[]},{"token":" learning","logprob":-0.00002348423,"top_logprobs":[]},{"token":" (","logprob":-1.671875,"top_logprobs":[]},{"token":"ML","logprob":-0.00040626526,"top_logprobs":[]},{"token":")","logprob":-0.00016212463,"top_logprobs":[]},{"token":" that","logprob":-0.13769531,"top_logprobs":[]},{"token":" emphasizes","logprob":-4.03125,"top_logprobs":[]},{"token":" the","logprob":-0.2890625,"top_logprobs":[]},{"token":" creation","logprob":-3.109375,"top_logprobs":[]},{"token":" of","logprob":-0.00024032593,"top_logprobs":[]},{"token":" **","logprob":-1.2265625,"top_logprobs":[]},{"token":"artificial","logprob":-0.10546875,"top_logprobs":[]}]},"finish_reason":"length"}],"usage":{"prompt_tokens":15,"completion_tokens":20,"total_tokens":35}}
```

# What does this PR do?

A few cases where you're using a mistral structure or mixtral structure
but not a llama tokenizer, why not make it to call the AutoTokenizer in
exception handling.

Similar PR #619

@Narsil

Close #1652

# What does this PR do?

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This PR resolves a couple 

- [X] adjusts the tool response to align with openai's tools response
type
- [X] bumps pydantic to `2.6.4` in all apps (resolves dependency issue
when running tests)
- [X] bump `outlines` version and fix import for new name

This PR fixes the broken urls in the idefics tests causing CI to fail

This PR adds `force_downcast_after` to `FastRMSNorm.forward` which is
used in the Gemma model. References
https://github.com/huggingface/transformers/pull/29402 and
https://github.com/huggingface/transformers/pull/29729

Setting `force_downcast_after=True` will perform the `hidden_states *
weight` multiplication in f32 and then downcast to half. This differs
slightly from the current implementation which first casts the
`hidden_states` to a half and then multiples.

This PR bumps `minijinja` and adds tests for all core models as
identified by @xenova 🙏

Inspiration:
https://github.com/huggingface/huggingface.js/blob/main/packages/jinja/test/e2e.test.js

TODO:
- [X] add new test to iterate over known templates
- [X] add default templates
- [x] add custom templates

# What does this PR do?

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## Before submitting
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other checks if that's the case).
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guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests),
      Pull Request section?
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      to it if that's the case.
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Signed-off-by: Sachin Varghese <sachin.mathew31@gmail.com>

Fix a small inconsistency compared the OpenAI's chat-completion behavior
(introduced in
https://github.com/huggingface/text-generation-inference/pull/1427 cc
@drbh). When using `stream=True`, each chunk has an `index` value in
`ChatCompletionChoice`. This index is not meant to be the index of the
generated token but the index of the choice, which is always 0 (since
TGI always return a single choice).

See https://platform.openai.com/docs/api-reference/chat/object:
> index _integer_
> The index of the choice in the list of choices.

---

So instead of 

```js
data:{"id":"","object":"text_completion","created":1710508199,"model":"HuggingFaceH4/zephyr-7b-beta","system_fingerprint":"1.4.3-sha-e6bb3ff8","choices":[{"index":1,"delta":{"role":"assistant","content":"I"},"logprobs":null,"finish_reason":null}]}
data:{"id":"","object":"text_completion","created":1710508199,"model":"HuggingFaceH4/zephyr-7b-beta","system_fingerprint":"1.4.3-sha-e6bb3ff8","choices":[{"index":2,"delta":{"role":"assistant","content":"'"},"logprobs":null,"finish_reason":null}]}
data:{"id":"","object":"text_completion","created":1710508199,"model":"HuggingFaceH4/zephyr-7b-beta","system_fingerprint":"1.4.3-sha-e6bb3ff8","choices":[{"index":3,"delta":{"role":"assistant","content":"m"},"logprobs":null,"finish_reason":"length"}]}
```

if should return
```js
data:{"id":"","object":"text_completion","created":1710508199,"model":"HuggingFaceH4/zephyr-7b-beta","system_fingerprint":"1.4.3-sha-e6bb3ff8","choices":[{"index":0,"delta":{"role":"assistant","content":"I"},"logprobs":null,"finish_reason":null}]}
data:{"id":"","object":"text_completion","created":1710508199,"model":"HuggingFaceH4/zephyr-7b-beta","system_fingerprint":"1.4.3-sha-e6bb3ff8","choices":[{"index":0,"delta":{"role":"assistant","content":"'"},"logprobs":null,"finish_reason":null}]}
data:{"id":"","object":"text_completion","created":1710508199,"model":"HuggingFaceH4/zephyr-7b-beta","system_fingerprint":"1.4.3-sha-e6bb3ff8","choices":[{"index":0,"delta":{"role":"assistant","content":"m"},"logprobs":null,"finish_reason":"length"}]}
```

**EDIT:** I also edited ToolCall.index to be always `0` (instead of the
generated token index) but for this one I'm actually unsure. It might be
the index of the tool in the array of tools? OpenAI's documentation
doesn't provide any information about it:
> index _integer_

---

I also noticed that in OpenAI's example, the last chunk doesn't have a
delta and is the only one that has a `finish_reason` returning. TGI is
slightly different since the last chunk has both the last delta (i.e.
the last generated token) + the finish reason. I don't think this is
worth fixing since it is not a requirement according to the docs/specs
(at least not that I know of).

# What does this PR do?
Fix the following carsh when build the docker on Ubuntu22.04

```
error[E0432]: unresolved import `nix::sys::signal::Signal`
 --> launcher/src/main.rs:2:30
  |
2 | use nix::sys::signal::{self, Signal};
  |                              ^^^^^^ no `Signal` in `sys::signal`
  |
  = help: consider importing this type alias instead:
          ctrlc::Signal

error[E0432]: unresolved import `nix::unistd::Pid`
   --> launcher/src/main.rs:3:5
    |
3   | use nix::unistd::Pid;
    |     ^^^^^^^^^^^^^^^^ no `Pid` in `unistd`
    |
note: found an item that was configured out
   --> /usr/local/cargo/registry/src/index.crates.io-6f17d22bba15001f/nix-0.27.1/src/unistd.rs:183:12
    |
183 | pub struct Pid(pid_t);
    |            ^^^
    = note: the item is gated behind the `process` feature

error[E0425]: cannot find function `kill` in module `signal`

```



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---------
Signed-off-by: yuanwu <yuan.wu@intel.com>
Co-authored-by: drbh <david.richard.holtz@gmail.com>

Falcon models are long superseded by better models like Zephyr and
OpenHermes. This PR updates the docs accordingly

# What does this PR do?

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This PR fixes how the grammar mask is index when generating text and
adds a new test to ensure the grammars work with non flash models

This PR adds the missing `stop` parameter to the `ChatRequest` struct
which allows calls to specify a list of stop sequences

This WIP PR (will) add support for legacy OpenAI `v1/completions` API.

This should allow TGI to be a drop in replacement for OpenAI when using
tools that rely on the completions api

Should fix:
https://github.com/huggingface/text-generation-inference/issues/1468

# What does this PR do?

Fixes #1616

According to the [aiohttp.ClientTimeout
docs](https://docs.aiohttp.org/en/stable/client_reference.html#aiohttp.ClientTimeout),
the arguments should be in seconds. This PR removes the multiplication
by 60.

@OlivierDehaene OR @Narsil

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This PR fixes parallel grammar requests, currently grammar states are
not concatenated correctly when a new request is added to the batch and
this results in incorrect generation. This PR updates the `concatenate`
function to correctly include the previous states.

fixes: #1601

See #1584

---------
Co-authored-by: Cheng Kuan Yong Jason <jasoncky96@gmail.com>

# What does this PR do?

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# What does this PR do?

It was meant to be in seconds float
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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

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