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80 Commits

Author SHA1 Message Date
Nicolas Patry a55dfb2700 Upgrade deps after release. 2024-05-24 11:23:06 +00:00
Nicolas Patry ac7076b64d
Upgrading to rust 1.78. (#1851)
# What does this PR do?

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2024-05-06 13:48:11 +02:00
Nicolas Patry a25737139d
Updating Phi3 (long context). (#1849)
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2024-05-02 19:07:10 +02:00
OlivierDehaene 2d0a7173d4 v2.0.1 2024-04-18 17:20:36 +02:00
Nicolas Patry f9ee2c41b9
Upgrading all versions. (#1759) 2024-04-18 17:17:40 +02:00
OlivierDehaene c38a7d7ddd
v2.0.0 (#1736) 2024-04-12 18:38:34 +02:00
Nicolas Patry 1b2670c823
Improve the defaults for the launcher (#1727)
# 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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2024-04-12 14:20:31 +02:00
Nicolas Patry 842f6658e2 Revert "Easier defaults for models stemmed from configs."
This reverts commit b83aab9bb3.
2024-04-11 12:51:57 +00:00
Nicolas Patry b83aab9bb3 Easier defaults for models stemmed from configs. 2024-04-11 12:48:39 +00:00
Nicolas Patry 4634b00c2a
Adding Llava-Next (Llava 1.6) with full support. (#1709)
# 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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2024-04-09 21:32:00 +02:00
OlivierDehaene 4ee0a0c401
v1.4.5 (#1686) 2024-03-29 19:17:24 +01:00
OlivierDehaene 6c4496a1a3
v1.4.4 (#1668) 2024-03-22 18:44:05 +01:00
Nicolas Patry f171bdc823
Inline images for multimodal models. (#1666) 2024-03-22 17:14:54 +01:00
drbh de6cb15fa5
fix: improve tool type, bump pydantic and outlines (#1650)
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
2024-03-21 12:45:56 -04:00
drbh dfbd9a39a2
feat: bump minijina and add test for core templates (#1626)
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
2024-03-20 09:13:46 -04:00
OlivierDehaene e6bb3ff81f
v1.4.3 (#1609) 2024-02-28 16:12:14 +01:00
OlivierDehaene 9c1cb81cd8
v1.4.2 (#1585) 2024-02-21 14:50:57 +01:00
OlivierDehaene fa8a8e05af
fix(router): fix openapi and add jsonschema validation (#1578) 2024-02-21 11:05:32 +01:00
OlivierDehaene 4139054b82
v1.4.1 (#1568) 2024-02-16 17:50:57 +01:00
OlivierDehaene 09b7c26bbd
feat(server): add frequency penalty (#1541) 2024-02-08 18:41:25 +01:00
OlivierDehaene c2d4a3b5c7
v1.4.0 (#1494) 2024-01-26 19:04:57 +01:00
drbh 0eabc83541
feat: supports openai chat completions API (#1427)
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
2024-01-16 11:07:41 +01:00
OlivierDehaene fbeb1c4475
fix: follow base model for tokenizer in router (#1424)
Close #1422
2024-01-10 16:35:54 +01:00
OlivierDehaene 630800eed3 v1.3.4 2023-12-22 15:46:04 +01:00
OlivierDehaene f3aea78fb6 v1.3.3 2023-12-15 01:20:42 +01:00
OlivierDehaene 88aae2595d v1.3.2 2023-12-12 18:10:22 +01:00
OlivierDehaene ec6d4592d5 v1.3.1 2023-12-11 16:46:44 +01:00
OlivierDehaene d0841cc8eb v1.3.0 2023-12-11 14:55:03 +01:00
Nicolas Patry 9ecfa16b12
Speculative (#1308) 2023-12-11 12:46:30 +01:00
OlivierDehaene ccd5725a0c v1.2.0 2023-11-30 15:18:15 +01:00
OlivierDehaene f9910d13e2
feat: remove flume (#1184) 2023-10-23 15:51:12 +02:00
Nicolas Patry 95a4bb696a
Support eetq weight only quantization (#1068)
# What does this PR do?

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---------

Co-authored-by: zhaosida <zhaosida@corp.netease.com>
2023-09-27 11:42:57 +02:00
Nicolas Patry a049864270
Preping 1.1.0 (#1066)
# What does this PR do?

Upgrade all relevant versions and dependencies.

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2023-09-27 10:40:18 +02:00
Nicolas Patry 05dd14fdb9
Fix `tokenizers==0.13.4` . (#838)
# What does this PR do?

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2023-08-14 19:26:19 +02:00
Nicolas Patry 09eca64227
Version 1.0.1 (#836)
# What does this PR do?

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2023-08-14 11:23:11 +02:00
OlivierDehaene 3ef5ffbc64
v1.0.0 (#727) 2023-07-28 17:43:46 +02:00
OlivierDehaene 9f18f4c006
v0.9.4 (#713) 2023-07-27 19:25:15 +02:00
OlivierDehaene cf83f9b66f
v0.9.3 (#634) 2023-07-18 18:11:20 +02:00
OlivierDehaene c58a0c185b
v0.9.2 (#616) 2023-07-14 16:31:48 +02:00
OlivierDehaene b7327205a6
feat(launcher): add arg validation and drop subprocess (#595) 2023-07-13 14:22:37 +02:00
OlivierDehaene 31b36cca21
v0.9.1 (#558) 2023-07-06 16:05:42 +02:00
OlivierDehaene e28a809004
v0.9.0 (#525) 2023-07-01 19:25:41 +02:00
OlivierDehaene f59fb8b630
feat(router): add ngrok integration (#453) 2023-06-16 16:25:11 +02:00
OlivierDehaene e7248fe90e v0.8.2 2023-06-01 19:49:13 +02:00
OlivierDehaene db2ebe3947 v0.8.1 2023-05-31 12:08:40 +02:00
OlivierDehaene 081b926584 v0.8.0 2023-05-30 18:39:35 +02:00
OlivierDehaene 951930fbff
feat(benchmarker): add summary tables (#368) 2023-05-25 13:38:36 +02:00
OlivierDehaene d31562f300
v0.7.0 (#353) 2023-05-23 21:20:49 +02:00
OlivierDehaene e250282213
feat(docker): add benchmarking tool to docker image (#298) 2023-05-09 13:19:31 +02:00
Nicolas Patry 411b0d4e1f
chore(github): add templates (#264) 2023-05-02 15:43:19 +02:00