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Ludovic LEROUX
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Merge remote-tracking branch 'upstream/master' into golgeek/chat_template
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.github/workflows/image_build.yml

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run: |
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docker pull localai/localai:${{ steps.meta.outputs.version }}
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docker tag localai/localai:${{ steps.meta.outputs.version }} localai/localai:${{ inputs.latest-image }}
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docker push localai/localai:${{ inputs.latest-image }}
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docker pull quay.io/go-skynet/local-ai:${{ steps.meta.outputs.version }}
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docker tag quay.io/go-skynet/local-ai:${{ steps.meta.outputs.version }} quay.io/go-skynet/local-ai:${{ inputs.latest-image }}
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docker push quay.io/go-skynet/local-ai:${{ inputs.latest-image }}
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run: |
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docker pull localai/localai:${{ steps.meta_aio_dockerhub.outputs.version }}
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docker tag localai/localai:${{ steps.meta_aio_dockerhub.outputs.version }} localai/localai:${{ inputs.latest-image-aio }}
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docker push localai/localai:${{ inputs.latest-image-aio }}
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docker pull quay.io/go-skynet/local-ai:${{ steps.meta_aio.outputs.version }}
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docker tag quay.io/go-skynet/local-ai:${{ steps.meta_aio.outputs.version }} quay.io/go-skynet/local-ai:${{ inputs.latest-image-aio }}
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docker push quay.io/go-skynet/local-ai:${{ inputs.latest-image-aio }}

Makefile

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# llama.cpp versions
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GOLLAMA_STABLE_VERSION?=2b57a8ae43e4699d3dc5d1496a1ccd42922993be
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CPPLLAMA_VERSION?=cc4a95426d17417d3c83f12bdb514fbe8abe2a88
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CPPLLAMA_VERSION?=1b67731e184e27a465b8c5476061294a4af668ea
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# gpt4all version
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GPT4ALL_REPO?=https://github.com/nomic-ai/gpt4all
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RWKV_VERSION?=661e7ae26d442f5cfebd2a0881b44e8c55949ec6
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# whisper.cpp version
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WHISPER_CPP_VERSION?=13c22321d1ac758ce68a429c23104e234b440769
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WHISPER_CPP_VERSION?=8f253ef3af1c62c04316ba4afa7145fc4d701a8c
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# bert.cpp version
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BERT_VERSION?=6abe312cded14042f6b7c3cd8edf082713334a4d

backend/python/autogptq/autogptq.py

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self.model_name = "Qwen-VL-Chat"
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model = AutoModelForCausalLM.from_pretrained(model_path,
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trust_remote_code=request.TrustRemoteCode,
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use_triton=request.UseTriton,
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device_map="auto").eval()
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else:
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model = AutoGPTQForCausalLM.from_quantized(model_path,

backend/python/common-env/transformers/transformers-nvidia.yml

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- sudachipy
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- sudachidict_core
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- vocos
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- vllm==0.3.2
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- vllm>=0.4.0
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- transformers>=4.38.2 # Updated Version
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- transformers_stream_generator==0.0.5
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- xformers==0.0.23.post1

backend/python/common-env/transformers/transformers-rocm.yml

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- sudachipy
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- sudachidict_core
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- vocos
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- vllm==0.3.2
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- vllm>=0.4.0
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- transformers>=4.38.2 # Updated Version
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- transformers_stream_generator==0.0.5
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- xformers==0.0.23.post1

backend/python/common-env/transformers/transformers.yml

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- sudachipy
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- sudachidict_core
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- vocos
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- vllm==0.3.2
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- vllm>=0.4.0
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- transformers>=4.38.2 # Updated Version
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- transformers_stream_generator==0.0.5
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- xformers==0.0.23.post1

docs/content/docs/features/gpt-vision.md

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"messages": [{"role": "user", "content": [{"type":"text", "text": "What is in the image?"}, {"type": "image_url", "image_url": {"url": "https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg" }}], "temperature": 0.9}]}'
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```
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Grammars and function tools can be used as well in conjunction with vision APIs:
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```bash
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curl http://localhost:8080/v1/chat/completions -H "Content-Type: application/json" -d '{
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"model": "llava", "grammar": "root ::= (\"yes\" | \"no\")",
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"messages": [{"role": "user", "content": [{"type":"text", "text": "Is there some grass in the image?"}, {"type": "image_url", "image_url": {"url": "https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg" }}], "temperature": 0.9}]}'
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```
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### Setup
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All-in-One images have already shipped the llava model as `gpt-4-vision-preview`, so no setup is needed in this case.
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To setup the LLaVa models, follow the full example in the [configuration examples](https://github.com/mudler/LocalAI/blob/master/examples/configurations/README.md#llava).
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docs/content/docs/features/openai-functions.md

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}'
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```
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Grammars and function tools can be used as well in conjunction with vision APIs:
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```bash
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curl http://localhost:8080/v1/chat/completions -H "Content-Type: application/json" -d '{
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"model": "llava", "grammar": "root ::= (\"yes\" | \"no\")",
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"messages": [{"role": "user", "content": [{"type":"text", "text": "Is there some grass in the image?"}, {"type": "image_url", "image_url": {"url": "https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg" }}], "temperature": 0.9}]}'
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```
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## 💡 Examples
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A full e2e example with `docker-compose` is available [here](https://github.com/go-skynet/LocalAI/tree/master/examples/functions).

docs/data/version.json

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{
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"version": "v2.11.0"
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"version": "v2.12.1"
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}

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