feat(aio): add intel profile (#1901)

* feat(aio): add intel profile

* docs: clarify AIO images features

README.md

@@ -38,6 +38,10 @@
 </a>
 </p>
 
+> :bulb: Get help - [❓FAQ](https://localai.io/faq/) [💭Discussions](https://github.com/go-skynet/LocalAI/discussions) [:speech_balloon: Discord](https://discord.gg/uJAeKSAGDy) [:book: Documentation website](https://localai.io/)
+>
+> [💻 Quickstart](https://localai.io/basics/getting_started/) [📣 News](https://localai.io/basics/news/) [ 🛫 Examples ](https://github.com/go-skynet/LocalAI/tree/master/examples/) [ 🖼️ Models ](https://localai.io/models/) [ 🚀 Roadmap ](https://github.com/mudler/LocalAI/issues?q=is%3Aissue+is%3Aopen+label%3Aroadmap)
+
 [![tests](https://github.com/go-skynet/LocalAI/actions/workflows/test.yml/badge.svg)](https://github.com/go-skynet/LocalAI/actions/workflows/test.yml)[![Build and Release](https://github.com/go-skynet/LocalAI/actions/workflows/release.yaml/badge.svg)](https://github.com/go-skynet/LocalAI/actions/workflows/release.yaml)[![build container images](https://github.com/go-skynet/LocalAI/actions/workflows/image.yml/badge.svg)](https://github.com/go-skynet/LocalAI/actions/workflows/image.yml)[![Bump dependencies](https://github.com/go-skynet/LocalAI/actions/workflows/bump_deps.yaml/badge.svg)](https://github.com/go-skynet/LocalAI/actions/workflows/bump_deps.yaml)[![Artifact Hub](https://img.shields.io/endpoint?url=https://artifacthub.io/badge/repository/localai)](https://artifacthub.io/packages/search?repo=localai)
 
 **LocalAI** is the free, Open Source OpenAI alternative. LocalAI act as a drop-in replacement REST API that’s compatible with OpenAI (Elevenlabs, Anthropic... ) API specifications for local AI inferencing. It allows you to run LLMs, generate images, audio (and not only) locally or on-prem with consumer grade hardware, supporting multiple model families. Does not require GPU.

aio/cpu/embeddings.yaml

@@ -1,11 +1,5 @@
-backend: bert-embeddings
-embeddings: true
-f16: true
-
-gpu_layers: 90
-mmap: true
 name: text-embedding-ada-002
-
+backend: bert-embeddings
 parameters:
   model: huggingface://mudler/all-MiniLM-L6-v2/ggml-model-q4_0.bin
 

aio/cpu/image-gen.yaml

@@ -50,4 +50,13 @@ download_files:
   uri: "https://github.com/EdVince/Stable-Diffusion-NCNN/releases/download/naifu/UNetModel-MHA-fp16.bin"
 - filename: "stablediffusion_assets/vocab.txt"
   sha256: "e30e57b6f1e47616982ef898d8922be24e535b4fa3d0110477b3a6f02ebbae7d"
-  uri: "https://raw.githubusercontent.com/EdVince/Stable-Diffusion-NCNN/main/x86/linux/assets/vocab.txt"
+  uri: "https://raw.githubusercontent.com/EdVince/Stable-Diffusion-NCNN/main/x86/linux/assets/vocab.txt"
+
+usage: |
+        curl http://localhost:8080/v1/images/generations \
+          -H "Content-Type: application/json" \
+          -d '{
+            "prompt": "<positive prompt>|<negative prompt>",
+            "step": 25,
+            "size": "512x512"
+          }'

aio/cpu/vision.yaml

@@ -1,8 +1,6 @@
 backend: llama-cpp
 context_size: 4096
 f16: true
-
-gpu_layers: 90
 mmap: true
 name: gpt-4-vision-preview
 
@@ -14,13 +12,6 @@ roles:
 mmproj: bakllava-mmproj.gguf
 parameters:
   model: bakllava.gguf
-  temperature: 0.2
-  top_k: 40
-  top_p: 0.95
-  seed: -1
-mirostat: 2
-mirostat_eta: 1.0
-mirostat_tau: 1.0
 
 template:
   chat: |

aio/entrypoint.sh

@@ -30,6 +30,7 @@ function detect_gpu() {
                 echo "Intel GPU detected"
                 if [ -d /opt/intel ]; then
                     GPU_ACCELERATION=true
+                    GPU_VENDOR=intel
                 else
                     echo "Intel GPU detected, but Intel GPU drivers are not installed. GPU acceleration will not be available."
                 fi
@@ -75,7 +76,8 @@ function detect_gpu_size() {
             echo "Unable to determine NVIDIA GPU memory size. Falling back to CPU."
             GPU_SIZE=gpu-8g
         fi
-
+    elif [ "$GPU_ACCELERATION" = true ] && [ "$GPU_VENDOR" = "intel" ]; then
+        GPU_SIZE=intel
     # Default to a generic GPU size until we implement GPU size detection for non NVIDIA GPUs
     elif [ "$GPU_ACCELERATION" = true ]; then
         echo "Non-NVIDIA GPU detected. Specific GPU memory size detection is not implemented."

aio/gpu-8g/embeddings.yaml

@@ -1,6 +1,5 @@
 name: text-embedding-ada-002
 backend: sentencetransformers
-embeddings: true
 parameters:
   model: all-MiniLM-L6-v2
 

aio/gpu-8g/image-gen.yaml

@@ -20,7 +20,6 @@ usage: |
           -H "Content-Type: application/json" \
           -d '{
             "prompt": "<positive prompt>|<negative prompt>",
-            "model": "dreamshaper",
             "step": 25,
             "size": "512x512"
           }'

aio/gpu-8g/vision.yaml

@@ -1,8 +1,6 @@
 backend: llama-cpp
 context_size: 4096
 f16: true
-
-gpu_layers: 90
 mmap: true
 name: gpt-4-vision-preview
 

aio/intel/embeddings.yaml

@@ -0,0 +1,12 @@
+name: text-embedding-ada-002
+backend: sentencetransformers
+parameters:
+  model: all-MiniLM-L6-v2
+
+usage: |
+    You can test this model with curl like this:
+
+    curl http://localhost:8080/embeddings -X POST -H "Content-Type: application/json" -d '{
+      "input": "Your text string goes here",
+      "model": "text-embedding-ada-002"
+    }'

aio/intel/image-gen.yaml

@@ -0,0 +1,20 @@
+name: stablediffusion
+parameters:
+  model: runwayml/stable-diffusion-v1-5
+backend: diffusers
+step: 25
+f16: true
+diffusers:
+  pipeline_type: StableDiffusionPipeline
+  cuda: true
+  enable_parameters: "negative_prompt,num_inference_steps"
+  scheduler_type: "k_dpmpp_2m"
+
+usage: |
+        curl http://localhost:8080/v1/images/generations \
+          -H "Content-Type: application/json" \
+          -d '{
+            "prompt": "<positive prompt>|<negative prompt>",
+            "step": 25,
+            "size": "512x512"
+          }'

aio/intel/speech-to-text.yaml

@@ -0,0 +1,18 @@
+name: whisper-1
+backend: whisper
+parameters:
+  model: ggml-whisper-base.bin
+
+usage: |
+    ## example audio file
+    wget --quiet --show-progress -O gb1.ogg https://upload.wikimedia.org/wikipedia/commons/1/1f/George_W_Bush_Columbia_FINAL.ogg
+
+    ## Send the example audio file to the transcriptions endpoint
+    curl http://localhost:8080/v1/audio/transcriptions \
+         -H "Content-Type: multipart/form-data" \
+         -F file="@$PWD/gb1.ogg" -F model="whisper-1"
+
+download_files:
+- filename: "ggml-whisper-base.bin"
+  sha256: "60ed5bc3dd14eea856493d334349b405782ddcaf0028d4b5df4088345fba2efe"
+  uri: "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-base.bin"

aio/intel/text-to-speech.yaml

@@ -0,0 +1,15 @@
+name: tts-1
+download_files:
+  - filename: voice-en-us-amy-low.tar.gz
+    uri: https://github.com/rhasspy/piper/releases/download/v0.0.2/voice-en-us-amy-low.tar.gz
+
+parameters:
+  model: en-us-amy-low.onnx
+
+usage: |
+    To test if this model works as expected, you can use the following curl command:
+
+    curl http://localhost:8080/tts -H "Content-Type: application/json" -d '{
+      "model":"tts-1",
+      "input": "Hi, this is a test."
+    }'

aio/intel/text-to-text.yaml

@@ -0,0 +1,51 @@
+name: gpt-4
+mmap: false
+f16: false
+parameters:
+  model: huggingface://NousResearch/Hermes-2-Pro-Mistral-7B-GGUF/Hermes-2-Pro-Mistral-7B.Q6_K.gguf
+
+roles:
+  assistant_function_call: assistant
+  function: tool
+template:
+  chat_message: |
+    <|im_start|>{{if eq .RoleName "assistant"}}assistant{{else if eq .RoleName "system"}}system{{else if eq .RoleName "function"}}{{.Role}}{{else if eq .RoleName "user"}}user{{end}}
+    {{ if eq .RoleName "assistant_function_call" }}<tool_call>{{end}}
+    {{ if eq .RoleName "function" }}<tool_result>{{end}}
+    {{if .Content}}{{.Content}}{{end}}
+    {{if .FunctionCall}}{{toJson .FunctionCall}}{{end}}
+    {{ if eq .RoleName "assistant_function_call" }}</tool_call>{{end}}
+    {{ if eq .RoleName "function" }}</tool_result>{{end}}
+    <|im_end|>
+  # https://huggingface.co/NousResearch/Hermes-2-Pro-Mistral-7B-GGUF#prompt-format-for-function-calling
+  function: |
+    <|im_start|>system
+    You are a function calling AI model. You are provided with function signatures within <tools></tools> XML tags. You may call one or more functions to assist with the user query. Don't make assumptions about what values to plug into functions. Here are the available tools: 
+    <tools>
+    {{range .Functions}}
+    {'type': 'function', 'function': {'name': '{{.Name}}', 'description': '{{.Description}}', 'parameters': {{toJson .Parameters}} }}
+    {{end}}
+    </tools> 
+    Use the following pydantic model json schema for each tool call you will make: 
+    {'title': 'FunctionCall', 'type': 'object', 'properties': {'arguments': {'title': 'Arguments', 'type': 'object'}, 'name': {'title': 'Name', 'type': 'string'}}, 'required': ['arguments', 'name']} 
+    For each function call return a json object with function name and arguments within <tool_call></tool_call> XML tags as follows:
+    <tool_call>
+    {'arguments': <args-dict>, 'name': <function-name>}
+    </tool_call><|im_end|>
+    {{.Input}}
+    <|im_start|>assistant
+    <tool_call>
+  chat: |
+    {{.Input}}
+    <|im_start|>assistant
+  completion: |
+    {{.Input}}
+context_size: 4096
+stopwords:
+- <|im_end|>
+- <dummy32000>
+usage: |
+      curl http://localhost:8080/v1/chat/completions -H "Content-Type: application/json" -d '{
+          "model": "gpt-4",
+          "messages": [{"role": "user", "content": "How are you doing?", "temperature": 0.1}]
+      }'

aio/intel/vision.yaml

@@ -0,0 +1,35 @@
+backend: llama-cpp
+context_size: 4096
+mmap: false
+f16: false
+name: gpt-4-vision-preview
+
+roles:
+  user: "USER:"
+  assistant: "ASSISTANT:"
+  system: "SYSTEM:"
+
+mmproj: llava-v1.6-7b-mmproj-f16.gguf
+parameters:
+  model: llava-v1.6-mistral-7b.Q5_K_M.gguf
+  temperature: 0.2
+  top_k: 40
+  top_p: 0.95
+  seed: -1
+
+template:
+  chat: |
+    A chat between a curious human and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the human's questions.
+    {{.Input}}
+    ASSISTANT:
+
+download_files:
+- filename: llava-v1.6-mistral-7b.Q5_K_M.gguf
+  uri: huggingface://cjpais/llava-1.6-mistral-7b-gguf/llava-v1.6-mistral-7b.Q5_K_M.gguf
+- filename: llava-v1.6-7b-mmproj-f16.gguf
+  uri: huggingface://cjpais/llava-1.6-mistral-7b-gguf/mmproj-model-f16.gguf
+
+usage: |
+    curl http://localhost:8080/v1/chat/completions -H "Content-Type: application/json" -d '{
+        "model": "gpt-4-vision-preview",
+        "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}]}'

docs/content/docs/overview.md

@@ -49,7 +49,6 @@ icon = "info"
 </a>
 </p>
 
-
 > 💡 Get help - [❓FAQ](https://localai.io/faq/) [💭Discussions](https://github.com/go-skynet/LocalAI/discussions) [💭Discord](https://discord.gg/uJAeKSAGDy)
 >
 > [💻 Quickstart](https://localai.io/basics/getting_started/) [📣 News](https://localai.io/basics/news/) [ 🛫 Examples ](https://github.com/go-skynet/LocalAI/tree/master/examples/) [ 🖼️ Models ](https://localai.io/models/) [ 🚀 Roadmap ](https://github.com/mudler/LocalAI/issues?q=is%3Aissue+is%3Aopen+label%3Aroadmap)

docs/content/docs/reference/aio-images.md

@@ -7,6 +7,15 @@ weight = 26
 
 All-In-One images are images that come pre-configured with a set of models and backends to fully leverage almost all the LocalAI featureset. These images are available for both CPU and GPU environments. The AIO images are designed to be easy to use and requires no configuration. Models configuration can be found [here](https://github.com/mudler/LocalAI/tree/master/aio) separated by size.
 
+What you can find configured out of the box:
+
+- Image generation
+- Text generation
+- Text to audio
+- Audio transcription
+- Embeddings
+- GPT Vision
+
 
 | Description | Quay | Docker Hub                                   |
 | --- | --- |-----------------------------------------------|