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feat: add ci for modules
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‎.github/workflows/upload-pypi-dev.yml‎

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@@ -74,14 +74,23 @@ jobs:
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run: |
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echo "VERSION=$(poetry version --short)" >> $GITHUB_ENV
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- name: Build and tag Docker image
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# Build and tag Docker images with both :latest and :[NEW_VERSION]
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- name: Proxy Build and tag Docker images
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working-directory: ./deploy
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run: |
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docker build \
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--build-arg LLMSTUDIO_VERSION=${{ env.VERSION }} \
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-t tensoropsai/llmstudio:${{ env.VERSION }} \
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.
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make version=${{ env.VERSION }} build-proxy
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- name: Push Docker image to Docker Hub
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# Build and tag Docker images with both :latest and :[NEW_VERSION]
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- name: Tracker Build and tag Docker images
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working-directory: ./deploy
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run: |
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docker push tensoropsai/llmstudio:${{ env.VERSION }}
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make version=${{ env.VERSION }} build-tracker
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# Push both Docker images to Docker Hub
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- name: Push Proxy Docker images to Docker Hub
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run: |
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docker push tensoropsai/llmstudio-proxy:${{ env.VERSION }}
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# Push both Docker images to Docker Hub
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- name: Push Tracker Docker images to Docker Hub
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run: |
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docker push tensoropsai/llmstudio-tracker:${{ env.VERSION }}

‎.github/workflows/upload-pypi.yml‎

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@@ -72,17 +72,24 @@ jobs:
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password: ${{ secrets.DOCKER_PASSWORD }}
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# Build and tag Docker images with both :latest and :[NEW_VERSION]
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- name: Build and tag Docker images
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- name: Proxy Build and tag Docker images
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working-directory: ./deploy
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run: |
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docker build \
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--build-arg LLMSTUDIO_VERSION=${{ env.VERSION }} \
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-t tensoropsai/llmstudio:latest \
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-t tensoropsai/llmstudio:${{ env.VERSION }} \
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.
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make version=${{ env.VERSION }} build-proxy
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# Build and tag Docker images with both :latest and :[NEW_VERSION]
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- name: Tracker Build and tag Docker images
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working-directory: ./deploy
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run: |
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make version=${{ env.VERSION }} build-tracker
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# Push both Docker images to Docker Hub
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- name: Push Proxy Docker images to Docker Hub
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run: |
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docker push tensoropsai/llmstudio-proxy:${{ env.VERSION }}
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docker push tensoropsai/llmstudio-proxy:latest
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# Push both Docker images to Docker Hub
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- name: Push Docker images to Docker Hub
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- name: Push Tracker Docker images to Docker Hub
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run: |
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docker push tensoropsai/llmstudio:${{ env.VERSION }}
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docker push tensoropsai/llmstudio:latest
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docker push tensoropsai/llmstudio-tracker:${{ env.VERSION }}
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docker push tensoropsai/llmstudio-tracker:latest

‎README.md‎

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@@ -26,30 +26,33 @@ Don't forget to check out [https://docs.llmstudio.ai](docs) page.
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Install the latest version of **LLMstudio** using `pip`. We suggest that you create and activate a new environment using `conda`
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For full version:
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```bash
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pip install llmstudio
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pip install 'llmstudio[proxy,tracker]'
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```
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Install `bun` if you want to use the UI
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For lightweight (core) version:
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```bash
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curl -fsSL https://bun.sh/install | bash
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pip install llmstudio
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```
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Create a `.env` file at the same path you'll run **LLMstudio**
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```bash
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OPENAI_API_KEY="sk-api_key"
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ANTHROPIC_API_KEY="sk-api_key"
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VERTEXAI_KEY="sk-api-key"
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```
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Now you should be able to run **LLMstudio** using the following command.
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```bash
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llmstudio server --ui
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llmstudio server --proxy --tacker
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```
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When the `--ui` flag is set, you'll be able to access the UI at [http://localhost:3000](http://localhost:3000)
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When the `--proxy` flag is set, you'll be able to access the [Swagger at http://0.0.0.0:50001/docs (default port)](http://0.0.0.0:50001/docs)
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When the `--tracker` flag is set, you'll be able to access the [Swagger at http://0.0.0.0:50002/docs (default port)](http://0.0.0.0:50002/docs)
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## 📖 Documentation
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‎deploy/Makefile‎

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build-proxy:
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docker build --build-arg LLMSTUDIO_VERSION=$(version) \
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-t tensoropsai/llmstudio-proxy:latest \
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-t tensoropsai/llmstudio-proxy:$(version) \
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-f proxy.Dockerfile \
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.
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build-tracker:
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docker build --build-arg LLMSTUDIO_VERSION=$(version) \
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-t tensoropsai/llmstudio-tracker:latest \
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-t tensoropsai/llmstudio-tracker:$(version) \
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-f tracker.Dockerfile \
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.
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build: build-tracker build-proxy
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run:
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docker compose -f docker-compose.yml up

‎deploy/docker-compose.yml‎

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version: "3.8"
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services:
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llmstudio-proxy:
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image: tensoropsai/llmstudio-proxy
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restart: always
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env_file:
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- .env
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ports:
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- 8001:50001
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llmstudio-tracking:
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image: tensoropsai/llmstudio-tracker
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restart: always
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env_file:
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- .env
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ports:
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- 8002:50002

‎deploy/proxy.Dockerfile‎

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FROM python:3.11-slim
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ENV PYTHONUNBUFFERED=1
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# Install tools
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RUN apt-get clean && apt-get update
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# Install llmstudio
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ARG LLMSTUDIO_VERSION
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RUN pip install 'llmstudio[proxy]'==${LLMSTUDIO_VERSION}
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CMD ["llmstudio", "server", "--proxy"]

‎deploy/tracker.Dockerfile‎

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FROM python:3.11-slim
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ENV PYTHONUNBUFFERED=1
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# Install tools
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RUN apt-get clean && apt-get update
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# Install llmstudio
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ARG LLMSTUDIO_VERSION
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RUN pip install 'llmstudio[tracker]'==${LLMSTUDIO_VERSION}
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RUN pip install psycopg2-binary
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CMD ["llmstudio", "server", "--tracker"]

‎libs/llmstudio/README.md‎

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Original file line numberDiff line numberDiff line change
@@ -26,30 +26,33 @@ Don't forget to check out [https://docs.llmstudio.ai](docs) page.
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Install the latest version of **LLMstudio** using `pip`. We suggest that you create and activate a new environment using `conda`
2828

29+
For full version:
2930
```bash
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pip install llmstudio
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pip install 'llmstudio[proxy,tracker]'
3132
```
3233

33-
Install `bun` if you want to use the UI
34-
34+
For lightweight (core) version:
3535
```bash
36-
curl -fsSL https://bun.sh/install | bash
36+
pip install llmstudio
3737
```
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3939
Create a `.env` file at the same path you'll run **LLMstudio**
4040

4141
```bash
4242
OPENAI_API_KEY="sk-api_key"
4343
ANTHROPIC_API_KEY="sk-api_key"
44+
VERTEXAI_KEY="sk-api-key"
4445
```
4546

4647
Now you should be able to run **LLMstudio** using the following command.
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4849
```bash
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llmstudio server --ui
50+
llmstudio server --proxy --tacker
5051
```
5152

52-
When the `--ui` flag is set, you'll be able to access the UI at [http://localhost:3000](http://localhost:3000)
53+
When the `--proxy` flag is set, you'll be able to access the [Swagger at http://0.0.0.0:50001/docs (default port)](http://0.0.0.0:50001/docs)
54+
55+
When the `--tracker` flag is set, you'll be able to access the [Swagger at http://0.0.0.0:50002/docs (default port)](http://0.0.0.0:50002/docs)
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## 📖 Documentation
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‎libs/proxy/README.md‎

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Original file line numberDiff line numberDiff line change
@@ -43,13 +43,13 @@ OPENAI_API_KEY="sk-api_key"
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ANTHROPIC_API_KEY="sk-api_key"
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```
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Now you should be able to run **LLMstudio** using the following command.
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Now you should be able to run **LLMstudio Proxy** using the following command.
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4848
```bash
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llmstudio server --ui
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llmstudio server --proxy
5050
```
5151

52-
When the `--ui` flag is set, you'll be able to access the UI at [http://localhost:3000](http://localhost:3000)
52+
When the `--proxy` flag is set, you'll be able to access the [Swagger at http://0.0.0.0:50001/docs (default port)](http://0.0.0.0:50001/docs)
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## 📖 Documentation
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‎libs/proxy/llmstudio_proxy/config.py‎

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defaults = {
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"LLMSTUDIO_ENGINE_HOST": "localhost",
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"LLMSTUDIO_ENGINE_HOST": "0.0.0.0",
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"LLMSTUDIO_ENGINE_PORT": str(assign_port(50001)),
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}
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