CI for each module

.github/workflows/upload-pypi-dev.yml

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

.github/workflows/upload-pypi.yml

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

README.md

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

deploy/Makefile

@@ -0,0 +1,18 @@
+build-proxy:
+	docker build --build-arg LLMSTUDIO_VERSION=$(version) \
+	-t tensoropsai/llmstudio-proxy:latest \
+	-t tensoropsai/llmstudio-proxy:$(version) \
+	-f proxy.Dockerfile \
+	.
+
+build-tracker:
+	docker build --build-arg LLMSTUDIO_VERSION=$(version) \
+	-t tensoropsai/llmstudio-tracker:latest \
+	-t tensoropsai/llmstudio-tracker:$(version) \
+	-f tracker.Dockerfile \
+	.
+
+build: build-tracker build-proxy
+
+run:
+	docker compose -f docker-compose.yml up

deploy/docker-compose.yml

@@ -0,0 +1,17 @@
+version: "3.8"
+
+services:
+  llmstudio-proxy:
+    image: tensoropsai/llmstudio-proxy
+    restart: always
+    env_file:
+      - .env
+    ports:
+      - 8001:50001
+  llmstudio-tracking:
+    image: tensoropsai/llmstudio-tracker
+    restart: always
+    env_file:
+      - .env
+    ports:
+      - 8002:50002

deploy/proxy.Dockerfile

@@ -0,0 +1,11 @@
+FROM python:3.11-slim
+ENV PYTHONUNBUFFERED=1
+
+# Install tools
+RUN apt-get clean && apt-get update
+
+# Install llmstudio
+ARG LLMSTUDIO_VERSION
+RUN pip install 'llmstudio[proxy]'==${LLMSTUDIO_VERSION}
+
+CMD ["llmstudio", "server", "--proxy"]

deploy/tracker.Dockerfile

@@ -0,0 +1,12 @@
+FROM python:3.11-slim
+ENV PYTHONUNBUFFERED=1
+
+# Install tools
+RUN apt-get clean && apt-get update
+
+# Install llmstudio
+ARG LLMSTUDIO_VERSION
+RUN pip install 'llmstudio[tracker]'==${LLMSTUDIO_VERSION}
+RUN pip install psycopg2-binary
+
+CMD ["llmstudio", "server", "--tracker"]

libs/llmstudio/README.md

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

libs/llmstudio/pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "llmstudio"
-version = "1.0.0"
+version = "1.0.1"
 description = "Prompt Perfection at Your Fingertips"
 authors = ["Cláudio Lemos <[email protected]>"]
 license = "MIT"
@@ -20,8 +20,8 @@ python-dotenv = "^0"
 langchain = "^0"
 langchain-experimental = "^0"
 llmstudio-core = "1.0.0"
-llmstudio-tracker = { version = "1.0.0", optional = true }
-llmstudio-proxy = { version = "1.0.0", optional = true }
+llmstudio-tracker = { version = "1.0.1", optional = true }
+llmstudio-proxy = { version = "1.0.1", optional = true }
 
 [tool.poetry.extras]
 proxy = ["llmstudio-proxy"]

libs/proxy/README.md

@@ -43,13 +43,13 @@ OPENAI_API_KEY="sk-api_key"
 ANTHROPIC_API_KEY="sk-api_key"
 ```
 
-Now you should be able to run **LLMstudio** using the following command.
+Now you should be able to run **LLMstudio Proxy** using the following command.
 
 ```bash
-llmstudio server --ui
+llmstudio server --proxy
 ```
 
-When the `--ui` flag is set, you'll be able to access the UI at [http://localhost:3000](http://localhost:3000)
+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)
 
 ## 📖 Documentation
 

libs/proxy/llmstudio_proxy/config.py

@@ -21,7 +21,7 @@ def assign_port(default_port=None):
 
 
 defaults = {
-    "LLMSTUDIO_ENGINE_HOST": "localhost",
+    "LLMSTUDIO_ENGINE_HOST": "0.0.0.0",
     "LLMSTUDIO_ENGINE_PORT": str(assign_port(50001)),
 }
 

libs/proxy/pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "llmstudio-proxy"
-version = "1.0.0"
+version = "1.0.1"
 description = ""
 authors = ["Diogo Goncalves <[email protected]>"]
 readme = "README.md"

libs/tracker/README.md

@@ -27,29 +27,22 @@ Don't forget to check out [https://docs.llmstudio.ai](docs) page.
 Install the latest version of **LLMstudio** using `pip`. We suggest that you create and activate a new environment using `conda`
 
 ```bash
-pip install llmstudio
-```
-
-Install `bun` if you want to use the UI
-
-```bash
-curl -fsSL https://bun.sh/install | bash
+pip install 'llmstudio[tracker]'
 ```
 
 Create a `.env` file at the same path you'll run **LLMstudio**
 
 ```bash
 OPENAI_API_KEY="sk-api_key"
-ANTHROPIC_API_KEY="sk-api_key"
 ```
 
-Now you should be able to run **LLMstudio** using the following command.
+Now you should be able to run **LLMstudio Tracker** using the following command.
 
 ```bash
-llmstudio server --ui
+llmstudio server --tacker
 ```
 
-When the `--ui` flag is set, you'll be able to access the UI at [http://localhost:3000](http://localhost:3000)
+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)
 
 ## 📖 Documentation
 

libs/tracker/llmstudio_tracker/config.py

@@ -21,7 +21,7 @@ def assign_port(default_port=None):
 
 
 defaults = {
-    "LLMSTUDIO_TRACKING_HOST": "localhost",
+    "LLMSTUDIO_TRACKING_HOST": "0.0.0.0",
     "LLMSTUDIO_TRACKING_PORT": str(assign_port(50002)),
     "LLMSTUDIO_TRACKING_URI": "sqlite:///./llmstudio_mgmt.db",
 }

libs/tracker/pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "llmstudio-tracker"
-version = "1.0.0"
+version = "1.0.1"
 description = ""
 authors = ["Diogo Goncalves <[email protected]>"]
 readme = "README.md"