Merge branch 'main' into patch-1

.gitignore

@@ -53,11 +53,11 @@ node_modules
 # Environments
 env
 env3
-.env
+.env*
 .env*.local
-.venv
-env/
-venv/
+.venv*
+env*/
+venv*/
 ENV/
 env.bak/
 venv.bak/

.pre-commit-config.yaml

@@ -3,43 +3,37 @@ repos:
     rev: v4.4.0
     hooks:
       - id: trailing-whitespace
-        files: llmstudio/
-        exclude: ^llmstudio/ui/
+        files: libs/
       - id: end-of-file-fixer
-        files: llmstudio/
-        exclude: ^llmstudio/ui/
+        files: libs/
       - id: check-yaml
-        files: llmstudio/
-        exclude: ^llmstudio/ui/
+        files: libs/
       - id: check-added-large-files
-        files: llmstudio/
-        exclude: ^llmstudio/ui/
+        files: libs/
 
   - repo: https://github.com/psf/black
     rev: 22.12.0
     hooks:
       - id: black
-        files: llmstudio/
-        exclude: ^llmstudio/ui/
+        files: libs/
 
   - repo: https://github.com/pycqa/isort
     rev: 5.12.0
     hooks:
       - id: isort
-        files: llmstudio/
-        exclude: ^llmstudio/ui/
+        files: libs/
         args:
           - "--profile=black"
 
-  - repo: https://github.com/myint/autoflake
-    rev: v1.4
+  - repo: https://github.com/PyCQA/autoflake
+    rev: v2.3.1
     hooks:
       - id: autoflake
-        files: llmstudio/
-        exclude: ^llmstudio/ui/
+        files: libs/
+        exclude: 'libs/core/llmstudio_core/providers/__init__.py|libs/llmstudio/llmstudio/providers/__init__.py'
         args:
-          # - --remove-all-unused-imports
-          - --recursive
-          - --remove-unused-variables
-          - --in-place
-        additional_dependencies: [flake8]
+        - --remove-all-unused-imports
+        - --recursive
+        - --remove-unused-variables
+        - --in-place
+        additional_dependencies: [flake8]

Makefile

@@ -1,2 +1,2 @@
-start-db:
-	docker compose up --build
+format:
+	pre-commit run --all-files

docs/how-to/deploy-on-gke/deploy-on-google-kubernetes-engine.mdx

@@ -1,3 +1,7 @@
+---
+title: "Deploy on Google Kubernetes Engine"
+---
+
 Learn how to deploy LLMstudio as a containerized application on Google Kubernetes Engine and make calls from a local repository.
 
 
@@ -18,20 +22,20 @@ This example demonstrates a public deployment. For a private service accessible
   <Step title="Select Deploy">
     Go to **Workloads** and **Create a new Deployment**.
     <Frame>
-      <img src="how-to/deploy-on-gke/images/step-2.png" />
+      <img src="images/step-2.png" />
     </Frame>
   </Step>
   <Step title="Name Your Deployment">
     Rename your project. We will call the one in this guide **llmstudio-on-gcp**.
     <Frame>
-      <img src="how-to/deploy-on-gke/images/step-3.png" />
+      <img src="images/step-3.png" />
     </Frame>
   </Step>
   <Step title="Select Your Cluster">
     Choose between **creating a new cluster** or **using an existing cluster**. 
     For this guide, we will create a new cluster and use the default region.
     <Frame>
-      <img src="how-to/deploy-on-gke/images/step-4.png" />
+      <img src="images/step-4.png" />
     </Frame>
   </Step>
   <Step title="Proceed to Container Details">
@@ -47,7 +51,7 @@ This example demonstrates a public deployment. For a private service accessible
     ```
     Set it as the **Image path** to your container.
     <Frame>
-      <img src="how-to/deploy-on-gke/images/step-6.png" />
+      <img src="images/step-6.png" />
     </Frame>
   </Step>
   <Step title="Set Environment Variables">
@@ -63,7 +67,7 @@ Additionally, set the `GOOGLE_API_KEY` environment variable to enable calls to G
 <Tip>Refer to **SDK/LLM/Providers** for instructions on setting up other providers.</Tip>
 
 <Frame>
-  <img src="how-to/deploy-on-gke/images/step-7.png" />
+  <img src="images/step-7.png" />
 </Frame>
 
   </Step>
@@ -74,13 +78,13 @@ Additionally, set the `GOOGLE_API_KEY` environment variable to enable calls to G
     Select **Expose deployment as a new service** and leave the first item as is.
 
     <Frame>
-      <img src="how-to/deploy-on-gke/images/step-9-1.png" />
+      <img src="images/step-9-1.png" />
     </Frame>
 
     Add two other items, and expose the ports defined in the **Set Environment Variables** step.
 
     <Frame>
-      <img src="how-to/deploy-on-gke/images/step-9-2.png" />
+      <img src="images/step-9-2.png" />
     </Frame>
   </Step>
   <Step title="Deploy">
@@ -108,7 +112,7 @@ Now let's make a call to our LLMstudio instance on GCP!
 
         Go to your newly deployed **Workload**, scroll to the **Exposing services** section, and take note of the Host of your endpoint.
         <Frame>
-          <img src="how-to/deploy-on-gke/images/step-env.png" />
+          <img src="images/step-env.png" />
         </Frame>
 
         Create your `.env` file with the following:
@@ -141,7 +145,7 @@ Now let's make a call to our LLMstudio instance on GCP!
         ```
 
         <Frame>
-          <img src="how-to/deploy-on-gke/images/step-llmstudio-call.png" />
+          <img src="images/step-llmstudio-call.png" />
         </Frame>
 
 

docs/quickstart.mdx

@@ -45,7 +45,7 @@ description: "Let's have you setup LLMstudio"
 Using it in a Python notebook is also fairly simple! Just run the following cell:
 
 ```python
-from llmstudio import LLM
+from llmstudio.providers import LLM
 model = LLM("anthropic/claude-2.1")
 model.chat("What are Large Language Models?")
 ```