Refactor project

Signed-off-by: kerthcet <[email protected]>

.github/workflow/kube-workflow-init.yaml

@@ -0,0 +1,10 @@
+name: Initialization Workflow
+
+on:
+  workflow_dispatch:
+
+jobs:
+  init:
+    uses: kerthcet/github-workflow-as-kube/.github/workflows/[email protected]
+    secrets:
+      AGENT_TOKEN: ${{ secrets.AGENT_TOKEN }}

.github/workflow/kube-workflow.yaml

@@ -0,0 +1,21 @@
+name: Event Workflow
+
+on:
+  issues:
+    types:
+      - opened
+  issue_comment:
+    types:
+      - created
+  pull_request_target:
+    types:
+      - opened
+      - synchronize
+      - labeled
+      - unlabeled
+
+jobs:
+  event-handler:
+    uses: kerthcet/github-workflow-as-kube/.github/workflows/[email protected]
+    secrets:
+      AGENT_TOKEN: ${{ secrets.AGENT_TOKEN }}

Dockerfile

@@ -1,14 +1,14 @@
 FROM python:3.10-slim
 
-RUN mkdir -p /app/llmaz
+RUN mkdir -p /app/llmboard
 WORKDIR /app
 
 COPY requirements.txt .
 RUN python -m pip install --upgrade pip && \
     pip install -r requirements.txt
 
 COPY main.py .
-COPY llmaz/ ./llmaz
+COPY llmboard/ ./llmboard
 
 EXPOSE 7860
 CMD ["python", "main.py"]

README.md

@@ -1,17 +1,7 @@
-# Console for LLMAZ
+# ChatUI for LLMs on llmaz
 
-A dashboard for [llmaz](https://github.com/InftyAI/llmaz) to interact with LLM workloads.
+A console for [llmaz](https://github.com/InftyAI/llmaz) to interact with LLM workloads.
 
 ## How to deploy
 
 Run `make launch` then visit `http://localhost:7860` for Console.
-
-![console](./docs/asserts/preview.jpg)
-
-## 👏 Contributors
-
-Thanks to all these contributors. You're the heroes.
-
-<a href="https://github.com/InftyAI/llmaz-webui/graphs/contributors">
-  <img src="https://contrib.rocks/image?repo=InftyAI/llmaz-webui" />
-</a>

llmboard/libs/consts.py

@@ -0,0 +1,12 @@
+# GVKs
+group = "llmaz.io"
+version = "v1alpha1"
+openmodel_plural = "openmodels"
+
+# object label keys.
+label_key_family_name = "llmaz.io/model-family-name"
+label_key_model_name = "llmaz.io/model-name"
+
+# Model hubs.
+huggingface = "Huggingface"
+modelscope = "ModelScope"

llmboard/libs/inference_service.py

@@ -0,0 +1,9 @@
+from dataclasses import dataclass
+
+
+@dataclass(frozen=True)
+class InferenceService:
+    name: str
+    namespace: str
+    model_family_name: str
+    model_name: str

llmboard/libs/models.py

@@ -0,0 +1,21 @@
+from kubernetes import client
+from kubernetes.client import CustomObjectsApi
+
+from llmboard.libs.consts import group, version, openmodel_plural
+
+
+def get_openmodel_objects(api: CustomObjectsApi, namespace: None):
+    try:
+        if namespace:
+            # TODO: we do not support namespaced models yet.
+            raise NotImplementedError("do not support namespaced models yet")
+        else:
+            response = api.list_cluster_custom_object(
+                group=group,
+                version=version,
+                plural=openmodel_plural,
+            )
+        return response.get("items", [])
+    except client.exceptions.ApiException as e:
+        print(f"Error fetching OpenModel objects: {e}")
+        return []

llmboard/webui/engine.py

@@ -0,0 +1,12 @@
+from kubernetes import config
+from llmboard.libs.models import get_openmodel_objects
+
+
+class Engine:
+    def __init__(self) -> None:
+        # config.load_incluster_config()
+        pass
+
+    def get_models(self):
+        # objs = get_openmodel_objects()
+        pass

llmboard/webui/webui.py

@@ -0,0 +1,17 @@
+import gradio as gr
+
+from llmboard.webui.engine import Engine
+from llmboard.webui.webui_chat import create_chat_webui
+from llmboard.webui.webui_market import create_market_webui
+
+
+def launch_webui() -> gr.Blocks:
+    engine = Engine()
+
+    with gr.Blocks(title="llmboard") as blocks:
+        #  TODO: Model Market Tab, list and create serving services.
+        # create_market_webui(engine)
+        #  Serving Tab
+        create_chat_webui(engine)
+
+    return blocks