working demo with working inference services and eveeryhting

Author: chasecadet

authbackup.yml

@@ -0,0 +1,82 @@
+apiVersion: v1
+items:
+- apiVersion: security.istio.io/v1beta1
+  kind: AuthorizationPolicy
+  metadata:
+    annotations:
+      metacontroller.k8s.io/last-applied-configuration: '{"apiVersion":"security.istio.io/v1beta1","kind":"AuthorizationPolicy","metadata":{"labels":{"controller-uid":"087b40d8-1cdb-4c27-93f1-240663a11120"},"name":"ml-pipeline-visualizationserver","namespace":"christensenc3526"},"spec":{"rules":[{"from":[{"source":{"principals":["cluster.local/ns/kubeflow/sa/ml-pipeline"]}}]}],"selector":{"matchLabels":{"app":"ml-pipeline-visualizationserver"}}}}'
+    creationTimestamp: "2024-02-01T16:18:49Z"
+    generation: 1
+    labels:
+      controller-uid: 087b40d8-1cdb-4c27-93f1-240663a11120
+    name: ml-pipeline-visualizationserver
+    namespace: christensenc3526
+    ownerReferences:
+    - apiVersion: v1
+      blockOwnerDeletion: true
+      controller: true
+      kind: Namespace
+      name: christensenc3526
+      uid: 087b40d8-1cdb-4c27-93f1-240663a11120
+    resourceVersion: "1287486"
+    uid: 225ad4f4-6e86-429b-a8bd-de0239d9588b
+  spec:
+    rules:
+    - from:
+      - source:
+          principals:
+          - cluster.local/ns/kubeflow/sa/ml-pipeline
+    selector:
+      matchLabels:
+        app: ml-pipeline-visualizationserver
+- apiVersion: security.istio.io/v1beta1
+  kind: AuthorizationPolicy
+  metadata:
+    annotations:
+      role: admin
+      user: christensenc3526@gmail.com
+    name: ns-owner-access-istio
+    namespace: christensenc3526
+    ownerReferences:
+    - apiVersion: kubeflow.org/v1
+      blockOwnerDeletion: true
+      controller: true
+      kind: Profile
+      name: christensenc3526
+      uid: 83504f57-d3c3-406d-8c6b-cd5442091687
+    resourceVersion: "1287526"
+    uid: 2365c954-ebef-417b-b333-6ff4a8bc826f
+  spec:
+    rules:
+    - from:
+      - source:
+          principals:
+          - cluster.local/ns/istio-system/sa/istio-ingressgateway-service-account
+          - cluster.local/ns/kubeflow/sa/ml-pipeline-ui
+      when:
+      - key: request.headers[x-goog-authenticated-user-email]
+        values:
+        - accounts.google.com:christensenc3526@gmail.com
+    - when:
+      - key: source.namespace
+        values:
+        - christensenc3526
+    - to:
+      - operation:
+          paths:
+          - /healthz
+          - /metrics
+          - /wait-for-drain
+    - from:
+      - source:
+          principals:
+          - cluster.local/ns/kubeflow/sa/notebook-controller-service-account
+      to:
+      - operation:
+          methods:
+          - GET
+          paths:
+          - '*/api/kernels'
+kind: List
+metadata:
+  resourceVersion: ""

dockerfiles/frontend/dockerfile

@@ -4,5 +4,5 @@ ADD src/requirements.txt /workspace/requirements.txt
 RUN pip install -r requirements.txt
 ADD src/app.py src/theme.py images/app-header.png /workspace/
 ENV HOME=/workspace
-EXPOSE 80
+EXPOSE 8080
 CMD [ "python3" , "/workspace/app.py" ]

dockerfiles/frontend/src/app.py

@@ -1,24 +1,26 @@
 import json
 import requests
-
+from fastapi import FastAPI
 import gradio as gr
 from theme import TileDBTheme
-
-
+import os
+import uvicorn 
+app = FastAPI()
+CUSTOM_PATH = os.environ.get("CUSTOM_PATH", "/tiledb")
 DOMAIN_NAME = "svc.cluster.local"
 NAMESPACE = open("/var/run/secrets/kubernetes.io/serviceaccount/namespace", "r").read()
 DEPLOYMENT_NAME = "llm"
 MODEL_NAME = DEPLOYMENT_NAME
 SVC = f"{DEPLOYMENT_NAME}-transformer.{NAMESPACE}.{DOMAIN_NAME}"
-URL = f"https://{SVC}/v1/models/{MODEL_NAME}:predict"
+URL = f"http://{SVC}/v1/models/{MODEL_NAME}:predict"
 
 SYSTEM_MESSAGE = "You are an AI assistant. You will be given a task. You must generate a detailed answer."
 INSTRUCTION = "Use the following pieces of context to answer the question at the end. If you don't know the answer, just say that you don't know, don't try to make up an answer."
 
 example_questions = [
-    ["What is TileDB?"],
-    ["What makes TileDB a great vector database?"],
-    ["Does the TileDB vector database use sparse or dense arrays?"]
+    ["How does this demo work?"],
+    ["Why TileDB for vector databases?"],
+    ["Do vector datatbases use dense or sparse arrays?"]
 ]
 
 
@@ -53,8 +55,8 @@ def llm_service(question, system, instruction, temperature, num_docs, max_tokens
     return json.loads(response.text)["predictions"][0]
 
 
-if __name__ == "__main__":
-    with gr.Blocks(theme=TileDBTheme()) as app:
+def create_gradio_app():
+    with gr.Blocks(theme=TileDBTheme()) as demo:
         gr.Markdown("![ai-enabled-search](file/app-header.png)")
         with gr.Row():
             question = gr.Textbox(label="Question", autofocus=True)
@@ -130,5 +132,15 @@ def llm_service(question, system, instruction, temperature, num_docs, max_tokens
             outputs=[question, system, instruction, temperature, num_docs,
                      max_tokens, top_k, top_p, context_check, output])
 
-    app.launch(server_name="0.0.0.0", server_port=8080)
+    return demo
 
+
+@app.get("/")
+def read_main():
+    return {"message": "This is the main app. Access the Gradio interface at /tiledb"}
+
+if __name__ == "__main__":
+    io=create_gradio_app()
+    gradio_app = gr.routes.App.create_app(io)
+    app.mount(CUSTOM_PATH, gradio_app)
+    uvicorn.run(app, host="0.0.0.0", port=8080)

dockerfiles/frontend/src/requirements.txt

@@ -1 +1,3 @@
 gradio==3.44.4
+fastapi
+uvicorn

dockerfiles/frontend/src/theme.py

@@ -3,7 +3,7 @@
 from gradio.themes.utils import colors
 
 # Define TileDB colors here
-TILEDB_PRIMARY = "#2A7DE1"  # Example primary color
+TILEDB_PRIMARY = "##2a7de1"  # Example primary color
 TILEDB_SECONDARY = "#F3F4F6"  # Example secondary color
 TILEDB_BACKGROUND = "#374151"  # Example background color
 TILEDB_TEXT = "#6E707A"  # Example text color
@@ -16,8 +16,8 @@ class TileDBTheme(Base):
     def __init__(
             self,
             *,
-            primary_hue: Union[colors.Color, str] = TILEDB_PRIMARY,
-            neutral_hue: Union[colors.Color, str] = TILEDB_BACKGROUND,
+            primary_hue: Union[colors.Color, str] = colors.slate,
+            neutral_hue: Union[colors.Color, str] = colors.cyan,
             ):
         super().__init__(
             primary_hue=primary_hue,

dockerfiles/frontend/src/working-gradio.py

@@ -0,0 +1,28 @@
+from fastapi import FastAPI
+import gradio as gr
+import os
+
+app = FastAPI()
+CUSTOM_PATH = os.environ.get("CUSTOM_PATH", "/tiledb")
+
+# Define the Gradio interface function
+def greet(name, intensity):
+    return "Hello " * intensity + name + "!"
+
+# Create the Gradio interface
+io = gr.Interface(fn=greet, inputs=["text", "slider"], outputs="text")
+
+# Create a Gradio app from the interface
+gradio_app = gr.routes.App.create_app(io)
+
+# Mount the Gradio app on the custom path within the FastAPI application
+app.mount(CUSTOM_PATH, gradio_app)
+
+@app.get("/")
+def read_main():
+    return {"message": "This is the main app. Access the Gradio interface at /tiledb"}
+
+if __name__ == "__main__":
+    import uvicorn
+    uvicorn.run(app, host="0.0.0.0", port=8080)
+

manifests/frontend.yml

@@ -1,39 +1,82 @@
 apiVersion: apps/v1
 kind: Deployment
 metadata:
-  name: llm-deployment
+  name: demo-deployment
+  namespace: christensenc3526
   labels:
-    app: llm
+    app: demo
 spec:
   replicas: 1
   selector:
     matchLabels:
-      app: llm
+      app: demo
   template:
     metadata:
       labels:
-        app: llm
+        app: demo
     spec:
       containers:
-      - name: llm-container
-        image: <your-docker-image-name>:<tag>
+      - name: demo-app
+        image: chasechristensen/tiledb_demo_frontend:v22
         ports:
-        - containerPort: 8080
-        env:
-        - name: GRADIO_SERVER_PORT
-          value: "8080"
-        - name: GRADIO_SERVER_NAME
-          value: "0.0.0.0"
+          - name: http
+            containerPort: 8080
+            protocol: TCP  
 ---
 apiVersion: v1
 kind: Service
 metadata:
-  name: llm-transformer-default
+  name: demo
+  namespace: christensenc3526
 spec:
   selector:
-    app: llm
+    app: demo
   ports:
   - protocol: TCP
     port: 80
     targetPort: 8080
+    name: http  
+---
+apiVersion: networking.istio.io/v1beta1
+kind: VirtualService
+metadata:
+  name: tiledb-virtual-service
+  namespace: christensenc3526  # Match this with your service's namespace
+spec:
+  gateways:
+    - kubeflow-gateway
+  hosts:
+    - '*'
+  http:
+    - match:
+        - uri:
+            prefix: /tiledb
+      rewrite:
+        uri: /
+      route:
+        - destination:
+            host: demo.christensenc3526.svc.cluster.local
+            port:
+              number: 80
+       
+---
+
+apiVersion: security.istio.io/v1beta1
+kind: AuthorizationPolicy
+metadata:
+  name: demo-service-external-access
+  namespace: christensenc3526
+spec:
+  action: ALLOW
+  rules:
+  - to:
+    - operation:
+        methods: ["GET", "POST"]  # Adjust based on the methods your service requires
+        paths: ["/tiledb/*"]  # Adjust if your service listens on different paths
+  - from:
+    - source:
+        requestPrincipals: ["*"]  # Allows access from any authenticated user (consider narrowing this down)
+  selector:
+    matchLabels:
+      app: demo