Cleaning

.env_template

@@ -0,0 +1,12 @@
+# GCP Project Configuration (for deployment)
+PROJECT_ID=your-project-id
+REGION=europe-west1
+REPOSITORY=repo-name
+SERVICE_NAME=app-name
+
+# --- Models ---
+# Mandatory for MedSigLIP model download
+HF_TOKEN=take-from-model-download-site
+# --- Hardware (Optional Overrides) ---
+MEMORY=8Gi
+CPU=4

app/services/vertex_client.py

@@ -1,77 +0,0 @@
-import os
-import logging
-try:
-    from google.cloud import aiplatform
-    from google.oauth2 import service_account
-    import google.auth
-    GOOGLE_CLOUD_AVAILABLE = True
-except ImportError:
-    GOOGLE_CLOUD_AVAILABLE = False
-    aiplatform = None
-    service_account = None
-    google = None
-
-logger = logging.getLogger(__name__)
-
-class VertexClient:
-    def __init__(self):
-        self.project_id = os.environ.get("PROJECT_ID")
-        self.location = os.environ.get("LOCATION", "us-central1")
-        self.endpoint_id = os.environ.get("ENDPOINT_ID") # ID of the deployed MedGemma endpoint
-        self.credentials_path = os.environ.get("GOOGLE_APPLICATION_CREDENTIALS")
-        
-        self.setup_complete = False
-        
-        if not GOOGLE_CLOUD_AVAILABLE:
-            logger.warning("google-cloud-aiplatform not installed. Vertex AI client will be mocked.")
-            return
-
-        if self.project_id:
-            try:
-                # If credentials path is set, explicit load (dev), else default (cloud run)
-                if self.credentials_path and os.path.exists(self.credentials_path):
-                    creds = service_account.Credentials.from_service_account_file(self.credentials_path)
-                else:
-                    creds, _ = google.auth.default()
-
-                aiplatform.init(
-                    project=self.project_id,
-                    location=self.location,
-                    credentials=creds
-                )
-                self.setup_complete = True
-                logger.info(f"Vertex AI initialized for project {self.project_id}")
-            except Exception as e:
-                logger.error(f"Failed to initialize Vertex AI: {e}")
-
-    async def predict(self, prompt: str, max_tokens: int = 256, temperature: float = 0.2) -> str:
-        if not self.setup_complete:
-            logger.info("Returning mock prediction because Vertex AI is not configured.")
-            return "Mock Response: Vertex AI is not configured. This is a dummy prediction."
-        
-        if not self.endpoint_id:
-            return "Endpoint ID not configured."
-
-        try:
-            # Get Endpoint
-            endpoint = aiplatform.Endpoint(self.endpoint_id)
-            
-            # Predict
-            # Structure depends on the model serving container. 
-            # MedGemma usually expects instances=[{"prompt": ...}]
-            instances = [{"prompt": prompt, "max_tokens": max_tokens, "temperature": temperature}]
-            
-            response = endpoint.predict(instances=instances)
-            
-            # Parse prediction (assuming standard format, adjust based on actual model output)
-            # Typically response.predictions is a list
-            if response.predictions:
-                 return str(response.predictions[0])
-            else:
-                 return "No prediction returned."
-
-        except Exception as e:
-            logger.error(f"Prediction failed: {e}")
-            raise e
-
-vertex_client = VertexClient()

bin/generate-api.sh

@@ -1,27 +0,0 @@
-#!/bin/bash
-
-# Exit on error
-set -e
-
-echo "Generating Python models..."
-
-# Find datamodel-codegen in path or venv
-if command -v datamodel-codegen >/dev/null 2>&1; then
-    CODEGEN_BIN="datamodel-codegen"
-elif [ -f "./venv/bin/datamodel-codegen" ]; then
-    CODEGEN_BIN="./venv/bin/datamodel-codegen"
-else
-    echo "datamodel-codegen not found. Attempting to install..."
-    pip install datamodel-code-generator || ./venv/bin/pip install datamodel-code-generator
-    CODEGEN_BIN="datamodel-codegen"
-    if ! command -v "$CODEGEN_BIN" >/dev/null 2>&1 && [ -f "./venv/bin/datamodel-codegen" ]; then
-        CODEGEN_BIN="./venv/bin/datamodel-codegen"
-    fi
-fi
-
-if ! "$CODEGEN_BIN" --input openapi.yaml --output app/models.py; then
-    echo "Error: Python model generation failed. Check openapi.yaml for syntax errors."
-    exit 1
-fi
-
-echo "API Generation for Python Complete!"

docker-test.sh

@@ -1,5 +0,0 @@
-#!/bin/bash
-# Helper script to run tests inside the Docker container
-
-echo "Running tests in the 'app' container..."
-docker compose exec app pytest "$@"

generate-api.sh

@@ -1,27 +0,0 @@
-#!/bin/bash
-
-# Exit on error
-set -e
-
-echo "Generating Python models..."
-
-# Find datamodel-codegen in path or venv
-if command -v datamodel-codegen >/dev/null 2>&1; then
-    CODEGEN_BIN="datamodel-codegen"
-elif [ -f "./venv/bin/datamodel-codegen" ]; then
-    CODEGEN_BIN="./venv/bin/datamodel-codegen"
-else
-    echo "datamodel-codegen not found. Attempting to install..."
-    pip install datamodel-code-generator || ./venv/bin/pip install datamodel-code-generator
-    CODEGEN_BIN="datamodel-codegen"
-    if ! command -v "$CODEGEN_BIN" >/dev/null 2>&1 && [ -f "./venv/bin/datamodel-codegen" ]; then
-        CODEGEN_BIN="./venv/bin/datamodel-codegen"
-    fi
-fi
-
-if ! "$CODEGEN_BIN" --input openapi.yaml --output app/models.py; then
-    echo "Error: Python model generation failed. Check openapi.yaml for syntax errors."
-    exit 1
-fi
-
-echo "API Generation for Python Complete!"

openapi.yaml

@@ -1,35 +0,0 @@
-openapi: 3.0.3
-info:
-  title: Dermatolog AI Scan
-  description: AI application for dermatology analysis
-  version: 1.0.0
-paths:
-  /api/health:
-    get:
-      summary: Health check endpoint
-      operationId: health_check
-      responses:
-        '200':
-          description: Successful Response
-          content:
-            application/json:
-              schema:
-                $ref: '#/components/schemas/HealthCheckResponse'
-components:
-  schemas:
-    HealthCheckResponse:
-      properties:
-        status:
-          type: string
-          title: Status
-        database:
-          type: string
-          title: Database
-        gcp_project:
-          type: string
-          title: Gcp Project
-      type: object
-      required:
-        - status
-        - database
-      title: HealthCheckResponse

package.json

@@ -9,8 +9,7 @@
     "scripts": {
         "test": "node --experimental-vm-modules node_modules/jest/bin/jest.js",
         "test:watch": "node --experimental-vm-modules node_modules/jest/bin/jest.js --watch",
-        "test:coverage": "node --experimental-vm-modules node_modules/jest/bin/jest.js --coverage",
-        "generate-api": "bash bin/generate-api.sh"
+        "test:coverage": "node --experimental-vm-modules node_modules/jest/bin/jest.js --coverage"
     },
     "devDependencies": {
         "@jest/globals": "^29.7.0",