Add a Gemini API proxy route.

.env

@@ -3,3 +3,4 @@
 # If you want to push to a local instance of explorer, then specify the app-api docker container name like: 
 # http://<app-api-docker-container-name>:8000 to push to the local explorer instance.
 INVARIANT_API_URL=https://explorer.invariantlabs.ai
+GUADRAILS_API_URL=https://guardrail.invariantnet.com

proxy/routes/gemini.py

@@ -0,0 +1,61 @@
+"""Proxy service to forward requests to the Gemini APIs"""
+
+import json
+
+from common.config_manager import ProxyConfig, ProxyConfigManager
+from fastapi import APIRouter, Depends, Request, Response
+from utils.constants import IGNORED_HEADERS
+
+proxy = APIRouter()
+
+
+def _extract_dataset_name_and_endpoint(endpoint: str):
+    """Extracts the dataset name and endpoint from the given endpoint."""
+    endpoint_parts = endpoint.split("/")
+    dataset_name = None
+    if endpoint_parts[1] == "models":
+        # Case 1: Without dataset_name
+        # `endpoint = <version>/models/<model-name>:generateContent`
+        reconstructed_endpoint = "/".join(endpoint_parts)
+    elif endpoint_parts[2] == "models":
+        # Case 2: With dataset_name
+        # `endpoint = <dataset-name>/<version>/models/<model-name>:generateContent`
+        dataset_name = endpoint_parts[0]
+        reconstructed_endpoint = "/".join(endpoint_parts[1:])
+    else:
+        # Case 3: Invalid endpoint
+        return Response(
+            content=f"Invalid endpoint: {endpoint} - the endpoint should be in the format: \
+            /api/v1/proxy/gemini/<version>/models/<model-name>:generateContent or \
+            /api/v1/proxy/gemini/<dataset-name>/<version>models/<model-name>:generateContent",
+            status_code=400,
+        )
+    return dataset_name, reconstructed_endpoint
+
+
+@proxy.post(
+    "/gemini/{endpoint:path}",
+)
+async def gemini_generate_content_proxy(
+    request: Request,
+    endpoint: str,
+    config: ProxyConfig = Depends(ProxyConfigManager.get_config),  # pylint: disable=unused-argument
+) -> Response:
+    """Proxy calls to the OpenAI APIs"""
+    headers = {
+        k: v for k, v in request.headers.items() if k.lower() not in IGNORED_HEADERS
+    }
+    headers["accept-encoding"] = "identity"
+
+    request_body_bytes = await request.body()
+    request_body_json = json.loads(request_body_bytes)
+    api_key = headers.get("x-goog-api-key")
+    print(f"API Key: {api_key}")
+    print("request body json: ", request_body_json)
+    dataset_name, reconstructed_endpoint = _extract_dataset_name_and_endpoint(endpoint)
+
+    print(f"API Key: {api_key}")
+    print("Processed Endpoint: ", reconstructed_endpoint)
+    print("Dataset Name: ", dataset_name)
+
+    return {}

proxy/serve.py

@@ -3,6 +3,7 @@
 import fastapi
 import uvicorn
 from routes.anthropic import proxy as anthropic_proxy
+from routes.gemini import proxy as gemini_proxy
 from routes.open_ai import proxy as open_ai_proxy
 from starlette_compress import CompressMiddleware
 
@@ -26,6 +27,8 @@ router.include_router(open_ai_proxy, prefix="/proxy", tags=["open_ai_proxy"])
 
 router.include_router(anthropic_proxy, prefix="/proxy", tags=["anthropic_proxy"])
 
+router.include_router(gemini_proxy, prefix="/proxy", tags=["gemini_proxy"])
+
 app.include_router(router)
 
 

run.sh

@@ -20,11 +20,13 @@ up() {
       shift
   done
 
-  if [[ -n "$POLICIES_FILE_PATH" && -f "$POLICIES_FILE_PATH" ]]; then
-    POLICIES_FILE_PATH=$(realpath "$POLICIES_FILE_PATH")
-  else
+  if [[ -n "$POLICIES_FILE_PATH" ]]; then
+    if [[ -f "$POLICIES_FILE_PATH" ]]; then
+      POLICIES_FILE_PATH=$(realpath "$POLICIES_FILE_PATH")
+    else
       echo "Error: Specified policies file does not exist: $POLICIES_FILE_PATH"
       exit 1
+    fi
   fi
 
   # Start Docker Compose with the correct environment variable