Update src/gradio_server.py

src/gradio_server.py

@@ -1,12 +1,11 @@
 import gradio as gr
 import os
 import sys
-from typing import Annotated
-
-from fastapi import FastAPI, Form, UploadFile
+from fastapi import FastAPI
 from pydantic import BaseModel
 from hamilton import driver
 from pandas import DataFrame
+from fastapi.middleware.cors import CORSMiddleware
 
 # Add the src directory to the Python path
 sys.path.append(os.path.join(os.path.dirname(__file__), 'src'))
@@ -19,13 +18,23 @@ from decouple import config
 
 app = FastAPI()
 
-config = {"loader": "pd", 
-          "embedding_service": "openai", 
-          "api_key": config("OPENAI_API_KEY"), 
-          "model_name": "text-embedding-ada-002",
-          "mistral_public_url": config("MISTRAL_PUBLIC_URL"),
-          "ner_public_url": config("NER_PUBLIC_URL")
-          }  # or "pd"
+# Enable CORS for Gradio to communicate with FastAPI
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["*"],
+    allow_credentials=True,
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
+
+config = {
+    "loader": "pd",
+    "embedding_service": "openai",
+    "api_key": config("OPENAI_API_KEY"),
+    "model_name": "text-embedding-ada-002",
+    "mistral_public_url": config("MISTRAL_PUBLIC_URL"),
+    "ner_public_url": config("NER_PUBLIC_URL"),
+}
 
 dr = (
     driver.Builder()
@@ -49,13 +58,11 @@ class PolicyEnforcementRequest(BaseModel):
     violation_context: dict
 
 class RadicalizationDetectionResponse(BaseModel):
-    """Response to the /detect endpoint"""
     values: dict
     
 class PolicyEnforcementResponse(BaseModel):
-    """Response to the /generate_policy_enforcement endpoint"""
     values: dict
-    
+
 @app.post("/detect_radicalization")
 def detect_radicalization(
     request: RadicalizationDetectionRequest
@@ -65,8 +72,6 @@ def detect_radicalization(
         final_vars=["detect_glorification"],
         inputs={"project_root": ".", "user_input": request.user_text}
     )
-    print(results)
-    print(type(results))
     if isinstance(results, DataFrame):
         results = results.to_dict(orient="dict")
     return RadicalizationDetectionResponse(values=results)
@@ -79,8 +84,6 @@ def generate_policy_enforcement(
         final_vars=["get_enforcement_decision"],
         inputs={"project_root": ".", "user_input": request.user_text, "violation_context": request.violation_context}
     )
-    print(results)
-    print(type(results))
     if isinstance(results, DataFrame):
         results = results.to_dict(orient="dict")
     return PolicyEnforcementResponse(values=results)
@@ -118,3 +121,7 @@ iface2 = gr.Interface(
 
 # Combine the interfaces in a Tabbed interface
 iface_combined = gr.TabbedInterface([iface, iface2], ["Detect Radicalization", "Policy Enforcement"])
+
+if __name__ == "__main__":
+    # Launch Gradio interface (no need to launch Uvicorn separately)
+    iface_combined.launch(server_name="0.0.0.0", server_port=7860)