- Test commit for new gradio app logic (calling the deployed backend directly)

Dockerfile

@@ -1,36 +1,25 @@
-# Stage 1: Use a base image to perform the login and pull the private image
-FROM docker:latest AS base
+# Use the official Python image from the Docker Hub
+FROM python:3.9-slim
 
-# log in to Docker Hub
-RUN --mount=type=secret,id=DOCKER_HUB_USERNAME,mode=0444,required=true \
-    --mount=type=secret,id=DOCKER_HUB_PASSWORD,mode=0444,required=true
+# Importing HF space secrets as environment variables
+ENV AUTH_KEY=${AUTH_KEY}
+ENV AUTH_KEY=${API_URL}
+ENV AUTH_KEY=${API_PORT}
 
-RUN cat /run/secrets/DOCKER_HUB_USERNAME
-
-RUN echo "$(cat /run/secrets/DOCKER_HUB_PASSWORD)" | docker login -u "$(cat /run/secrets/DOCKER_HUB_USERNAME)" --password-stdin
-
-# Stage 2: Use authenticated session to pull the base image and build the application
-FROM intelligencenoborders/inobo:scinobo-claim-verification
-
-# Create user and set environment variables
-RUN useradd -m -u 1000 user && \
-    chown -R user /app
+# Set the working directory in the container
+WORKDIR /app
 
-USER user
-ENV HOME=/home/user \
-    PATH=/home/user/.local/bin:$PATH
+# Copy the current directory contents into the container at /app
+COPY . /app
 
-# Set the working directory in the container
-WORKDIR /app/src
+# Install any needed packages specified in requirements.txt
+RUN pip install --no-cache-dir -r requirements.txt
 
-# Expose the port that Gradio will run on
+# Expose the port the app runs on
 EXPOSE 7860
 
-ENV PYTHONUNBUFFERED=1 \
-    GRADIO_ALLOW_FLAGGING=never \
-    GRADIO_NUM_PORTS=1 \
-    GRADIO_SERVER_NAME=0.0.0.0 \
-    SYSTEM=spaces 
+# Define environment variable to avoid buffering in logs
+ENV PYTHONUNBUFFERED=1
 
-# Run app.py when the container launches
-CMD ["python", "-m", "claim_analysis.server.gradio_app"]
+# Run the application
+CMD ["python", "gradio_app.py"]

gradio_app.py

@@ -0,0 +1,67 @@
+import os
+import gradio as gr
+import requests
+
+# retrieve HF space secrets
+auth_key = os.getenv('AUTH_KEY')
+api_url = os.getenv('API_URL')
+api_port = os.getenv('API_PORT')
+
+HEADERS = {
+    'Content-Type': 'application/json'
+}
+
+def news_analysis(text):
+    try:
+        response = requests.post(
+            f'{api_url}:{api_port}/news_analysis',
+            json={
+                'doc_id': '1',
+                'text': text,
+                'auth_key': auth_key
+            },
+            headers=HEADERS
+        )
+        response.raise_for_status()
+        return response.json()
+    except requests.exceptions.RequestException as error:
+        print('Error fetching data from news_analysis:', error)
+        raise
+
+def claim_verification(text):
+    try:
+        response = requests.post(
+            f'{api_url}:{api_port}/claim_verification',
+            json={
+                'doc_id': '1',
+                'text': text,
+                'auth_key': auth_key
+            },
+            headers=HEADERS
+        )
+        response.raise_for_status()
+        return response.json()
+    except requests.exceptions.RequestException as error:
+        print('Error fetching data from claim_verification:', error)
+        raise
+
+iface_news_analysis = gr.Interface(
+    fn=news_analysis,
+    inputs=gr.inputs.Textbox(lines=10, label="News Article Text"),
+    outputs=gr.outputs.JSON(label="Classification Result"),
+    title="News Analysis",
+    description="Classify the domain of a news article and detect major claims."
+)
+
+iface_claim_verification = gr.Interface(
+    fn=claim_verification,
+    inputs=gr.inputs.Textbox(lines=10, label="Claim Text"),
+    outputs=gr.outputs.JSON(label="Verification Result"),
+    title="Claim Verification",
+    description="Verify claims made in a news article."
+)
+
+iface = gr.TabbedInterface([iface_news_analysis, iface_claim_verification], ["News Analysis", "Claim Verification"])
+
+# launch the interface
+iface.launch(server_name="0.0.0.0", server_port=7860)

requirements.txt

@@ -0,0 +1,2 @@
+gradio==3.0.10
+requests==2.28.1