Translate functionality

.github/workflows/f24_translator-syntax-squad.yml

@@ -0,0 +1,67 @@
+# Docs for the Azure Web Apps Deploy action: https://github.com/Azure/webapps-deploy
+# More GitHub Actions for Azure: https://github.com/Azure/actions
+# More info on Python, GitHub Actions, and Azure App Service: https://aka.ms/python-webapps-actions
+
+name: Build and deploy Python app to Azure Web App - translator-syntax-squad
+
+on:
+  push:
+    branches:
+      - f24
+  workflow_dispatch:
+
+jobs:
+  build:
+    runs-on: ubuntu-latest
+
+    steps:
+      - uses: actions/checkout@v4
+
+      - name: Set up Python version
+        uses: actions/setup-python@v1
+        with:
+          python-version: '3.10'
+
+      - name: Create and start virtual environment
+        run: |
+          python -m venv venv
+          source venv/bin/activate
+
+      - name: Install dependencies
+        run: pip install -r requirements.txt
+
+      # Optional: Add step to run tests here (PyTest, Django test suites, etc.)
+      - name: Zip artifact for deployment
+        run: zip release.zip ./* -r
+
+      - name: Upload artifact for deployment jobs
+        uses: actions/upload-artifact@v3
+        with:
+          name: python-app
+          path: |
+            release.zip
+            !venv/
+
+  deploy:
+    runs-on: ubuntu-latest
+    needs: build
+    environment:
+      name: 'Production'
+      url: ${{ steps.deploy-to-webapp.outputs.webapp-url }}
+
+    steps:
+      - name: Download artifact from build job
+        uses: actions/download-artifact@v3
+        with:
+          name: python-app
+
+      - name: Unzip artifact for deployment
+        run: unzip release.zip
+
+      - name: 'Deploy to Azure Web App'
+        uses: azure/webapps-deploy@v2
+        id: deploy-to-webapp
+        with:
+          app-name: 'translator-syntax-squad'
+          slot-name: 'Production'
+          publish-profile: ${{ secrets.AZUREAPPSERVICE_PUBLISHPROFILE_4FFDAD9CBC40474FBAD90E3F1361DB55 }}

src/translator.py

@@ -1,34 +1,94 @@
-def translate_content(content: str) -> tuple[bool, str]:
-    if content == "这是一条中文消息":
-        return False, "This is a Chinese message"
-    if content == "Ceci est un message en français":
-        return False, "This is a French message"
-    if content == "Esta es un mensaje en español":
-        return False, "This is a Spanish message"
-    if content == "Esta é uma mensagem em português":
-        return False, "This is a Portuguese message"
-    if content  == "これは日本語のメッセージです":
-        return False, "This is a Japanese message"
-    if content == "이것은 한국어 메시지입니다":
-        return False, "This is a Korean message"
-    if content == "Dies ist eine Nachricht auf Deutsch":
-        return False, "This is a German message"
-    if content == "Questo è un messaggio in italiano":
-        return False, "This is an Italian message"
-    if content == "Это сообщение на русском":
-        return False, "This is a Russian message"
-    if content == "هذه رسالة باللغة العربية":
-        return False, "This is an Arabic message"
-    if content == "यह हिंदी में संदेश है":
-        return False, "This is a Hindi message"
-    if content == "นี่คือข้อความภาษาไทย":
-        return False, "This is a Thai message"
-    if content == "Bu bir Türkçe mesajdır":
-        return False, "This is a Turkish message"
-    if content == "Đây là một tin nhắn bằng tiếng Việt":
-        return False, "This is a Vietnamese message"
-    if content == "Esto es un mensaje en catalán":
-        return False, "This is a Catalan message"
-    if content == "This is an English message":
-        return True, "This is an English message"
-    return True, content
+import openai
+import time
+
+# Use your actual API Key and Endpoint
+openai.api_key = os.getenv("OPENAI_API_KEY") 
+openai.api_base = "https://barbol.openai.azure.com/"  # Your endpoint base URL
+openai.api_type = "azure"
+openai.api_version = "2024-08-01-preview"
+deployment_name = "barbol-gpt-4"
+
+def get_translation(post: str) -> str:
+    # Define the translation prompt in a conversational format
+    messages = [
+        {"role": "system", "content": "You are a helpful assistant that translates text to English."},
+        {"role": "user", "content": f"Translate the following text to English: {post}"}
+    ]
+
+    wait_time = 5
+
+    while True:
+        try:
+            # Use the ChatCompletion endpoint with the gpt-4 model
+            response = openai.ChatCompletion.create(
+                engine="barbol-gpt-4",
+                messages=messages,
+                max_tokens=100,
+                temperature=0.2,
+            )
+
+            # Extract and return the translation from the response
+            translation = response.choices[0].message['content'].strip()
+            return translation
+
+        except openai.error.RateLimitError:
+            print(f"Rate limit exceeded. Waiting for {wait_time} seconds before retrying...")
+            time.sleep(wait_time)
+        except Exception as e:
+            print("Error in translation:", e)
+            return ""
+
+def get_language(post: str) -> str:
+    # Define the prompt to determine the exact language of the text
+    messages = [
+        {"role": "system", "content": "You are a helpful assistant that detects the language of the given text and returns the name of the language, starting with a capital letter and a one word response(eg. English, Spanish, Arabic, Russian)."},
+        {"role": "user", "content": f"Identify the language of the following text: {post}"}
+    ]
+
+    wait_time = 5
+
+    while True:
+        try:
+            # Use the ChatCompletion endpoint to determine language
+            response = openai.ChatCompletion.create(
+                engine="barbol-gpt-4",
+                messages=messages,
+                max_tokens=10,
+                temperature=0.0,
+            )
+
+            # Extract and return the detected language from the response
+            detected_language = response.choices[0].message['content'].strip()
+            return detected_language
+
+        except openai.error.RateLimitError:
+            print(f"Rate limit exceeded. Waiting for {wait_time} seconds before retrying...")
+            time.sleep(wait_time)
+        except Exception as e:
+            print("Error in language detection:", e)
+            return ""
+
+def translate_content(post: str) -> str:
+    """
+    Detects the language of the text and translates it into English if it's not already in English.
+    """
+    try:
+        # Step 1: Detect the language of the text
+        detected_language = get_language(post)
+        print(f"Detected Language: {detected_language}")
+
+        # Step 2: Translate if the text is not in English
+        if detected_language != "English":
+            print(f"Translating text from {detected_language} to English...")
+            return get_translation(post)
+        else:
+            print("Text is already in English. No translation needed.")
+            return post
+
+    except Exception as e:
+        print("Error in translate_content:", e)
+        return ""
+
+
+
+