Update app.py

app.py

@@ -2,9 +2,10 @@ import openai
 import requests
 import json
 import wikipedia
-import requests
 from bs4 import BeautifulSoup
 import gradio as gr
+from googletrans import Translator
+import langid
 
 # Set up the OpenAI API client
 openai.api_key = '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'  # Replace with your actual API key
@@ -12,8 +13,11 @@ openai.api_key = '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'  # Replac
 # Set up Google SERP API credentials
 serp_api_key = '03c74289238ba82d2889379e7a958a07b56c45de'  # Replace with your actual Google SERP API key
 
+# Set up Google Translate client
+translator = Translator(service_urls=['translate.google.com'])
+
 # Function to send a message and receive a response from the chatbot
-def chat(message):
+def chat(message, target_lang):
     try:
         response = openai.Completion.create(
             engine='text-davinci-003',  # Choose the language model/engine you want to use
@@ -22,7 +26,9 @@ def chat(message):
             n=1,  # Number of responses to generate
             stop=None,  # Specify a stop token to end the response
         )
-        return response.choices[0].text.strip()
+        response_text = response.choices[0].text.strip()
+        translated_text = translator.translate(response_text, dest=target_lang).text
+        return translated_text
     except Exception as e:
         print("An error occurred:", e)
         return ""
@@ -82,7 +88,11 @@ def search_wikipedia(query):
         if search_results:
             page_title = search_results[0]
             page_summary = wikipedia.summary(page_title)
-            return page_summary
+
+            # Translate the summary to English
+            page_summary_en = translator.translate(page_summary, dest='en').text
+
+            return page_summary_en
         else:
             print(".")
             return None
@@ -103,7 +113,15 @@ def search_wikipedia(query):
 def generate_summary(user_input):
     output = get_latest_answers(user_input)
     page_summary = search_wikipedia(user_input)
-    chat_answer = chat(user_input)
+
+    # Translate the user input to English
+    user_input_en = translator.translate(user_input, dest='en').text
+
+    chat_answer_en = chat(user_input_en, 'en')
+
+    # Translate the chatbot's response back to the detected input language
+    detected_lang = langid.classify(user_input)[0]
+    chat_answer = translator.translate(chat_answer_en, dest=detected_lang).text
 
     # Generate summarized paragraph using OpenAI API
     response = openai.Completion.create(
@@ -115,9 +133,27 @@ def generate_summary(user_input):
 
     return summarized_paragraph
 
+# Function to detect the input language
+def detect_language(text):
+    detected_lang = langid.classify(text)[0]
+    return detected_lang
+
+# Function to translate text to English
+def translate_to_english(text):
+    translated_text = translator.translate(text, dest='en').text
+    return translated_text
+
+# Function to translate text to the detected input language
+def translate_to_input_language(text, input_lang):
+    translated_text = translator.translate(text, dest=input_lang).text
+    return translated_text
+
 # Define the Gradio interface
 def summarizer_interface(user_input):
-    summarized_text = generate_summary(user_input)
+    input_lang = detect_language(user_input)
+    user_input_english = translate_to_english(user_input)
+    summarized_text_english = generate_summary(user_input_english)
+    summarized_text = translate_to_input_language(summarized_text_english, input_lang)
     return summarized_text
 
 iface = gr.Interface(