Update app.py

app.py

@@ -7,6 +7,12 @@ import time
 import tempfile
 from huggingface_hub import InferenceClient
 
+from deep_translator import GoogleTranslator
+
+def get_translation(context_custom, language = 'en'):
+    translated = GoogleTranslator(source = 'auto', target = language).translate(text = context_custom)
+    return translated
+
 client = InferenceClient("mistralai/Mixtral-8x7B-Instruct-v0.1")
 
 system_instructions1 = "<s>[SYSTEM] You are AI assistant named DorjGPT, Keep conversation very short, clear, friendly and concise. The text provided is a request for a specific type of response from you, the virtual assistant. The request asks you to provide friendly responses as if super interlligent AI assistant. The expectation is that I will avoid introductions and start answering the query directly, elaborating on all aspects of the request. As an AI-powered assistant, your task is to generate responses that appear as if they are created by the user and not an AI-powered assistant. [USER]"
@@ -31,7 +37,8 @@ async def generate1(prompt, history=[], b=None):
         seed=42,
     )
     #formatted_prompt = system_instructions1 + prompt + "[JARVIS]"
-    formatted_prompt = format_prompt(f"{system_instructions1}, {prompt}", history) + "[DORJGPT]"
+    prompt_en = get_translation(prompt)
+    formatted_prompt = format_prompt(f"{system_instructions1}, {prompt_en}", history) + "[DORJGPT]"
     stream = client.text_generation(
         formatted_prompt, **generate_kwargs, stream=True, details=True, return_full_text=True)
 
@@ -39,9 +46,10 @@ async def generate1(prompt, history=[], b=None):
     for response in stream:
         output += response.token.text
     output = output.replace("</s>","")
-    history.append([prompt, output])
+    output_mn = get_translation(output, language="mn")
+    history.append([prompt_en, output])
 
-    communicate = edge_tts.Communicate(output)
+    communicate = edge_tts.Communicate(output_mn)
     with tempfile.NamedTemporaryFile(delete=False, suffix=".wav") as tmp_file:
         tmp_path = tmp_file.name
         await communicate.save(tmp_path)