Update chatbot.py

chatbot.py

@@ -138,90 +138,92 @@ class Comsatsbot:
                     continue
         return "Sorry, unable to provide an answer at this time."
 
-    def detect_language(self, question):
-        for api_key in self.api_keys:
-            self.client = Groq(api_key=api_key)
-            for model in self.models:
-                try:
-                    chat_completion = self.client.chat.completions.create(
-                        messages=[
-                            {
-                                "role": "system",
-                                "content": """
-You are an expert agent and your task is to detect the language. 
-Return a JSON: {'detected_language': 'urdu' or 'english'}
-"""
-                            },
-                            {
-                                "role": "user",
-                                "content": f"Detect the language for: {question}"
-                            }
-                        ],
-                        model=model,
-                        max_tokens=256,
-                        response_format={"type": "json_object"},
-                    )
-                    response = json.loads(chat_completion.choices[0].message.content)
-                    return response['detected_language'].lower()
-                except Exception:
-                    time.sleep(2)
-                    continue
-        return "english"
-
-    def translate_urdu(self, text):
-        for api_key in self.api_keys:
-            self.client = Groq(api_key=api_key)
-            for model in self.models:
-                try:
-                    chat_completion = self.client.chat.completions.create(
-                        messages=[
-                            {
-                                "role": "system",
-                                "content": """
-Translate the following text into proper Urdu. Return a JSON: 
-{'text': 'translated urdu text'}
-"""
-                            },
-                            {
-                                "role": "user",
-                                "content": f"Translate this: {text}"
-                            }
-                        ],
-                        model=model,
-                        max_tokens=512,
-                        response_format={"type": "json_object"},
-                    )
-                    response = json.loads(chat_completion.choices[0].message.content)
-                    return response['text']
-                except Exception:
-                    time.sleep(2)
-                    continue
-        return text
-
-    def response(self, question, chat_id):
-        chat_history = self.load_chat(chat_id)
-
-        for entry in chat_history:
-            self.memory.save_context({"input": entry["question"]}, {"output": entry["answer"]})
-
-        language = self.detect_language(question)
-
-        if language == 'urdu':
-            question_translation = GoogleTranslator(source='ur', target='en').translate(question)
-            context = self.faiss_retriever.invoke(question_translation)
-        else:
-            context = self.faiss_retriever.invoke(question)
-
-        combined_context = '\n'.join([doc.page_content for doc in context])
-        answer = self.generate_response(question, self.memory.load_memory_variables({})['history'], combined_context)
-
-        self.update_chat(chat_id, question, answer)
-
-        if language == 'urdu':
-            return self.translate_urdu(answer)
-        return answer
-                      
-
+   def detect_language(self, question):
+    for api_key in self.api_keys:
+        self.client = Groq(api_key=api_key)
+        for model in self.models:
+            try:
+                chat_completion = self.client.chat.completions.create(
+                    messages=[
+                        {
+                            "role": "system",
+                            "content": """
+                                You are an expert agent and your task is to detect the language. 
+                                Return a JSON: {'detected_language': 'urdu' or 'english'}
+                            """
+                        },
+                        {
+                            "role": "user",
+                            "content": f"Detect the language for: {question}"
+                        }
+                    ],
+                    model=model,
+                    max_tokens=256,
+                    response_format={"type": "json_object"},
+                )
+                response = json.loads(chat_completion.choices[0].message.content)
+                return response['detected_language'].lower()
+            except Exception:
+                time.sleep(2)
+                continue
+    return "english"
+
+def translate_urdu(self, text):
+    for api_key in self.api_keys:
+        self.client = Groq(api_key=api_key)
+        for model in self.models:
+            try:
+                chat_completion = self.client.chat.completions.create(
+                    messages=[
+                        {
+                            "role": "system",
+                            "content": """
+                                Translate the following text into proper Urdu. Return a JSON: 
+                                {'text': 'translated urdu text'}
+                            """
+                        },
+                        {
+                            "role": "user",
+                            "content": f"Translate this: {text}"
+                        }
+                    ],
+                    model=model,
+                    max_tokens=512,
+                    response_format={"type": "json_object"},
+                )
+                response = json.loads(chat_completion.choices[0].message.content)
+                return response['text']
+            except Exception:
+                time.sleep(2)
+                continue
+    return text
+
+ def response(self, question, chat_id):
+    chat_history = self.load_chat(chat_id)
+
+    for entry in chat_history:
+        self.memory.save_context({"input": entry["question"]}, {"output": entry["answer"]})
+
+    language = self.detect_language(question)
+
+    if language == 'urdu':
+        question_translation = GoogleTranslator(source='ur', target='en').translate(question)
+        context = self.faiss_retriever.invoke(question_translation)
+    else:
+        context = self.faiss_retriever.invoke(question)
+
+    combined_context = '\n'.join([doc.page_content for doc in context])
+    answer = self.generate_response(question, self.memory.load_memory_variables({})['history'], combined_context)
+
+    self.update_chat(chat_id, question, answer)
+
+    if language == 'urdu':
+        return self.translate_urdu(answer)
+    return answer
+     
+
+   
+