Update app.py

app.py

@@ -107,24 +107,17 @@ def transliterate_to_sinhala(text):
 
 # interface = gr.Interface.load("huggingface/microsoft/Phi-3-mini-4k-instruct")
 
-API_URL = "https://api-inference.huggingface.co/models/microsoft/Phi-3-mini-4k-instruct"
-headers = {"Authorization": f"Bearer {access_token}"}
+# API_URL = "https://api-inference.huggingface.co/models/microsoft/Phi-3-mini-4k-instruct"
+# headers = {"Authorization": f"Bearer {access_token}"}
 
-def query(payload):
-	response = requests.post(API_URL, headers=headers, json=payload)
-	return response.json()
+ai_pipe = pipeline("text-generation", model="google/gemma-2b-it", token = access_token)
 
+# def query(payload):
+# 	response = requests.post(API_URL, headers=headers, json=payload)
+# 	return response.json()
+    
 def conversation_predict(text):
-    response_json = query({
-    	"inputs": f"{text}",
-    })
-    if 'generated_text' in response_json[0]:
-        ai_response = response_json[0]['generated_text']
-    elif 'text' in response_json[0]:
-        ai_response = response_json[0]['text']
-    else:
-        ai_response = response_json[0]
-
+    ai_response = ai_pipe([{"role": "user", "content": f"{text}"}])
     return ai_response
 
 def ai_predicted(user_input):