import gradio as gr def chatbot_response(message): message = message.lower() if "mituweli" in message or "ubwisungane" in message: return "Kugira ngo wiyandikishe kuri mituweli, jya kuri irembo.gov.rw, uhitemo 'Ubwisungane mu kwivuza'. Wuzuza ifishi, wishyure hakoreshejwe Mobile Money." elif "indangamuntu" in message: return "Niba wabuze indangamuntu, jya kuri Irembo uhitemo 'Gusaba indangamuntu nshya' cyangwa saba raporo kuri RIB mbere." elif "icyemezo cy’amavuko" in message or "acte de naissance" in message: return "Icyemezo cy’amavuko gisabirwa kuri Irembo. Hitamo 'Serivisi z’irangamimerere' hanyuma usabe icyemezo." elif "nakurikira gute" in message or "service yanjye" in message: return "Jya kuri konti yawe kuri Irembo.gov.rw, ujye ahanditse 'Serivisi zasabwe' urebe aho igeze." else: return "Ndakumva! Ariko sinabashije kumenya ibyo ushaka neza. Gerageza kubaza ibijyanye na serivisi nk'icyemezo, mituweli, cyangwa indangamuntu." iface = gr.Interface(fn=chatbot_response, inputs=gr.Textbox(lines=2, placeholder="Andika ikibazo cyawe hano..."), outputs="text", title="UmusekeBot", description="Chatbot ifasha kumenya uko wasaba serivisi kuri Irembo cyangwa ahandi.") iface.launch()

app.py

@@ -1,64 +1,28 @@
 import gradio as gr
-from huggingface_hub import InferenceClient
 
-"""
-For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
-"""
-client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
+def chatbot_response(message):
+    message = message.lower()
 
+    if "mituweli" in message or "ubwisungane" in message:
+        return "Kugira ngo wiyandikishe kuri mituweli, jya kuri irembo.gov.rw, uhitemo 'Ubwisungane mu kwivuza'. Wuzuza ifishi, wishyure hakoreshejwe Mobile Money."
+    
+    elif "indangamuntu" in message:
+        return "Niba wabuze indangamuntu, jya kuri Irembo uhitemo 'Gusaba indangamuntu nshya' cyangwa saba raporo kuri RIB mbere."
 
-def respond(
-    message,
-    history: list[tuple[str, str]],
-    system_message,
-    max_tokens,
-    temperature,
-    top_p,
-):
-    messages = [{"role": "system", "content": system_message}]
+    elif "icyemezo cy’amavuko" in message or "acte de naissance" in message:
+        return "Icyemezo cy’amavuko gisabirwa kuri Irembo. Hitamo 'Serivisi z’irangamimerere' hanyuma usabe icyemezo."
 
-    for val in history:
-        if val[0]:
-            messages.append({"role": "user", "content": val[0]})
-        if val[1]:
-            messages.append({"role": "assistant", "content": val[1]})
+    elif "nakurikira gute" in message or "service yanjye" in message:
+        return "Jya kuri konti yawe kuri Irembo.gov.rw, ujye ahanditse 'Serivisi zasabwe' urebe aho igeze."
 
-    messages.append({"role": "user", "content": message})
+    else:
+        return "Ndakumva! Ariko sinabashije kumenya ibyo ushaka neza. Gerageza kubaza ibijyanye na serivisi nk'icyemezo, mituweli, cyangwa indangamuntu."
 
-    response = ""
+iface = gr.Interface(fn=chatbot_response,
+                     inputs=gr.Textbox(lines=2, placeholder="Andika ikibazo cyawe hano..."),
+                     outputs="text",
+                     title="UmusekeBot",
+                     description="Chatbot ifasha kumenya uko wasaba serivisi kuri Irembo cyangwa ahandi.")
 
-    for message in client.chat_completion(
-        messages,
-        max_tokens=max_tokens,
-        stream=True,
-        temperature=temperature,
-        top_p=top_p,
-    ):
-        token = message.choices[0].delta.content
+iface.launch()
 
-        response += token
-        yield response
-
-
-"""
-For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
-"""
-demo = gr.ChatInterface(
-    respond,
-    additional_inputs=[
-        gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
-        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
-        gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
-        gr.Slider(
-            minimum=0.1,
-            maximum=1.0,
-            value=0.95,
-            step=0.05,
-            label="Top-p (nucleus sampling)",
-        ),
-    ],
-)
-
-
-if __name__ == "__main__":
-    demo.launch()