Update app.py

app.py

@@ -1,26 +1,14 @@
 import os
 import gradio as gr
+from groq import Groq
 import langdetect
 import requests
 import random
-from groq import Groq
-
 
 GROQ_API_KEY = os.getenv("GROQ_API_KEY", "")
 
 client = Groq(api_key=os.getenv("GROQ_API_KEY"))
 
-model="llama-3.3-70b-versatile"
-import os
-import gradio as gr
-from huggingface_hub import InferenceClient
-import langdetect
-import requests
-import random
-
-GROQ_API_KEY = os.getenv("GROQ_API_KEY", "")
-client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
-
 def detect_language(text):
     """Detects whether the input text is in French or English."""
     lang = langdetect.detect(text)
@@ -33,6 +21,7 @@ def find_reservation_link(query):
     response = requests.get(search_url)
     data = response.json()
     
+    # Extract the first link
     if "items" in data and len(data["items"]) > 0:
         return data["items"][0]["link"]
     
@@ -49,51 +38,71 @@ def handle_button_click(button_text):
         return "Plan a 1-week trip for me."
     return ""
 
-def respond(
-    message,
-    history: list[tuple[str, str]],
-    system_message,
-    max_tokens,
-    temperature,
-    top_p,
-):
-    messages = [{"role": "system", "content": system_message}]
+def chat_with_bot(message, history):
+    """Handles user queries and maintains chat memory."""
     
-    for val in history:
-        if val[0]:
-            messages.append({"role": "user", "content": val[0]})
-        if val[1]:
-            messages.append({"role": "assistant", "content": val[1]})
-
-    messages.append({"role": "user", "content": message})
+    if message in ["Trip recommendations", "Send me somewhere!", "1 week planned vacations"]:
+        message = handle_button_click(message)
     
-    response = ""
+    # Detect language (default to English if detection is uncertain)
+    language = detect_language(message)
+
+    system_message = {
+        "en": "You help users plan trips. Keep responses short and clear. If a user asks about specifically booking a flight, hotel, or reservation, try to find a relevant link. Else, don't give a link.",
+        "fr": "Vous aidez les utilisateurs à planifier des voyages. Réponses courtes et simples. Si un utilisateur demande spécifiquement une réservation d'hôtel ou de vol, essayez de trouver un lien pertinent. Sinon, pas besoin."
+    }
+
+    # Convert history into Groq-compatible message format
+    messages = [{"role": "system", "content": system_message[language]}]
     
-    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
-        response += token
-        yield response
+    for user_msg, bot_msg in history:
+        messages.append({"role": "user", "content": user_msg})
+        messages.append({"role": "assistant", "content": bot_msg})
+
+    # Add the latest user message
+    messages.append({"role": "user", "content": message})
+
+    # Check if the user is looking for reservations
+    if any(keyword in message.lower() for keyword in ["book a flight", "hotel reservation", "car rental", "book a room"]):
+        link = find_reservation_link(message)
+        return history + [(message, f"Here's a link that might help: {link}")], ""
+
+    # Call Groq's AI model
+    response = client.chat.completions.create(
+        model="llama-3.3-70b-versatile",
+        messages=messages,
+        temperature=0.7,
+        max_tokens=1024,
+        top_p=1
+    )
 
-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)",
-        ),
-    ],
-)
+    bot_reply = response.choices[0].message.content
+    history.append((message, bot_reply))
+    return history, ""
 
-demo.launch(server_name="0.0.0.0", server_port=7860, share=True)
+# Gradio interface with memory
+with gr.Blocks() as demo:
+    gr.Markdown("# 🌍 ***FlightAI - Your Travel Assistant - Votre Assistant de Voyage*** ✈️\n")
+    
+    chatbot = gr.Chatbot()
+    chatbot.value = [
+        ("", "Hey! I'm FlightAI. Tell me your travel plans or pick a button below!\n\nSalut! Je suis FlightAI. Dis-moi ton projet de voyage ou choisis un bouton ci-dessous!")
+    ]
+    
+    with gr.Row():
+        btn1 = gr.Button("Trip recommendations / Recommendations de Voyage")
+        btn2 = gr.Button("Send me somewhere! / Envoyez-moi quelques part!")
+        btn3 = gr.Button("1 week planned vacations / Voyage d'une semaine planifié")
+    
+    user_input = gr.Textbox(placeholder="Type your travel question here...")
+    
+    def button_click(btn_text):
+        response, _ = chat_with_bot(btn_text, chatbot.value)
+        return response, ""
+    
+    btn1.click(button_click, inputs=[btn1], outputs=[chatbot, user_input])
+    btn2.click(button_click, inputs=[btn2], outputs=[chatbot, user_input])
+    btn3.click(button_click, inputs=[btn3], outputs=[chatbot, user_input])
+    user_input.submit(chat_with_bot, inputs=[user_input, chatbot], outputs=[chatbot, user_input])
+    
+    demo.launch()