general_chatbot / app.py
JaweriaGenAI's picture
Update app.py
299800e verified
raw
history blame
4.66 kB
import gradio as gr
import os, json, re, uuid
from datetime import datetime
from pydub import AudioSegment
import whisper
import requests
# πŸ” Load API key securely from environment
groq_key = os.getenv("GROQ_API_KEY")
# 🧠 Load Whisper model
whisper_model = whisper.load_model("base")
# πŸ’¬ Chat function
def chat_with_groq(message, history):
messages = [{"role": "system", "content": "You are JAWERIA'SBOT πŸ€– – cheerful, emoji-savvy, and sleek."}]
messages += history + [{"role": "user", "content": message}]
headers = {
"Authorization": f"Bearer {groq_key}",
"Content-Type": "application/json"
}
payload = {
"model": "llama3-70b-8192",
"messages": messages
}
response = requests.post("https://api.groq.com/openai/v1/chat/completions", headers=headers, json=payload)
reply = response.json()["choices"][0]["message"]["content"]
history += [{"role": "user", "content": message}, {"role": "assistant", "content": reply}]
return "", history, history
# πŸŽ™οΈ Audio transcription
def transcribe_audio(audio_path):
if audio_path is None or not os.path.exists(audio_path):
return "⚠️ No audio recorded."
try:
temp_wav = f"{uuid.uuid4()}.wav"
AudioSegment.from_file(audio_path).export(temp_wav, format="wav")
result = whisper_model.transcribe(temp_wav)
os.remove(temp_wav)
return result["text"]
except Exception as e:
return f"❌ Transcription error: {e}"
# πŸ’Ύ Save/load
def save_session(history):
prompt = next((m["content"] for m in history if m["role"] == "user"), "chat")
title = re.sub(r"[^\w\s]", "", prompt).strip()
title = " ".join(title.split()[:6])
timestamp = datetime.now().strftime("%b %d %Y %H-%M")
filename = f"{title} - {timestamp}.json"
with open(filename, "w", encoding="utf-8") as f:
json.dump(history, f, indent=2, ensure_ascii=False)
return f"βœ… Saved `{filename[:-5]}`"
def list_saved_files():
return sorted([f[:-5] for f in os.listdir() if f.endswith(".json")])
def load_chat(name):
filename = f"{name}.json"
try:
with open(filename, "r", encoding="utf-8") as f:
history = json.load(f)
return history, history, f"βœ… Loaded `{name}`"
except Exception as e:
return [], [], f"❌ Load error: {e}"
# 🌌 Gradio UI
with gr.Blocks(css="""
body {
background-color: #111 !important;
color: white !important;
}
* {
color: white !important;
}
h1 {
text-align: center !important;
color: #00ccff !important;
margin: auto !important;
}
.gr-chatbot-message, .gr-textbox, textarea, input[type='text'],
select, .gr-dropdown, .gr-markdown, .gr-label {
background-color: #222 !important;
color: white !important;
border-radius: 6px;
}
.gr-button {
background-color: #007acc !important;
color: white !important;
}
.gr-dropdown {
max-height: 150px;
overflow-y: auto;
}
""") as demo:
state = gr.State([])
gr.Markdown("# ✨ JAWERIA'SBOT πŸ€–")
gr.Markdown("<div style='text-align:center;'>Speak or type β€” your assistant listens and replies with text πŸ’¬</div>")
chatbot = gr.Chatbot(type="messages", height=350)
chat_input = gr.Textbox(label="πŸ’¬ Message", placeholder="Type or speak your message...")
send_btn = gr.Button("Send πŸš€")
with gr.Row():
voice_input = gr.Audio(label="🎀 Speak", type="filepath", interactive=True)
voice_btn = gr.Button("πŸŽ™οΈ Transcribe to Text")
with gr.Row():
new_chat_btn = gr.Button("πŸ†• New")
save_btn = gr.Button("πŸ’Ύ Save")
saved_dropdown = gr.Dropdown(label="πŸ“‚ Load Saved", choices=list_saved_files())
load_btn = gr.Button("πŸ“₯ Load")
save_msg = gr.Markdown()
load_msg = gr.Markdown()
# πŸ”— Bind events
send_btn.click(chat_with_groq, inputs=[chat_input, state], outputs=[chat_input, chatbot, state])
chat_input.submit(chat_with_groq, inputs=[chat_input, state], outputs=[chat_input, chatbot, state])
voice_btn.click(transcribe_audio, inputs=[voice_input], outputs=[chat_input])
new_chat_btn.click(fn=lambda: ("", [], []), outputs=[chat_input, chatbot, state])
save_btn.click(fn=save_session, inputs=[state], outputs=[save_msg])
save_btn.click(fn=list_saved_files, outputs=[saved_dropdown])
load_btn.click(fn=load_chat, inputs=[saved_dropdown], outputs=[chatbot, state, load_msg])
demo.load(fn=list_saved_files, outputs=[saved_dropdown])
demo.launch()