Updated files to fix runtime error and add gTTS

app.py

@@ -1,84 +1,42 @@
-import gradio as gr
-import requests
-import os
-import speech_recognition as sr
-import pyttsx3
-
-
-TOGETHER_API_KEY = "92269fefcc8df100e2d395daab78ba62c0f3b64dbd477227020dce924e7821fe"
-
-# Text-to-speech setup
-tts_engine = pyttsx3.init()
-
-def speak(text):
-    tts_engine.say(text)
-    tts_engine.runAndWait()
-
-# 🎤 Speech-to-text function
-def transcribe_audio(audio):
-    recognizer = sr.Recognizer()
-    with sr.AudioFile(audio) as source:
-        audio_data = recognizer.record(source)
-    try:
-        return recognizer.recognize_google(audio_data)
-    except sr.UnknownValueError:
-        return "Sorry, I could not understand your voice."
-    except sr.RequestError:
-        return "Could not request results from speech recognition service."
-
-# 🤖 Call Together API
-def call_together_api(message, history):
-    messages = [{"role": "system", "content": "You are Sambit AI, a helpful assistant."}]
-    for user_msg, ai_msg in history:
-        messages.append({"role": "user", "content": user_msg})
-        messages.append({"role": "assistant", "content": ai_msg})
-    messages.append({"role": "user", "content": message})
-
-    response = requests.post(
-        "https://api.together.xyz/v1/chat/completions",
-        headers={
-            "Authorization": f"Bearer {TOGETHER_API_KEY}",
-            "Content-Type": "application/json"
-        },
-        json={
-            "model": "meta-llama/Llama-3-70b-instruct",
-            "messages": messages,
-            "temperature": 0.7,
-        }
-    )
-
-    if response.status_code == 200:
-        reply = response.json()["choices"][0]["message"]["content"]
-        speak(reply)
-        return reply
-    elif response.status_code == 429:
-        return "Rate limit reached. Please wait a bit."
-    else:
-        return f"Error: {response.json()['error']['message']}"
-
-# 🎤🎧 UI function (text + voice input)
-def chatbot_interface(message, audio, history=[]):
-    if audio is not None:
-        message = transcribe_audio(audio)
-    if message.strip() == "":
-        return "", history
-    reply = call_together_api(message, history)
-    history.append((message, reply))
-    return "", history
-
-# 🎨 Dark theme UI
-with gr.Blocks(theme=gr.themes.Monochrome()) as demo:
-    gr.Markdown("# 🤖 Sambit AI\nAsk anything via text or voice")
-
-    chatbot = gr.Chatbot(type="messages")
-    msg = gr.Textbox(placeholder="Type your message here...", label="Text Input")
-    audio_input = gr.Audio(sources="microphone", type="filepath", label="Or speak here")
-
-    submit_btn = gr.Button("Send")
-
-    state = gr.State([])
-
-    submit_btn.click(chatbot_interface, inputs=[msg, audio_input, state], outputs=[msg, state])
-    msg.submit(chatbot_interface, inputs=[msg, audio_input, state], outputs=[msg, state])
-
-demo.launch()
+
+import gradio as gr
+from huggingface_hub import InferenceClient
+from gtts import gTTS
+import tempfile
+
+client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
+
+def speak_text(text):
+    tts = gTTS(text)
+    with tempfile.NamedTemporaryFile(delete=False, suffix=".mp3") as fp:
+        tts.save(fp.name)
+        return fp.name
+
+def respond(message, history):
+    history = history or []
+    prompt = ""
+    for user_msg, bot_msg in history:
+        prompt += f"<|user|> {user_msg}\n<|assistant|> {bot_msg}\n"
+    prompt += f"<|user|> {message}\n<|assistant|>"
+
+    response = client.text_generation(prompt, max_new_tokens=512, temperature=0.7, top_p=0.95, repetition_penalty=1.0, do_sample=True)
+    response = response.strip().split("<|assistant|>")[-1].strip()
+
+    history.append((message, response))
+    audio_path = speak_text(response)
+    return history, history, audio_path
+
+with gr.Blocks() as demo:
+    gr.Markdown("# Sambit AI 🤖")
+    chatbot = gr.Chatbot([], label="Chat with AI", type="messages")
+    msg = gr.Textbox(label="Type your message here")
+    audio_output = gr.Audio(label="AI Voice", interactive=False)
+
+    clear = gr.Button("Clear Chat")
+
+    state = gr.State([])
+
+    msg.submit(respond, [msg, state], [chatbot, state, audio_output])
+    clear.click(lambda: ([], [], None), None, [chatbot, state, audio_output])
+
+demo.launch()

requirements.txt

@@ -1,4 +1,4 @@
-gradio
-requests
-speechrecognition
-pyttsx3
+
+gradio
+huggingface_hub
+gTTS