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app.py

@@ -1,64 +1,84 @@
-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 respond(
-    message,
-    history: list[tuple[str, str]],
-    system_message,
-    max_tokens,
-    temperature,
-    top_p,
-):
-    messages = [{"role": "system", "content": system_message}]
-
-    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})
-
-    response = ""
-
-    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 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()
+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()

requirements.txt

@@ -1 +1,4 @@
-huggingface_hub==0.25.2
+gradio
+requests
+speechrecognition
+pyttsx3