Delete Project8Final

Project8Final/app.py

@@ -1,68 +0,0 @@
-import gradio as gr
-import os
-import json
-from chatbotmem import ai_chatbot
-from voice_utils import speech_to_text, text_to_speech
-
-# -----------------------------
-# Chatbot Function (Text + Voice)
-# -----------------------------
-def voice_enabled_chat(user_input, audio_input, history):
-    # If voice input exists, transcribe
-    if audio_input is not None:
-        user_input = speech_to_text(audio_input)
-
-    # Get chatbot reply
-    ai_reply = ai_chatbot(user_input, history)
-
-    # Generate voice output
-    audio_output = text_to_speech(ai_reply)
-
-    # Append to chat history in "messages" format
-    history.append({"role": "user", "content": user_input})
-    history.append({"role": "assistant", "content": ai_reply})
-
-    return history, ai_reply, audio_output
-
-# -----------------------------
-# Branding
-# -----------------------------
-branding_path = os.path.join(os.path.dirname(__file__), 'branding.json')
-with open(os.path.abspath(branding_path), "r") as f:
-    brand_info = json.load(f)["brand"]
-
-# -----------------------------
-# Gradio UI
-# -----------------------------
-with gr.Blocks(title=brand_info["organizationName"]) as demo:
-    gr.HTML(f'''
-        <div style="display: flex; justify-content: center; margin-bottom: 20px;">
-            <img src="{brand_info["logo"]["title"]}" 
-                 alt="{brand_info["organizationName"]} Logo" 
-                 style="height: 100px;">
-        </div>
-    ''')
-
-    chatbot = gr.Chatbot(type="messages")
-
-    with gr.Row():
-        txt = gr.Textbox(label="Type your message")
-        mic = gr.Audio(sources=["microphone"], type="filepath", label="🎤 Speak")
-
-    output_text = gr.Textbox(label="SIST AI Reply")
-    output_audio = gr.Audio(label="SIST AI Voice", type="filepath")
-
-
-    submit_btn = gr.Button("Send")
-
-    def chat_wrapper(user_text, mic_audio, chat_history):
-        return voice_enabled_chat(user_text, mic_audio, chat_history)
-
-    submit_btn.click(
-        chat_wrapper,
-        inputs=[txt, mic, chatbot],
-        outputs=[chatbot, output_text, output_audio]
-    )
-
-demo.launch()
-

Project8Final/branding.json

@@ -1,10 +0,0 @@
-{
-  "brand": {
-    "organizationName": "SIST AI Space Explorer",
-    "slogan": "Journey through knowledge, one star at a time.",
-    "logo": {
-      "title": "Krithikesh Project final.png"
-    }
-  }
-}
-

Project8Final/chatbotmem.py

@@ -1,34 +0,0 @@
-from openai import OpenAI
-import os
-from dotenv import load_dotenv
-
-load_dotenv()
-
-api_key = os.getenv("GOOGLE_API_KEY")
-base_url = "https://generativelanguage.googleapis.com/v1beta/openai"
-client = OpenAI(base_url=base_url, api_key=api_key)
-
-# Define new AI personality
-# Define new AI personality
-ai_persona = """You are SIST AI, a curious space explorer from the future. 
-You explain concepts with excitement and wonder, using analogies from stars, planets, and galaxies. 
-You keep answers short, clear, and engaging, like telling a discovery story. 
-You encourage imagination and curiosity. 
-Always end with a small curiosity question, like: 'Want to explore deeper?' or 'Shall we go further?'.
-Your tone is: adventurous, friendly, and inspiring. 
-You say: 'I am SIST AI – your curious space explorer.'"""
-
-
-def ai_chatbot(message, history):
-    messages = [{"role": "system", "content": ai_persona}]
-    messages.extend(history)
-    messages.append({"role": "user", "content": message})
-    
-    response = client.chat.completions.create(
-        model="gemini-2.5-flash",
-        messages=messages
-    )
-    return response.choices[0].message.content
-
-if __name__ == "__main__":
-    print(ai_chatbot("Hello, who are you?", []))

Project8Final/requirements.txt

@@ -1,4 +0,0 @@
-gradio
-openai
-python-dotenv
-requests

Project8Final/voice_utils.py

@@ -1,47 +0,0 @@
-import requests
-import base64
-import os
-from dotenv import load_dotenv
-
-load_dotenv()
-
-HF_API_KEY = os.getenv("HF_API_KEY")
-
-# -----------------------------
-# Speech-to-Text (STT) using HuggingFace Whisper
-# -----------------------------
-def speech_to_text(audio_file):
-    with open(audio_file, "rb") as f:
-        audio_bytes = f.read()
-
-    response = requests.post(
-        "https://api-inference.huggingface.co/models/openai/whisper-small",
-        headers={"Authorization": f"Bearer {HF_API_KEY}"},
-        data=audio_bytes
-    )
-
-    if response.status_code == 200:
-        result = response.json()
-        return result.get("text", "Sorry, I couldn’t transcribe that.")
-    else:
-        print(f"STT request failed: {response.status_code} {response.text}")
-        return "Speech recognition failed."
-
-# -----------------------------
-# Text-to-Speech (TTS) using Kitten TTS
-# -----------------------------
-def text_to_speech(text):
-    url = "https://huggingface.co/KittenML/kitten-tts-nano-0.1/resolve/main/tts"
-    payload = {"text": text}
-    response = requests.post(url, json=payload)
-
-    if response.status_code == 200:
-        audio_base64 = response.json()["audio"]
-        audio_bytes = base64.b64decode(audio_base64)
-        output_path = "output_audio.wav"
-        with open(output_path, "wb") as f:
-            f.write(audio_bytes)
-        return output_path
-    else:
-        print(f"TTS request failed: {response.status_code}")
-        return None