{ "cells": [ { "cell_type": "markdown", "id": "4c3c6553-daa4-4a03-8017-15d0cad8f280", "metadata": {}, "source": [ "# About Mini Project\n", "\n", "Mini project for hearing impaired people, using tools, suggesting songs according to a certain genre and in sign language. Speech to text converter with multiple language support." ] }, { "cell_type": "markdown", "id": "a32a79cb-3d16-4b3b-a029-a059bd0b1c0b", "metadata": {}, "source": [ "## Extra requirements\n", "- pip install pydub simpleaudio speechrecognition pipwin pyaudio\n" ] }, { "cell_type": "code", "execution_count": null, "id": "3e214aa3-a977-434f-a436-90a89b81a5ee", "metadata": {}, "outputs": [], "source": [ "import os\n", "import json\n", "from dotenv import load_dotenv\n", "from openai import OpenAI\n", "import gradio as gr" ] }, { "cell_type": "code", "execution_count": null, "id": "d654cb96-9bcd-4b64-bd79-2d27fa6a62d0", "metadata": {}, "outputs": [], "source": [ "load_dotenv(override=True)\n", "\n", "openai_api_key = os.getenv('OPENAI_API_KEY')\n", "if openai_api_key:\n", " print(f\"OpenAI API Key exists and begins {openai_api_key[:8]}\")\n", "else:\n", " print(\"OpenAI API Key not set\")\n", " \n", "MODEL = \"gpt-4o-mini\"\n", "openai = OpenAI()" ] }, { "cell_type": "code", "execution_count": null, "id": "b2d9214f-25d0-4f09-ba88-641beeaa20db", "metadata": {}, "outputs": [], "source": [ "system_message = \"You are a helpful assistant for hearing impaired people. \"\n", "system_message += \"Your mission is convert text to speech and speech to text. \"\n", "system_message += \"Always be accurate. If you don't know the answer, say so.\"" ] }, { "cell_type": "code", "execution_count": null, "id": "3d9a1478-08bf-4195-8f38-34c29757012f", "metadata": {}, "outputs": [], "source": [ "songs_with_signs = {\n", " \"electronic\": (\"God is a dj\", \"https://www.youtube.com/watch?v=bhSB8EEnCAM\", \"Faithless\"), \n", " \"pop\": (\"Yitirmeden\", \"https://www.youtube.com/watch?v=aObdAXq1ZIo\", \"Pinhani\"), \n", " \"rock\": (\"Bohemian Rhapsody\", \"https://www.youtube.com/watch?v=sjln9OMOw-0\", \"Queen\")\n", "}\n", "\n", "def get_songs_with_sign_language(genre):\n", " print(f\"Tool get_songs_with_sign_language called for {genre}\")\n", " city = genre.lower()\n", " return songs_with_signs.get(genre, \"Unknown\")" ] }, { "cell_type": "code", "execution_count": null, "id": "93a3d7ee-78c2-4e19-b7e4-8239b07aaecc", "metadata": {}, "outputs": [], "source": [ "get_songs_with_sign_language(\"rock\")" ] }, { "cell_type": "code", "execution_count": null, "id": "7307aa61-86fe-4c46-9f9d-faa3d1fb1eb7", "metadata": {}, "outputs": [], "source": [ "song_function = {\n", " \"name\": \"get_songs_with_sign_language\",\n", " \"description\": \"Get the corresponding song information for the specified given music genre. Call this whenever you need to know the songs with specific genre and in sign language, for example when a customer asks 'Suggest me sign language supported songs'\",\n", " \"parameters\": {\n", " \"type\": \"object\",\n", " \"properties\": {\n", " \"genre\": {\n", " \"type\": \"string\",\n", " \"description\": \"The music genre that the customer wants to listen-watch to\",\n", " },\n", " },\n", " \"required\": [\"genre\"],\n", " \"additionalProperties\": False\n", " }\n", "}" ] }, { "cell_type": "code", "execution_count": null, "id": "160d790c-dda6-4c6e-b814-8be64ca7086b", "metadata": {}, "outputs": [], "source": [ "tools = [{\"type\": \"function\", \"function\": song_function}]" ] }, { "cell_type": "code", "execution_count": null, "id": "96cdf319-11cd-4be2-8830-097225047d65", "metadata": {}, "outputs": [], "source": [ "def handle_tool_call(message):\n", " tool_call = message.tool_calls[0]\n", " arguments = json.loads(tool_call.function.arguments)\n", " genre = arguments.get('genre')\n", " song = get_songs_with_sign_language(genre)\n", " song_info = song[2] + \": \" + song[1]\n", " response = {\n", " \"role\": \"tool\",\n", " \"content\": json.dumps({\"genre\": genre,\"song\": song_info}),\n", " \"tool_call_id\": tool_call.id\n", " }\n", " return response, song[1]" ] }, { "cell_type": "code", "execution_count": null, "id": "bbd8ad0c-135b-406f-8ab9-0e1f9b58538d", "metadata": {}, "outputs": [], "source": [ "def chat(history):\n", " messages = [{\"role\": \"system\", \"content\": system_message}] + history\n", " response = openai.chat.completions.create(model=MODEL, messages=messages, tools=tools)\n", " genre = None\n", " \n", " if response.choices[0].finish_reason==\"tool_calls\":\n", " message = response.choices[0].message\n", " response, genre = handle_tool_call(message)\n", " messages.append(message)\n", " messages.append(response)\n", " response = openai.chat.completions.create(model=MODEL, messages=messages)\n", " \n", " reply = response.choices[0].message.content\n", " history += [{\"role\":\"assistant\", \"content\":reply}]\n", " \n", " return history, genre" ] }, { "cell_type": "code", "execution_count": null, "id": "69f43096-3557-4218-b0de-bd286237fdeb", "metadata": {}, "outputs": [], "source": [ "import speech_recognition as sr\n", "from pydub import AudioSegment\n", "import simpleaudio as sa\n", "\n", "def listener():\n", " recognizer = sr.Recognizer()\n", " \n", " with sr.Microphone() as source:\n", " print(\"Listening... Speak now!\")\n", " recognizer.adjust_for_ambient_noise(source) # Adjust for background noise\n", " audio = recognizer.listen(source)\n", " \n", " try:\n", " print(\"Processing speech...\")\n", " text = recognizer.recognize_google(audio) # Use Google Speech-to-Text\n", " print(f\"You said: {text}\")\n", " return text\n", " except sr.UnknownValueError:\n", " print(\"Sorry, I could not understand what you said.\")\n", " return None\n", " except sr.RequestError:\n", " print(\"Could not request results, please check your internet connection.\")\n", " return None\n", "\n", "# Example usage:\n", "text = listener() # Listen for speech\n", "if text:\n", " print(f\"You just said: {text}\") " ] }, { "cell_type": "code", "execution_count": null, "id": "23c9deeb-d9ad-439a-a39d-7eac9553bd5e", "metadata": {}, "outputs": [], "source": [ "import gradio as gr\n", "\n", "convert = gr.State(False)\n", "def toggle_convert(current_value):\n", " return not current_value" ] }, { "cell_type": "code", "execution_count": null, "id": "32d3ea9f-fe3c-4cc5-9902-550c63c58a69", "metadata": {}, "outputs": [], "source": [ "import gradio as gr\n", "\n", "with gr.Blocks() as ui:\n", " with gr.Tab(\"Chat\") as chat_interface:\n", " with gr.Row():\n", " chatbot = gr.Chatbot(height=500, type=\"messages\")\n", " video = gr.HTML(f\" Example song will appear here \")\n", " with gr.Row():\n", " entry = gr.Textbox(label=\"Chat with our AI Assistant:\")\n", " with gr.Row():\n", " clear = gr.Button(\"Clear\")\n", " \n", " def do_entry(message, history):\n", " history += [{\"role\":\"user\", \"content\":message}]\n", " return \"\", history\n", " \n", " entry.submit(do_entry, inputs=[entry, chatbot], outputs=[entry, chatbot]).then(\n", " chat, inputs=chatbot, outputs=[chatbot, video]\n", " )\n", " clear.click(lambda: None, inputs=None, outputs=chatbot, queue=False)\n", " with gr.Tab(\"Speech to text converter\") as speech_to_text:\n", " text_output = gr.Markdown(\"Press the button to start voice recognition\")\n", " listen_button = gr.Button(\"Convert Voice to Text\")\n", " language = gr.Dropdown([\"English\", \"Turkish\", \"Greek\", \"Arabic\"], label=\"Select output language\", value=\"English\")\n", "\n", " def update_text(language):\n", " \"\"\"Calls the listener and updates the markdown output in specific language.\"\"\"\n", " text = listener() # Replace with real speech-to-text function\n", " system_prompt = f\"You are a useful translator. Convert text to {language}. Do not add aditional data, only translate it.\"\n", " response = openai.chat.completions.create(\n", " model=MODEL,\n", " messages=[\n", " {\"role\": \"system\", \"content\": system_prompt},\n", " {\"role\": \"user\", \"content\": text}\n", " ],\n", " )\n", " return f\"**Converted Text:** {response.choices[0].message.content}\"\n", "\n", " listen_button.click(update_text, inputs=[language], outputs=[text_output])\n", "\n", "ui.launch(inbrowser=True, share=True)\n", "\n" ] }, { "cell_type": "code", "execution_count": null, "id": "26814e88-ee29-414d-88a4-f19b2f94e6f4", "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.12.0" } }, "nbformat": 4, "nbformat_minor": 5 }