final app

.streamlit/config.toml

@@ -6,4 +6,5 @@ textColor="#f5f8fc"
 font="sans serif"
 
 [server]
-runOnSave = true
+runOnSave = true
+maxUploadSize = 10

app.py

@@ -0,0 +1,592 @@
+import streamlit as st
+from audio_recorder_streamlit import audio_recorder
+from groq_models import create_groq_agent, groq_chatbot, get_tools, summarizer_model
+from langchain_community.document_loaders import Docx2txtLoader
+from langchain_community.document_loaders import TextLoader
+from PIL import Image
+from io import BytesIO
+import base64
+import docx
+from streamlit_lottie import st_lottie
+import json
+from utils import set_safety_settings, about, extract_all_pages_as_images, speech_to_text
+import google.generativeai as genai
+import os, random, validators
+import tempfile
+import asyncio
+import edge_tts
+from dotenv import load_dotenv
+load_dotenv()
+
+st.set_page_config(
+    page_title="Super GPT",
+    page_icon="⚡",
+    layout="wide",
+    initial_sidebar_state="auto",
+    menu_items={"About": about(), "Get Help":"https://www.linkedin.com/in/aasher-kamal-a227a124b/"},
+)
+
+###--- Title ---###
+st.markdown("""
+    <h1 style='text-align: center;'>
+        <span style='color: #F81F6F;'>Super</span> 
+        <span style='color: #f5f8fc;'>AI Assistant</span>
+    </h1>
+""", unsafe_allow_html=True)
+
+
+google_models = [
+    "gemini-1.5-flash",
+    "gemini-1.5-pro",
+]
+
+groq_models = [
+    "llama-3.1-8b-instant",
+    "llama-3.1-70b-versatile",
+    "llama3-70b-8192",
+    "llama3-8b-8192",
+    "gemma2-9b-it",
+    "mixtral-8x7b-32768"
+]
+
+voices = {
+    "William":"en-AU-WilliamNeural",
+    "James":"en-PH-JamesNeural",
+    "Jenny":"en-US-JennyNeural",
+    "US Guy":"en-US-GuyNeural",
+    "Sawara":"hi-IN-SwaraNeural",
+}
+
+
+def speech_recoginition():
+    pass
+
+@st.cache_data
+def load_lottie_file(filepath: str):
+    with open(filepath, "r") as f:
+        return json.load(f)
+
+
+async def generate_speech(text, voice):
+    communicate = edge_tts.Communicate(text, voice)
+    with tempfile.NamedTemporaryFile(delete=False, suffix=".mp3") as temp_file:
+        await communicate.save(temp_file.name)
+        temp_file_path = temp_file.name
+    return temp_file_path
+
+
+def get_audio_player(file_path):
+    with open(file_path, "rb") as f:
+        data = f.read()
+        b64 = base64.b64encode(data).decode()
+        return f'<audio autoplay="true" src="data:audio/mp3;base64,{b64}">'
+
+def generate_voice(text, voice):
+    text_to_speak = (text).translate(str.maketrans('', '', '#-*_😊👋😄😁🥳👍🤩😂😎')) # Removing special chars and emojis
+    with st.spinner("Generating voice response..."):
+        temp_file_path = asyncio.run(generate_speech(text_to_speak, voice)) 
+        audio_player_html = get_audio_player(temp_file_path)  # Create an audio player
+        st.markdown(audio_player_html, unsafe_allow_html=True)
+        os.unlink(temp_file_path)  # Clean up the temporary audio file
+
+
+def get_llm_info(available_models):
+    with st.sidebar:
+        tip =tip = "Select Gemini models if you require multi-modal capabilities (text, image, audio and video inputs)"
+        model = st.selectbox("Choose LLM:", available_models, help=tip)
+
+        model_type = None
+        if model.startswith(("llama", "gemma", "mixtral")): model_type = "groq"
+        elif model.startswith("gemini"): model_type = "google"
+
+        with st.popover("⚙️Model Parameters", use_container_width=True):
+            temp = st.slider("Temperature:", min_value=0.0,
+                                            max_value=2.0, value=0.5, step=0.5)
+            
+            max_tokens = st.slider("Maximum Tokens:", min_value=100,
+                                        max_value=2000, value=400, step=200)
+    return model, model_type, temp, max_tokens
+
+
+###--- Function to convert base64 to temp file ---###
+def base64_to_temp_file(base64_string, unique_name, file_extension):
+    base64_string = base64_string.split(",")[1]
+    file_bytes = BytesIO(base64.b64decode(base64_string))
+    temp_file_path = f"{unique_name}.{file_extension}"
+    with open(temp_file_path, "wb") as temp_file:
+        temp_file.write(file_bytes.read())
+    return temp_file_path
+
+##----Preparing messages for Gemini----##
+def messages_to_gemini(messages):
+    gemini_messages = []
+    prev_role = None
+    uploaded_files = set([file.display_name.split(".")[0] for file in genai.list_files()])
+
+    for message in messages:
+        if prev_role and (prev_role == message["role"]):
+            gemini_message = gemini_messages[-1]
+        else:
+            gemini_message = {
+                "role": "model" if message["role"] == "assistant" else "user",
+                "parts": [],
+            }
+
+        for content in message["content"]:
+            if content["type"] in ["text","docx_file"]:
+                gemini_message["parts"].append(content[content["type"]])
+
+            elif content["type"] == "image_url":
+                gemini_message["parts"].append(base64_to_image(content["image_url"]["url"]))
+
+            elif content["type"] in ["video_file", "audio_file", "speech_input"]:
+                file_name = content['unique_name']
+
+                if file_name not in uploaded_files:
+                    temp_file_path = base64_to_temp_file(content[content["type"]], file_name, "mp4" if content["type"] == "video_file" else "wav")
+
+                    with st.spinner(f"Sending {content['type'].replace('_', ' ')} to Gemini..."):
+                        gemini_message["parts"].append(genai.upload_file(path=temp_file_path))
+                    os.remove(temp_file_path)
+
+            elif content["type"] == "pdf_file":
+                if content['pdf_file'].split(".")[0] not in uploaded_files:
+                    with st.spinner("Sending your PDF to Gemini..."):
+                        gemini_message["parts"].append(genai.upload_file(path=content['pdf_file']))
+                    os.remove(content['pdf_file'])
+
+        if prev_role != message["role"]:
+            gemini_messages.append(gemini_message)
+
+        prev_role = message["role"]
+
+    return gemini_messages
+
+
+##-- Converting base64 to image ---##
+def base64_to_image(base64_string):
+    base64_string = base64_string.split(",")[1]
+    
+    return Image.open(BytesIO(base64.b64decode(base64_string)))
+
+
+def add_pdf_docx_file_to_messages():
+    if st.session_state.pdf_docx_uploaded:
+        file_type = st.session_state.pdf_docx_uploaded.type
+        if file_type == "application/pdf":
+        # Save the PDF file
+            pdf_id = random.randint(1000, 9999)
+            pdf_filename = f"pdf_{pdf_id}.pdf"
+            with open(pdf_filename, "wb") as f:
+                f.write(st.session_state.pdf_docx_uploaded.read())
+            
+            # Add the PDF file to session_state messages
+            st.session_state.messages.append(
+                {
+                    "role": "user", 
+                    "content": [{
+                        "type": "pdf_file",
+                        "pdf_file": pdf_filename,
+                    }]
+                }
+            )
+        else:
+            file_content = st.session_state.pdf_docx_uploaded
+            text = ""
+            doc = docx.Document(file_content)
+            full_text = []
+
+            for para in doc.paragraphs:
+                full_text.append(para.text)
+            text += " ".join(full_text)
+
+            # Add the PDF file to session_state messages
+            st.session_state.messages.append(
+                {
+                    "role": "user", 
+                    "content": [{
+                        "type": "docx_file",
+                        "docx_file": text,
+                    }]
+                }
+            )
+
+
+def save_uploaded_video(video_file, file_path):
+    with open(file_path, "wb") as f:
+        f.write(video_file.read())
+
+##--- Function for adding media files to session_state messages ---###
+def add_media_files_to_messages():
+    if st.session_state.uploaded_file:
+        file_type = st.session_state.uploaded_file.type
+        file_content = st.session_state.uploaded_file.getvalue()
+        
+        if file_type.startswith("image"):
+            img = base64.b64encode(file_content).decode()
+            st.session_state.messages.append(
+                {
+                    "role": "user", 
+                    "content": [{
+                        "type": "image_url",
+                        "image_url": {"url": f"data:{file_type};base64,{img}"}
+                    }]
+                }
+            )
+        elif file_type == "video/mp4":
+            video_base64 = base64.b64encode(file_content).decode()
+            unique_id = random.randint(1000, 9999)
+            # file_name = st.session_state.uploaded_file.name
+            # file_path = os.path.join(tempfile.gettempdir(), file_name)
+            # save_uploaded_video(st.session_state.uploaded_file, file_path)
+
+            st.session_state.messages.append(
+                {
+                    "role": "user", 
+                    "content": [{
+                        "type": "video_file",
+                        "video_file": f"data:{file_type};base64,{video_base64}",
+                        "unique_name": f"temp_{unique_id}"
+                    }]
+                }
+            )
+        elif file_type.startswith("audio"):
+            audio_base64 = base64.b64encode(file_content).decode()
+            unique_id = random.randint(1000, 9999)
+            st.session_state.messages.append(
+                {
+                    "role": "user", 
+                    "content": [{
+                        "type": "audio_file",
+                        "audio_file": f"data:{file_type};base64,{audio_base64}",
+                        "unique_name": f"temp_{unique_id}"
+                    }]
+                }
+            )
+
+###--- FUNCTION TO ADD CAMERA IMAGE TO MESSAGES ---##
+def add_camera_img_to_messages():
+    if "camera_img" in st.session_state and st.session_state.camera_img:
+        img = base64.b64encode(st.session_state.camera_img.getvalue()).decode()
+        st.session_state.messages.append(
+            {
+                "role": "user", 
+                "content": [{
+                    "type": "image_url",
+                    "image_url": {"url": f"data:image/jpeg;base64,{img}"}
+                }]
+            }
+        )
+
+##--- FUNCTION TO RESET CONVERSATION ---##
+def reset_conversation():
+    if "messages" in st.session_state and len(st.session_state.messages) > 0:
+        st.session_state.pop("messages", None)
+    if "groq_chat_history" in st.session_state and len(st.session_state.groq_chat_history) > 1:
+        st.session_state.pop("groq_chat_history", None)
+
+    for file in genai.list_files():
+        genai.delete_file(file.name)
+
+    # Reset the uploaded files list
+    if "uploaded_files" in st.session_state:
+        st.session_state.pop("uploaded_files", None)
+
+    if "pdf_docx_uploaded" in st.session_state:
+        st.session_state.pop("pdf_docx_uploaded", None)
+
+##--- FUNCTION TO STREAM GEMINI RESPONSE ---##
+def stream_gemini_response(model_params, api_key):
+    response_message = ""
+
+    genai.configure(api_key=api_key)
+    model = genai.GenerativeModel(
+            model_name = model_params["model"],
+            generation_config={
+                "temperature": model_params["temperature"],
+                "max_output_tokens": model_params["max_tokens"],
+            },
+            safety_settings=set_safety_settings(),
+            system_instruction="""You are a helpful assistant who asnwers user's questions professionally and politely."""
+        )
+    gemini_messages = messages_to_gemini(st.session_state.messages)
+
+    for chunk in model.generate_content(contents=gemini_messages, stream=True):
+        chunk_text = chunk.text or ""
+        response_message += chunk_text
+        yield chunk_text
+
+    st.session_state.messages.append({
+    "role": "assistant", 
+    "content": [
+        {
+            "type": "text",
+            "text": response_message,
+        }
+    ]})
+
+if "summarize" not in st.session_state:
+    st.session_state.summarize = False
+##--- API KEYS ---##
+with st.sidebar:
+    st.logo("logo.png")
+    api_cols = st.columns(2)
+    with api_cols[0]:
+        with st.popover("🔐 Groq", use_container_width=True):
+            groq_api_key = st.text_input("Click [here](https://console.groq.com/keys) to get your Groq API key", value=os.getenv("GROQ_API_KEY") , type="password")
+    
+    with api_cols[1]:
+        with st.popover("🔐 Google", use_container_width=True):
+            google_api_key = st.text_input("Click [here](https://aistudio.google.com/app/apikey) to get your Google API key", value=os.getenv("GOOGLE_API_KEY") , type="password")
+ 
+##--- API KEY CHECK ---##
+if (groq_api_key == "" or groq_api_key is None or "gsk" not in groq_api_key) and (google_api_key == "" or google_api_key is None or "AIza" not in google_api_key):
+    st.warning("Please Add an API Key to proceed.")
+
+####--- LLM SIDEBAR ---###
+else:
+    with st.sidebar:
+        st.divider()
+        columns = st.columns(2)
+        # animation
+        with columns[0]:
+            lottie_animation = load_lottie_file("animation.json")
+            if lottie_animation:
+                st_lottie(lottie_animation, height=100, width=100, quality="high", key="lottie_anim")
+
+        with columns[1]:
+            if st.toggle("Voice Response"):
+                response_voice = st.selectbox("Available Voices:", options=voices.keys(), key="voice_response")
+    
+        available_models = [] + (google_models if google_api_key else []) + (groq_models if groq_api_key else [])
+        model, model_type, temperature, max_tokens = get_llm_info(available_models)
+
+        model_params = {
+                "model": model,
+                "temperature": temperature,
+                "max_tokens": max_tokens
+            }
+        st.divider()
+
+        ###---- Google Gemini Sidebar Customization----###
+        if model_type == "google":
+            st.write("Upload a file or take a picture")
+
+            media_cols = st.columns(2)
+
+            with media_cols[0]:
+                with st.popover("📁 Upload", use_container_width=True):
+                    st.file_uploader(
+                        "Upload an image, audio or a video", 
+                        type=["png", "jpg", "jpeg", "wav", "mp3", "mp4"], 
+                        accept_multiple_files=False,
+                        key="uploaded_file",
+                        on_change=add_media_files_to_messages,
+                    )
+
+            with media_cols[1]:                    
+                with st.popover("📷 Camera", use_container_width=True):
+                    activate_camera = st.checkbox("Activate camera")
+                    if activate_camera:
+                        st.camera_input(
+                            "Take a picture", 
+                            key="camera_img",
+                            on_change=add_camera_img_to_messages,
+                        )
+            st.divider()
+            tip = "If you upload a PDF, it will be sent to LLM."
+            pdf_upload = st.file_uploader("Upload a PDF", type=["pdf", "docx"], key="pdf_docx_uploaded", on_change=add_pdf_docx_file_to_messages, help=tip)
+        
+        ###---- Groq Models Sidebar Customization----###
+        else:
+            groq_llm_type = st.radio(label="Select the LLM type:", key="groq_llm_type",options=["Agent", "Chatbot", "Summarizer"], horizontal=True)
+            if groq_llm_type == "Summarizer":
+                url = st.text_input("Enter YT video or Webpage URL:", key="url_to_summarize",
+                                    help="Only Youtube videos having captions can be summarized.")
+                
+                summarize_button = st.button("Summarize", type="primary", use_container_width=True, key="summarize")
+
+            elif groq_llm_type == "Agent":
+                tools = st.multiselect("Select Tools for Agent",key="selected_tools",default=["Wikipedia", "ArXiv", "DuckDuckGo Search"],
+                                       options=["Wikipedia", "ArXiv", "DuckDuckGo Search"])
+                
+
+######-----  Main Interface -----#######
+    chat_col1, chat_col2 = st.columns([1,4])
+
+    with chat_col1:
+        ###--- Audio Recording ---###
+        audio_bytes = audio_recorder("Speak",
+                                     pause_threshold=3,
+                                     neutral_color="#f5f8fc",
+                                     recording_color="#f81f6f",
+                                     icon_name="microphone-lines",
+                                     icon_size="3x")
+
+        ###--- Reset Conversation ---###
+        st.button(
+                "🗑 Reset",
+                use_container_width=True,
+                on_click=reset_conversation,
+                help="If clicked, conversation will be reset.",
+            )
+###--- Session state variable ---###
+        if "pdf_docx_uploaded" not in st.session_state:
+            st.session_state.pdf_docx_uploaded = None
+
+        if st.session_state.pdf_docx_uploaded:
+            file_name = st.session_state.pdf_docx_uploaded.name
+            st.info(f"Your file :green['{file_name}'] has been uploaded!")
+
+
+    if "messages" not in st.session_state:
+        st.session_state.messages = []
+    if "uploaded_files" not in st.session_state:
+        st.session_state.uploaded_files = []
+    if "groq_chat_history" not in st.session_state:
+        st.session_state.groq_chat_history = []
+
+    ###-- Handle speech input --###
+    speech_file_added = False
+    if "prev_speech_hash" not in st.session_state:
+        st.session_state.prev_speech_hash = None
+
+    if audio_bytes and st.session_state.prev_speech_hash != hash(audio_bytes):
+        st.session_state.prev_speech_hash = hash(audio_bytes)
+        speech_base64 = base64.b64encode(audio_bytes).decode()
+        unique_id = random.randint(1000, 9999)
+
+        st.session_state.messages.append(
+            {
+                "role": "user",
+                "content": [{
+                    "type": "speech_input",
+                    "speech_input": f"data:audio/wav;base64,{speech_base64}",
+                    "unique_name": f"temp_{unique_id}"
+                }]
+            }
+        )
+        speech_file_added = True
+
+        
+    with chat_col2:
+        message_container = st.container(height=400, border=False)
+
+        for message in st.session_state.messages:
+            avatar = "assistant.png" if message["role"] == "assistant" else "user.png"
+            valid_content = [
+                content for content in message["content"]
+                if not (
+                    (content["type"] == "text" and content["text"] == "Please Answer the Question asked in the audio.") or
+                    content["type"] in ["pdf_file","docx_file"]
+                )
+            ]
+            if valid_content:
+                with message_container.chat_message(message["role"], avatar=avatar):
+                    for content in message["content"]:
+                        if content["type"] == "text":
+                            st.markdown(content["text"])
+                        elif content["type"] == "image_url":      
+                            st.image(content["image_url"]["url"])
+                        elif content["type"] == "video_file":
+                            st.video(content["video_file"])
+                        elif content["type"] == "audio_file":
+                            st.audio(content["audio_file"], autoplay=True)
+                        elif content["type"] == "speech_input":
+                            st.audio(content["speech_input"])
+
+        for msg in st.session_state.groq_chat_history:
+            avatar = "assistant.png" if msg["role"] == "assistant" else "user.png"
+            with message_container.chat_message(msg["role"], avatar=avatar):
+                st.markdown(msg['content'])
+
+ ###---- Summarizer model------###
+    if model_type == "groq" and groq_llm_type == "Summarizer":
+        if st.session_state.summarize:
+            with message_container.chat_message("assistant", avatar="assistant.png"):
+                if not url.strip():
+                    st.error("Please enter a URL")
+                elif not validators.url(url):
+                    st.error("Please enter a valid URL")
+                else:
+                    with st.spinner("Summarizing..."):
+                        final_response = summarizer_model(model_params=model_params, api_key=groq_api_key, url=url)
+                    st.markdown(final_response)
+                st.session_state.groq_chat_history.append({"role": "assistant", "content": final_response})
+
+###----- User Question -----###
+    else:
+        if prompt:= st.chat_input("Type you question", key="question") or speech_file_added:
+    ###------- GROQ MODELS --------###
+            if model_type == "groq":
+
+                if not speech_file_added:
+                    message_container.chat_message("user", avatar="user.png").markdown(prompt)
+                    st.session_state.groq_chat_history.append({"role": "user", "content": prompt})
+                else:
+                    speech_to_text = speech_to_text(audio_bytes)
+                    message_container.chat_message("user", avatar="user.png").markdown(speech_to_text)
+                    st.session_state.groq_chat_history.append({"role": "user", "content": speech_to_text})
+                    
+                with message_container.chat_message("assistant", avatar="assistant.png"):
+                
+                    try:
+                        if groq_llm_type == "Chatbot":
+                            final_response = st.write_stream(groq_chatbot(model_params=model_params, api_key=groq_api_key,
+                                        question=prompt, chat_history=st.session_state.groq_chat_history))
+
+                        elif groq_llm_type == "Agent":
+                            final_response = create_groq_agent(model_params=model_params, api_key=groq_api_key,
+                                                                            question=prompt,
+                                                                            tools=get_tools(tools),
+                                                                            chat_history=st.session_state.groq_chat_history,)
+                            
+                            st.markdown(final_response)
+                        st.session_state.groq_chat_history.append({"role": "assistant", "content": final_response})
+
+                        if "voice_response" in st.session_state and st.session_state.voice_response:
+                            response_voice = st.session_state.voice_response
+                            generate_voice(final_response, voices[response_voice])
+
+                    except Exception as e:
+                        st.error(f"An error occurred: {e}", icon="❌")
+            
+    ###-------- GEMINI MODELS -------###
+            else:
+                if not speech_file_added:
+                    message_container.chat_message("user", avatar="user.png").markdown(prompt)
+
+                    st.session_state.messages.append(
+                                {
+                                    "role": "user", 
+                                    "content": [{
+                                        "type": "text",
+                                        "text": prompt,
+                                    }]
+                                }
+                            )
+            ###----Google Gemini Response----###
+                else:
+                    st.session_state.messages.append(
+                                {
+                                    "role": "user", 
+                                    "content": [{
+                                        "type": "text",
+                                        "text": "Please Answer the Question asked in the audio.",
+                                    }]
+                                }
+                            )
+
+                ###----- Generate response -----###
+                with message_container.chat_message("assistant", avatar="assistant.png"):
+                    try:
+                        final_response = st.write_stream(stream_gemini_response(model_params=model_params, api_key= google_api_key))
+
+                        if "voice_response" in st.session_state and st.session_state.voice_response:
+                            response_voice = st.session_state.voice_response
+                            generate_voice(final_response, voices[response_voice])
+        
+                    except Exception as e:
+                        st.error(f"An error occurred: {e}", icon="❌")
+
+            

groq_models.py

@@ -80,25 +80,29 @@ def create_groq_agent(model_params, api_key, tools, question, chat_history):
     return response['output']
 
 
-def get_tools():
-    wikipedia = WikipediaAPIWrapper(top_k_results=2, doc_content_chars_max=500)
-    wikipedia_tool = Tool(name="Wikipedia",
-                        func=wikipedia.run,
-                        description="A useful tool for searching the Internet to find information on world events, issues, dates, years, etc.")
-    arxiv = ArxivAPIWrapper(top_k_results=2, doc_content_chars_max=500)
-    arxiv_tool = Tool(name="ArXiv",
-                      func=arxiv.run,
-                      description="A useful tool for searching scientific and research papers."
-
-    )
-    search = DuckDuckGoSearchRun()
-    search_tool = Tool(
-        name="DuckDuckGo Search",
-        func=search.run,
-        description="Useful for when you need to search the internet to find latest information, facts and figures that another tool can't find.",
-    )
-
-    return [arxiv_tool, wikipedia_tool, search_tool]
+def get_tools(selected_tools):
+    # Define all available tools
+    tools = {
+        "Wikipedia": Tool(
+            name="Wikipedia",
+            func=WikipediaAPIWrapper(top_k_results=2, doc_content_chars_max=500).run,
+            description="A useful tool for searching the Internet to find information on world events, issues, dates, years, etc."
+        ),
+        "ArXiv": Tool(
+            name="ArXiv",
+            func=ArxivAPIWrapper(top_k_results=2, doc_content_chars_max=500).run,
+            description="A useful tool for searching scientific and research papers."
+        ),
+        "DuckDuckGo Search": Tool(
+            name="DuckDuckGo Search",
+            func=DuckDuckGoSearchRun().run,
+            description="Useful for when you need to search the internet to find latest information, facts and figures that another tool can't find."
+        )
+    }
+
+    # Filter and return only the tools selected by the user
+    return [tools[tool_name] for tool_name in selected_tools]
+
 
 def summarizer_model(model_params, api_key, url):
     llm = ChatGroq(model=model_params['model'], api_key=api_key,

requirements.txt

@@ -10,10 +10,13 @@ langchain
 langchain-groq
 langchain_community
 pypdf
-pdfplumber
 edge-tts
 arxiv
 wikipedia
 duckduckgo-search
 langchainhub
-validators
+validators
+docx
+SpeechRecognition
+youtube-transcript-api
+pytube

utils.py

@@ -2,6 +2,8 @@ import streamlit as st
 from streamlit_vertical_slider import vertical_slider
 import pdfplumber
 from langchain_core.prompts import ChatPromptTemplate
+import speech_recognition as sr
+import tempfile
 
 @st.dialog("Confirm Selection 👇", width="large")
 def visualize_display_page(selection_dict):
@@ -84,4 +86,21 @@ def set_safety_settings():
     },
 ]
 
-    return safety_settings
+    return safety_settings
+
+def speech_to_text(audio_bytes):
+    with tempfile.NamedTemporaryFile(suffix=".wav", delete=False) as recording:
+        recording.write(audio_bytes)
+        temp_file_path = recording.name
+        
+    r = sr.Recognizer()
+    with sr.AudioFile(temp_file_path) as source:
+        recorded_voice = r.record(source)
+
+        try:
+            text = r.recognize_google(recorded_voice, language="en")
+            return text
+        except sr.UnknownValueError as e:
+            st.error(e)
+        except sr.RequestError as e:
+            print("could not request result from google speech recognition service: {0}".format(e))