Update app.py

app.py

@@ -1,11 +1,8 @@
 import os
-from groq import Groq
-import pandas as pd
-import speech_recognition as sr
-import pyttsx3
 import streamlit as st
+from groq import Groq
 
-# API_KEY
+# API_KEY (Replace with your actual Groq API key)
 API = "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"
 
 # Set up the Groq client
@@ -13,78 +10,42 @@ client = Groq(api_key=API)
 
 # Function to process user input with Llama model
 def process_prompt(prompt, model="llama-3.3-70b-versatile"):
-    chat_completion = client.chat.completions.create(
-        messages=[{"role": "user", "content": prompt}],
-        model=model,
-        stream=False
-    )
-    return chat_completion.choices[0].message.content
-
-# Function to process uploaded files
-def process_file(file):
-    if file.type == "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet":
-        data = pd.read_excel(file)
-    elif file.type == "text/csv":
-        data = pd.read_csv(file)
-    else:
-        return "Unsupported file format."
-    return data
-
-# Function to generate human-friendly responses for file data
-def analyze_file_data(data):
-    summary = f"File contains {data.shape[0]} rows and {data.shape[1]} columns."
-    response = f"""
-    **File Analysis:**
-    - 📄 Total Rows: {data.shape[0]}
-    - 📊 Total Columns: {data.shape[1]}
-    - First Few Rows:
-    {data.head().to_markdown()}
-    """
-    return response
-
-# Function for speech-to-text
-def speech_to_text():
-    recognizer = sr.Recognizer()
-    with sr.Microphone() as source:
-        st.write("🎙️ Listening...")
-        audio = recognizer.listen(source)
     try:
-        return recognizer.recognize_google(audio)
-    except sr.UnknownValueError:
-        return "Sorry, I didn't catch that."
+        chat_completion = client.chat.completions.create(
+            messages=[{"role": "user", "content": prompt}],
+            model=model,
+            stream=False
+        )
+        return chat_completion.choices[0].message.content
+    except Exception as e:
+        print(f"Error processing prompt: {e}")  # Log the error for debugging
+        return "An error occurred. Please try again later."
+
+# Function for chat history management (using session_state)
+def get_chat_history():
+    chat_history = st.session_state.get("chat_history", [])
+    return chat_history
 
-# Function for text-to-speech
-def text_to_speech(text):
-    engine = pyttsx3.init()
-    engine.say(text)
-    engine.runAndWait()
+def update_chat_history(user_input, response):
+    chat_history = get_chat_history()
+    chat_history.append(("User", user_input))
+    chat_history.append(("Bot", response))
+    st.session_state["chat_history"] = chat_history
 
 # Streamlit UI
 def chatbot_ui():
     st.title("📢 Real-Time AI Chatbot")
 
-    # File upload feature
-    st.sidebar.header("📂 File Management")
-    uploaded_file = st.sidebar.file_uploader("Upload a file (CSV/Excel)", type=["csv", "xlsx"])
-    if uploaded_file:
-        data = process_file(uploaded_file)
-        st.sidebar.write(analyze_file_data(data))
-        if st.sidebar.button("Delete File"):
-            uploaded_file = None
-            st.sidebar.write("File deleted.")
-
     # Chat section
     st.header("💬 Chat Section")
-    chat_history = st.session_state.get("chat_history", [])
-    
+    chat_history = get_chat_history()
+
     with st.form("chat_form", clear_on_submit=True):
         user_input = st.text_input("Type your message or prompt here...")
         submitted = st.form_submit_button("Send")
         if submitted and user_input:
             response = process_prompt(user_input)
-            chat_history.append(("User", user_input))
-            chat_history.append(("Bot", response))
-            st.session_state["chat_history"] = chat_history
+            update_chat_history(user_input, response)
 
     # Display chat history
     for sender, message in chat_history:
@@ -98,16 +59,5 @@ def chatbot_ui():
         chat_file = "\n".join([f"{sender}: {message}" for sender, message in chat_history])
         st.download_button("Download", chat_file, "chat_history.txt", "text/plain")
 
-    # Speech-to-Text Section
-    st.header("🎙️ Speech-to-Text")
-    if st.button("Start Speech Recognition"):
-        st.write(f"**👂 You said:** {speech_to_text()}")
-
-    # Text-to-Speech Section
-    st.header("🔊 Text-to-Speech")
-    tts_text = st.text_input("Enter text to convert to speech:")
-    if st.button("Speak Text"):
-        text_to_speech(tts_text)
-
 if __name__ == "__main__":
-    chatbot_ui()
+    chatbot_ui()