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.env

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+GOOGLE_API_KEY=AIzaSyB8XqUjANeAvV1Z8O24wKzD90gly3jZmTA
+
+
+

.gitignore

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+# Created by venv; see https://docs.python.org/3/library/venv.html
+*

README.md

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----
-title: ML Galaxy
-emoji: ⚡
-colorFrom: yellow
-colorTo: pink
-sdk: streamlit
-sdk_version: 1.41.1
-app_file: app.py
-pinned: false
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# gemini-pro-streamlit-chatbot
+This repository is about building a chatbot using Google's Gemini-Pro with streamlit.

app.py

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+import os
+import streamlit as st
+from dotenv import load_dotenv
+import google.generativeai as gen_ai
+
+# Load environment variables
+load_dotenv()
+
+# Configure Streamlit page settings
+st.set_page_config(
+    page_title="ML Galaxy!",
+    page_icon=":brain:",  # Favicon emoji
+    layout="centered",  # Page layout option
+)
+
+# Retrieve the Google API key from the environment
+GOOGLE_API_KEY = os.getenv("GOOGLE_API_KEY")
+
+# Check if the API key is loaded
+if not GOOGLE_API_KEY:
+    st.error("API key not found! Please set the GOOGLE_API_KEY in your .env file.")
+    st.stop()
+
+# Configure the Generative AI model
+try:
+    gen_ai.configure(api_key=GOOGLE_API_KEY)
+    model = gen_ai.GenerativeModel("gemini-pro")
+except Exception as e:
+    st.error(f"Error initializing the Gemini-Pro model: {e}")
+    st.stop()
+
+# Function to translate roles between Gemini-Pro and Streamlit terminology
+def translate_role_for_streamlit(user_role):
+    return "assistant" if user_role == "model" else user_role
+
+# Initialize the chat session if not already present in session state
+if "chat_session" not in st.session_state:
+    try:
+        st.session_state.chat_session = model.start_chat(history=[])
+    except Exception as e:
+        st.error(f"Error initializing chat session: {e}")
+        st.stop()
+
+# Display the chatbot's title
+st.title("🤖 ML Galaxy")
+
+# Display the chat history
+try:
+    for message in st.session_state.chat_session.history:
+        with st.chat_message(translate_role_for_streamlit(message.role)):
+            st.markdown(message.parts[0].text)
+except Exception as e:
+    st.error(f"Error displaying chat history: {e}")
+
+# Input field for user's message
+user_prompt = st.chat_input("Ask Gemini-Pro...")
+if user_prompt:
+    # Add the user's message to the chat and display it
+    st.chat_message("user").markdown(user_prompt)
+
+    # Send the user's message to Gemini-Pro and get the response
+    try:
+        gemini_response = st.session_state.chat_session.send_message(user_prompt)
+        # Display Gemini-Pro's response
+        with st.chat_message("assistant"):
+            st.markdown(gemini_response.text)
+    except Exception as e:
+        st.error(f"Error processing your message: {e}")

pyvenv.cfg

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+home = C:\Python313
+include-system-site-packages = false
+version = 3.13.1
+executable = C:\Python313\python.exe
+command = C:\Python313\python.exe -m venv c:\ML_Notes_chatbot\.venv

requirements.txt

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+python-dotenv==1.0.1
+google-generativeai==0.3.2
+streamlit==1.30.0
+deep-translator
+deep-translator
+streamlit
+