🤖 Gemini 1.5 Pro Chatbot 💬

This project implements a simple chatbot using Google's Gemini 1.5 Pro model via the google-generativeai library.

✨ Features

Interactive Chat: Engage in a conversation with the Gemini 1.5 Pro model. 💬
Safety Settings: Built-in safety mechanisms to filter content related to harassment, hate speech, sexually explicit material, and dangerous content. 🛡️
Conversation History: Maintains the context of the conversation for more coherent interactions. 🧠

Python 3.7 or higher 🐍
google-generativeai library: Install using pip install google-generativeai
dotenv library: Install using pip install python-dotenv
Google Account: You'll need a Google account to be able access the Google AI Studio. ☁️
Gemini API : Ensure that the Gemini API is active. ✅

Obtain your API Key: 🗝️
- Go to the Google AI Studio.
- Get API Key.
- Create API Key".
- Copy.
- Important: Store this API key securely. 🔐
Create a .env file: 📝
- In the project directory, create a file named .env.
- Add the following line to the file, replacing YOUR_API_KEY with your actual API key:
```
API_KEY=YOUR_API_KEY
```
Run the Chatbot: ▶️
- Execute the Python script (e.g., python chatbot.py).
- Start typing to chat with the chatbot! 💬
- To exit the program, type exit. 🚪

google.generativeai: Imports the necessary library for interacting with the Gemini API.
dotenv: Loads the API key from the .env file.
genai.configure(api_key=api_key): Sets up your authentication for the API. 🔑
model = genai.GenerativeModel(...): Initializes the Gemini 1.5 Pro model with specified parameters:
- model_name: Specifies the Gemini model to use.
- generation_config: Controls model behavior:
  - temperature: Higher values (e.g., 1) make the output more creative/random; lower values (e.g., 0.2) make it more deterministic. 🌡️
  - top_p: Nucleus sampling parameter - influences the diversity of generated text.
  - top_k: Top-k sampling parameter - limits the selection of words to the top k most probable words.
  - max_output_tokens: Sets the maximum length of the model's responses.
- safety_settings: Defines safety thresholds for various content categories. 🛡️
convo = model.start_chat(...): Initiates a chat session with the model, optionally providing conversation history. 💬
convo.send_message(user_input): Sends the user's input to the model. ➡️
print(convo.last.text): Displays the model's response. ⬅️
conversation_history: Keeps track of the conversation turns. 🔁

Experiment with the temperature parameter in generation_config to adjust the chatbot's creativity. 🌡️
Explore different safety settings to customize the content filtering. 🛡️
Consider expanding the chatbot's functionality by adding features like:
- User authentication 👤
- Topic-specific responses 🎯
- Integration with other services 🔗

Remember to replace YOUR_API_KEY in the .env file with your actual API key! 🔑