update README.MD

README.md

@@ -1,10 +1,55 @@
 ---
 title: AI Tutor Chatbot
-emoji: 🌍
+emoji: 🧑🏻‍🏫
 colorFrom: gray
 colorTo: pink
 sdk: gradio
 sdk_version: 4.19.1
 app_file: scripts/gradio-ui.py
 pinned: false
----
+---
+---
+This project creates a helpful and accurate AI Tutor chatbot, leveraging GPT-3.5-Turbo and a RAG system. We design it to address student questions about AI with precision and clarity.
+
+### Installation
+
+1. **Create a new Python environment:**
+
+    ```bash
+    python -m venv .venv
+    ```
+
+    This command creates a virtual environment named `.venv`.
+
+2. **Activate the environment:**
+
+    For macOS and Linux:
+
+    ```bash
+    source .venv/bin/activate
+    ```
+
+3. **Install the dependencies:**
+
+    ```bash
+    pip install -r requirements.txt
+    ```
+
+### Usage
+
+1. **Set environment variables:**
+
+    Before running the application, you need to set up your OpenAI API key and MongoDB URI as environment variables:
+
+    ```bash
+    export OPENAI_API_KEY=your_openai_api_key_here
+    export MONGODB_URI=your_mongodb_uri_here
+    ```
+
+2. **Run the application:**
+
+    ```bash
+    python scripts/gradio-ui.py
+    ```
+
+    This command starts the Gradio interface for the AI Tutor chatbot.

scripts/gradio-ui.py

@@ -65,7 +65,7 @@
 vector_store = ChromaVectorStore(chroma_collection=chroma_collection)
 index = VectorStoreIndex.from_vector_store(vector_store=vector_store)
 
-# Initialize query engine
+# Initialize OpenAI models
 llm = OpenAI(temperature=0, model="gpt-3.5-turbo-0125", max_tokens=None)
 embeds = OpenAIEmbedding(model="text-embedding-3-large", mode="text_search")
 
@@ -284,9 +284,8 @@ def get_answer(history, sources: Optional[list[str]] = None):
     # )
 
     chatbot.like(log_likes, completion)
-
     submit_email.click(log_emails, email, email)
     email.submit(log_emails, email, email)
 
-demo.queue()
-demo.launch(debug=True, share=False)
+demo.queue(default_concurrency_limit=CONCURRENCY_COUNT)
+demo.launch(debug=False, share=False)