merge

README.md

@@ -13,7 +13,6 @@ app_port: 7860
      height="auto"/>
 </p>
 
-
 ## <h1 align="center" id="heading">:wave: Welcome to Beyond ChatGPT!!</h1>
 
 For a step-by-step YouTube video walkthrough, watch this! [Deploying Chainlit app on Hugging Face](https://www.youtube.com/live/pRbbZcL0NMI?si=NAYhMZ_suAY84f06&t=2119)
@@ -39,35 +38,37 @@ That's it! Head to the next step and start building your application!
 
 </details>
 
-
 <details>
   <summary>🏗️ Building Your First LLM App</summary>
 
 1. Clone [this](https://github.com/AI-Maker-Space/Beyond-ChatGPT/tree/main) repo.
 
-     ``` bash
-     git clone https://github.com/AI-Maker-Space/Beyond-ChatGPT.git
-     ```
+   ```bash
+   git clone https://github.com/AI-Maker-Space/Beyond-ChatGPT.git
+   ```
 
 2. Navigate inside this repo
-     ``` bash
-     cd Beyond-ChatGPT
-     ```
+
+   ```bash
+   cd Beyond-ChatGPT
+   ```
 
 3. Install the packages required for this python envirnoment in `requirements.txt`.
-     ``` bash
-     pip install -r requirements.txt
-     ``` 
+
+   ```bash
+   pip install -r requirements.txt
+   ```
 
 4. Open your `.env` file. Replace the `###` in your `.env` file with your OpenAI Key and save the file.
-     ``` bash
-     OPENAI_API_KEY=sk-###
-     ```
+
+   ```bash
+   OPENAI_API_KEY=sk-###
+   ```
 
 5. Let's try deploying it locally. Make sure you're in the python environment where you installed Chainlit and OpenAI. Run the app using Chainlit. This may take a minute to run.
-     ``` bash
-     chainlit run app.py -w
-     ```
+   ```bash
+   chainlit run app.py -w
+   ```
 
 <p align = "center" draggable=”false”>
 <img src="https://github.com/AI-Maker-Space/LLMOps-Dev-101/assets/37101144/54bcccf9-12e2-4cef-ab53-585c1e2b0fb5"> 
@@ -77,27 +78,26 @@ Great work! Let's see if we can interact with our chatbot.
 
 <p align = "center" draggable=”false”>
 <img src="https://github.com/AI-Maker-Space/LLMOps-Dev-101/assets/37101144/854e4435-1dee-438a-9146-7174b39f7c61"> 
-</p> 
+</p>
 
 Awesome! Time to throw it into a docker container and prepare it for shipping!
-</details>
-
 
+</details>
 
 <details>
   <summary>🐳 Containerizing our App</summary>
 
 1. Let's build the Docker image. We'll tag our image as `llm-app` using the `-t` parameter. The `.` at the end means we want all of the files in our current directory to be added to our image.
-     
-     ``` bash
-     docker build -t llm-app .
-     ```
+
+   ```bash
+   docker build -t llm-app .
+   ```
 
 2. Run and test the Docker image locally using the `run` command. The `-p`parameter connects our **host port #** to the left of the `:` to our **container port #** on the right.
-    
-     ``` bash
-     docker run -p 7860:7860 llm-app
-     ```
+
+   ```bash
+   docker run -p 7860:7860 llm-app
+   ```
 
 3. Visit http://localhost:7860 in your browser to see if the app runs correctly.
 
@@ -106,8 +106,8 @@ Awesome! Time to throw it into a docker container and prepare it for shipping!
 </p>
 
 Great! Time to ship!
-</details>
 
+</details>
 
 <details>
   <summary>🚀 Deploying Your First LLM App</summary>
@@ -119,7 +119,7 @@ Great! Time to ship!
 </p>
 
 2. Setup your space as shown below:
-   
+
 - Owner: Your username
 - Space Name: `llm-app`
 - License: `Openrail`
@@ -187,4 +187,4 @@ Who else is diving into the world of AI? Let's connect! 🌐💡
 
 <p></p>
 
-### That's it for now!  And so it begins.... :)
+### That's it for now! And so it begins.... :)