Merge pull request #153 from stfc/wex-project-brief

DOC: Added a directory and read me for a project.

README.md

@@ -106,3 +106,8 @@ One terraform script to create a private network on openstack along with a route
 
 A Python script that when run, creates a filter word cloud from the summary of tickets over a time period.
 [More Here](word_cloud_generator/)
+
+## wex_llm_app
+
+Developed by Cloud WEX Students. A web application to host and interact with a large language model instance.
+[More Here](wex_llm_app)

wex_llm_app/README.md

@@ -0,0 +1,59 @@
+**Project Title:** End-end deployment of a Large Language Model web application
+
+**Project Overview:**
+
+Create a web application that allows users to send questions to a LLM backend and receive a response. The page will display the user's question, response and the response time.
+
+**Functional Requirements:**
+
+1. User Input:
+    * A text input field for users to enter questions.
+    * A submit button to send the question to the backend.
+2. LLM Backend:
+    * Intergrate with an Ollama LLM API instance using basic auth or tokens.
+    * Send streamed/completed responses to the users session.
+3. Response Display:
+    * Display the users question.
+    * Display the LLM response either streamed or complete.
+4. Response Time Measurment:
+    * Measure and display the round trip time (RTT) and generation time.
+5. Instructions for self-hosting:
+    * Provide simple setup instructions for a user to host their own LLM.
+
+**Non-Functional Requirements (Priority):**
+
+1. Performance (Medium):
+    * Ensure the webpage responds in a timely mannor. Think complete/streamed responses.
+2. Security (High):
+    * Implement basic auth or API tokens for authentication with the backend.
+    * Set up HTTPS using Let's Encrypt to encrypt traffic to the backend.
+3. Usability (Low):
+    * Design an intuitive interface for users to submit questions and view responses.
+
+**Technical Requirements:**
+
+1. Frontend:
+        * Build the webpage using HTML, CSS and JavaScript.
+        * Use native JavaScript APIs to make HTTP requests to the backend.
+2. Backend:
+        * Use the Ollama LLM API with authentication for receiving user questions and sending responses.
+        * (To be investigated) Use a database to store authentication information.
+3. Infrastructure:
+        * Use Terraform to provision multiple VM instances and networking.
+        * Configure machines/containers using Ansible playbooks to ensure consistency in deployment.
+        * Run the web server on multiple VM instances, each with its own Docker container.
+        * Use an Apache container to host the website within each Web VM.
+        * Set up a separate VM instance (with or without Docker) to run HAProxy and Let's Encrypt services.
+        * Configure HAProxy to load balance traffic across the multiple web server instances.
+        * Host the Ollama service directly on a separate GPU VM.
+
+**Useful Resources:**
+
+1. [HTML, CSS, JS resources](https://developer.mozilla.org/en-US/)
+2. [HTML Tutorial](https://www.w3schools.com/html/)
+3. [CSS Tutorial](https://www.w3schools.com/css/)
+4. [JavaScript Tutorial](https://www.w3schools.com/js/)
+5. [Terraform Documentation](https://registry.terraform.io/providers/terraform-provider-openstack/openstack/latest/docs)
+6. [Ansible Documentation](https://docs.ansible.com/)
+7. [Docker Documnetation](https://docs.docker.com/)
+8. [Ollama Documentation](https://github.com/ollama/ollama)