Update structure of the repo

Author: titipata

README.md

@@ -1,68 +1,13 @@
-# BME Lab
+# Hands-on Machine Learning Lab for Biomedical Engineering Students
 
 This is part of the code for BME Lab at Mahidol University.
-Lab II teaches 3rd year student where we aim to have them run 
 
-## Lab II: Running Large Language Model
+### Building Machine Learning Application with Gradio
 
-**Task 1: Running Open WebUI**
+Gradio is a powerful tool for creating web interfaces for machine learning models.
+In this lab, students will learn to build practical medical applications using Gradio's intuitive interface.
 
-- Download [Ollama](https://ollama.com/) on your laptop, then run `ollama run llama3.1`
+### Generative AI
 
-Here, you can run prompt Llama3.1 on your local machine. After running Ollama, you can connect with Open WebUI:
-
-- Download [docker](https://www.docker.com/products/docker-desktop/) on your laptop
-- Run [Open WebUI](https://github.com/open-webui/open-webui) using `docker` and goes to http://localhost:3000/ to prompt! You can check the section "If Ollama is on your computer, use this command: ..."
-
-**Task 2: Connect Python with Ollama**
-
-You can connect Python using [Langchain](https://www.langchain.com/) with Ollama.
-Use [`00_Connect_Ollama_with_Langchain`](https://github.com/biodatlab/bme-labs/blob/main/notebooks/00_Connect_Ollama_with_Langchain.ipynb) to try it out after running Ollama.
-
-```py
-%%capture
-!pip install langchain
-!pip install langchain_community
-```
-
-```py
-# Code from https://stackoverflow.com/a/78430197/3626961
-from langchain_community.llms import Ollama
-from langchain import PromptTemplate # Added
-
-llm = Ollama(model="llama3.1", stop=["<|eot_id|>"]) # Added stop token
-
-def get_model_response(user_prompt, system_prompt):
-    # NOTE: No f string and no whitespace in curly braces
-    template = """
-        <|begin_of_text|>
-        <|start_header_id|>system<|end_header_id|>
-        {system_prompt}
-        <|eot_id|>
-        <|start_header_id|>user<|end_header_id|>
-        {user_prompt}
-        <|eot_id|>
-        <|start_header_id|>assistant<|end_header_id|>
-        """
-
-    # Added prompt template
-    prompt = PromptTemplate(
-        input_variables=["system_prompt", "user_prompt"],
-        template=template
-    )
-    
-    # Modified invoking the model
-    response = llm(prompt.format(system_prompt=system_prompt, user_prompt=user_prompt))
-    
-    return response
-
-# Example
-user_prompt = "What is 1 + 1?"
-system_prompt = "You are a helpful assistant doing as the given prompt."
-get_model_response(user_prompt, system_prompt)
-```
-
-**Task 3: Transcribe Youtube video and summarize the transcriptions**
-
-- Use [`01_Thonburian_Whisper_Longform_Youtube`](https://github.com/biodatlab/bme-labs/blob/main/notebooks/01_Thonburian_Whisper_Longform_Youtube.ipynb) to transcribe the text from Youtube URL (select one URL) and [`02_Ollama_Summarize_Transcript`](https://github.com/biodatlab/bme-labs/blob/main/notebooks/02_Ollama_Summarize_Transcript.ipynb) to write a summarization prompt
-- Your task is to write a prompt to summarize the text from your selected Youtube URL
+This lab will explore the practical applications of Large Language Models (LLMs) using Ollama and OpenWebUI.
+Students will work with locally-hosted models, learning how to interact with them.

generative-ai/README.md

@@ -0,0 +1,64 @@
+# Generative AI Lab: Up and Running your First Large Language Model (LLM)
+
+### Task 1: Setting up Ollama and Running Open WebUI
+
+**Setting up Ollama**
+- Download [Ollama](https://ollama.com/) on your laptop, then run `ollama run llama3.1`
+- Here, you can run prompt Llama3.1 on your local machine. After running Ollama, you can connect with Open WebUI:
+
+**Setting up Open WebUI**
+- Download [docker](https://www.docker.com/products/docker-desktop/) on your laptop
+- Run [Open WebUI](https://github.com/open-webui/open-webui) using `docker` and goes to http://localhost:3000/ to prompt! You can check the section "If Ollama is on your computer, use this command: ..."
+
+### Task 2: Connect Python with Ollama
+
+You can connect Python using [Langchain](https://www.langchain.com/) with Ollama.
+Use [`00_Connect_Ollama_with_Langchain`](https://github.com/biodatlab/bme-labs/blob/main/notebooks/00_Connect_Ollama_with_Langchain.ipynb) to try it out after running Ollama.
+
+```py
+%%capture
+!pip install langchain
+!pip install langchain_community
+```
+
+```py
+# Code from https://stackoverflow.com/a/78430197/3626961
+from langchain_community.llms import Ollama
+from langchain import PromptTemplate # Added
+
+llm = Ollama(model="llama3.1", stop=["<|eot_id|>"]) # Added stop token
+
+def get_model_response(user_prompt, system_prompt):
+    # NOTE: No f string and no whitespace in curly braces
+    template = """
+        <|begin_of_text|>
+        <|start_header_id|>system<|end_header_id|>
+        {system_prompt}
+        <|eot_id|>
+        <|start_header_id|>user<|end_header_id|>
+        {user_prompt}
+        <|eot_id|>
+        <|start_header_id|>assistant<|end_header_id|>
+        """
+
+    # Added prompt template
+    prompt = PromptTemplate(
+        input_variables=["system_prompt", "user_prompt"],
+        template=template
+    )
+    
+    # Modified invoking the model
+    response = llm(prompt.format(system_prompt=system_prompt, user_prompt=user_prompt))
+    
+    return response
+
+# Example
+user_prompt = "What is 1 + 1?"
+system_prompt = "You are a helpful assistant doing as the given prompt."
+get_model_response(user_prompt, system_prompt)
+```
+
+**Task 3: Transcribe Youtube video and summarize the transcriptions**
+
+- Use [`01_Thonburian_Whisper_Longform_Youtube`](https://github.com/biodatlab/bme-labs/blob/main/notebooks/01_Thonburian_Whisper_Longform_Youtube.ipynb) to transcribe the text from Youtube URL (select one URL) and [`02_Ollama_Summarize_Transcript`](https://github.com/biodatlab/bme-labs/blob/main/notebooks/02_Ollama_Summarize_Transcript.ipynb) to write a summarization prompt
+- Your task is to write a prompt to summarize the text from your selected Youtube URL

agents/README.md renamed to generative-ai/agents/README.md

@@ -0,0 +1 @@
+# Building ML Application with Gradio