Updated README instructions and clarified how things work.

README.md

@@ -19,18 +19,27 @@ YouTube contains an incredible amount of knowledge, much of which is locked insi
 
 ### Setup
 - **Linux**
-    1. X
-    2. Create a virtual env: `python -m venv`
+    1. Download necessary packages (Python3, ffmpeg[sudo apt install ffmpeg / dnf install ffmpeg], ?)
+    2. Create a virtual env: `python -m venv ./`
     3. Launch/activate your virtual env: `. .\scripts\activate.sh`
-    4. `pip install -r requirements.txt`
-    5. 
+    4. See `Linux && Windows`
 - **Windows**
-    1. X
-    2. Create a virtual env: `python -m venv`
+    1. Download necessary packages (Python3, [ffmpeg](https://www.gyan.dev/ffmpeg/builds/), ?)
+    2. Create a virtual env: `python -m venv .\`
     3. Launch/activate your virtual env: `. .\scripts\activate.ps1`
-    4. `pip install -r requirements.txt`
-    5. 
-
+    4. See `Linux && Windows`
+- **Linux && Windows**
+    1. `pip install -r requirements.txt` - may take a bit of time...
+    2. Run `python ./diarize.py <video_url>` - The video URL does _not_ have to be a youtube URL. It can be any site that ytdl supports.
+    3. You'll then be asked if you'd like to run the transcription through GPU(1) or CPU(2).
+    4. Next, the video will be downloaded to the local directory by ytdl.
+    5. Then the video will be transcribed by faster_whisper. (You can see this in the console output)
+      * The resulting transcription output will be stored as both a json file with timestamps, as well as a txt file with no timestamps.
+    6. Finally, you can have the transcription summarized through feeding it into an LLM of your choice.
+    7. For running it locally, here's the commands to do so:
+      * FIXME
+    8. For feeding the transcriptions to the API of your choice, simply use the corresponding script for your API provider.
+      * FIXME: add scripts for OpenAI api (generic) and others
 
 ### Credits
 - [original](https://github.com/the-crypt-keeper/tldw)