docs: Pass on README.md

README.md

@@ -1,104 +1,181 @@
 # Colab CLI
 
-A command-line interface for Google Colab. Create sessions, run code, manage files, and capture work — all without leaving your terminal.
+A command-line interface for Google Colab. Provision high-performance CPU, GPU, and TPU runtimes, execute local code, manage remote files, and orchestrate automated cloud pipelines — directly from your terminal.
 
-> Why? The agents are coming.
+Designed to support seamless developer productivity, headless automation, and AI agent integrations.
 
-## Install
+---
 
-With uv
+## Key Features
 
-```bash
-uv tool install -U google-colab-cli
-```
+* **Instant VM Provisioning:** Spin up CPU, GPU (T4, L4, G4, H100, A100), or TPU (v5e1, v6e1) runtimes in seconds.
+* **Robust Code Execution:** Run local Python scripts, Jupyter Notebooks (`.ipynb`), or piped `stdin` code; launch interactive REPLs or raw TTY console shells.
+* **Ephemeral Job Runner (`colab run`):** Provision a fresh VM, execute a local script with forwarded arguments, retrieve output files, and automatically tear down the runtime in a single command.
+* **Automatic Keep-Alive:** Built-in background daemon automatically prevents idle VM termination, keeping resource allocations active without requiring open browser tabs.
+* **Seamless Workspace Automation:** Mount Google Drive, authenticate Google Cloud Platform (GCP) credentials, and install dependencies with high-performance `uv` package management.
+* **State & Log Archival:** Inspect local session states or export interactive history logs to standard Jupyter Notebooks, Markdown, or structured JSONL.
+
+---
 
-or with pip
+## Installation
+
+Install the package using `uv` (recommended) or standard `pip`:
 
 ```bash
-pip install -U google-colab-cli
-```
+# Using uv (recommended)
+uv tool install google-colab-cli
 
+# Using pip
+pip install google-colab-cli
+```
 
-Note: If you have a non-standard default package index (Googlers), you may also need to add `--index https://pypi.org/simple`.
+---
 
+## Quick Start
 
-## Quick start
+Run a CPU-based VM runtime, execute some code, and clean up:
 
 ```bash
-colab new                              # provision a CPU session
-echo "print('hello')" | colab exec     # run code
-colab stop                             # release the VM
+# 1. Provision a new session
+colab new
+
+# 2. Execute code from stdin
+echo "print('Hello from Google Colab!')" | colab exec
+
+# 3. Stop and release the VM resource
+colab stop
 ```
 
-When only one session is active you can omit `-s <session>`; the CLI selects it automatically.
+> [!NOTE]
+> When only one session is active, you can omit the `-s, --session` option;
+> the CLI automatically knows it.
+
+
+---
 
-## Commands
+## Command Index
 
-### Sessions
+Run `colab <command> --help` to view specific options, defaults, and detailed help.
+
+### Session Management
 | Command | Description |
 | --- | --- |
-| `colab new [-s NAME] [--gpu T4\|L4\|A100\|H100] [--tpu v5e1\|v6e1]` | Provision a new session (CPU by default) |
-| `colab sessions` | List all active sessions on the backend |
-| `colab status [-s NAME]` | Show one session, or all locally-known sessions |
-| `colab stop -s NAME` | Terminate a session |
-| `colab url [-s NAME] [--open]` | Print a browser URL that opens the session in Colab |
+| `colab new [-s NAME] [--gpu GPU] [--tpu TPU]` | Allocate a new CPU, GPU, or TPU VM runtime |
+| `colab sessions` | List all active sessions currently active on the backend |
+| `colab status [-s NAME]` | Display hardware, status, and local metadata for active sessions |
+| `colab restart-kernel [-s NAME]` | Restart the active session's Jupyter kernel |
+| `colab stop [-s NAME]` | Terminate a session VM and tear down its keep-alive daemon |
+| `colab url [-s NAME] [--open]` | Print or open a browser URL connecting to the active session |
 
 ### Execution
 | Command | Description |
 | --- | --- |
-| `colab exec [-s NAME] [-f FILE] [--output-image PATH]` | Run Python from stdin, a `.py` file, or a `.ipynb` notebook |
-| `colab repl [-s NAME] [--output-image PATH]` | Interactive Python REPL (or one-shot if stdin is piped) |
-| `colab console [-s NAME]` | Raw TTY shell on the VM (or one-shot if stdin is piped) |
+| `colab run [--gpu GPU] [--tpu TPU] [--keep] SCRIPT [ARGS...]` | Run a local script on a fresh VM, forwarding arguments, then release it |
+| `colab exec [-s NAME] [-f FILE] [--output-image PATH]` | Execute Python code from stdin, a local `.py` file, or a `.ipynb` notebook |
+| `colab repl [-s NAME] [--output-image PATH]` | Start an interactive Python REPL on the VM (exits cleanly on piped EOF) |
+| `colab console [-s NAME]` | Connect to a raw interactive TTY shell (tmux) on the remote VM |
 
-### Files
+### File Operations
 | Command | Description |
 | --- | --- |
-| `colab ls [-s NAME] [PATH]` | List remote files |
-| `colab upload -s NAME LOCAL REMOTE` | Upload a file |
-| `colab download -s NAME REMOTE LOCAL` | Download a file |
-| `colab rm -s NAME PATH` | Delete a remote file |
-| `colab edit -s NAME PATH` | Edit a remote file in `$EDITOR` |
+| `colab ls [-s NAME] [PATH]` | List remote files on the VM |
+| `colab upload [-s NAME] LOCAL REMOTE` | Upload a local file to the VM filesystem |
+| `colab download [-s NAME] REMOTE LOCAL` | Download a remote file from the VM filesystem |
+| `colab rm [-s NAME] PATH` | Delete a remote file on the VM filesystem |
+| `colab edit [-s NAME] PATH` | Edit a remote file in-place using your local `$EDITOR` |
 
-### Automation & utility
+### Automation & Utilities
 | Command | Description |
 | --- | --- |
-| `colab auth -s NAME` | Authenticate the VM for GCP services |
-| `colab drivemount -s NAME [PATH]` | Mount Google Drive (default `/content/drive`) |
-| `colab install -s NAME [-r requirements.txt \| pkg ...]` | Install packages with `uv` (falls back to `pip`) |
-| `colab log [-s NAME] [-n N] [-o FILE]` | View or export session history (`.ipynb`/`.md`/`.txt`/`.jsonl`) |
-| `colab pay` | Open the Colab signup page |
-| `colab version` | Print the installed version |
-| `colab update [--install]` | Check for a newer release (and optionally install it) |
-| `colab help` | Show usage |
-
-### Global options
-- `--auth {oauth2,adc}` — authentication strategy (default `oauth2`)
-- `-c, --client-oauth-config PATH` — OAuth client config (default `~/.colab-cli-oauth-config.json`)
-- `--config PATH` — session state file (default `~/.config/colab-cli/sessions.json`)
-- `--logtostderr` — send all output to stderr
-
-## Examples
+| `colab auth [-s NAME]` | Authenticate the VM for GCP services (BigQuery, GCS, etc.) |
+| `colab drivemount [-s NAME] [PATH]` | Mount Google Drive on the VM (default: `/content/drive`) |
+| `colab install [-s NAME] [-r FILE \| PKG...]` | Install packages on the VM using `uv` (falls back to `pip`) |
+| `colab log [-s NAME] [-n N] [-o FILE]` | View or export session history (`.ipynb`, `.md`, `.txt`, `.jsonl`) |
+| `colab pay` | Open the Colab subscription page to manage compute units |
+| `colab version` | Print the installed version of the CLI |
+| `colab update [--install]` | Check for a newer release (and optionally upgrade the CLI in place) |
+
+### Global Options
+* `--auth {oauth2,adc}` — Authentication strategy for the Colab API (default: `adc`).
+* `-c, --client-oauth-config PATH` — Path to public OAuth client credentials configuration (default: `~/.colab-cli-oauth-config.json`).
+* `--config PATH` — Path to local session metadata storage (default: `~/.config/colab-cli/sessions.json`).
+* `--logtostderr` — Direct debug logging output to stderr.
+
+---
+
+## Practical Examples
+
+### Accelerator Training with Checkpoint Retrieval
+
+Provision an A100 GPU, install requirements, run a local training script, retrieve the resulting model weights, and terminate the VM:
 
 ```bash
-# Train a model on an A100, save the checkpoint locally
 colab new -s trainer --gpu A100
 colab install -s trainer torch transformers
 colab exec -s trainer -f train.py
 colab download -s trainer checkpoints/model.bin ./model.bin
 colab stop -s trainer
+```
+
+### Workspace Notebook Execution with Drive Integration
 
-# Mount Drive and analyze a notebook
+Mount Google Drive, run a local notebook against the VM kernel (outputs are written back into `report_output.ipynb`), export a Markdown log of the execution, and clean up:
+
+```bash
 colab new -s analysis
 colab drivemount -s analysis
-colab exec -s analysis -f analysis.ipynb       # writes analysis_output.ipynb
-colab log -s analysis -o report.ipynb
+colab exec -s analysis -f report.ipynb
+colab log -s analysis -o execution_log.md
 colab stop -s analysis
 ```
 
-## Notes
+---
+
+## Usage Notes
+
+* **TTY Requirements:** The interactive commands `repl` and `console` require a local TTY. When running inside automated scripts or pipelines, make sure to pipe stdin (e.g., `echo "print(1)" | colab repl`) to trigger non-interactive execution modes.
+* **Transparent Code Execution:** When calling `colab exec -f file.py`, the CLI reads the file locally and transmits its content to the remote kernel. You do not need to manually upload files before execution.
+* **Storage & State Paths:** Session tokens and metadata are stored at `~/.config/colab-cli/sessions.json`. Global CLI settings are located at `~/.config/colab-cli/settings.json`. These can be customized or isolated via the global `--config` flag.
+
+### Ephemeral Accelerator Jobs
+
+Use `colab run` to run a local script on dedicated hardware without manual session lifecycle management. The CLI handles provisioning, script execution, and immediate VM teardown automatically:
+
+```bash
+# Run train.py on a T4 GPU and release the VM on completion
+colab run --gpu T4 train.py
+```
+
+### Shebang Execution Support
+
+To execute a local file directly on a remote accelerator, place the `colab run` interpreter in the shebang line:
+
+```python
+#!/usr/bin/env -S colab run --gpu L4 --keep
+import torch
+
+print("L4 GPU Available:", torch.cuda.is_available())
+print("Device Name:", torch.cuda.get_device_name(0))
+```
+
+Make the script executable (`chmod +x script.py`) and run it: `./script.py`. The `--keep` option tells the CLI to preserve the session VM on completion so you can re-execute or inspect logs.
+
+---
+
+## Deep Dive Documentation
+
+For comprehensive architectural overviews and deep-dives into specific CLI sub-systems, refer to the detailed documentation:
+
+* [Session Management & Keep-Alive Architecture](docs/01_session_management.md)
+* [Interactive & Non-Interactive Execution Design](docs/02_execution_and_interactive.md)
+* [File Management & Jupyter Contents API](docs/03_file_management.md)
+* [Authentication Providers & VM Automation](docs/04_automation_and_utility.md)
+* [Ephemeral Job Runner Design](docs/05_run_command.md)
+
+To view interactive walkthroughs of eleven real-world automated scenarios, check out the [Demo Walkthroughs](docs/demos.md).
+
+---
 
-- `repl` and `console` require a TTY when run interactively. Pipe stdin to use them in scripts.
-- `exec` reads files locally and ships their contents to the VM — local edits don't require uploading.
-- Session metadata is stored at `~/.config/colab-cli/sessions.json`. Settings (auto-update etc.) live at `~/.config/colab-cli/settings.json`.
+## Contributing
 
-See [`CONTRIBUTING.md`](./CONTRIBUTING.md) for how to file feedback.
+Feedback and contributions are welcome! Please read [`CONTRIBUTING.md`](./CONTRIBUTING.md) for details.