diff --git a/.gitignore b/.gitignore
new file mode 100644
index 0000000..335ec95
--- /dev/null
+++ b/.gitignore
@@ -0,0 +1 @@
+*.tar.gz
diff --git a/api/readme.md b/api/readme.md
index 5ae6ffd..a14fdfc 100644
--- a/api/readme.md
+++ b/api/readme.md
@@ -1,9 +1,15 @@
 # Chatbots API
 
-FastAPI and PyTorch
+[FastAPI](https://fastapi.tiangolo.com/) and [PyTorch](https://pytorch.org/)
 
-To build yourself you'll need to first train a model with ../train
+To build one yourself you'll need to first [train a model](../train),  
+place the entire directory (checkpoints aren't needed) containing pytorch_model.bin in [bots](./src/bots), 
+then edit or duplicate [cartman.py](./src/bots/cartman.py).
 
-My image compressed is 1.4GB
+Cartman Docker images for are availible for 
+[x86_64](https://doordesk.net/files/chatbots_api_x86_64.tar.gz) (1.6GB) and 
+[aarch64](https://doordesk.net/files/chatbots_api_x86_64.tar.gz) (1.4GB)
 
-Scripts in test to talk to it
+See [run](./run) and [test](./test) to interact with it
+
+Live demo [here](https://doordesk.net/cartman)
diff --git a/train/.gitignore b/train/.gitignore
index 33a1886..2099bbc 100644
--- a/train/.gitignore
+++ b/train/.gitignore
@@ -1,3 +1,5 @@
 __pycache__/
 .ipynb_checkpoints/
 cartman/
+cached/
+runs/
diff --git a/train/clean.py b/train/clean.py
index e5ad18e..b874f84 100644
--- a/train/clean.py
+++ b/train/clean.py
@@ -1,18 +1,28 @@
 import pandas as pd
-df = pd.read_csv('./data/All-seasons.csv')
-cleanlines = pd.Series(
-    [cell
+
+INPUT_FILE_PATH = './data/All-seasons.csv'
+OUPUT_FILE_PATH = './data/train_data.csv'
+
+
+df = pd.read_csv(INPUT_FILE_PATH)
+
+clean_lines = pd.Series(
+    [filter_lines
         .replace('\n', '')
         .replace('(', '')
         .replace(')', '')
         .replace('  ', ' ')
         .strip()
-        for cell in df.Line
+        for filter_lines in df.Line
      ]
 )
 
-train = pd.DataFrame(df.Character)
-train['line'] = cleanlines
-train.columns = ['name', 'line']
+train_data = pd.DataFrame(df.Character)
+del df
 
-train.to_csv('./data/train.csv', index=False)
+train_data['line'] = clean_lines
+
+train_data.columns = ['name', 'line']
+
+
+train_data.to_csv(OUPUT_FILE_PATH, index=False)