Upload EDEN model and code

README.md

@@ -52,16 +52,38 @@ First install the two dependencies (one time):
 pip3 install torch transformers
 ```
 
-### Option 1: one terminal command
+### Option 1: chat with EDEN in the terminal (recommended)
 
-Paste this whole line into your terminal. It downloads the model the first time
-and prints the cleaned-up sentence:
+This opens a simple interactive interface, similar to Ollama. Type or paste
+rough text, press Enter, and get the cleaned-up version. Type `/bye` or press
+Ctrl+D to quit.
 
 ```bash
-python3 -c "from transformers import AutoModel, AutoTokenizer; t=AutoTokenizer.from_pretrained('Rybib/EDEN'); m=AutoModel.from_pretrained('Rybib/EDEN', trust_remote_code=True).eval(); print(m.enhance(t, 'i relly wnt this to sound beter'))"
+python3 examples/try_eden.py
 ```
 
-### Option 2: a Python script
+macOS users can also double-click `Try EDEN.command` to open the same interface
+in a terminal window.
+
+Example session:
+
+```text
+>>> their are alot of reasons why this dont work proper
+There are a lot of reasons why this do not work proper.
+
+>>> /bye
+Goodbye.
+```
+
+### Option 2: one terminal command
+
+Paste this whole line into your terminal to clean a single sentence:
+
+```bash
+python3 -c "from transformers import AutoModel, AutoTokenizer; t=AutoTokenizer.from_pretrained('Rybib/EDEN', trust_remote_code=True); m=AutoModel.from_pretrained('Rybib/EDEN', trust_remote_code=True).eval(); print(m.enhance(t, 'i relly wnt this to sound beter'))"
+```
+
+### Option 3: a Python script
 
 The lines below are Python, not terminal commands. Save them as a file such as
 `run.py`, then run `python3 run.py`. Do not paste them straight into the
@@ -72,7 +94,7 @@ from transformers import AutoModel, AutoTokenizer
 
 model_id = "Rybib/EDEN"
 
-tokenizer = AutoTokenizer.from_pretrained(model_id)
+tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
 model = AutoModel.from_pretrained(model_id, trust_remote_code=True).eval()
 
 rough = "i relly wnt this sentance to sound more profesional"
@@ -80,19 +102,6 @@ print(model.enhance(tokenizer, rough))
 # I really want this sentence to sound more professional.
 ```
 
-### Option 3: interactive helper script
-
-This repository includes `examples/try_eden.py`, which loads the model and lets
-you type text and get it cleaned up:
-
-```bash
-python3 examples/try_eden.py                    # interactive
-python3 examples/try_eden.py "fix this sentance" # one-shot
-```
-
-macOS users can also double-click `Try EDEN.command` to open an interactive
-session in a terminal window.
-
 The `enhance` method handles long inputs by splitting them into sentence-aware
 chunks, rewriting each chunk, and joining the results.
 

examples/try_eden.py

@@ -1,19 +1,40 @@
-"""Try the published EDEN model with no setup beyond pip install.
+"""Talk to EDEN in the terminal, similar to how Ollama works.
 
-This downloads the model from the Hugging Face Hub the first time it runs and
-caches it. After that it works offline.
+This downloads the published model from the Hugging Face Hub the first time it
+runs and caches it. After that it works offline.
 
 Usage:
-    python try_eden.py                      # interactive: type text, get it fixed
-    python try_eden.py "some rough text"    # one-shot: fix the given text
+    python3 try_eden.py                       # open the chat interface
+    python3 try_eden.py "some rough text"     # one-shot: clean the given text
 """
 
 import sys
 
 MODEL_ID = "Rybib/EDEN"
 
+# ANSI styles, used only when writing to a real terminal.
+_TTY = sys.stdout.isatty()
+BOLD = "\033[1m" if _TTY else ""
+DIM = "\033[2m" if _TTY else ""
+GREEN = "\033[32m" if _TTY else ""
+CYAN = "\033[36m" if _TTY else ""
+RESET = "\033[0m" if _TTY else ""
 
-def main() -> None:
+BANNER = f"""{CYAN}{BOLD}
+  EDEN  ::  Encoder Decoder Enhancement Network
+{RESET}{DIM}  Type or paste rough text and press Enter to clean it up.
+  Commands:  /help   show help      /bye  quit      (Ctrl+D also quits)
+{RESET}"""
+
+HELP = f"""{DIM}
+  Just type or paste text, then press Enter, and EDEN rewrites it.
+  Commands:
+    /help      show this help
+    /bye       quit (so do /exit, /quit, and Ctrl+D)
+{RESET}"""
+
+
+def load_model():
     try:
         from transformers import AutoModel, AutoTokenizer
     except ImportError:
@@ -21,28 +42,41 @@ def main() -> None:
         print("    pip3 install torch transformers")
         sys.exit(1)
 
-    print(f"Loading {MODEL_ID} (first run downloads about 430 MB, please wait) ...")
-    tokenizer = AutoTokenizer.from_pretrained(MODEL_ID)
+    print(f"{DIM}Loading {MODEL_ID} (first run downloads about 430 MB) ...{RESET}")
+    tokenizer = AutoTokenizer.from_pretrained(MODEL_ID, trust_remote_code=True)
     model = AutoModel.from_pretrained(MODEL_ID, trust_remote_code=True).eval()
-    print("Ready.\n")
+    return model, tokenizer
+
 
+def main() -> None:
+    model, tokenizer = load_model()
+
+    # One-shot mode: clean the text passed as arguments and exit.
     args = [a for a in sys.argv[1:] if a.strip()]
     if args:
-        text = " ".join(args)
-        print(model.enhance(tokenizer, text))
+        print(model.enhance(tokenizer, " ".join(args)))
         return
 
-    print("Type rough text and press Enter to clean it up.")
-    print("Press Ctrl+C or Ctrl+D to quit.\n")
+    # Interactive chat mode.
+    print(BANNER)
     while True:
         try:
-            text = input("rough> ").strip()
+            text = input(f"{GREEN}{BOLD}>>> {RESET}").strip()
         except (EOFError, KeyboardInterrupt):
-            print("\nGoodbye.")
+            print(f"\n{DIM}Goodbye.{RESET}")
             return
+
         if not text:
             continue
-        print("clean> " + model.enhance(tokenizer, text) + "\n")
+        if text.lower() in {"/bye", "/exit", "/quit", "/q"}:
+            print(f"{DIM}Goodbye.{RESET}")
+            return
+        if text.lower() in {"/help", "/h", "/?"}:
+            print(HELP)
+            continue
+
+        cleaned = model.enhance(tokenizer, text)
+        print(f"{CYAN}{cleaned}{RESET}\n")
 
 
 if __name__ == "__main__":

examples/use_with_transformers.py

@@ -19,7 +19,7 @@ from transformers import AutoModel, AutoTokenizer
 # Point this at the published model id or a local path to this repository.
 MODEL_ID = REPO_ROOT
 
-tokenizer = AutoTokenizer.from_pretrained(MODEL_ID)
+tokenizer = AutoTokenizer.from_pretrained(MODEL_ID, trust_remote_code=True)
 model = AutoModel.from_pretrained(MODEL_ID, trust_remote_code=True).eval()
 
 examples = [