From 9e96914c765df852e0fee6f08b1009c3796ed551 Mon Sep 17 00:00:00 2001
From: thibaut <thibaut@konsensus.network>
Date: Sat, 1 Mar 2025 21:23:37 +0100
Subject: [PATCH] Revert extra changes to cli

---
 book_maker/cli.py | 8 +++++---
 1 file changed, 5 insertions(+), 3 deletions(-)

diff --git a/book_maker/cli.py b/book_maker/cli.py
index 2dd1c5a..001ecfc 100644
--- a/book_maker/cli.py
+++ b/book_maker/cli.py
@@ -55,6 +55,7 @@ def parse_prompt_arg(prompt_arg):
     if not any(prompt_arg.endswith(ext) for ext in [".json", ".txt", ".md"]):
         try:
             # user can define prompt by passing a json string
+            # eg: --prompt '{"system": "You are a professional translator who translates computer technology books", "user": "Translate \`{text}\` to {language}"}'
             prompt = json.loads(prompt_arg)
         except json.JSONDecodeError:
             # if not a json string, treat it as a template string
@@ -67,12 +68,13 @@ def parse_prompt_arg(prompt_arg):
                 prompt = {"user": f.read()}
         elif prompt_arg.endswith(".json"):
             # if it's a json file, treat it as a json object
+            # eg: --prompt prompt_template_sample.json
             with open(prompt_arg, encoding="utf-8") as f:
                 prompt = json.load(f)
     else:
         raise FileNotFoundError(f"{prompt_arg} not found")
 
-    # Validate the prompt
+    # if prompt is None or any(c not in prompt["user"] for c in ["{text}", "{language}"]):
     if prompt is None or any(c not in prompt["user"] for c in ["{text}"]):
         raise ValueError("prompt must contain `{text}`")
 
@@ -85,6 +87,7 @@ def parse_prompt_arg(prompt_arg):
     print("prompt config:", prompt)
     return prompt
 
+
 def main():
     translate_model_list = list(MODEL_DICT.keys())
     parser = argparse.ArgumentParser()
@@ -281,7 +284,7 @@ def main():
         "--accumulated_num",
         dest="accumulated_num",
         type=int,
-        default=200000,
+        default=1,
         help="""Wait for how many tokens have been accumulated before starting the translation.
 gpt3.5 limits the total_token to 4090.
 For example, if you use --accumulated_num 1600, maybe openai will output 2200 tokens
@@ -299,7 +302,6 @@ So you are close to reaching the limit. You have to choose your own value, there
         "--batch_size",
         dest="batch_size",
         type=int,
-        default=500,
         help="how many lines will be translated by aggregated translation(This options currently only applies to txt files)",
     )
     parser.add_argument(