Merge branch 'main' of https://github.com/yihong0618/bilingual_book_maker

Signed-off-by: yihong0618 <zouzou0208@gmail.com>

.github/workflows/docs.yaml

@@ -11,6 +11,6 @@ jobs:
       - uses: actions/checkout@v2
       - uses: actions/setup-python@v2
         with:
-          python-version: '3.9'
+          python-version: '3.10'
       - run: pip install mkdocs mkdocs-material
-      - run: mkdocs gh-deploy --force
+      - run: mkdocs gh-deploy --force

.github/workflows/make_test_ebook.yaml

@@ -27,10 +27,10 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - uses: actions/checkout@v3
-      - name: install python 3.9 
+      - name: install python 3.10
         uses: actions/setup-python@v4
         with:
-          python-version: '3.9'
+          python-version: '3.10'
           cache: 'pip' # caching pip dependencies
       - name: Check formatting (black)
         run: |
@@ -71,7 +71,7 @@ jobs:
             
       - name: Rename and Upload ePub
         if: env.OPENAI_API_KEY != null
-        uses: actions/upload-artifact@v3
+        uses: actions/upload-artifact@v4
         with:
           name: epub_output
           path: "test_books/lemo_bilingual.epub"

.gitignore

@@ -138,3 +138,10 @@ log/
 *.srt
 *.txt
 *.bin
+*.epub
+
+# For markdown files in user directories
+.cursorrules
+books/
+prompts/
+.pdm-python

.pdm-python

@@ -1 +0,0 @@
-/home/yihong/use_now/bilingual_book_maker/.venv/bin/python

Dockerfile

@@ -4,10 +4,10 @@ RUN apt-get update
 
 WORKDIR /app
 
-COPY requirements.txt setup.py .
+COPY requirements.txt .
 
 RUN pip install -r /app/requirements.txt
 
 COPY . .
 
-ENTRYPOINT ["python3", "make_book.py"]
+ENTRYPOINT ["python3", "make_book.py"]

README.md

@@ -167,6 +167,21 @@ bbook --book_name test_books/animal_farm.epub --openai_key ${openai_key} --test
   - If you don't need to set the `system` role content, you can simply set it up like this: `--prompt "Translate {text} to {language}."` or `--prompt prompt_template_sample.txt` (example of a text file can be found at [./prompt_template_sample.txt](./prompt_template_sample.txt)).
 
   - If you need to set the `system` role content, you can use the following format: `--prompt '{"user":"Translate {text} to {language}", "system": "You are a professional translator."}'` or `--prompt prompt_template_sample.json` (example of a JSON file can be found at [./prompt_template_sample.json](./prompt_template_sample.json)).
+  
+  - You can now use [PromptDown](https://github.com/btfranklin/promptdown) format (`.md` files) for more structured prompts: `--prompt prompt_md.prompt.md`. PromptDown supports both traditional system messages and developer messages (used by newer AI models). Example:
+  
+      ```markdown
+      # Translation Prompt
+      
+      ## Developer Message
+      You are a professional translator who specializes in accurate translations.
+      
+      ## Conversation
+      
+      | Role  | Content                                           |
+      |-------|---------------------------------------------------|
+      | User  | Please translate the following text into {language}:\n\n{text} |
+      ```
 
   - You can also set the `user` and `system` role prompt by setting environment variables: `BBM_CHATGPTAPI_USER_MSG_TEMPLATE` and `BBM_CHATGPTAPI_SYS_MSG`.
 

book_maker/cli.py

@@ -13,7 +13,60 @@ def parse_prompt_arg(prompt_arg):
     if prompt_arg is None:
         return prompt
 
-    if not any(prompt_arg.endswith(ext) for ext in [".json", ".txt"]):
+    # Check if it's a path to a markdown file (PromptDown format)
+    if prompt_arg.endswith(".md") and os.path.exists(prompt_arg):
+        try:
+            from promptdown import StructuredPrompt
+
+            structured_prompt = StructuredPrompt.from_promptdown_file(prompt_arg)
+
+            # Initialize our prompt structure
+            prompt = {}
+
+            # Handle developer_message or system_message
+            # Developer message takes precedence if both are present
+            if (
+                hasattr(structured_prompt, "developer_message")
+                and structured_prompt.developer_message
+            ):
+                prompt["system"] = structured_prompt.developer_message
+            elif (
+                hasattr(structured_prompt, "system_message")
+                and structured_prompt.system_message
+            ):
+                prompt["system"] = structured_prompt.system_message
+
+            # Extract user message from conversation
+            if (
+                hasattr(structured_prompt, "conversation")
+                and structured_prompt.conversation
+            ):
+                for message in structured_prompt.conversation:
+                    if message.role.lower() == "user":
+                        prompt["user"] = message.content
+                        break
+
+            # Ensure we found a user message
+            if "user" not in prompt or not prompt["user"]:
+                raise ValueError(
+                    "PromptDown file must contain at least one user message"
+                )
+
+            print(f"Successfully loaded PromptDown file: {prompt_arg}")
+
+            # Validate required placeholders
+            if any(c not in prompt["user"] for c in ["{text}"]):
+                raise ValueError(
+                    "User message in PromptDown must contain `{text}` placeholder"
+                )
+
+            return prompt
+        except Exception as e:
+            print(f"Error parsing PromptDown file: {e}")
+            # Fall through to other parsing methods
+
+    # Existing parsing logic for JSON strings and other formats
+    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}"}'
@@ -349,7 +402,17 @@ So you are close to reaching the limit. You have to choose your own value, there
     translate_model = MODEL_DICT.get(options.model)
     assert translate_model is not None, "unsupported model"
     API_KEY = ""
-    if options.model in ["openai", "chatgptapi", "gpt4", "gpt4omini", "gpt4o"]:
+    if options.model in [
+        "openai",
+        "chatgptapi",
+        "gpt4",
+        "gpt4omini",
+        "gpt4o",
+        "o1preview",
+        "o1",
+        "o1mini",
+        "o3mini",
+    ]:
         if OPENAI_API_KEY := (
             options.openai_key
             or env.get(
@@ -471,6 +534,10 @@ So you are close to reaching the limit. You have to choose your own value, there
             "gpt4",
             "gpt4omini",
             "gpt4o",
+            "o1",
+            "o1preview",
+            "o1mini",
+            "o3mini",
         ], "only support chatgptapi for deployment_id"
         if not options.api_base:
             raise ValueError("`api_base` must be provided when using `deployment_id`")
@@ -495,6 +562,14 @@ So you are close to reaching the limit. You have to choose your own value, there
         e.translate_model.set_gpt4omini_models()
     if options.model == "gpt4o":
         e.translate_model.set_gpt4o_models()
+    if options.model == "o1preview":
+        e.translate_model.set_o1preview_models()
+    if options.model == "o1":
+        e.translate_model.set_o1_models()
+    if options.model == "o1mini":
+        e.translate_model.set_o1mini_models()
+    if options.model == "o3mini":
+        e.translate_model.set_o3mini_models()
     if options.model.startswith("claude-"):
         e.translate_model.set_claude_model(options.model)
     if options.block_size > 0:

book_maker/translator/__init__.py

@@ -16,6 +16,10 @@ MODEL_DICT = {
     "gpt4": ChatGPTAPI,
     "gpt4omini": ChatGPTAPI,
     "gpt4o": ChatGPTAPI,
+    "o1preview": ChatGPTAPI,
+    "o1": ChatGPTAPI,
+    "o1mini": ChatGPTAPI,
+    "o3mini": ChatGPTAPI,
     "google": Google,
     "caiyun": Caiyun,
     "deepl": DeepL,

book_maker/translator/chatgptapi_translator.py

@@ -48,6 +48,21 @@ GPT4o_MODEL_LIST = [
     "gpt-4o-2024-08-06",
     "chatgpt-4o-latest",
 ]
+O1PREVIEW_MODEL_LIST = [
+    "o1-preview",
+    "o1-preview-2024-09-12",
+]
+O1_MODEL_LIST = [
+    "o1",
+    "o1-2024-12-17",
+]
+O1MINI_MODEL_LIST = [
+    "o1-mini",
+    "o1-mini-2024-09-12",
+]
+O3MINI_MODEL_LIST = [
+    "o3-mini",
+]
 
 
 class ChatGPTAPI(Base):
@@ -215,40 +230,6 @@ class ChatGPTAPI(Base):
         lines = [line.strip() for line in lines if line.strip() != ""]
         return lines
 
-    def get_best_result_list(
-        self,
-        plist_len,
-        new_str,
-        sleep_dur,
-        result_list,
-        max_retries=15,
-    ):
-        if len(result_list) == plist_len:
-            return result_list, 0
-
-        best_result_list = result_list
-        retry_count = 0
-
-        while retry_count < max_retries and len(result_list) != plist_len:
-            print(
-                f"bug: {plist_len} -> {len(result_list)} : Number of paragraphs before and after translation",
-            )
-            print(f"sleep for {sleep_dur}s and retry {retry_count+1} ...")
-            time.sleep(sleep_dur)
-            retry_count += 1
-            result_list = self.translate_and_split_lines(new_str)
-            if (
-                len(result_list) == plist_len
-                or len(best_result_list) < len(result_list) <= plist_len
-                or (
-                    len(result_list) < len(best_result_list)
-                    and len(best_result_list) > plist_len
-                )
-            ):
-                best_result_list = result_list
-
-        return best_result_list, retry_count
-
     def log_retry(self, state, retry_count, elapsed_time, log_path="log/buglog.txt"):
         if retry_count == 0:
             return
@@ -318,48 +299,131 @@ class ChatGPTAPI(Base):
         return new_text
 
     def translate_list(self, plist):
-        sep = "\n\n\n\n\n"
-        # new_str = sep.join([item.text for item in plist])
+        plist_len = len(plist)
 
-        new_str = ""
-        i = 1
-        for p in plist:
+        # Create a list of original texts and add clear numbering markers to each paragraph
+        formatted_text = ""
+        for i, p in enumerate(plist, 1):
             temp_p = copy(p)
             for sup in temp_p.find_all("sup"):
                 sup.extract()
-            new_str += f"({i}) {temp_p.get_text().strip()}{sep}"
-            i = i + 1
+            para_text = temp_p.get_text().strip()
+            # Using special delimiters and clear numbering
+            formatted_text += f"PARAGRAPH {i}:\n{para_text}\n\n"
 
-        if new_str.endswith(sep):
-            new_str = new_str[: -len(sep)]
+        print(f"plist len = {plist_len}")
 
-        new_str = self.join_lines(new_str)
+        original_prompt_template = self.prompt_template
 
-        plist_len = len(plist)
-
-        print(f"plist len = {len(plist)}")
-
-        result_list = self.translate_and_split_lines(new_str)
-
-        start_time = time.time()
-
-        result_list, retry_count = self.get_best_result_list(
-            plist_len,
-            new_str,
-            6,  # WTF this magic number here?
-            result_list,
+        structured_prompt = (
+            f"Translate the following {plist_len} paragraphs to {{language}}. "
+            f"CRUCIAL INSTRUCTION: Format your response using EXACTLY this structure:\n\n"
+            f"TRANSLATION OF PARAGRAPH 1:\n[Your translation of paragraph 1 here]\n\n"
+            f"TRANSLATION OF PARAGRAPH 2:\n[Your translation of paragraph 2 here]\n\n"
+            f"... and so on for all {plist_len} paragraphs.\n\n"
+            f"You MUST provide EXACTLY {plist_len} translated paragraphs. "
+            f"Do not merge, split, or rearrange paragraphs. "
+            f"Translate each paragraph independently but consistently. "
+            f"Keep all numbers and special formatting in your translation. "
+            f"Each original paragraph must correspond to exactly one translated paragraph."
         )
 
-        end_time = time.time()
+        self.prompt_template = structured_prompt + " ```{text}```"
 
-        state = "fail" if len(result_list) != plist_len else "success"
-        log_path = "log/buglog.txt"
+        translated_text = self.translate(formatted_text, False)
 
-        self.log_retry(state, retry_count, end_time - start_time, log_path)
-        self.log_translation_mismatch(plist_len, result_list, new_str, sep, log_path)
+        # Extract translations from structured output
+        translated_paragraphs = []
+        for i in range(1, plist_len + 1):
+            pattern = (
+                r"TRANSLATION OF PARAGRAPH "
+                + str(i)
+                + r":(.*?)(?=TRANSLATION OF PARAGRAPH \d+:|\Z)"
+            )
+            matches = re.findall(pattern, translated_text, re.DOTALL)
+
+            if matches:
+                translated_paragraph = matches[0].strip()
+                translated_paragraphs.append(translated_paragraph)
+            else:
+                print(f"Warning: Could not find translation for paragraph {i}")
+                loose_pattern = (
+                    r"(?:TRANSLATION|PARAGRAPH|PARA).*?"
+                    + str(i)
+                    + r".*?:(.*?)(?=(?:TRANSLATION|PARAGRAPH|PARA).*?\d+.*?:|\Z)"
+                )
+                loose_matches = re.findall(loose_pattern, translated_text, re.DOTALL)
+                if loose_matches:
+                    translated_paragraphs.append(loose_matches[0].strip())
+                else:
+                    translated_paragraphs.append("")
+
+        self.prompt_template = original_prompt_template
+
+        # If the number of extracted paragraphs is incorrect, try the alternative extraction method.
+        if len(translated_paragraphs) != plist_len:
+            print(
+                f"Warning: Extracted {len(translated_paragraphs)}/{plist_len} paragraphs. Using fallback extraction."
+            )
+
+            all_para_pattern = r"(?:TRANSLATION|PARAGRAPH|PARA).*?(\d+).*?:(.*?)(?=(?:TRANSLATION|PARAGRAPH|PARA).*?\d+.*?:|\Z)"
+            all_matches = re.findall(all_para_pattern, translated_text, re.DOTALL)
+
+            if all_matches:
+                # Create a dictionary to map translation content based on paragraph numbers
+                para_dict = {}
+                for num_str, content in all_matches:
+                    try:
+                        num = int(num_str)
+                        if 1 <= num <= plist_len:
+                            para_dict[num] = content.strip()
+                    except ValueError:
+                        continue
+
+                # Rebuild the translation list in the original order
+                new_translated_paragraphs = []
+                for i in range(1, plist_len + 1):
+                    if i in para_dict:
+                        new_translated_paragraphs.append(para_dict[i])
+                    else:
+                        new_translated_paragraphs.append("")
+
+                if len(new_translated_paragraphs) == plist_len:
+                    translated_paragraphs = new_translated_paragraphs
+
+        if len(translated_paragraphs) < plist_len:
+            translated_paragraphs.extend(
+                [""] * (plist_len - len(translated_paragraphs))
+            )
+        elif len(translated_paragraphs) > plist_len:
+            translated_paragraphs = translated_paragraphs[:plist_len]
+
+        return translated_paragraphs
+
+    def extract_paragraphs(self, text, paragraph_count):
+        """Extract paragraphs from translated text, ensuring paragraph count is preserved."""
+        # First try to extract by paragraph numbers (1), (2), etc.
+        result_list = []
+        for i in range(1, paragraph_count + 1):
+            pattern = rf"\({i}\)\s*(.*?)(?=\s*\({i + 1}\)|\Z)"
+            match = re.search(pattern, text, re.DOTALL)
+            if match:
+                result_list.append(match.group(1).strip())
+
+        # If exact pattern matching failed, try another approach
+        if len(result_list) != paragraph_count:
+            pattern = r"\((\d+)\)\s*(.*?)(?=\s*\(\d+\)|\Z)"
+            matches = re.findall(pattern, text, re.DOTALL)
+            if matches:
+                # Sort by paragraph number
+                matches.sort(key=lambda x: int(x[0]))
+                result_list = [match[1].strip() for match in matches]
+
+        # Fallback to original line-splitting approach
+        if len(result_list) != paragraph_count:
+            lines = text.splitlines()
+            result_list = [line.strip() for line in lines if line.strip() != ""]
 
-        # del (num), num. sometime (num) will translated to num.
-        result_list = [re.sub(r"^(\(\d+\)|\d+\.|(\d+))\s*", "", s) for s in result_list]
         return result_list
 
     def set_deployment_id(self, deployment_id):
@@ -422,6 +486,54 @@ class ChatGPTAPI(Base):
             print(f"Using model list {model_list}")
             self.model_list = cycle(model_list)
 
+    def set_o1preview_models(self):
+        # for issue #375 azure can not use model list
+        if self.deployment_id:
+            self.model_list = cycle(["o1-preview"])
+        else:
+            my_model_list = [
+                i["id"] for i in self.openai_client.models.list().model_dump()["data"]
+            ]
+            model_list = list(set(my_model_list) & set(O1PREVIEW_MODEL_LIST))
+            print(f"Using model list {model_list}")
+            self.model_list = cycle(model_list)
+
+    def set_o1_models(self):
+        # for issue #375 azure can not use model list
+        if self.deployment_id:
+            self.model_list = cycle(["o1"])
+        else:
+            my_model_list = [
+                i["id"] for i in self.openai_client.models.list().model_dump()["data"]
+            ]
+            model_list = list(set(my_model_list) & set(O1_MODEL_LIST))
+            print(f"Using model list {model_list}")
+            self.model_list = cycle(model_list)
+
+    def set_o1mini_models(self):
+        # for issue #375 azure can not use model list
+        if self.deployment_id:
+            self.model_list = cycle(["o1-mini"])
+        else:
+            my_model_list = [
+                i["id"] for i in self.openai_client.models.list().model_dump()["data"]
+            ]
+            model_list = list(set(my_model_list) & set(O1MINI_MODEL_LIST))
+            print(f"Using model list {model_list}")
+            self.model_list = cycle(model_list)
+
+    def set_o3mini_models(self):
+        # for issue #375 azure can not use model list
+        if self.deployment_id:
+            self.model_list = cycle(["o3-mini"])
+        else:
+            my_model_list = [
+                i["id"] for i in self.openai_client.models.list().model_dump()["data"]
+            ]
+            model_list = list(set(my_model_list) & set(O3MINI_MODEL_LIST))
+            print(f"Using model list {model_list}")
+            self.model_list = cycle(model_list)
+
     def set_model_list(self, model_list):
         model_list = list(set(model_list))
         print(f"Using model list {model_list}")

book_maker/translator/gemini_translator.py

@@ -44,6 +44,7 @@ GEMINIFLASH_MODEL_LIST = [
     "gemini-1.5-flash-001",
     "gemini-1.5-flash-002",
     "gemini-2.0-flash-exp",
+    "gemini-2.5-flash-preview-04-17",
 ]
 
 

book_maker/translator/google_translator.py

@@ -2,7 +2,7 @@ import re
 import requests
 from rich import print
 
-
+from book_maker.utils import TO_LANGUAGE_CODE, LANGUAGES
 from .base_translator import Base
 
 
@@ -13,7 +13,14 @@ class Google(Base):
 
     def __init__(self, key, language, **kwargs) -> None:
         super().__init__(key, language)
-        self.api_url = "https://translate.google.com/translate_a/single?client=it&dt=qca&dt=t&dt=rmt&dt=bd&dt=rms&dt=sos&dt=md&dt=gt&dt=ld&dt=ss&dt=ex&otf=2&dj=1&hl=en&ie=UTF-8&oe=UTF-8&sl=auto&tl=zh-CN"
+
+        # Convert language name to code if needed, otherwise use as-is
+        if language.lower() in TO_LANGUAGE_CODE:
+            language_code = TO_LANGUAGE_CODE[language.lower()]
+        else:
+            language_code = language
+
+        self.api_url = f"https://translate.google.com/translate_a/single?client=it&dt=qca&dt=t&dt=rmt&dt=bd&dt=rms&dt=sos&dt=md&dt=gt&dt=ld&dt=ss&dt=ex&otf=2&dj=1&hl=en&ie=UTF-8&oe=UTF-8&sl=auto&tl={language_code}"
         self.headers = {
             "Content-Type": "application/x-www-form-urlencoded",
             "User-Agent": "GoogleTranslate/6.29.59279 (iPhone; iOS 15.4; en; iPhone14,2)",

docs/model_lang.md

@@ -2,7 +2,7 @@
 ## Models
 `-m, --model <Model>` <br>
 
-Currently `bbook_maker` supports these models: `chatgptapi` , `gpt3` , `google` , `caiyun` , `deepl` , `deeplfree` , `gpt4` , `gpt4omini` , `claude` , `customapi`.
+Currently `bbook_maker` supports these models: `chatgptapi` , `gpt3` , `google` , `caiyun` , `deepl` , `deeplfree` , `gpt4` , `gpt4omini` , `o1-preview` , `o1` , `o1-mini` , `o3-mini` , `claude` , `customapi`.
 Default model is `chatgptapi` . 
 
 ### OPENAI models

docs/prompt.md

@@ -19,6 +19,32 @@ To tweak the prompt, use the `--prompt` parameter. Valid placeholders for the `u
 
 You can also set the `user` and `system` role prompt by setting environment variables: `BBM_CHATGPTAPI_USER_MSG_TEMPLATE` and `BBM_CHATGPTAPI_SYS_MSG`.
 
+- You can now use PromptDown format (`.md` files) for more structured prompts: `--prompt prompt_md.prompt.md`
+
+        # Translation Prompt
+        
+        ## System Message
+        You are a professional translator who specializes in accurate translations.
+        
+        ## Conversation
+        
+        | Role  | Content                                  |
+        |-------|------------------------------------------|
+        | User  | Please translate the following text into {language}:\n\n{text} |
+        
+        # OR using Developer Message (for newer AI models)
+        
+        # Translation Prompt
+        
+        ## Developer Message
+        You are a professional translator who specializes in accurate translations.
+        
+        ## Conversation
+        
+        | Role  | Content                                  |
+        |-------|------------------------------------------|
+        | User  | Please translate the following text into {language}:\n\n{text} |
+
 ## Examples
 ```sh
 python3 make_book.py --book_name test_books/animal_farm.epub --prompt prompt_template_sample.txt

pdm.lock

@@ -4,8 +4,11 @@
 [metadata]
 groups = ["default"]
 strategy = ["cross_platform", "inherit_metadata"]
-lock_version = "4.4.1"
-content_hash = "sha256:7792e48118ca2396a823aeef510a3bbec973033b44e04c7d81368e0285275716"
+lock_version = "4.5.0"
+content_hash = "sha256:2fb0dba3fe80797eb75ebae386f9bac949e07192d24d6f60f8b5f0f89bc284bc"
+
+[[metadata.targets]]
+requires_python = ">=3.10"
 
 [[package]]
 name = "aiohttp"
@@ -105,6 +108,9 @@ version = "0.6.0"
 requires_python = ">=3.8"
 summary = "Reusable constraint types to use with typing.Annotated"
 groups = ["default"]
+dependencies = [
+    "typing-extensions>=4.0.0; python_version < \"3.9\"",
+]
 files = [
     {file = "annotated_types-0.6.0-py3-none-any.whl", hash = "sha256:0641064de18ba7a25dee8f96403ebc39113d0cb953a01429249d5c7564666a43"},
     {file = "annotated_types-0.6.0.tar.gz", hash = "sha256:563339e807e53ffd9c267e99fc6d9ea23eb8443c08f112651963e24e22f84a5d"},
@@ -112,23 +118,22 @@ files = [
 
 [[package]]
 name = "anthropic"
-version = "0.26.1"
-requires_python = ">=3.7"
+version = "0.49.0"
+requires_python = ">=3.8"
 summary = "The official Python library for the anthropic API"
 groups = ["default"]
 dependencies = [
     "anyio<5,>=3.5.0",
     "distro<2,>=1.7.0",
     "httpx<1,>=0.23.0",
-    "jiter<1,>=0.1.0",
+    "jiter<1,>=0.4.0",
     "pydantic<3,>=1.9.0",
     "sniffio",
-    "tokenizers>=0.13.0",
-    "typing-extensions<5,>=4.7",
+    "typing-extensions<5,>=4.10",
 ]
 files = [
-    {file = "anthropic-0.26.1-py3-none-any.whl", hash = "sha256:2812b9b250b551ed8a1f0a7e6ae3f005654098994f45ebca5b5808bd154c9628"},
-    {file = "anthropic-0.26.1.tar.gz", hash = "sha256:26680ff781a6f678a30a1dccd0743631e602b23a47719439ffdef5335fa167d8"},
+    {file = "anthropic-0.49.0-py3-none-any.whl", hash = "sha256:bbc17ad4e7094988d2fa86b87753ded8dce12498f4b85fe5810f208f454a8375"},
+    {file = "anthropic-0.49.0.tar.gz", hash = "sha256:c09e885b0f674b9119b4f296d8508907f6cff0009bc20d5cf6b35936c40b4398"},
 ]
 
 [[package]]
@@ -155,6 +160,9 @@ requires_python = ">=3.7"
 summary = "Timeout context manager for asyncio programs"
 groups = ["default"]
 marker = "python_version < \"3.11\""
+dependencies = [
+    "typing-extensions>=3.6.5; python_version < \"3.8\"",
+]
 files = [
     {file = "async-timeout-4.0.3.tar.gz", hash = "sha256:4640d96be84d82d02ed59ea2b7105a0f7b33abe8703703cd0ab0bf87c427522f"},
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@@ -166,6 +174,9 @@ version = "23.2.0"
 requires_python = ">=3.7"
 summary = "Classes Without Boilerplate"
 groups = ["default"]
+dependencies = [
+    "importlib-metadata; python_version < \"3.8\"",
+]
 files = [
     {file = "attrs-23.2.0-py3-none-any.whl", hash = "sha256:99b87a485a5820b23b879f04c2305b44b951b502fd64be915879d77a7e8fc6f1"},
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@@ -465,6 +476,7 @@ summary = "Composable command line interface toolkit"
 groups = ["default"]
 dependencies = [
     "colorama; platform_system == \"Windows\"",
+    "importlib-metadata; python_version < \"3.8\"",
 ]
 files = [
     {file = "click-8.1.7-py3-none-any.whl", hash = "sha256:ae74fb96c20a0277a1d615f1e4d73c8414f5a98db8b799a7931d1582f3390c28"},
@@ -614,7 +626,7 @@ files = [
 
 [[package]]
 name = "google-ai-generativelanguage"
-version = "0.6.4"
+version = "0.6.15"
 requires_python = ">=3.7"
 summary = "Google Ai Generativelanguage API client library"
 groups = ["default"]
@@ -622,11 +634,12 @@ dependencies = [
     "google-api-core[grpc]!=2.0.*,!=2.1.*,!=2.10.*,!=2.2.*,!=2.3.*,!=2.4.*,!=2.5.*,!=2.6.*,!=2.7.*,!=2.8.*,!=2.9.*,<3.0.0dev,>=1.34.1",
     "google-auth!=2.24.0,!=2.25.0,<3.0.0dev,>=2.14.1",
     "proto-plus<2.0.0dev,>=1.22.3",
-    "protobuf!=3.20.0,!=3.20.1,!=4.21.0,!=4.21.1,!=4.21.2,!=4.21.3,!=4.21.4,!=4.21.5,<5.0.0dev,>=3.19.5",
+    "proto-plus<2.0.0dev,>=1.25.0; python_version >= \"3.13\"",
+    "protobuf!=4.21.0,!=4.21.1,!=4.21.2,!=4.21.3,!=4.21.4,!=4.21.5,<6.0.0dev,>=3.20.2",
 ]
 files = [
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+    {file = "google_ai_generativelanguage-0.6.15-py3-none-any.whl", hash = "sha256:5a03ef86377aa184ffef3662ca28f19eeee158733e45d7947982eb953c6ebb6c"},
+    {file = "google_ai_generativelanguage-0.6.15.tar.gz", hash = "sha256:8f6d9dc4c12b065fe2d0289026171acea5183ebf2d0b11cefe12f3821e159ec3"},
 ]
 
 [[package]]
@@ -716,12 +729,12 @@ files = [
 
 [[package]]
 name = "google-generativeai"
-version = "0.5.4"
+version = "0.8.5"
 requires_python = ">=3.9"
 summary = "Google Generative AI High level API client library and tools."
 groups = ["default"]
 dependencies = [
-    "google-ai-generativelanguage==0.6.4",
+    "google-ai-generativelanguage==0.6.15",
     "google-api-core",
     "google-api-python-client",
     "google-auth>=2.15.0",
@@ -731,7 +744,7 @@ dependencies = [
     "typing-extensions",
 ]
 files = [
-    {file = "google_generativeai-0.5.4-py3-none-any.whl", hash = "sha256:036d63ee35e7c8aedceda4f81c390a5102808af09ff3a6e57e27ed0be0708f3c"},
+    {file = "google_generativeai-0.8.5-py3-none-any.whl", hash = "sha256:22b420817fb263f8ed520b33285f45976d5b21e904da32b80d4fd20c055123a2"},
 ]
 
 [[package]]
@@ -750,8 +763,8 @@ files = [
 
 [[package]]
 name = "groq"
-version = "0.8.0"
-requires_python = ">=3.7"
+version = "0.22.0"
+requires_python = ">=3.8"
 summary = "The official Python library for the groq API"
 groups = ["default"]
 dependencies = [
@@ -760,11 +773,11 @@ dependencies = [
     "httpx<1,>=0.23.0",
     "pydantic<3,>=1.9.0",
     "sniffio",
-    "typing-extensions<5,>=4.7",
+    "typing-extensions<5,>=4.10",
 ]
 files = [
-    {file = "groq-0.8.0-py3-none-any.whl", hash = "sha256:f5e4e892d45001241a930db451e633ca1f0007e3f749deaa5d7360062fcd61e3"},
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+    {file = "groq-0.22.0-py3-none-any.whl", hash = "sha256:f53d3966dff713aaa635671c2d075ebb932b0d48e3c4031ede9b84a2a6694c79"},
+    {file = "groq-0.22.0.tar.gz", hash = "sha256:9d090fbe4a051655faff649890d18aaacb3121393ad9d55399171fe081f1057b"},
 ]
 
 [[package]]
@@ -835,6 +848,9 @@ version = "0.14.0"
 requires_python = ">=3.7"
 summary = "A pure-Python, bring-your-own-I/O implementation of HTTP/1.1"
 groups = ["default"]
+dependencies = [
+    "typing-extensions; python_version < \"3.8\"",
+]
 files = [
     {file = "h11-0.14.0-py3-none-any.whl", hash = "sha256:e3fe4ac4b851c468cc8363d500db52c2ead036020723024a109d37346efaa761"},
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@@ -863,6 +879,7 @@ summary = "A comprehensive HTTP client library."
 groups = ["default"]
 dependencies = [
     "pyparsing!=3.0.0,!=3.0.1,!=3.0.2,!=3.0.3,<4,>=2.4.2; python_version > \"3.0\"",
+    "pyparsing<3,>=2.4.2; python_version < \"3.0\"",
 ]
 files = [
     {file = "httplib2-0.22.0-py3-none-any.whl", hash = "sha256:14ae0a53c1ba8f3d37e9e27cf37eabb0fb9980f435ba405d546948b009dd64dc"},
@@ -943,6 +960,7 @@ requires_python = ">=3.8"
 summary = "Read metadata from Python packages"
 groups = ["default"]
 dependencies = [
+    "typing-extensions>=3.6.4; python_version < \"3.8\"",
     "zipp>=0.5",
 ]
 files = [
@@ -1022,6 +1040,39 @@ files = [
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 ]
 
+[[package]]
+name = "jsonschema"
+version = "4.23.0"
+requires_python = ">=3.8"
+summary = "An implementation of JSON Schema validation for Python"
+groups = ["default"]
+dependencies = [
+    "attrs>=22.2.0",
+    "importlib-resources>=1.4.0; python_version < \"3.9\"",
+    "jsonschema-specifications>=2023.03.6",
+    "pkgutil-resolve-name>=1.3.10; python_version < \"3.9\"",
+    "referencing>=0.28.4",
+    "rpds-py>=0.7.1",
+]
+files = [
+    {file = "jsonschema-4.23.0-py3-none-any.whl", hash = "sha256:fbadb6f8b144a8f8cf9f0b89ba94501d143e50411a1278633f56a7acf7fd5566"},
+    {file = "jsonschema-4.23.0.tar.gz", hash = "sha256:d71497fef26351a33265337fa77ffeb82423f3ea21283cd9467bb03999266bc4"},
+]
+
+[[package]]
+name = "jsonschema-specifications"
+version = "2024.10.1"
+requires_python = ">=3.9"
+summary = "The JSON Schema meta-schemas and vocabularies, exposed as a Registry"
+groups = ["default"]
+dependencies = [
+    "referencing>=0.31.0",
+]
+files = [
+    {file = "jsonschema_specifications-2024.10.1-py3-none-any.whl", hash = "sha256:a09a0680616357d9a0ecf05c12ad234479f549239d0f5b55f3deea67475da9bf"},
+    {file = "jsonschema_specifications-2024.10.1.tar.gz", hash = "sha256:0f38b83639958ce1152d02a7f062902c41c8fd20d558b0c34344292d417ae272"},
+]
+
 [[package]]
 name = "langdetect"
 version = "1.0.9"
@@ -1036,24 +1087,26 @@ files = [
 
 [[package]]
 name = "litellm"
-version = "1.38.10"
+version = "1.67.0.post1"
 requires_python = "!=2.7.*,!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,!=3.6.*,!=3.7.*,>=3.8"
 summary = "Library to easily interface with LLM API providers"
 groups = ["default"]
 dependencies = [
     "aiohttp",
     "click",
+    "httpx>=0.23.0",
     "importlib-metadata>=6.8.0",
     "jinja2<4.0.0,>=3.1.2",
-    "openai>=1.27.0",
+    "jsonschema<5.0.0,>=4.22.0",
+    "openai>=1.68.2",
+    "pydantic<3.0.0,>=2.0.0",
     "python-dotenv>=0.2.0",
-    "requests<3.0.0,>=2.31.0",
-    "tiktoken>=0.4.0",
+    "tiktoken>=0.7.0",
     "tokenizers",
 ]
 files = [
-    {file = "litellm-1.38.10-py3-none-any.whl", hash = "sha256:4d33465eacde566832b9d7aa7677476e61aa7ba4ec26631fb1c8411c87219ed1"},
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+    {file = "litellm-1.67.0.post1-py3-none-any.whl", hash = "sha256:b7b3c6a6a032b059a45b326673d24318dc8b65b1016a93194c9ea7ee94b0e00d"},
+    {file = "litellm-1.67.0.post1.tar.gz", hash = "sha256:1adf69769ee5df93c834c093fad760f406feeb6c59e79638c3f448226887554d"},
 ]
 
 [[package]]
@@ -1322,22 +1375,23 @@ files = [
 
 [[package]]
 name = "openai"
-version = "1.30.3"
-requires_python = ">=3.7.1"
+version = "1.75.0"
+requires_python = ">=3.8"
 summary = "The official Python library for the openai API"
 groups = ["default"]
 dependencies = [
     "anyio<5,>=3.5.0",
     "distro<2,>=1.7.0",
     "httpx<1,>=0.23.0",
+    "jiter<1,>=0.4.0",
     "pydantic<3,>=1.9.0",
     "sniffio",
     "tqdm>4",
-    "typing-extensions<5,>=4.7",
+    "typing-extensions<5,>=4.11",
 ]
 files = [
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+    {file = "openai-1.75.0-py3-none-any.whl", hash = "sha256:fe6f932d2ded3b429ff67cc9ad118c71327db32eb9d32dd723de3acfca337125"},
+    {file = "openai-1.75.0.tar.gz", hash = "sha256:fb3ea907efbdb1bcfd0c44507ad9c961afd7dce3147292b54505ecfd17be8fd1"},
 ]
 
 [[package]]
@@ -1351,18 +1405,29 @@ files = [
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 ]
 
+[[package]]
+name = "promptdown"
+version = "0.9.0"
+requires_python = ">=3.10"
+summary = "A package for loading promptdown files, which are a special type of markdown file for defining structured LLM prompts"
+groups = ["default"]
+files = [
+    {file = "promptdown-0.9.0-py3-none-any.whl", hash = "sha256:9ebd7044517217d00f61966dfe8297ee06328d11a6ca52d1b48c96739e5fc01a"},
+    {file = "promptdown-0.9.0.tar.gz", hash = "sha256:5727cf275a62f0feb6754fec4182b4a240a7e2bd2615e2381498d75d386c4087"},
+]
+
 [[package]]
 name = "proto-plus"
-version = "1.23.0"
-requires_python = ">=3.6"
-summary = "Beautiful, Pythonic protocol buffers."
+version = "1.26.1"
+requires_python = ">=3.7"
+summary = "Beautiful, Pythonic protocol buffers"
 groups = ["default"]
 dependencies = [
-    "protobuf<5.0.0dev,>=3.19.0",
+    "protobuf<7.0.0,>=3.19.0",
 ]
 files = [
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+    {file = "proto_plus-1.26.1.tar.gz", hash = "sha256:21a515a4c4c0088a773899e23c7bbade3d18f9c66c73edd4c7ee3816bc96a012"},
 ]
 
 [[package]]
@@ -1603,6 +1668,22 @@ files = [
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 ]
 
+[[package]]
+name = "referencing"
+version = "0.36.2"
+requires_python = ">=3.9"
+summary = "JSON Referencing + Python"
+groups = ["default"]
+dependencies = [
+    "attrs>=22.2.0",
+    "rpds-py>=0.7.0",
+    "typing-extensions>=4.4.0; python_version < \"3.13\"",
+]
+files = [
+    {file = "referencing-0.36.2-py3-none-any.whl", hash = "sha256:e8699adbbf8b5c7de96d8ffa0eb5c158b3beafce084968e2ea8bb08c6794dcd0"},
+    {file = "referencing-0.36.2.tar.gz", hash = "sha256:df2e89862cd09deabbdba16944cc3f10feb6b3e6f18e902f7cc25609a34775aa"},
+]
+
 [[package]]
 name = "regex"
 version = "2024.4.28"
@@ -1677,7 +1758,7 @@ files = [
 
 [[package]]
 name = "requests"
-version = "2.32.2"
+version = "2.32.3"
 requires_python = ">=3.8"
 summary = "Python HTTP for Humans."
 groups = ["default"]
@@ -1688,23 +1769,122 @@ dependencies = [
     "urllib3<3,>=1.21.1",
 ]
 files = [
-    {file = "requests-2.32.2-py3-none-any.whl", hash = "sha256:fc06670dd0ed212426dfeb94fc1b983d917c4f9847c863f313c9dfaaffb7c23c"},
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+    {file = "requests-2.32.3-py3-none-any.whl", hash = "sha256:70761cfe03c773ceb22aa2f671b4757976145175cdfca038c02654d061d6dcc6"},
+    {file = "requests-2.32.3.tar.gz", hash = "sha256:55365417734eb18255590a9ff9eb97e9e1da868d4ccd6402399eaf68af20a760"},
 ]
 
 [[package]]
 name = "rich"
-version = "13.7.1"
-requires_python = ">=3.7.0"
+version = "14.0.0"
+requires_python = ">=3.8.0"
 summary = "Render rich text, tables, progress bars, syntax highlighting, markdown and more to the terminal"
 groups = ["default"]
 dependencies = [
     "markdown-it-py>=2.2.0",
     "pygments<3.0.0,>=2.13.0",
+    "typing-extensions<5.0,>=4.0.0; python_version < \"3.11\"",
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 files = [
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+    {file = "rich-14.0.0.tar.gz", hash = "sha256:82f1bc23a6a21ebca4ae0c45af9bdbc492ed20231dcb63f297d6d1021a9d5725"},
+]
+
+[[package]]
+name = "rpds-py"
+version = "0.24.0"
+requires_python = ">=3.9"
+summary = "Python bindings to Rust's persistent data structures (rpds)"
+groups = ["default"]
+files = [
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 [[package]]
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 [[package]]
 name = "tiktoken"
-version = "0.7.0"
-requires_python = ">=3.8"
+version = "0.9.0"
+requires_python = ">=3.9"
 summary = "tiktoken is a fast BPE tokeniser for use with OpenAI's models"
 groups = ["default"]
 dependencies = [
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 ]
 
 [[package]]
@@ -1897,7 +2073,7 @@ files = [
 
 [[package]]
 name = "tqdm"
-version = "4.66.4"
+version = "4.67.1"
 requires_python = ">=3.7"
 summary = "Fast, Extensible Progress Meter"
 groups = ["default"]
@@ -1905,8 +2081,8 @@ dependencies = [
     "colorama; platform_system == \"Windows\"",
 ]
 files = [
-    {file = "tqdm-4.66.4-py3-none-any.whl", hash = "sha256:b75ca56b413b030bc3f00af51fd2c1a1a5eac6a0c1cca83cbb37a5c52abce644"},
-    {file = "tqdm-4.66.4.tar.gz", hash = "sha256:e4d936c9de8727928f3be6079590e97d9abfe8d39a590be678eb5919ffc186bb"},
+    {file = "tqdm-4.67.1-py3-none-any.whl", hash = "sha256:26445eca388f82e72884e0d580d5464cd801a3ea01e63e5601bdff9ba6a48de2"},
+    {file = "tqdm-4.67.1.tar.gz", hash = "sha256:f8aef9c52c08c13a65f30ea34f4e5aac3fd1a34959879d7e59e63027286627f2"},
 ]
 
 [[package]]
@@ -1951,6 +2127,7 @@ groups = ["default"]
 dependencies = [
     "idna>=2.0",
     "multidict>=4.0",
+    "typing-extensions>=3.7.4; python_version < \"3.8\"",
 ]
 files = [
     {file = "yarl-1.9.4-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:a8c1df72eb746f4136fe9a2e72b0c9dc1da1cbd23b5372f94b5820ff8ae30e0e"},

prompt_md.prompt.md

@@ -0,0 +1,11 @@
+# Translation Prompt
+
+## Developer Message
+
+You are a professional translator who specializes in accurate, natural-sounding translations that preserve the original meaning, tone, and style of the text.
+
+## Conversation
+
+| Role  | Content                                                                   |
+|-------|---------------------------------------------------------------------------|
+| User  | Please translate the following text into {language}:\n\n{text}            |

pyproject.toml

@@ -4,7 +4,7 @@ description = "The bilingual_book_maker is an AI translation tool that uses Chat
 readme = "README.md"
 license = {text = "MIT"}
 dynamic = ["version"]
-requires-python = ">=3.9"
+requires-python = ">=3.10"
 authors = [
     { name = "yihong0618", email = "zouzou0208@gmail.com" },
 ]
@@ -28,10 +28,12 @@ dependencies = [
     "tiktoken",
     "tqdm",
     "groq>=0.5.0",
+    "promptdown>=0.9.0",
 ]
 
 [project.scripts]
 bbook_maker = "book_maker.cli:main"
+promptdown = "promptdown_cli:main"
 
 [project.urls]
 Homepage = "https://github.com/yihong0618/bilingual_book_maker"

requirements.txt

@@ -53,6 +53,7 @@ mdurl==0.1.2
 multidict==6.0.5
 openai==1.30.3
 packaging==24.0
+promptdown==0.9.0
 proto-plus==1.23.0
 protobuf==4.25.3
 pyasn1==0.6.0