fix lint

Makefile

@@ -2,7 +2,7 @@
 
 setup:
 	docker compose down
-	docker compose up -d
+	docker compose up -d --build
 
 enter_container:
 	docker exec -it python_app bash

src/__init__.py

@@ -1,9 +1,4 @@
-
-import logging
-
 # import sentry_sdk
-from common import settings
-from sentry_sdk.integrations.logging import LoggingIntegration
 
 
 # sentry_logging = LoggingIntegration(level=logging.INFO, event_level=logging.ERROR)
@@ -13,4 +8,4 @@
 #         integrations=[sentry_logging],
 #         environment=settings.ENV,
 #         traces_sample_rate=1.0,
-#     )
+#     )

src/common/__init__.py

@@ -9,7 +9,5 @@
 
 settings = read_yaml(os.path.join(base_dir, f"src/common/yaml_configs/{env}.yaml"))
 
-init_logger(
-    os.path.join(settings.BASE_DIR, "src/common/logger/logging_config.yaml")
-)
+init_logger(os.path.join(settings.BASE_DIR, "src/common/logger/logging_config.yaml"))
 app_logger = logging.getLogger(__name__)

src/common/config.py

@@ -1,5 +1,3 @@
-import os
-
 import yaml
 from pydantic import HttpUrl
 from pydantic_settings import BaseSettings

src/common/yaml_configs/local.yaml

@@ -1,3 +1,3 @@
 ENV: "local"
 SENTRY_DSN:
-OPENAI_API_KEY: your-api-key
+OPENAI_API_KEY: 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

src/main.py

@@ -1,71 +1,88 @@
+import urllib.parse
+import uuid
+from typing import Any
+
 import streamlit as st
 import streamlit_mermaid as stmd
-import uuid
-from src.model.models import EnglishWord
-from src.common import app_logger
+from pydantic import ValidationError
+from service import OpenAISSEClient, WordQuestionBuilder
 
-from service import WordQuestionBuilder, OpenAISSEClient
+from src.common import app_logger
+from src.model.models import EnglishWord
 
 USER_NAME = "user"
 ASSISTANT_NAME = "assistant"
 
 
-def init_page():
+def init_page() -> None:
     st.set_page_config(
-        page_title="Utilizer: Boost your English active vocabulary 📚",
-        page_icon="📚"
+        page_title="UtiAIzer: Boost your English active vocabulary 📚", page_icon="📚"
     )
-    st.header("Utilizer: Boost your English active vocabulary")
+    st.header("UtiAIzer: Boost your English active vocabulary")
+    st.write(":orange[Generated by chatgpt. No responsibility for any content.]")
 
-
-def generate_session_id():
+def generate_session_id() -> str:
     return str(uuid.uuid4())
 
 
-def convart_to_url_part(sentence):
-    return sentence.replace(" ", "%20")
+def convart_to_url_part(sentence: str) -> str:
+    return urllib.parse.quote(sentence)
+
 
-def convart_to_under_score(sentence):
-    converted =  sentence.replace(" ", "_")
+def convart_to_under_score(sentence: str) -> str:
+    converted = sentence.replace(" ", "_")
     # del the fisrt, last char if it is "_"
     if converted[0] == "_":
         converted = converted[1:]
     if converted[-1] == "_":
         converted = converted[:-1]
     return converted
 
-def build_elsa_link(user_msg):
-    return f"\n - [Go To ELSA：{user_msg}](https://elsaspeak.com/en/learn-english/how-to-pronounce/{convart_to_url_part(user_msg)})"
 
+def build_elsa_link(user_msg: str) -> str:
+    return f"\n - [Go To ELSA:{user_msg}](https://elsaspeak.com/en/learn-english/how-to-pronounce/{convart_to_url_part(user_msg)})"
 
-def build_youglish_link(user_msg):
-    return f"\n\n - [Go To Youglish：{user_msg}](https://youglish.com/pronounce/{convart_to_url_part(user_msg)}/english?)"
 
+def build_youglish_link(user_msg: str) -> str:
+    return f"\n\n - [Go To Youglish:{user_msg}](https://youglish.com/pronounce/{convart_to_url_part(user_msg)}/english?)"
 
-def build_mermaid_graph_str(user_msg, result_str):
 
+def build_mermaid_graph_str(user_msg: str, result_str: str) -> str:
+    app_logger.info(f"result_str: {result_str}")
     li = map(convart_to_under_score, result_str.split("|"))
-    # skip the first element
+    # skip the first and second
+    next(li)
     next(li)
 
     code = f"""
     graph TD
-        {user_msg} --> {next(li)}
-        {user_msg} --> {next(li)}
-        {user_msg} --> {next(li)}
-        {user_msg} --> {next(li)}
+        {convart_to_under_score(user_msg)} --> {next(li)}
+        {convart_to_under_score(user_msg)} --> {next(li)}
+        {convart_to_under_score(user_msg)} --> {next(li)}
+        {convart_to_under_score(user_msg)} --> {next(li)}
     """
     return code
 
 
-def ask_llm_sse(key, user_msg, assistant_msg, message_placeholder, is_collocation=False):
+def ask_llm_sse(
+    key: str,
+    user_msg: str,
+    assistant_msg: str,
+    message_placeholder: Any,
+    is_collocation: bool = False,
+) -> tuple[str, str]:
     question = WordQuestionBuilder.call(key=key, word=EnglishWord(value=user_msg))
     answers = OpenAISSEClient.call(question)
 
     result_str = ""
+    count = 0
     for answer in answers:
+        if count == 60:
+            assistant_msg += "\n\n :red[Too many answers.] \n\n"
+            message_placeholder.write(assistant_msg)
+            break
 
-        if answer.value == '[END]':
+        if answer.value == "[END]":
             message_placeholder.write(assistant_msg)
             break
 
@@ -74,55 +91,107 @@ def ask_llm_sse(key, user_msg, assistant_msg, message_placeholder, is_collocatio
             message_placeholder.write(assistant_msg + "▌")
 
         result_str += answer.value
+        count += 1
 
     return assistant_msg, result_str
 
 
-def ask_several_questions_in_order(user_msg, assistant_msg, message_placeholder):
+def ask_several_questions_in_order(
+    user_msg: str, assistant_msg: str, message_placeholder: Any
+) -> str:
     # Meaning
-    assistant_msg += f"\n\n #### Meaning \n\n"
-    assistant_msg, _ = ask_llm_sse(key="meaning", user_msg=user_msg, assistant_msg=assistant_msg,
-                                   message_placeholder=message_placeholder)
+    assistant_msg += "\n\n #### Meaning \n\n"
+    assistant_msg, _ = ask_llm_sse(
+        key="meaning",
+        user_msg=user_msg,
+        assistant_msg=assistant_msg,
+        message_placeholder=message_placeholder,
+    )
     # Pronunciation
-    assistant_msg += f"\n\n #### Pronunciation \n\n"
+    assistant_msg += "\n\n #### Pronunciation \n\n"
     assistant_msg += "\n - IPA: "
-    assistant_msg, _ = ask_llm_sse(key="pronunciation", user_msg=user_msg, assistant_msg=assistant_msg,
-                                   message_placeholder=message_placeholder)
+    assistant_msg, _ = ask_llm_sse(
+        key="pronunciation",
+        user_msg=user_msg,
+        assistant_msg=assistant_msg,
+        message_placeholder=message_placeholder,
+    )
     # pronunciation_tip
     assistant_msg += "\n - Pronunciation Tip: "
-    assistant_msg, _ = ask_llm_sse(key="pronunciation_tip", user_msg=user_msg, assistant_msg=assistant_msg,
-                                   message_placeholder=message_placeholder)
+    assistant_msg, _ = ask_llm_sse(
+        key="pronunciation_tip",
+        user_msg=user_msg,
+        assistant_msg=assistant_msg,
+        message_placeholder=message_placeholder,
+    )
     # st.write(build_youglish_link(user_msg)
     assistant_msg += build_youglish_link(user_msg)
     assistant_msg += build_elsa_link(user_msg)
     message_placeholder.write(assistant_msg)
 
-    # Origin
-    assistant_msg += f"\n\n #### Origin \n\n"
-    assistant_msg, _ = ask_llm_sse(key="origin", user_msg=user_msg, assistant_msg=assistant_msg,
-                                   message_placeholder=message_placeholder)
+    # # Origin
+    # assistant_msg += f"\n\n #### Origin \n\n"
+    # assistant_msg, _ = ask_llm_sse(key="origin", user_msg=user_msg, assistant_msg=assistant_msg,
+    #                                message_placeholder=message_placeholder)
     # Synonym
-    assistant_msg += f"\n\n #### Synonym \n\n"
-    assistant_msg, _ = ask_llm_sse(key="synonym", user_msg=user_msg, assistant_msg=assistant_msg,
-                                   message_placeholder=message_placeholder)
+    assistant_msg += "\n\n #### Synonym \n\n"
+    assistant_msg, _ = ask_llm_sse(
+        key="synonym",
+        user_msg=user_msg,
+        assistant_msg=assistant_msg,
+        message_placeholder=message_placeholder,
+    )
+
+    # Synonym
+    assistant_msg += "\n\n #### Antonym \n\n"
+    assistant_msg, _ = ask_llm_sse(
+        key="antonym",
+        user_msg=user_msg,
+        assistant_msg=assistant_msg,
+        message_placeholder=message_placeholder,
+    )
+
     # Example Sentence
-    assistant_msg += f"\n\n #### Example Sentence \n\n"
-    assistant_msg, result_str = ask_llm_sse(key="example_sentence", user_msg=user_msg, assistant_msg=assistant_msg,
-                                            message_placeholder=message_placeholder)
-    assistant_msg += build_elsa_link(result_str)
+    assistant_msg += "\n\n #### Example Sentence \n\n"
+    assistant_msg, result_str = ask_llm_sse(
+        key="example_sentence",
+        user_msg=user_msg,
+        assistant_msg=assistant_msg,
+        message_placeholder=message_placeholder,
+    )
+
+    # if AI find the example sentence, then build the url
+    if "I'm sorry" not in result_str and "Sorry" not in result_str:
+        assistant_msg += build_elsa_link(result_str)
+
+    # # making_sentence_tips
+    # assistant_msg += "\n\n #### Making Sentence Tips \n\n"
+    # assistant_msg, _ = ask_llm_sse(
+    #     key="making_sentence_tips",
+    #     user_msg=user_msg,
+    #     assistant_msg=assistant_msg,
+    #     message_placeholder=message_placeholder,
+    # )
 
     # Collocation
-    assistant_msg += f"\n\n #### Collocation MindMap \n\n"
-    assistant_msg, result_str = ask_llm_sse(key="collocation", user_msg=user_msg, assistant_msg=assistant_msg,
-                                             message_placeholder=message_placeholder, is_collocation=True)
+    assistant_msg += "\n\n #### Collocation MindMap \n\n"
+    assistant_msg, result_str = ask_llm_sse(
+        key="collocation",
+        user_msg=user_msg,
+        assistant_msg=assistant_msg,
+        message_placeholder=message_placeholder,
+        is_collocation=True,
+    )
     app_logger.info(f"result_str: {result_str}")
     code = build_mermaid_graph_str(user_msg, result_str)
     assistant_msg += code
     app_logger.info(f"code: {code}")
     stmd.st_mermaid(code)
+
     return assistant_msg
 
-def ask():
+
+def ask() -> None:
     current_session = st.session_state.current_session
     chat_log = st.session_state.chat_sessions[current_session]
     # 現在のセッションのチャット履歴を表示
@@ -139,13 +208,23 @@ def ask():
         with st.chat_message(ASSISTANT_NAME):
             message_placeholder = st.empty()
             assistant_msg = ""
-            assistant_msg = ask_several_questions_in_order(user_msg, assistant_msg, message_placeholder)
+            try:
+                assistant_msg = ask_several_questions_in_order(
+                    user_msg, assistant_msg, message_placeholder
+                )
+            except ValidationError:
+                st.error(
+                    "Please enter english word or phrase that is 30 characters or less including spaces."
+                )
+            except Exception as e:
+                app_logger.exception(e)
+                # st.error('Sorry, something went wrong.')
         # セッションにチャットログを追加
         chat_log.append({"name": USER_NAME, "msg": user_msg})
         chat_log.append({"name": ASSISTANT_NAME, "msg": assistant_msg})
 
 
-def main():
+def main() -> None:
     init_page()
 
     # セッション情報の初期化
@@ -158,7 +237,9 @@ def main():
 
     # Sidebarの実装
     session_list = list(st.session_state.chat_sessions.keys())
-    selected_session = st.sidebar.selectbox("Select Chat Session", session_list, index=len(session_list) - 1)
+    selected_session = st.sidebar.selectbox(
+        "Select Chat Session", session_list, index=len(session_list) - 1
+    )
     st.session_state.current_session = selected_session
 
     if st.sidebar.button("New Chat"):
@@ -169,5 +250,5 @@ def main():
     ask()
 
 
-if __name__ == '__main__':
+if __name__ == "__main__":
     main()

src/model/models.py

@@ -1,15 +1,19 @@
 from pydantic import BaseModel, Field, validator
 
 
+class NotEnglishError(ValueError):
+    pass
+
+
 class EnglishWord(BaseModel):
-    value: str = Field(max_length=20)
+    value: str = Field(max_length=30)
 
     @validator("value")
-    def is_english(cls, v):
+    def is_english(cls, v: str) -> str:
         try:
-            v.encode('ascii')
+            v.encode("ascii")
         except UnicodeEncodeError:
-            raise ValueError("English only")
+            raise NotEnglishError("English only") from None
         return v
 
 

src/service/__init__.py

@@ -1,7 +1,7 @@
-from .question_builder import WordQuestionBuilder
 from .openai_sse_client import OpenAISSEClient
+from .question_builder import WordQuestionBuilder
 
 __all__ = [
     "WordQuestionBuilder",
     "OpenAISSEClient",
-]
+]