Dev madina

[madina1203]

PR Type

• Enhancement
• Documentation

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Description

• Updated SpectrumPlotter input parsing and error handling.

• Improved database retrieval to check previous interactions.

• Refactored Streamlit interface using dialogs and added video content.

• Updated deployment scripts, configuration files, and license info.

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Changes walkthrough 📝

	Relevant files
Miscellaneous	1 files tool_interpreter.py Remove outdated commented API key setup code.                        +0/-5
Enhancement	6 files tool_spectrum.py Revamp input_data processing and nested JSON error handling. +66/-40  main.py Clean up imports and streamline env variable loading.        +22/-47  tools_database.py Enhance data retrieval to check previous interaction when data is null. +58/-10  utils.py Introduce IntRange class for argument range validation.    +24/-0    postgres_tool_database.py Add initialize_db method for database connection management. +3/-0      streamlit_app.py Replace modal usage with st.dialog and add illustrative videos. +54/-44
Documentation	2 files questions.py Adjust question list formatting with minor punctuation fix. +2/-2      README.md Update environment activation command and change license to Apache 2.0. +3/-3
Configuration changes	3 files setup.sh Add setup script for Streamlit config and Heroku deployment. +12/-0    .python-version Specify Python version 3.11 for the project.                          +1/-0      Procfile Add Procfile to run the Streamlit app on Heroku.                  +1/-0

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⚡ Recommended focus areas for review Docstring Format The _run method in SpectrumPlotter now contains complex logic for parsing various input types but lacks a proper Google style docstring. Adding a detailed docstring with descriptions for all parameters and return values would improve clarity. self, input_data: Union[str, Dict[str, Any]] = None, usi: Optional[str] = None, run_manager: Optional[CallbackManagerForToolRun] = None, ) -> Dict[str, Any]: session_dir = create_user_session(self.session_id, user_session_dir=True) db_manager = tools_database() os.makedirs(session_dir, exist_ok=True) # If input_data is provided, it should be used instead of the other parameters if input_data: # If input_data is a string if isinstance(input_data, str): # Check if it's a CSV file path if input_data.endswith(".csv"): df = pd.read_csv(input_data) # Check required columns if not {'usi'}.issubset(df.columns): return {"error": "CSV file must contain 'usi' column."} first_row = df.iloc[0] usi = first_row['usi'] else: # Attempt to parse the string as JSON try: parsed = json.loads(input_data) except Exception as e: return {"error": f"Invalid input_data format: {e}"} # If the parsed object contains '__arg1' if isinstance(parsed, dict) and '__arg1' in parsed: inner_val = parsed['__arg1'] # If the inner value is a string, try to parse it as JSON if isinstance(inner_val, str): try: inner_json = json.loads(inner_val) except Exception as e: return {"error": f"Invalid nested JSON in '__arg1': {e}"} elif isinstance(inner_val, dict): inner_json = inner_val else: return {"error": "Unexpected type for '__arg1' value."} if 'usi' in inner_json: usi = inner_json['usi'] else: return {"error": "Missing 'usi' key in nested JSON."} # Otherwise, if the parsed JSON directly has 'usi' elif 'usi' in parsed: usi = parsed['usi'] else: return {"error": "Invalid JSON structure. Must contain 'usi'."} # If input_data is already a dictionary elif isinstance(input_data, dict): if 'usi' in input_data: usi = input_data['usi'] elif '__arg1' in input_data: inner_val = input_data['__arg1'] if isinstance(inner_val, str): try: inner_json = json.loads(inner_val) except Exception as e: return {"error": f"Invalid nested JSON in '__arg1': {e}"} elif isinstance(inner_val, dict): inner_json = inner_val else: return {"error": "Unexpected type for '__arg1' value."} if 'usi' in inner_json: usi = inner_json['usi'] else: return {"error": "Missing 'usi' key in nested JSON."} else: return {"error": "Invalid input. Provide a dictionary with 'usi' or '__arg1'."} else: return { "error": "Invalid input type. Provide a dictionary with 'usi' or a valid CSV file path." } Missing Docstring The new IntRange class is useful but does not include a Google DocString format. Consider documenting its purpose, arguments, and methods in Google format for better maintainability. class IntRange: def __init__(self, start, end): self.start = start self.end = end self.range = range(start, end + 1) def __contains__(self, item): return item in self.range def __iter__(self): # for help display return iter([f"[{self.start}, {self.end}]"]) def __str__(self): return f"[{self.start}, {self.end}]" def __repr__(self): return self.__str__() Function Documentation The new add_videos_to_content function improves UI functionality. To be consistent with documentation standards, add a Google docstring detailing its purpose, parameters (if any), and return value. def add_videos_to_content(): st.markdown("---") st.subheader("Illustrative videos") st.markdown("Here are some illustrative videos to help you understand how to use MetaboT.") st.video("https://youtu.be/R6OiFt9ryxY") st.markdown("---") st.video("https://youtu.be/LpywYlHBWpw")

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PR Code Suggestions ✨

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Category	Suggestion	Impact
Possible issue	Yield proper range integers Change the iterator to yield the full range of integers (instead of a single string) so that choices in argparse work correctly. app/core/utils.py [131-133] def __iter__(self): - # for help display - return iter([f"[{self.start}, {self.end}]"]) + return iter(self.range) Apply this suggestion Suggestion importance[1-10]: 8 __ Why: The improved code returns the actual range of integers instead of a string representation, which is a functional improvement for use cases like argparse that expect integer choices.	Medium
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