record-generator: LLM #635
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WalkthroughThe pull request introduces significant changes to the Flatfile plugin system by replacing the existing Changes
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Actionable comments posted: 12
🧹 Outside diff range and nitpick comments (8)
import/anthropic/jest.config.js (1)
7-11: Consider using path.resolve for more robust file paths.The setup files are correctly configured, but using relative paths might cause issues if the directory structure changes. Consider using
path.resolvefor more robust path handling.Here's an example of how you could refactor this:
const path = require('path'); module.exports = { // ... setupFiles: [path.resolve(__dirname, '../../test/dotenv-config.js')], setupFilesAfterEnv: [ path.resolve(__dirname, '../../test/betterConsoleLog.js'), path.resolve(__dirname, '../../test/unit.cleanup.js'), ], // ... }flatfilers/sandbox/src/index.ts (2)
7-11: Configuration for anthropicGenerator looks good, but consider debug flag.The configuration for
anthropicGeneratoris well-structured and includes appropriate parameters for generating example records. However, thedebugflag is set totrue, which might not be suitable for production use.Consider adding a comment explaining the purpose of the debug flag or setting it to
falsefor production deployments:anthropicGenerator({ job: 'generateExampleRecords', numberOfRecords: 10, - debug: true, + debug: false, // Set to true for development/testing })
49-59: Action for generating example records added correctly.The new action for generating example records using Anthropic is well-configured and provides clear information about its purpose and behavior. The configuration aligns well with the anthropicGenerator setup.
For consistency, consider using camelCase for the operation name to match JavaScript conventions:
{ - operation: 'generateExampleRecords', + operation: 'generateExampleRecords', label: 'Generate Example Records', description: 'This custom action code generates example records using Anthropic.', primary: false, mode: 'foreground', type: 'string', },import/anthropic/README.MD (2)
20-26: LGTM: Parameters section is clear and informative. Minor punctuation fix needed.The parameters section effectively describes the configuration object for the
anthropicGeneratorfunction, including all relevant properties, their types, and default values.There's a minor punctuation issue on line 26. Consider removing the colon after "default: false" for consistency with the other parameter descriptions.
-- `debug` (boolean): Whether to log debug information (default: false): ++ `debug` (boolean): Whether to log debug information (default: false)
71-73: Enhance the error handling section with more specific details.While the error handling section provides basic information, it could be more helpful to users if it included:
- Examples of common errors and how they are logged.
- Information on where to find the logs.
- Any specific error codes or messages users might encounter.
Consider expanding this section to provide more actionable information for troubleshooting. For example:
## Error Handling The plugin includes robust error handling and logging to ensure reliable operation. Errors during the generation or insertion process are logged for easy troubleshooting. Common errors you might encounter include: - API key authentication issues - Rate limiting errors - Invalid sheet configuration Logs can be found in [specify location, e.g., console output or a specific log file]. If you encounter persistent errors, please check the [specify where, e.g., GitHub Issues page] for known issues or to report new ones.import/anthropic/src/anthropic.generator.ts (2)
1-2: Review import statement for 'TextBlock'Importing
TextBlockdirectly from@anthropic-ai/sdk/resourcesmay couple your code to internal module paths that could change in future updates. Consider importingTextBlockfrom the main package to reduce the risk of breaking changes.Apply this diff to adjust the import:
-import { TextBlock } from '@anthropic-ai/sdk/resources' +import { TextBlock } from '@anthropic-ai/sdk'
5-47: Consider adding unit tests for 'generateExampleRecords'Adding unit tests for this function will help ensure it behaves as expected, especially with various field configurations and counts. It will also aid in catching future regressions.
Would you like assistance in creating unit tests for this function or opening a GitHub issue to track this task?
import/anthropic/src/anthropic.plugin.ts (1)
41-42: Use consistent logging methods instead ofconsole.dirUsing
console.dirfor logging deviates from the established logging pattern and may not integrate well with logging systems.Replace
console.dirwith thelogInfoutility for consistency:- console.dir(exampleRecords, { depth: null }) + logInfo( + '@flatfile/plugin-import-anthropic', + 'Generated example records:', + exampleRecords + )This ensures that all logs go through the same logging framework.
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import/anthropic/package.jsonis excluded by!**/*.jsonimport/faker/package.jsonis excluded by!**/*.jsonpackage-lock.jsonis excluded by!**/package-lock.json,!**/*.json
📒 Files selected for processing (7)
- flatfilers/sandbox/src/index.ts (2 hunks)
- import/anthropic/README.MD (1 hunks)
- import/anthropic/jest.config.js (1 hunks)
- import/anthropic/rollup.config.mjs (1 hunks)
- import/anthropic/src/anthropic.generator.ts (1 hunks)
- import/anthropic/src/anthropic.plugin.ts (1 hunks)
- import/anthropic/src/index.ts (1 hunks)
✅ Files skipped from review due to trivial changes (2)
- import/anthropic/rollup.config.mjs
- import/anthropic/src/index.ts
🧰 Additional context used
🪛 LanguageTool
import/anthropic/README.MD
[uncategorized] ~56-~56: Loose punctuation mark.
Context: ...following property: -numberOfRecords: The number of example records to genera...(UNLIKELY_OPENING_PUNCTUATION)
[misspelling] ~60-~60: Use “a” instead of ‘an’ if the following word doesn’t start with a vowel sound, e.g. ‘a sentence’, ‘a university’.
Context: ... plugin checks if the record is already an generated example. 2. If not, it retrie...(EN_A_VS_AN)
[style] ~77-~77: The phrase ‘feel free to’ is used quite frequently. Consider using a less frequent alternative to set your writing apart from others and make it sound more professional.
Context: ...ontributing Contributions are welcome! Please feel free to submit a Pull Request.(FEEL_FREE_TO_STYLE_ME)
🔇 Additional comments (12)
import/anthropic/jest.config.js (4)
2-2: LGTM: Appropriate test environment.The
testEnvironmentis correctly set to 'node', which is suitable for a server-side JavaScript/TypeScript project.
4-6: LGTM: Correct TypeScript transformation setup.The
transformconfiguration is properly set up to use 'ts-jest' for.tsand.tsxfiles, enabling Jest to process TypeScript code correctly.
12-12: Review the necessity of the 60-second test timeout.The
testTimeoutis set to 60 seconds, which is relatively long for unit tests. While this might be necessary for time-consuming operations, it could potentially hide performance issues.Consider reviewing your tests to see if this long timeout is necessary. If possible, try to optimize your tests to run faster and reduce this timeout. You can use the following command to identify slow tests:
This will help you identify which tests are taking a long time to run, allowing you to focus on optimizing them.
14-15: Review forceExit and passWithNoTests configurations.The
forceExit: trueconfiguration forces Jest to exit after all tests complete. While this might be necessary if there are hanging handles in the tests, it's generally not recommended as it can mask cleanup issues.The
passWithNoTests: trueconfiguration allows the test suite to pass when no tests are found. This can be useful during development but might hide issues in a CI/CD pipeline.Consider reviewing these configurations:
For
forceExit, try to identify and fix any hanging handles in your tests. You can use the following command to run Jest without forceExit and see if there are any issues:For
passWithNoTests, ensure that this configuration doesn't hide actual test failures in your CI/CD pipeline. You might want to add a check in your pipeline to ensure that tests exist and are being run.flatfilers/sandbox/src/index.ts (2)
2-2: LGTM: Import statement for anthropicGenerator added correctly.The import statement for
anthropicGeneratorfrom the Anthropic plugin is correctly added, which aligns with the PR objective of introducing the Anthropic record generator.
Line range hint
1-67: Overall changes look good, but consider documenting the pivot table removal.The replacement of
pivotTablePluginwithanthropicGeneratoris well-implemented and aligns with the PR objectives. The new configuration and actions support the Anthropic-based example record generation effectively.However, the removal of the pivot table functionality might impact existing users. Please ensure that:
- This change is documented in the changelog or release notes.
- Users are informed about the new way to generate example data.
- If pivot table functionality is still needed, provide guidance on alternative methods.
To verify the impact of removing the pivot table functionality, you can run the following script:
This script will help identify any remaining references to the pivot table functionality that might need to be updated or removed.
import/anthropic/README.MD (5)
1-10: LGTM: Info card section is well-structured and informative.The info card provides a clear and concise overview of the plugin, including its name, purpose, and the event type it responds to.
12-18: LGTM: Features section is comprehensive and well-presented.The features section effectively highlights the key capabilities of the plugin, providing users with a clear understanding of its functionality and benefits.
28-34: LGTM: Installation section is clear and straightforward.The installation instructions are concise and provide the necessary command to install the plugin using npm.
36-50: LGTM: Example usage section is well-structured and informative.The example usage section provides a clear and concise TypeScript code snippet demonstrating how to import and use the plugin with relevant configuration options.
1-77: Overall, the README is well-structured and informative, with room for minor improvements.The documentation provides a comprehensive overview of the @flatfile/plugin-import-anthropic, covering essential aspects such as features, installation, usage, and behavior. To further enhance its effectiveness:
- Consider reorganizing the sections as suggested earlier for a more logical flow of information.
- Expand the error handling and contributing sections to provide more specific and actionable information.
- Address the minor grammatical and stylistic issues noted in previous comments.
These improvements will make the documentation even more valuable for users and potential contributors.
🧰 Tools
🪛 LanguageTool
[uncategorized] ~56-~56: Loose punctuation mark.
Context: ...following property: -numberOfRecords: The number of example records to genera...(UNLIKELY_OPENING_PUNCTUATION)
[misspelling] ~60-~60: Use “a” instead of ‘an’ if the following word doesn’t start with a vowel sound, e.g. ‘a sentence’, ‘a university’.
Context: ... plugin checks if the record is already an generated example. 2. If not, it retrie...(EN_A_VS_AN)
[style] ~77-~77: The phrase ‘feel free to’ is used quite frequently. Consider using a less frequent alternative to set your writing apart from others and make it sound more professional.
Context: ...ontributing Contributions are welcome! Please feel free to submit a Pull Request.(FEEL_FREE_TO_STYLE_ME)
import/anthropic/src/anthropic.plugin.ts (1)
45-45: Handle potential errors when inserting recordsInserting records into the sheet may fail due to data validation issues or API constraints, and currently, these errors aren't specifically handled.
Ensure that
exampleRecordscomply with the expected data schema before insertion.Would you like assistance in implementing validation checks for the generated records to ensure they meet the required schema?
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Actionable comments posted: 26
🧹 Outside diff range and nitpick comments (4)
import/llm/jest.config.js (1)
7-11: LGTM: Comprehensive test setup configuration.The setup files are well-configured to prepare the test environment. However, consider adding comments to explain the purpose of each setup file for better maintainability.
Consider adding comments like this:
setupFiles: [ '../../test/dotenv-config.js', // Load environment variables ], setupFilesAfterEnv: [ '../../test/betterConsoleLog.js', // Enhance console logging for tests '../../test/unit.cleanup.js', // Perform cleanup after each test ],flatfilers/sandbox/src/index.ts (1)
Line range hint
1-68: Overall review summaryThe changes in this file align well with the PR objectives, replacing the
pivotTablePluginwith thellmRecordGenerator. The implementation looks good overall, but there are a few points to address:
- Verify the correct model name ('gpt-4o' vs 'gpt-4').
- Consider adjusting the debug and numberOfRecords settings in the llmRecordGenerator configuration.
- Review the new action configuration, particularly the mode and type settings.
Please address these points to improve the robustness and flexibility of the implementation.
Consider extracting configuration values (like model name, number of records, etc.) into environment variables or a configuration file. This would make the code more maintainable and easier to adjust for different environments.
import/llm/README.MD (2)
20-28: Consider adding type information to parameters.The Parameters section provides a clear description of the configuration object properties. To enhance clarity and assist with type checking, consider adding type information for each parameter.
Here's a suggested improvement:
- `llmSecretName` (string): The name of the secret that contains the LLM API key. - `model` (string): The name of the LLM to use. - `job` (string): The sheet-level operation name to listen for in the job:ready event. - `numberOfRecords` (number, optional): The number of example records to generate. Default: 10. - `debug` (boolean, optional): Whether to log debug information. Default: false.
56-64: Consider enhancing the Behavior and Contributing sections.Both the Behavior and Contributing sections provide valuable information. However, they could be improved to offer more comprehensive guidance to users and potential contributors.
Consider the following enhancements:
Behavior section:
- Add information about error handling and logging.
- Mention any potential limitations or edge cases users should be aware of.
- Provide guidance on how to troubleshoot common issues.
Contributing section:
- Add more specific guidelines for contributions (e.g., coding standards, commit message format).
- Include a link to a more detailed contributing guide, if available.
- Mention the process for submitting issues or feature requests.
Example for an expanded Contributing section:
## Contributing Contributions are welcome! Here are some ways you can contribute to this project: 1. Report bugs or request features by opening an issue. 2. Submit pull requests to fix bugs or add new features. 3. Improve documentation or add examples. Please ensure your code adheres to the project's coding standards and include tests for new features. For more detailed information, please refer to our [Contributing Guide](link-to-contributing-guide).🧰 Tools
🪛 LanguageTool
[style] ~64-~64: The phrase ‘feel free to’ is used quite frequently. Consider using a less frequent alternative to set your writing apart from others and make it sound more professional.
Context: ...ontributing Contributions are welcome! Please feel free to submit a Pull Request.(FEEL_FREE_TO_STYLE_ME)
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⛔ Files ignored due to path filters (2)
import/llm/package.jsonis excluded by!**/*.jsonpackage-lock.jsonis excluded by!**/package-lock.json,!**/*.json
📒 Files selected for processing (9)
- flatfilers/sandbox/src/index.ts (2 hunks)
- import/llm/README.MD (1 hunks)
- import/llm/jest.config.js (1 hunks)
- import/llm/rollup.config.mjs (1 hunks)
- import/llm/src/generate.records.plugin.ts (1 hunks)
- import/llm/src/generate.records.util.ts (1 hunks)
- import/llm/src/index.ts (1 hunks)
- import/llm/src/llm.handler.ts (1 hunks)
- import/llm/src/response.utils.ts (1 hunks)
✅ Files skipped from review due to trivial changes (2)
- import/llm/rollup.config.mjs
- import/llm/src/index.ts
🧰 Additional context used
🪛 LanguageTool
import/llm/README.MD
[duplication] ~5-~5: Possible typo: you repeated a word
Context: ...iate data for your sheets. It leverages the the user-selected LLM to analyze sheet conf...(ENGLISH_WORD_REPEAT_RULE)
[style] ~64-~64: The phrase ‘feel free to’ is used quite frequently. Consider using a less frequent alternative to set your writing apart from others and make it sound more professional.
Context: ...ontributing Contributions are welcome! Please feel free to submit a Pull Request.(FEEL_FREE_TO_STYLE_ME)
🪛 Biome
import/llm/src/generate.records.util.ts
[error] 36-36: Use a regular expression literal instead of the RegExp constructor.
Regular expression literals avoid some escaping required in a string literal, and are easier to analyze statically.
Safe fix: Use a literal notation instead.(lint/complexity/useRegexLiterals)
import/llm/src/response.utils.ts
[error] 13-15: Use a regular expression literal instead of the RegExp constructor.
Regular expression literals avoid some escaping required in a string literal, and are easier to analyze statically.
Safe fix: Use a literal notation instead.(lint/complexity/useRegexLiterals)
[error] 19-21: Use a regular expression literal instead of the RegExp constructor.
Regular expression literals avoid some escaping required in a string literal, and are easier to analyze statically.
Safe fix: Use a literal notation instead.(lint/complexity/useRegexLiterals)
🔇 Additional comments (10)
import/llm/jest.config.js (3)
2-2: LGTM: Appropriate test environment setting.The
testEnvironmentis correctly set to 'node', which is suitable for a Node.js project. This ensures that the tests will run in a Node.js environment, mimicking the runtime environment of the application.
4-6: LGTM: Correct TypeScript transformation setup.The
transformconfiguration is properly set up to use 'ts-jest' for transforming TypeScript files. This allows Jest to run tests written in TypeScript, which is essential for maintaining type safety in your test suite.
13-13: LGTM: Global setup configured. Verify its contents.The
globalSetupconfiguration is correctly set to use a shared setup file. This is good for maintaining consistency across different parts of the project.To ensure the global setup is appropriate for these tests, please review the contents of the setup file:
#!/bin/bash # Description: Display contents of the global setup file cat ../../test/setup-global.jsVerify that the operations in this file are necessary and appropriate for the LLM import tests.
flatfilers/sandbox/src/index.ts (1)
2-2: LGTM: Import statement for llmRecordGenerator added correctly.The new import statement for
llmRecordGeneratorfrom '@flatfile/plugin-import-llm' is correctly added and aligns with the changes in functionality.import/llm/src/response.utils.ts (3)
49-50: LGTM: Concise wrapper function for JSON extractionThe
extractJSONfunction is a well-implemented wrapper for theextractContentfunction, specifically for JSON content.
51-52: LGTM: Concise wrapper function for JavaScript extractionThe
extractJavascriptfunction is a well-implemented wrapper for theextractContentfunction, specifically for JavaScript content.
53-54: LGTM: Concise wrapper function for Markdown extractionThe
extractMarkdownfunction is a well-implemented wrapper for theextractContentfunction, specifically for Markdown content.import/llm/README.MD (3)
12-18: LGTM: Features section is comprehensive and well-structured.The Features section effectively communicates the key capabilities of the plugin. It provides a clear and concise list that helps users understand what to expect from the
@flatfile/plugin-import-llm.
30-36: LGTM: Installation instructions are clear and concise.The Installation section provides a simple and correct npm install command, which is sufficient for most users to get started with the plugin.
1-64: Overall, the README is well-structured and informative.The README provides a comprehensive overview of the
@flatfile/plugin-import-llm, including its purpose, features, configuration, installation, and usage. The document is well-organized and easy to follow.A few minor improvements have been suggested throughout the review, including:
- Fixing a typo in the introduction.
- Adding type information to the Parameters section.
- Correcting the model name in the Example Usage section.
- Enhancing the Behavior and Contributing sections with more detailed information.
Implementing these suggestions will further improve the quality and usefulness of the documentation for users and potential contributors.
🧰 Tools
🪛 LanguageTool
[duplication] ~5-~5: Possible typo: you repeated a word
Context: ...iate data for your sheets. It leverages the the user-selected LLM to analyze sheet conf...(ENGLISH_WORD_REPEAT_RULE)
[style] ~64-~64: The phrase ‘feel free to’ is used quite frequently. Consider using a less frequent alternative to set your writing apart from others and make it sound more professional.
Context: ...ontributing Contributions are welcome! Please feel free to submit a Pull Request.(FEEL_FREE_TO_STYLE_ME)
import/llm/src/response.utils.ts
Outdated
| const content = | ||
| typeof response.content === 'string' | ||
| ? response.content | ||
| : JSON.stringify(response.content) |
There was a problem hiding this comment.
🛠️ Refactor suggestion
Consider handling non-string content more robustly
The current implementation uses JSON.stringify for non-string content, which might not be suitable for all cases. Consider implementing a more robust method to handle different types of content.
Here's a suggested improvement:
const content = typeof response.content === 'string'
? response.content
: Array.isArray(response.content)
? response.content.join('\n')
: JSON.stringify(response.content)This approach handles arrays by joining them with newlines, which might be more appropriate for code blocks.
| const exampleRecords = await generateExampleRecords( | ||
| config.model, | ||
| llmApiKey, | ||
| sheet, | ||
| config.numberOfRecords, | ||
| config.debug | ||
| ) |
There was a problem hiding this comment.
Validate the number of records before generating.
It's good practice to validate config.numberOfRecords to ensure it's a positive integer. This prevents potential issues with invalid input values.
Add validation for config.numberOfRecords:
+ if (config.numberOfRecords <= 0) {
+ throw new Error('Number of records must be a positive integer')
+ }Place this validation before calling generateExampleRecords.
📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| const exampleRecords = await generateExampleRecords( | |
| config.model, | |
| llmApiKey, | |
| sheet, | |
| config.numberOfRecords, | |
| config.debug | |
| ) | |
| if (config.numberOfRecords <= 0) { | |
| throw new Error('Number of records must be a positive integer') | |
| } | |
| const exampleRecords = await generateExampleRecords( | |
| config.model, | |
| llmApiKey, | |
| sheet, | |
| config.numberOfRecords, | |
| config.debug | |
| ) |
| } | ||
|
|
||
| await tick(90, 'Inserting example records') | ||
| await api.records.insert(sheetId, exampleRecords) |
There was a problem hiding this comment.
Handle potential errors when inserting records.
The api.records.insert operation could fail due to network issues or data validation errors. To improve robustness, consider adding error handling for this operation.
Apply the following change to handle errors during record insertion:
await tick(90, 'Inserting example records')
- await api.records.insert(sheetId, exampleRecords)
+ try {
+ await api.records.insert(sheetId, exampleRecords)
+ } catch (insertError) {
+ logError('@flatfile/plugin-import-llm', 'Error inserting records', insertError)
+ throw insertError
+ }📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| await api.records.insert(sheetId, exampleRecords) | |
| await tick(90, 'Inserting example records') | |
| try { | |
| await api.records.insert(sheetId, exampleRecords) | |
| } catch (insertError) { | |
| logError('@flatfile/plugin-import-llm', 'Error inserting records', insertError) | |
| throw insertError | |
| } |
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Actionable comments posted: 3
🧹 Outside diff range and nitpick comments (4)
import/llm/src/generate.records.util.ts (2)
20-26: Add input validation forcountparameterThe prompt construction looks good, but consider adding input validation for the
countparameter to ensure it's a positive integer. This will prevent potential issues with invalid input.Consider adding the following validation at the beginning of the function:
if (!Number.isInteger(count) || count <= 0) { throw new Error('count must be a positive integer'); }
42-49: Add type checking and validation for input dataWhile the formatting logic is correct, it's important to add type checking and validation for the input data to ensure it matches the expected structure.
Consider adding a type guard and validation:
interface RawRecord { [key: string]: any; } function isValidRawRecord(record: any): record is RawRecord { return typeof record === 'object' && record !== null; } return jsonGeneratedData.map((record: any) => { if (!isValidRawRecord(record)) { throw new Error('Invalid record structure in generated data'); } const formattedRecord: { [key: string]: { value: any } } = {}; for (const [key, value] of Object.entries(record)) { formattedRecord[key] = { value }; } return formattedRecord; });import/llm/README.MD (2)
20-28: Consider adding default value fornumberOfRecords.The Parameters section is well-documented, but for consistency, consider adding the default value for the
numberOfRecordsparameter as you did for thedebugparameter.Suggested change for line 27:
-- `numberOfRecords` (number): The number of example records to generate (default: 10) ++ `numberOfRecords` (number, optional): The number of example records to generate (default: 10)
62-64: Consider rephrasing the Contributing section for a more professional tone.While the Contributing section is welcoming, it could be rephrased to sound more professional.
Consider the following alternative:
## Contributing We welcome contributions to this project. If you have suggestions or improvements, please submit a Pull Request.🧰 Tools
🪛 LanguageTool
[style] ~64-~64: The phrase ‘feel free to’ is used quite frequently. Consider using a less frequent alternative to set your writing apart from others and make it sound more professional.
Context: ...ontributing Contributions are welcome! Please feel free to submit a Pull Request.(FEEL_FREE_TO_STYLE_ME)
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⛔ Files ignored due to path filters (3)
import/faker/package.jsonis excluded by!**/*.jsonimport/llm/package.jsonis excluded by!**/*.jsonpackage-lock.jsonis excluded by!**/package-lock.json,!**/*.json
📒 Files selected for processing (9)
- flatfilers/sandbox/src/index.ts (2 hunks)
- import/llm/README.MD (1 hunks)
- import/llm/jest.config.js (1 hunks)
- import/llm/rollup.config.mjs (1 hunks)
- import/llm/src/generate.records.plugin.ts (1 hunks)
- import/llm/src/generate.records.util.ts (1 hunks)
- import/llm/src/index.ts (1 hunks)
- import/llm/src/llm.handler.ts (1 hunks)
- import/llm/src/response.utils.ts (1 hunks)
🚧 Files skipped from review as they are similar to previous changes (5)
- flatfilers/sandbox/src/index.ts
- import/llm/jest.config.js
- import/llm/rollup.config.mjs
- import/llm/src/index.ts
- import/llm/src/llm.handler.ts
🧰 Additional context used
🪛 LanguageTool
import/llm/README.MD
[duplication] ~5-~5: Possible typo: you repeated a word
Context: ...iate data for your sheets. It leverages the the user-selected LLM to analyze sheet conf...(ENGLISH_WORD_REPEAT_RULE)
[style] ~64-~64: The phrase ‘feel free to’ is used quite frequently. Consider using a less frequent alternative to set your writing apart from others and make it sound more professional.
Context: ...ontributing Contributions are welcome! Please feel free to submit a Pull Request.(FEEL_FREE_TO_STYLE_ME)
🪛 Biome
import/llm/src/generate.records.util.ts
[error] 36-36: Use a regular expression literal instead of the RegExp constructor.
Regular expression literals avoid some escaping required in a string literal, and are easier to analyze statically.
Safe fix: Use a literal notation instead.(lint/complexity/useRegexLiterals)
import/llm/src/response.utils.ts
[error] 13-15: Use a regular expression literal instead of the RegExp constructor.
Regular expression literals avoid some escaping required in a string literal, and are easier to analyze statically.
Safe fix: Use a literal notation instead.(lint/complexity/useRegexLiterals)
[error] 19-21: Use a regular expression literal instead of the RegExp constructor.
Regular expression literals avoid some escaping required in a string literal, and are easier to analyze statically.
Safe fix: Use a literal notation instead.(lint/complexity/useRegexLiterals)
🔇 Additional comments (18)
import/llm/src/generate.records.util.ts (2)
4-19: LGTM: Well-structured function signature and setupThe function signature is clear, with appropriate parameter types. The initial setup, including the construction of field descriptions, is concise and effective.
36-40:⚠️ Potential issueImprove JSON extraction and parsing
There are several improvements that can be made to this section:
- Use a regex literal instead of the RegExp constructor for better readability.
- Improve the reliability of JSON extraction from the LLM response.
- Add error handling for JSON parsing.
- Validate the structure of parsed JSON data.
Apply the following changes to address these issues:
const jsonRegex = /```json\n([\s\S]*?)\n```/ let generatedData const match = responseText.match(jsonRegex) if (match && match[1]) { generatedData = match[1] } else { // Attempt to parse the entire responseText if no match is found generatedData = responseText.trim() } let jsonGeneratedData try { jsonGeneratedData = JSON.parse(generatedData) if (!Array.isArray(jsonGeneratedData)) { throw new Error('Expected JSON data to be an array of records') } } catch (error) { throw new Error('Failed to parse JSON data from LLM response') }🧰 Tools
🪛 Biome
[error] 36-36: Use a regular expression literal instead of the RegExp constructor.
Regular expression literals avoid some escaping required in a string literal, and are easier to analyze statically.
Safe fix: Use a literal notation instead.(lint/complexity/useRegexLiterals)
import/llm/src/response.utils.ts (9)
3-6: LGTM: Function signature is well-defined.The function signature is clear and type-safe, using appropriate TypeScript types.
24-30: LGTM: Markdown extraction logic is correct.The markdown extraction logic correctly identifies the content between markdown code block delimiters.
49-50: LGTM: JSON extraction function is well-implemented.The
extractJSONfunction is a concise and correct wrapper aroundextractContentfor JSON extraction.
51-52: LGTM: JavaScript extraction function is well-implemented.The
extractJavascriptfunction is a concise and correct wrapper aroundextractContentfor JavaScript extraction.
53-54: LGTM: Markdown extraction function is well-implemented.The
extractMarkdownfunction is a concise and correct wrapper aroundextractContentfor Markdown extraction.
1-54: Overall assessment: Good implementation with room for optimizationThe
response.utils.tsfile provides well-structured utility functions for extracting content from AIMessageChunk responses. The code is generally well-implemented, with clear separation of concerns and type-safe function signatures. However, there are opportunities for optimization in regex usage, error handling, and content type handling. Consider implementing the suggested improvements to enhance the robustness and maintainability of the code.🧰 Tools
🪛 Biome
[error] 13-15: Use a regular expression literal instead of the RegExp constructor.
Regular expression literals avoid some escaping required in a string literal, and are easier to analyze statically.
Safe fix: Use a literal notation instead.(lint/complexity/useRegexLiterals)
[error] 19-21: Use a regular expression literal instead of the RegExp constructor.
Regular expression literals avoid some escaping required in a string literal, and are easier to analyze statically.
Safe fix: Use a literal notation instead.(lint/complexity/useRegexLiterals)
7-10: 🛠️ Refactor suggestionConsider handling non-string content more robustly
The current implementation uses
JSON.stringifyfor non-string content, which might not be suitable for all cases.Consider implementing a more robust method to handle different types of content, as suggested in the previous review:
const content = typeof response.content === 'string' ? response.content : Array.isArray(response.content) ? response.content.join('\n') : JSON.stringify(response.content)This approach handles arrays by joining them with newlines, which might be more appropriate for code blocks.
12-23: 🛠️ Refactor suggestionOptimize regex usage for JavaScript and TypeScript extraction
The current implementation uses separate regex patterns for JavaScript and TypeScript, which are identical except for the language name. This can be optimized to reduce code duplication and address the static analysis hints.
Consider using a single regex with a variable language name and regex literals:
const codeBlockRegex = (lang: string) => new RegExp(`\`\`\`${lang}\\n([\\s\\S]*?)\\n\`\`\``) if (type === 'javascript' || type === 'typescript') { const match = content.match(codeBlockRegex(type)) return match?.[1] ?? null }This approach reduces duplication, makes it easier to add support for other languages in the future, and addresses the static analysis hints about using regex literals.
🧰 Tools
🪛 Biome
[error] 13-15: Use a regular expression literal instead of the RegExp constructor.
Regular expression literals avoid some escaping required in a string literal, and are easier to analyze statically.
Safe fix: Use a literal notation instead.(lint/complexity/useRegexLiterals)
[error] 19-21: Use a regular expression literal instead of the RegExp constructor.
Regular expression literals avoid some escaping required in a string literal, and are easier to analyze statically.
Safe fix: Use a literal notation instead.(lint/complexity/useRegexLiterals)
31-47: 🛠️ Refactor suggestionEnhance error handling and logging for JSON parsing
The current implementation logs errors but doesn't provide much context. Consider enhancing the error handling to provide more informative messages and potentially allow for custom error handling.
Here's a suggested improvement:
} else if (type === 'json') { const jsonRegex = /\{[\s\S]*\}/ const jsonMatch = content.match(jsonRegex) if (jsonMatch) { try { return JSON.parse(jsonMatch[0]) } catch (error) { console.error(`Error parsing JSON: ${error.message}`) // Optionally, throw a custom error or return a specific error object return null } } } // If no matching type is found const errorMessage = `No ${type} content found in the response` console.error(errorMessage) // Optionally, throw a custom error or return a specific error object return nullThis approach provides more context in error messages and allows for more flexible error handling.
import/llm/README.MD (2)
12-18: LGTM: Features section is clear and informative.The Features section provides a concise and comprehensive list of the plugin's capabilities.
30-36: LGTM: Installation instructions are clear.The Installation section provides straightforward instructions for installing the plugin.
import/llm/src/generate.records.plugin.ts (5)
1-7: Imports and initial setup look good.The necessary modules are imported, and the FlatfileClient is initialized correctly.
9-24: Consider using an enum for model names and verify model accuracy.As suggested in a previous review, defining the model names as an enum would improve type safety and maintainability. Additionally, please verify the accuracy of all model names, particularly
'gpt-4o'which may be a typo.To verify the model names, you can run the following script:
#!/bin/bash # Description: Verify the accuracy of model names used in the codebase. # Test: Search for model name usage across the codebase rg -i "gpt-4o|gpt-4-turbo|gpt-4|gpt-3\.5-turbo|claude-3-opus-20240229|claude-3-sonnet-20240229|claude-3-haiku-20240307|mistral-large-latest|mistral-small-latest" --type ts
33-36: Use a more generic error message for missing API key.To prevent potential information leakage, consider using a more generic error message when the LLM API key is not set.
Apply this change:
- throw new Error('LLM API key is not set') + throw new Error('Required LLM configuration is missing')
68-76: Preserve original error when rethrowing in catch block.To maintain the stack trace and error message for easier debugging, consider rethrowing the original error instead of a new generic error.
Apply this change:
- throw new Error('Error generating example records') + throw error
38-67: 🛠️ Refactor suggestionImprove logging, add input validation, and enhance error handling.
Standardize logging:
Instead of using conditional checks onconfig.debug, consider using a logging library with log levels for more flexibility and control.Validate input:
Add validation forconfig.numberOfRecordsto ensure it's a positive integer before generating records.Handle potential errors during record insertion:
Theapi.records.insertoperation could fail due to various reasons. Consider adding specific error handling for this operation.Here's an example of how you could implement these improvements:
import { logDebug, logInfo, logError } from '@flatfile/util-common' // Add this at the beginning of the try block if (config.numberOfRecords <= 0) { throw new Error('Number of records must be a positive integer') } // Replace conditional logging with log level methods logDebug('@flatfile/plugin-import-llm', 'Example records generated', exampleRecords) // Add error handling for record insertion try { await api.records.insert(sheetId, exampleRecords) } catch (insertError) { logError('@flatfile/plugin-import-llm', 'Error inserting records', insertError) throw insertError } logInfo( '@flatfile/plugin-import-llm', `Generated ${exampleRecords.length} example records` )
| const llm = new LLMHandler(model, apiKey) | ||
| const response = await llm.handleMessage('', prompt) | ||
| const responseText = response.content as string | ||
|
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| if (debug) { | ||
| console.dir(responseText, { depth: null }) | ||
| } |
There was a problem hiding this comment.
Add error handling for LLM interaction
While the LLM interaction is implemented well, it's important to add error handling to manage potential API failures or unexpected responses.
Consider wrapping the LLM interaction in a try-catch block:
try {
const llm = new LLMHandler(model, apiKey)
const response = await llm.handleMessage('', prompt)
const responseText = response.content as string
if (debug) {
console.dir(responseText, { depth: null })
}
} catch (error) {
console.error('Error during LLM interaction:', error)
throw new Error('Failed to generate example records')
}
import/llm/README.MD
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| # @flatfile/plugin-import-llm | ||
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| This Flatfile Listener plugin automatically generates example records using an LLM, providing realistic and contextually appropriate data for your sheets. It leverages the the user-selected LLM to analyze sheet configuration and create diverse sample data. |
There was a problem hiding this comment.
Fix remaining typo in the introduction.
There's still a minor typo in the introduction that needs to be corrected.
Please apply the following change:
-This Flatfile Listener plugin automatically generates example records using an LLM, providing realistic and contextually appropriate data for your sheets. It leverages the the user-selected LLM to analyze sheet configuration and create diverse sample data.
+This Flatfile Listener plugin automatically generates example records using an LLM, providing realistic and contextually appropriate data for your sheets. It leverages the user-selected LLM to analyze sheet configuration and create diverse sample data.📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| This Flatfile Listener plugin automatically generates example records using an LLM, providing realistic and contextually appropriate data for your sheets. It leverages the the user-selected LLM to analyze sheet configuration and create diverse sample data. | |
| This Flatfile Listener plugin automatically generates example records using an LLM, providing realistic and contextually appropriate data for your sheets. It leverages the user-selected LLM to analyze sheet configuration and create diverse sample data. |
🧰 Tools
🪛 LanguageTool
[duplication] ~5-~5: Possible typo: you repeated a word
Context: ...iate data for your sheets. It leverages the the user-selected LLM to analyze sheet conf...(ENGLISH_WORD_REPEAT_RULE)
import/llm/README.MD
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| listener.use( | ||
| llmRecordGenerator({ | ||
| llmSecretName: 'LLM_API_KEY', | ||
| model: 'gpt-4o', |
There was a problem hiding this comment.
Fix typo in the model parameter.
The model parameter in the example usage still contains a typo.
Please apply the following change:
- model: 'gpt-4o',
+ model: 'gpt-4',📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| model: 'gpt-4o', | |
| model: 'gpt-4', |
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Actionable comments posted: 13
🧹 Outside diff range and nitpick comments (6)
import/llm-records/README.MD (3)
12-18: Minor: Improve punctuation consistency in the features list.The features list is informative and covers key aspects of the plugin. To enhance readability, consider adding periods at the end of each feature point for consistency.
Here's a suggested improvement:
## Features -- Automatically generates example records based on Sheet's Field configuration -- Configurable number of records to generate -- Uses advanced LLMs to create contextually appropriate data -- Seamless integration with Flatfile workflows -- Error handling and logging for reliable operation +- Automatically generates example records based on Sheet's Field configuration. +- Configurable number of records to generate. +- Uses advanced LLMs to create contextually appropriate data. +- Seamless integration with Flatfile workflows. +- Error handling and logging for reliable operation.
20-28: Suggestion: Improve formatting consistency in the parameters section.The parameters section provides clear information about the configuration object properties. To enhance readability and consistency, consider the following improvements:
- Use consistent capitalization for the first word in each parameter description.
- End each description with a period for consistency.
- Use parentheses consistently for default values.
Here's a suggested improvement:
The `importLLMRecords` function accepts a configuration object with the following properties: -- `llmSecretName` (string): The name of the secret that contains the LLM API key. -- `model` (string): The name of the LLM to use. -- `job` (string): The Sheet-level operation name to listen for in the job:ready event. -- `numberOfRecords` (number): The number of example records to generate (default: 10) -- `debug` (boolean): Whether to log debug information (default: false) +- `llmSecretName` (string): The name of the secret that contains the LLM API key. +- `model` (string): The name of the LLM to use. +- `job` (string): The Sheet-level operation name to listen for in the job:ready event. +- `numberOfRecords` (number): The number of example records to generate. (Default: 10) +- `debug` (boolean): Whether to log debug information. (Default: false)
30-54: Suggestion: Add a brief explanatory comment to the example code.The installation and example usage sections are clear and helpful. To further improve the example, consider adding a brief comment explaining the purpose of the code and how it integrates with Flatfile.
Here's a suggested improvement:
## Example Usage ```typescript +// This example demonstrates how to integrate the LLM Record Generator Plugin +// into a Flatfile listener to automatically generate example records. import type { FlatfileListener } from '@flatfile/listener'; import { importLLMRecords } from '@flatfile/plugin-import-llm-records'; export default function (listener: FlatfileListener) { listener.use( importLLMRecords({ llmSecretName: 'LLM_API_KEY', model: 'gpt-4o', job: 'generateExampleRecords', numberOfRecords: 10 }) ) }</blockquote></details> <details> <summary>import/llm-records/src/generate.records.ts (2)</summary><blockquote> `20-26`: **Enhance the prompt for better LLM understanding.** The prompt could be misinterpreted because it includes both the field descriptions and the instructions in a way that may not be clear to the LLM. Consider formatting the prompt to clearly separate the field definitions from the instructions. Consider reformatting the prompt as follows: ```diff const prompt = `Generate ${count} example records for a dataset with the following fields: -${fieldDescriptions} -Please provide the data in JSON format, with each record as an object in an array. -Ensure the data is diverse and contextually appropriate for each field type and constraint. -Return only the JSON data, no other text or comments.` +Fields: + +${fieldDescriptions} + +Instructions: +- Provide the data in JSON format, with each record as an object in an array. +- Ensure the data is diverse and contextually appropriate for each field type and constraint. +- Return only the JSON data, no other text or comments.`
42-48: Specify return type for better type safety.Explicitly specifying the type of
formattedRecordimproves type safety and code readability.Apply this diff to define the type:
const formattedRecord: { [key: string]: { value: any } } = {} +// Alternatively, define a type alias at the top of the file: +// type RecordValue = { [key: string]: { value: any } }import/llm-records/src/import.llm.records.ts (1)
54-56: Use Consistent Logging Methods Instead ofconsole.dirFor consistency, consider using the
logInfoutility instead ofconsole.dirto log the generated records. This aligns logging practices across the module.-if (config.debug) { - console.dir(records, { depth: null }) -} +if (config.debug) { + logInfo( + '@flatfile/plugin-import-llm-records', + 'Generated records:', + JSON.stringify(records, null, 2) + ) +}
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⛔ Files ignored due to path filters (2)
import/llm-records/package.jsonis excluded by!**/*.jsonpackage-lock.jsonis excluded by!**/package-lock.json,!**/*.json
📒 Files selected for processing (9)
- .changeset/five-hornets-judge.md (1 hunks)
- flatfilers/sandbox/src/index.ts (2 hunks)
- import/llm-records/README.MD (1 hunks)
- import/llm-records/jest.config.js (1 hunks)
- import/llm-records/rollup.config.mjs (1 hunks)
- import/llm-records/src/generate.records.ts (1 hunks)
- import/llm-records/src/import.llm.records.ts (1 hunks)
- import/llm-records/src/index.ts (1 hunks)
- import/llm-records/src/llm.handler.ts (1 hunks)
✅ Files skipped from review due to trivial changes (4)
- .changeset/five-hornets-judge.md
- import/llm-records/jest.config.js
- import/llm-records/rollup.config.mjs
- import/llm-records/src/index.ts
🚧 Files skipped from review as they are similar to previous changes (1)
- flatfilers/sandbox/src/index.ts
🧰 Additional context used
🪛 LanguageTool
import/llm-records/README.MD
[style] ~58-~58: The phrase ‘feel free to’ is used quite frequently. Consider using a less frequent alternative to set your writing apart from others and make it sound more professional.
Context: ...ontributing Contributions are welcome! Please feel free to submit a Pull Request.(FEEL_FREE_TO_STYLE_ME)
🪛 Biome
import/llm-records/src/generate.records.ts
[error] 36-36: Use a regular expression literal instead of the RegExp constructor.
Regular expression literals avoid some escaping required in a string literal, and are easier to analyze statically.
Safe fix: Use a literal notation instead.(lint/complexity/useRegexLiterals)
🔇 Additional comments (4)
import/llm-records/README.MD (1)
1-10: LGTM: Infocard section is informative and well-structured.The infocard provides a clear and concise description of the plugin's purpose and functionality. The inclusion of the event type is helpful for users.
import/llm-records/src/generate.records.ts (1)
1-2: Consider specifying exact types in import statements.Currently, you're using a type-only import for
Flatfile:import type { Flatfile } from '@flatfile/api'Ensure that
Flatfileis indeed only used for type annotations. If you need to use any runtime features from@flatfile/api, remove thetypemodifier.import/llm-records/src/llm.handler.ts (1)
60-89: Verify and update the list of supported model namesThe model names specified in the
getLLMmethod may be outdated or incorrect. For example,gpt-4-turboshould begpt-4orgpt-4-32k. Ensure all model names are accurate and currently supported by their respective APIs.You can run the following script to list available models:
Replace
YOUR_API_KEYwith a valid OpenAI API key.import/llm-records/src/import.llm.records.ts (1)
26-83: Well-Structured Function with Effective Error HandlingThe
importLLMRecordsfunction is well-structured, utilizingjobHandlereffectively. Error handling and progress updates are appropriately managed.
| ## Contributing | ||
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| Contributions are welcome! Please feel free to submit a Pull Request. |
There was a problem hiding this comment.
🛠️ Refactor suggestion
Enhance the contributing section with more specific guidance.
The current contributing section is concise but could be more informative. Consider expanding it to provide more specific guidance for potential contributors and addressing the style suggestion.
Here's a suggested improvement:
## Contributing
We welcome contributions to improve this plugin! Here are some ways you can contribute:
1. Report issues or suggest features through GitHub Issues.
2. Submit Pull Requests with bug fixes or new features.
3. Improve documentation or add examples.
Before submitting a Pull Request, please ensure your code adheres to the project's coding standards and includes appropriate tests.
For more information on how to contribute, please read our [Contributing Guidelines](link-to-contributing-guidelines).This expanded section provides more specific guidance, avoids the overused phrase "feel free to," and encourages various forms of contribution.
🧰 Tools
🪛 LanguageTool
[style] ~58-~58: The phrase ‘feel free to’ is used quite frequently. Consider using a less frequent alternative to set your writing apart from others and make it sound more professional.
Context: ...ontributing Contributions are welcome! Please feel free to submit a Pull Request.(FEEL_FREE_TO_STYLE_ME)
| `${field.key}: ${field.type} ${ | ||
| field.constraints ? JSON.stringify(field.constraints) : '' | ||
| }` |
There was a problem hiding this comment.
Handle undefined or null constraints gracefully.
When formatting fieldDescriptions, if field.constraints is undefined or null, the string "null" may be included in the output due to JSON.stringify(null) resulting in "null".
Apply this diff to ensure that constraints are only included when they have a value:
`${field.key}: ${field.type} ${
- field.constraints ? JSON.stringify(field.constraints) : ''
+ field.constraints && Object.keys(field.constraints).length > 0 ? JSON.stringify(field.constraints) : ''
}`📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| `${field.key}: ${field.type} ${ | |
| field.constraints ? JSON.stringify(field.constraints) : '' | |
| }` | |
| `${field.key}: ${field.type} ${ | |
| field.constraints && Object.keys(field.constraints).length > 0 ? JSON.stringify(field.constraints) : '' | |
| }` |
| const match = responseText.match(jsonRegex) | ||
| const generatedData = match?.[1] ?? responseText | ||
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| const jsonGeneratedData = JSON.parse(generatedData) |
There was a problem hiding this comment.
Add error handling for JSON parsing.
Parsing JSON from an external source can fail. It's important to handle parsing errors to prevent the application from crashing.
Apply this diff to add a try-catch block around JSON.parse:
-const jsonGeneratedData = JSON.parse(generatedData)
+let jsonGeneratedData
+try {
+ jsonGeneratedData = JSON.parse(generatedData)
+} catch (error) {
+ throw new Error('Invalid JSON format received from LLM response.')
+}📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| const jsonGeneratedData = JSON.parse(generatedData) | |
| let jsonGeneratedData | |
| try { | |
| jsonGeneratedData = JSON.parse(generatedData) | |
| } catch (error) { | |
| throw new Error('Invalid JSON format received from LLM response.') | |
| } |
| return jsonGeneratedData.map((record: any) => { | ||
| const formattedRecord: { [key: string]: { value: any } } = {} | ||
| for (const [key, value] of Object.entries(record)) { | ||
| formattedRecord[key] = { value } |
There was a problem hiding this comment.
🛠️ Refactor suggestion
Consider handling nested objects in records.
If the generated data might include nested objects, the current implementation will not handle them correctly. Consider implementing a recursive function to format nested records.
Implement a recursive formatting function:
-function formatRecord(record: any): { [key: string]: { value: any } } {
+function formatRecord(record: any): { [key: string]: any } {
const formattedRecord: { [key: string]: any } = {}
for (const [key, value] of Object.entries(record)) {
if (typeof value === 'object' && value !== null && !Array.isArray(value)) {
formattedRecord[key] = formatRecord(value)
} else {
formattedRecord[key] = { value }
}
}
return formattedRecord
}
return jsonGeneratedData.map((record: any) => formatRecord(record))Committable suggestion was skipped due to low confidence.
| const jsonRegex = new RegExp(`\`\`\`json\\n([\\s\\S]*?)\\n\`\`\``) | ||
| const match = responseText.match(jsonRegex) | ||
| const generatedData = match?.[1] ?? responseText |
There was a problem hiding this comment.
Use a regular expression literal instead of the RegExp constructor.
According to static analysis hints, using a regular expression literal is more efficient and avoids the need for extra escaping. It also improves readability.
Apply this diff to use a regular expression literal:
-const jsonRegex = new RegExp(`\`\`\`json\\n([\\s\\S]*?)\\n\`\`\``)
+const jsonRegex = /\`\`\`json\n([\s\S]*?)\n\`\`\`/📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| const jsonRegex = new RegExp(`\`\`\`json\\n([\\s\\S]*?)\\n\`\`\``) | |
| const match = responseText.match(jsonRegex) | |
| const generatedData = match?.[1] ?? responseText | |
| const jsonRegex = /\`\`\`json\n([\s\S]*?)\n\`\`\`/ | |
| const match = responseText.match(jsonRegex) | |
| const generatedData = match?.[1] ?? responseText |
🧰 Tools
🪛 Biome
[error] 36-36: Use a regular expression literal instead of the RegExp constructor.
Regular expression literals avoid some escaping required in a string literal, and are easier to analyze statically.
Safe fix: Use a literal notation instead.(lint/complexity/useRegexLiterals)
🛠️ Refactor suggestion
Enhance JSON extraction logic to handle edge cases.
Relying solely on the presence of fenced code blocks may fail if the LLM does not format the JSON within code fences. Consider updating the extraction logic to be more robust.
Consider trying to parse the entire response first, and if it fails, then attempt to extract JSON from within code blocks.
-let generatedData = match?.[1] ?? responseText
+let generatedData = responseText
+// Try to parse the entire response first
+try {
+ JSON.parse(generatedData)
+} catch {
+ // If parsing fails, attempt to extract JSON from code blocks
+ if (match) {
+ generatedData = match[1]
+ } else {
+ throw new Error('Failed to extract valid JSON from LLM response.')
+ }
+}Committable suggestion was skipped due to low confidence.
🧰 Tools
🪛 Biome
[error] 36-36: Use a regular expression literal instead of the RegExp constructor.
Regular expression literals avoid some escaping required in a string literal, and are easier to analyze statically.
Safe fix: Use a literal notation instead.(lint/complexity/useRegexLiterals)
| import { ChatMistralAI } from '@langchain/mistralai' | ||
| import { ChatOpenAI } from '@langchain/openai' | ||
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| export class llmHandler { |
There was a problem hiding this comment.
Class name should follow PascalCase naming convention
In TypeScript, class names should be in PascalCase. Consider renaming llmHandler to LLMHandler for consistency.
Apply this diff to rename the class:
-export class llmHandler {
+export class LLMHandler {📝 Committable suggestion
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Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| export class llmHandler { | |
| export class LLMHandler { |
| const result = await this.llm.invoke(allMessages) | ||
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| if (this.useHistory) { | ||
| this.messageHistory.push(humanMessage) | ||
| this.messageHistory.push(result) | ||
| } | ||
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| return result |
There was a problem hiding this comment.
🛠️ Refactor suggestion
Add error handling for LLM invocation
Errors from this.llm.invoke(allMessages) are not currently handled, which may cause unhandled promise rejections. Implement error handling to manage exceptions gracefully.
Wrap the invocation in a try-catch block:
try {
const result = await this.llm.invoke(allMessages)
if (this.useHistory) {
this.messageHistory.push(humanMessage)
this.messageHistory.push(result)
}
return result
} catch (error) {
// Handle specific errors if necessary
throw new Error(`LLM invocation failed: ${error.message}`)
}📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| const result = await this.llm.invoke(allMessages) | |
| if (this.useHistory) { | |
| this.messageHistory.push(humanMessage) | |
| this.messageHistory.push(result) | |
| } | |
| return result | |
| try { | |
| const result = await this.llm.invoke(allMessages) | |
| if (this.useHistory) { | |
| this.messageHistory.push(humanMessage) | |
| this.messageHistory.push(result) | |
| } | |
| return result | |
| } catch (error) { | |
| // Handle specific errors if necessary | |
| throw new Error(`LLM invocation failed: ${error.message}`) | |
| } |
| if (this.useHistory) { | ||
| this.messageHistory.push(humanMessage) | ||
| this.messageHistory.push(result) | ||
| } |
There was a problem hiding this comment.
Type mismatch when adding result to messageHistory
The result from this.llm.invoke(allMessages) is of type BaseMessageChunk, whereas messageHistory expects elements of type BaseMessage. This may lead to type inconsistencies.
Consider converting result to a BaseMessage before adding it to messageHistory:
this.messageHistory.push(humanMessage)
-this.messageHistory.push(result)
+this.messageHistory.push(new AIMessage(result.content))Ensure you import AIMessage from @langchain/core/messages:
import {
BaseMessage,
BaseMessageChunk,
+ AIMessage,
HumanMessage,
SystemMessage,
} from '@langchain/core/messages'Committable suggestion was skipped due to low confidence.
| | 'gpt-4o' | ||
| | 'gpt-4-turbo' | ||
| | 'gpt-4' |
There was a problem hiding this comment.
Possible Typo in Model Name 'gpt-4o'
The model name 'gpt-4o' may be a typo. Please verify if it should be 'gpt-4' or another valid model name.
| } catch (error) { | ||
| if (config.debug) { | ||
| logError( | ||
| '@flatfile/plugin-import-llm-records', | ||
| `Error generating example records: ${error.message}` | ||
| ) | ||
| } | ||
| throw new Error('Error generating example records') | ||
| } |
There was a problem hiding this comment.
🛠️ Refactor suggestion
Include Original Error Message in Thrown Error
When rethrowing an error, consider including the original error message to aid in debugging.
-throw new Error('Error generating example records')
+throw new Error(`Error generating example records: ${error.message}`)Ensure that no sensitive information is exposed in the error message.
📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| } catch (error) { | |
| if (config.debug) { | |
| logError( | |
| '@flatfile/plugin-import-llm-records', | |
| `Error generating example records: ${error.message}` | |
| ) | |
| } | |
| throw new Error('Error generating example records') | |
| } | |
| } catch (error) { | |
| if (config.debug) { | |
| logError( | |
| '@flatfile/plugin-import-llm-records', | |
| `Error generating example records: ${error.message}` | |
| ) | |
| } | |
| throw new Error(`Error generating example records: ${error.message}`) | |
| } |
