Error Handling Strategies: Instead of relying on a feedback loop, we can also should proactively check for common errors and solve them in the first completion step. We can apply a layered strategy where initial steps involve simpler methods like 1) fine-tuning, 2) offering multiple choice alternatives, and 3) employing tools like mypy checkers. The last resort should be 4) human feedback:
Use of Specific Research and Tools: The feedback mentions reading specific papers 2311.04254 and 2203.14465 related to metastrategies.
Incremental Feedback and Latency Reduction: We should work incrementally to reduce latency in providing feedback, especially for non-LLM (Language Learning Models) information. This could involve tapping LSP information in the background to respond to user changes promptly. For this, we would need a VSCode extension, which is allowed as early as we deem it necessary to advance and solve the problems we disciver
Flexibility in Methods: There's an emphasis on being flexible with the methods used, including employing GPT-4 if it enhances the developer experience. Even time-consuming processes might be acceptable in some cases.
Hallucinations and Contextual Awareness: The tool should be aware of the coding context, like knowing if a function doesn’t exist. It's suggested to use LSP to intercept such instances, which is already used for code highlighting.
Practical Evaluation Over Scientific Studies: The feedback advises using the tool in real-world scenarios to evaluate its effectiveness rather than relying solely on scientific studies. It suggests a diversity of examples across different difficulty levels.
Tool Integration: We are allowed to package the LLMcoder into a VSCode extensions already. However, such integrations shouldn't be the priority unless they add significant value.
Terminology and Presentation: When discussing the tool, terminology should be clear, focusing on terms like 'analyzers' and 'repair'. Also, it's advised to keep the presentation focused, discussing one concept per slide.
Technical Suggestions: There are specific technical suggestions like using tree-sitter instead of AST (Abstract Syntax Tree) and considering the structure of projects through tools like ctags.
Error Handling Strategies: Instead of relying on a feedback loop, we can also should proactively check for common errors and solve them in the first completion step. We can apply a layered strategy where initial steps involve simpler methods like 1) fine-tuning, 2) offering multiple choice alternatives, and 3) employing tools like mypy checkers. The last resort should be 4) human feedback:
Use of Specific Research and Tools: The feedback mentions reading specific papers 2311.04254 and 2203.14465 related to metastrategies.
Incremental Feedback and Latency Reduction: We should work incrementally to reduce latency in providing feedback, especially for non-LLM (Language Learning Models) information. This could involve tapping LSP information in the background to respond to user changes promptly. For this, we would need a VSCode extension, which is allowed as early as we deem it necessary to advance and solve the problems we disciver
Flexibility in Methods: There's an emphasis on being flexible with the methods used, including employing GPT-4 if it enhances the developer experience. Even time-consuming processes might be acceptable in some cases.
Hallucinations and Contextual Awareness: The tool should be aware of the coding context, like knowing if a function doesn’t exist. It's suggested to use LSP to intercept such instances, which is already used for code highlighting.
Practical Evaluation Over Scientific Studies: The feedback advises using the tool in real-world scenarios to evaluate its effectiveness rather than relying solely on scientific studies. It suggests a diversity of examples across different difficulty levels.
Tool Integration: We are allowed to package the LLMcoder into a VSCode extensions already. However, such integrations shouldn't be the priority unless they add significant value.
Terminology and Presentation: When discussing the tool, terminology should be clear, focusing on terms like 'analyzers' and 'repair'. Also, it's advised to keep the presentation focused, discussing one concept per slide.
Technical Suggestions: There are specific technical suggestions like using tree-sitter instead of AST (Abstract Syntax Tree) and considering the structure of projects through tools like ctags.