Added logs for debugging

[sauravpanda]

Enhanced Logging for Chat Interface

• Purpose:
  Improve debugging and monitoring capabilities in the ChatInterface component.
• Key Changes:
  • Added console logs for model loading start, progress, and completion times.
  • Enhanced error logging to include model details and stack traces.
  • Introduced logging for text generation initiation and completion metrics.
  • Counted and logged the number of chunks received during text generation.
• Impact:
  These changes will facilitate easier troubleshooting and performance monitoring during model loading and text generation processes.

✨ Generated with love by Kaizen ❤️

Original Description

None

[kaizen-bot]

🔍 Code Review Summary

❗ Attention Required: This push has potential issues. 🚨

Overview

• Total Feedbacks: 3 (Critical: 3, Refinements: 0)
• Files Affected: 1
• Code Quality: [████████████████░░░░] 80% (Good)

🚨 Critical Issues

Logging (3 issues)

1. Excessive logging in the loadModel and handleSend functions

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📁 File: examples/chat-demo/src/components/ChatInterface.tsx
🔍 Reasoning:
While logging is important for debugging and monitoring, the current level of logging may negatively impact performance and readability of the codebase. Excessive logging can also lead to increased storage and processing requirements for log data.

💡 Solution:
Reduce the number of log statements and only log critical information. Consider using a logging library that supports different log levels (e.g., debug, info, warn, error) and only log at the appropriate level.

Current Code:

['console.log(`[BrowserAI] Starting to load model: ${selectedModel}`);', 'console.log(`[BrowserAI] Loading progress:`, progress);', 'console.log(`[BrowserAI] Loading progress:`, progressPercent);', 'console.log(`[BrowserAI] Model loaded successfully in ${loadTime.toFixed(0)}ms`);', 'console.log(`[BrowserAI] Starting text generation with input length: ${input.length}`);', "console.log('[BrowserAI] Text generation completed:',{", '  responseTimeMs: responseTime.toFixed(0),', '  outputLength: response.length,', '  chunks: chunkCount', '});']

Suggested Code:

['logger.debug(`[BrowserAI] Starting to load model: ${selectedModel}`);', 'logger.info(`[BrowserAI] Loading progress: ${progressPercent}%`);', 'logger.info(`[BrowserAI] Model loaded successfully in ${loadTime.toFixed(0)}ms`);', 'logger.debug(`[BrowserAI] Starting text generation with input length: ${input.length}`);', "logger.info('[BrowserAI] Text generation completed:',{", '  responseTimeMs: responseTime.toFixed(0),', '  outputLength: response.length,', '  chunks: chunkCount', '});']

2. Potential performance issues with the for await...of loop in the handleSend function

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📁 File: examples/chat-demo/src/components/ChatInterface.tsx
🔍 Reasoning:
The for await...of loop in the handleSend function may have performance implications, especially if the response from the API contains a large number of chunks. This loop iterates over the chunks and appends the content to the response variable, which could lead to performance issues if the response is large.

💡 Solution:
Consider optimizing the response handling by using a more efficient data structure, such as a StringBuilder or a Buffer, to accumulate the response. This can help reduce the number of string concatenations and improve the overall performance of the function.

Current Code:

["let response = '';", 'let chunkCount = 0;', 'for await (const chunk of chunks as AsyncIterable<{', '  choices: Array<{delta:{content?: string}}>,', '  usage: any', '}>){', '  chunkCount++;', "  const newContent = chunk.choices[0]?.delta.content || '';", '  const newUsage = chunk.usage;', '  response += newContent;', '}']

Suggested Code:

["let response = '';", 'let chunkCount = 0;', 'const responseBuilder = new StringBuilder();', 'for await (const chunk of chunks as AsyncIterable<{', '  choices: Array<{delta:{content?: string}}>,', '  usage: any', '}>){', '  chunkCount++;', "  const newContent = chunk.choices[0]?.delta.content || '';", '  const newUsage = chunk.usage;', '  responseBuilder.append(newContent);', '}', 'response = responseBuilder.toString();']

3. Potential security risk with logging sensitive information

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📁 File: examples/chat-demo/src/components/ChatInterface.tsx
🔍 Reasoning:
The error logging in the loadModel and handleSend functions includes sensitive information, such as the selected model and the error stack trace. This information could potentially be used by attackers to gain more insight into the application and its internals, potentially leading to security vulnerabilities.

💡 Solution:
Avoid logging sensitive information, such as error stack traces, that could be used by attackers to gain more insight into the application. Consider using a centralized error handling mechanism that can sanitize and filter out sensitive information before logging.

Current Code:

["console.error('[BrowserAI] Error loading model:',{", '  model: selectedModel,', '  error: error.message,', '  stack: error.stack', '});', "console.error('[BrowserAI] Error generating text:',{", '  model: selectedModel,', '  error: error.message,', '  stack: error.stack', '});']

Suggested Code:

["logger.error('[BrowserAI] Error loading model:',{", '  model: selectedModel,', '  error: error.message', '});', "logger.error('[BrowserAI] Error generating text:',{", '  model: selectedModel,', '  error: error.message', '});']

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✨ Generated with love by Kaizen ❤️

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