feat: Added Google Multimodal Live APIs

[gunpal5]

• Implemented Google multimodal live APIs. However Botsharp would still need to adapt it.
• Added unit testing for LLMs currently implemented for OpenAI, Google and Anthropic. more providers can be plugged in LLMProvider.cs

[GGHansome]

Auto Review Result:

Code Review Summary

Change Summary: This code introduces modifications in multiple parts of a chatbot AI plugin system. It primarily adds Google AI settings, functions, and tests related to chatbot completion, including real-time providers and embedding functionalities.

Issues Found

Issue 1: Null Safety Handling

• Description: In GetChatCompletionsStreamingAsync method, the parameter parameters.System is checked for null and initialized if null. This approach could lead to unintentional mutations if method behavior relies on parameters.System being a null value elsewhere.
• Suggestion: Instead of initializing with an empty list, consider using null-coalescing to maintain consistency in method behavior.
• Example:

  // Before
  if(parameters.System == null)
      parameters.System = new List<SystemMessage>();
  
  // After
  var systemMessages = parameters.System ?? new List<SystemMessage>();

Issue 2: Missing Newline at EOF

• Description: Several new files end without a newline character. This can cause issues with some POSIX compliant tools and diff utilities.
• Suggestion: Ensure that all files end with a newline character.

Issue 3: Incomplete Method Implementations

• Description: Methods such as TriggerModelInference, CancelModelResponse, and more appear to be incomplete or placeholders.
• Suggestion: Complete these methods or remove them if they are not required in the current release.
• Example:

  public async Task TriggerModelInference(string? instructions = null)
  {
    // Add logic here
  }

Overall Assessment

The code indicates significant integration with Google AI capabilities and adds multiple features regarding AI model handling and completion testing. However, there is room for improvement in code clarity, especially concerning null handling and proper testing implementation. It's recommended to adhere to code conventions such as ensuring files end with newline characters and ensuring that placeholder methods are either completed or removed if unused.

[GGHansome]

Auto Review Result:

Code Review Summary

Change Summary:
The changes primarily focus on integrating new logging and settings capabilities for Google AI, enhancing the initialization of AI clients, and adding a new feature provider for real-time systems. Updates also include additional unit tests for chat completions to ensure the functionality across different AI models such as Gemini and OpenAI. Furthermore, configurations are now more resilient in handling potential null values and missing providers, addressing existing potential null reference exceptions.

Identified Issues

Issue 1: [Null Reference Handling]

• Description: The code change uses a null-coalescing operator to handle potential null references in the parameters.System. This improves the code reliability but should be consistently applied across all potential nullable types.
• Suggestion: Ensure all list-type and external variable accesses are safeguarded using null-coalescing or appropriate checks.
• Example:

  // Before modification
  var prompt = $"{string.Join("\r\n", parameters.System.Select(x => x.Text))}\r\n";
  // After modification
  var prompt = $"{string.Join("\r\n", (parameters.System??new List<SystemMessage>()).Select(x => x.Text))}\r\n";

Issue 2: [Code Maintainability]

• Description: Many methods have a large number of parameters, which can be refactored into objects to pass around, improving readability and maintainability.
• Suggestion: Consider using parameter objects or tuples for complex method signatures.
• Example:

  // Consider refactoring long parameter lists into compact objects where possible.

Issue 3: [Testing Coverage]

• Description: New test cases are introduced in ChatCompletion_Tests, which is excellent. However, make sure these cover edge cases and potential failure points, especially around networking or model communication.
• Suggestion: Expand on the current tests by simulating failure states and edge cases not covered in basic cases.

Overall Evaluation

The code changes show a clear direction towards enhancing the system's robustness through better logging, configuration management, and expanded real-time capabilities. The introduction of well-structured test cases is a positive step towards maintaining code quality.
Key improvements should focus on further simplifying method signatures and ensuring comprehensive coverage of potential error states in all new functionality, especially around external service integrations.

[GGHansome]

Auto Review Result:

Code Review Summary

Change Overview: The provided code changes introduce several modifications across different files in the BotSharp codebase. The primary changes involve:

1. Making some properties nullable.
2. Formatting improvements for better readability.
3. Enhancements in dependency injection setups.
4. Addition of new classes and functions to extend the functionality, especially around the Google AI integration for real-time completions and testing.

These changes aim to improve code maintainability, readability, and expand functionality with new providers.

Identified Issues

Issue 1: Code Readability

• Description: The code has inconsistent formatting, which affects readability. Lines are excessively lengthy, and some blocks lack proper spacing and indentation.
• Suggestion: Ensure consistent code formatting adhering to industry standards, such as aligning method parameters and maintaining a consistent line length.
• Example:

  // Before
  public Task<bool> GetChatCompletionsAsync(Agent agent, List<RoleDialogModel> conversations, Func<RoleDialogModel, Task> onMessageReceived, Func<RoleDialogModel, Task> onFunctionExecuting)
  // After
  public Task<bool> GetChatCompletionsAsync(Agent agent, List<RoleDialogModel> conversations,
      Func<RoleDialogModel, Task> onMessageReceived, Func<RoleDialogModel, Task> onFunctionExecuting)

Issue 2: Nullable Reference Types

• Description: Some properties were changed to be explicitly nullable. However, their usage isn't entirely checked, which might lead to potential null reference exceptions.
• Suggestion: Implement null checks where these nullable properties are accessed to avoid runtime exceptions.
• Example:

  if (Parameters == null)
  {
      // Handle null case
  }

Issue 3: Logical Error

• Description: In ResponseDone method, there's a potential logic flaw in processing chat completion parts. Incorrectly assuming all parts will follow a specific structure can lead to errors.
• Suggestion: Add comprehensive validation and testing for parts of server content to ensure their validity before processing.
• Example:

  if (parts != null) {
      foreach (var part in parts) {
          if (part.FunctionCall != null) {
              // Process function call
          }
          else {
              // Handle non-function call part
          }
      }
  }

Overall Assessment

This code largely enhances the project by introducing new functionality and improving maintainability. However, focus on consistent formatting, comprehensive null handling, and robust validation is necessary to ensure reliability and readability. Future improvements could also include detailed documentation for new functionalities and testing procedures to ensure that these changes integrate seamlessly and effectively.

[GGHansome]

Auto Review Result:

Code Review Summary

Change Summary: The proposed changes include the introduction of optional types for certain properties, enhancements to function parameters, adjustments to improve code formatting, and additions of new functionalities such as real-time completion providers and unit tests. These changes aim to improve the code's robustness, readability, and extend the application’s feature set.

Identified Issues

Issue 1: Possible Null Reference [Code Style/Functionality]

• Description: The code introduces nullable reference types (FunctionParametersDef?), which can lead to null reference exceptions if not handled properly, particularly when initialized with non-null values initially.
• Suggestion: Ensure that all uses of Parameters are checked for nullity before use, or employ null-coalescing operations where it makes sense.
• Example:

  // Before Change
  public FunctionParametersDef Parameters { get; set; } = new FunctionParametersDef();
  // After Change
  public FunctionParametersDef? Parameters { get; set; } = new FunctionParametersDef();
  // Suggested Use
  var parameter = Parameters ?? new FunctionParametersDef();

Issue 2: Consistency in Formatting [Code Style]

• Description: In several places, there is inconsistent formatting, such as additional or missing line breaks, leading to potential readability issues.
• Suggestion: Adopt a consistent code formatting style across the entire codebase using tools like Prettier or ESLint for automatic formatting enforcement.
• Example:

  var prompt = $"{string.Join('\r\n', (parameters.System ?? new List<SystemMessage>()).Select(x => x.Text))}\r\n";

Issue 3: New Code Files Lack EOF newline [Code Style]

• Description: Some newly created files are missing a newline at the end of the file.
• Suggestion: Ensure all files end with a newline, adhering to POSIX standards for better compatibility across different tools and platforms.

Issue 4: Unused Variables [Code Quality]

• Description: There are instances of unused variables such as string prompt, which may contribute to confusion or increased maintenance burden.
• Suggestion: Remove unused variables or justify their presence with comments if they're placeholders for future work.

Issue 5: Complex Logic in Methods [Maintainability]

• Description: Some methods, like PrepareOptions, contain complex logic that could be broken down for better readability and maintainability.
• Suggestion: Refactor these methods into smaller, more focused helper methods.

Overall Evaluation

The changes expand the codebase with new functionalities while improving code readability through type annotations and formatting changes. However, attention is needed on certain areas such as proper handling of nullable types, consistent use of code formatting, and breaking down complex methods into simpler functions for enhanced clarity and maintainability. Addressing these issues will lead to a more robust code structure, facilitating easier updates and troubleshooting in the future.

[GGHansome]

Auto Review Result:

Code Review Summary

Change Summary: This code change introduces several modifications to the existing function definitions and class implementations, intended to enhance nullability awareness, improve formatting consistency, and integrate new dependencies and functionalities.

Issues Identified

Issue 1: Nullability and Initialization

• Description: The code introduces a nullable FunctionParametersDef with a default non-null constructor. This approach can be misleading about the potential nullability of the property.
• Suggestion: Consider removing the default value or adjusting the constructor to align with the property's intended nullability.
• Example:

  // Before
  public FunctionParametersDef Parameters { get; set; } = new FunctionParametersDef();
  // After
  public FunctionParametersDef? Parameters { get; set; }

Issue 2: Code Formatting and Consistency

• Description: Inconsistent use of spaces around operators and method parameters leads to reduced readability.
• Suggestion: Use a consistent code formatting tool and apply it uniformly across the codebase.
• Example:

  // Before
  var maxTokens = int.TryParse(state.GetState("max_tokens"), out var tokens)
                          ? tokens
                          : agent.LlmConfig?.MaxOutputTokens ?? LlmConstant.DEFAULT_MAX_OUTPUT_TOKEN;
  // After
  var maxTokens = int.TryParse(state.GetState("max_tokens"), out var tokens) ? 
                   tokens : agent.LlmConfig?.MaxOutputTokens ?? LlmConstant.DEFAULT_MAX_OUTPUT_TOKEN;

Issue 3: Missing Newline

• Description: Missing newline at the end of some files, which might cause issues with certain tools or version control systems.
• Suggestion: Ensure all files end with a newline.

Issue 4: Unused or Inefficient Code

• Description: Certain lines and imports appear unused or potentially inefficient in the way they're handled.
• Suggestion: Review and remove any dead code and optimize inefficiencies, such as redundant List instantiations.
• Example:

  // Potential improvement for redundant listing
  contents.Select(...)

Overall Evaluation

The overall structure of the code seems organized, with logical breaks in method implementations. However, issues in maintaining consistent style and handling nullable references should be addressed. Streamlining code readability and ensuring initialization aligns with nullability intentions will enhance the maintainability. Finally, regular application of formatting tools and code review processes can further improve code quality.

[GGHansome]

Auto Review Result:

Code Review Summary

Change Overview: The main objective of the code changes is to enhance the flexibility of setting default values, updating dependency injection registrations, and implementing new functionalities related to real-time chat and AI service providers.

Identified Issues

Issue 1: Nullable Reference Types [Best Practice]

• Description: The code changes involve making properties nullable without thorough checks on handling these null cases later in the application (e.g., FunctionParametersDef).
• Suggestion: Ensure every point of access to these now nullable properties includes a proper null check or default value assignment to prevent possible null reference exceptions.
• Example:

  // Before change
  public FunctionParametersDef Parameters { get; set; } = new FunctionParametersDef();
  // Suggested
  public FunctionParametersDef? Parameters { get; set; } = new FunctionParametersDef();
  
  // Ensure null checks wherever Parameters is used
  if (Parameters != null)
  {
      // Use parameters
  }
  ``

Issue 2: Inconsistency in Formatting [Formatting]

• Description: Code formatting appears inconsistent, with some lines having unnecessary new lines or incorrect indentation.
• Suggestion: Utilize a consistent linting tool to enforce a uniform code style throughout the project for improved readability.
• Example: No specific code change as it involves the whole file consistency.

Issue 3: Performance Consideration [Performance]

• Description: The method PrepareOptions can benefit from performance improvements by avoiding unnecessary object creation for JSON serialization/deserialization.
• Suggestion: Investigate ways to streamline JSON operations, possibly by using preconfigured options or object pooling strategies if serialization is performance-critical.

Overall Evaluation

The code appears to integrate significant improvements, especially in handling real-time and streaming functionalities in AI systems. However, attention to detail in handling potential null references and consistent coding standards is essential to ensure long-term maintainability and robustness. Employing static analysis tools could catch these before runtime, enhancing developer productivity and application stability.

[Oceania2018]

GoogleAiSettings settings

[Oceania2018]

What's this solution for?

[Oceania2018]

[Oceania2018]

Set Provider and Model, Start with BotSharp.Test.RealtimeVoice to test,
But it disconnect immediately. Can you help take a look? @gunpal5

"RealtimeModel": {
  "Provider": "google-ai",
  "Model": "gemini-2.0-flash-live-001",
  "InputAudioFormat": "pcm16",
  "OutputAudioFormat": "pcm16",
  "InterruptResponse": false
}