The error handling logic within the try-catch block is duplicated in several places, such as in generateContent and the onError handlers of generateStreamingContent. To improve maintainability and reduce code duplication, consider extracting this logic into a private helper method.

For example:

private <T> Flowable<T> handleError(SpringAIObservabilityHandler.RequestContext context, Throwable e) {
    observabilityHandler.recordError(context, e);
    SpringAIErrorMapper.MappedError mappedError = SpringAIErrorMapper.mapError(e);
    return Flowable.error(new RuntimeException(mappedError.getNormalizedMessage(), e));
}

The assertion assertThat(events).hasSizeGreaterThanOrEqualTo(1); is too weak for an integration test. It only confirms that at least one event was produced. To make this test more meaningful, you should add more specific assertions. For example, you could verify that a function call event was generated for getWeatherInfo and that the final response contains content from the tool's execution.

A function call must have a name to be valid. Using orElse("") can hide an invalid state where the name is missing, potentially leading to runtime errors downstream. It would be safer to throw an exception if the name is not present, ensuring consistency with how function responses are handled.

                functionCall.name().orElseThrow(() -> new IllegalStateException("Function call name is missing")),

The spring-ai.version in the "Complete Example pom.xml" is 1.1.0-M2, which is inconsistent with the version 1.1.0-M3 used in the "Basic Setup" example and the module's actual pom.xml. Please update this example to use 1.1.0-M3 for consistency.

This block for handling stopSequences can be simplified and made more idiomatic by using Java's Optional stream features. This improves readability and conciseness.

    contentConfig.stopSequences()
        .filter(sequences -> !sequences.isEmpty())
        .ifPresent(optionsBuilder::stopSequences);

The logic for creating ToolCallingChatOptions by manually copying properties is verbose and can be simplified. Using ToolCallingChatOptions.from(chatOptions) provides a much cleaner and more maintainable way to achieve the same result.

Using orElseThrow() without a supplier is a deprecated practice since Java 10 and can have minor performance implications as the exception is created eagerly. It's better to use the orElseThrow(Supplier) variant to create the exception lazily.

                    functionResponse.name().orElseThrow(() -> new IllegalStateException("Function response name is missing")),
                    toJson(functionResponse.response().orElseThrow(() -> new IllegalStateException("Function response body is missing"))));

The exceptions in extractTokenCount, extractInputTokenCount, and extractOutputTokenCount are silently ignored. This can make debugging difficult if there's an issue with parsing token usage from the model's response, as the error would be completely hidden. It's better to log these exceptions at a WARN or DEBUG level. You'll need to add a Logger field to the class to implement this.

The logic for extracting token usage could fail if the response metadata is missing or has an unexpected format. For improved robustness and consistency with the SpringAI class, it's advisable to wrap this token extraction logic in a try-catch block and log any exceptions that occur.

        .doOnSuccess(
            response -> {
              // Extract token usage if available
              int totalTokens = 0;
              try {
                if (response.getMetadata() != null && response.getMetadata().getUsage() != null) {
                  totalTokens = response.getMetadata().getUsage().getTotalTokens();
                }
              } catch (Exception e) {
                // Consider adding a logger to the class and logging this exception, e.g.:
                // logger.warn("Could not extract token count from embedding response metadata.", e);
              }
              observabilityHandler.recordSuccess(context, totalTokens, totalTokens, 0);
            })

StringBuffer is thread-safe, but its use here is redundant because all access to textAccumulator is already protected by a ReadWriteLock. Using a non-synchronized StringBuilder would be more performant in this context.

The current implementation drops the tool call ID when converting from a Spring AI AssistantMessage.ToolCall to an ADK Part. The ID is crucial for correctly associating tool responses with their corresponding calls, especially in multi-turn scenarios. Losing it can lead to incorrect behavior. The Part should be constructed with a FunctionCall object that includes the ID to ensure proper tracking.

          Map<String, Object> args =
              objectMapper.readValue(toolCall.arguments(), MAP_TYPE_REFERENCE);
          FunctionCall adkFunctionCall = FunctionCall.builder()
              .name(toolCall.name())
              .args(args)
              .id(toolCall.id())
              .build();
          parts.add(Part.fromFunctionCall(adkFunctionCall));

The project uses a milestone version (1.1.0-M3) of Spring AI. While this might be necessary for new features, it introduces a potential risk for consumers of this library, as milestone releases can have breaking changes and are not considered stable. It would be beneficial to either switch to a stable release if one that meets the requirements is available, or to add a comment here clarifying why this specific milestone version is necessary.

Using orElse("") for a missing FunctionResponse ID can hide potential issues and lead to silent failures, as the ID is essential for matching a tool's response to its original call. To improve robustness and align with the stricter handling of FunctionCall IDs, consider using orElseThrow() to ensure that a tool response always includes an ID.

The extractModelName method here provides a very basic fallback for determining the model name, which is inconsistent with the more robust, reflection-based approach used in SpringAIAutoConfiguration. To ensure consistent behavior for both auto-configured and manually instantiated SpringAI clients, the more advanced logic from SpringAIAutoConfiguration.extractModelNameFromInstance() should be centralized here or in a shared utility. This would make manual instantiation more reliable.

StringBuffer is used for textAccumulator, which is a legacy thread-safe class. Since all access to this field is already synchronized using a ReadWriteLock, you can replace it with the more modern and generally more performant StringBuilder without compromising thread safety.

A new ObjectMapper is instantiated within the lambda for every tool execution. This is inefficient and can impact performance, especially with frequent tool calls. It's better to create a single ObjectMapper instance and reuse it. Consider passing the ObjectMapper from MessageConverter into ToolConverter's constructor and storing it as a field.