Spring AI: Streaming Tool Calls & Observation Context Issue
In the realm of Spring AI, a perplexing issue arises when dealing with streaming tool calls, specifically within the ObservationContext. This article delves into the intricacies of the problem, offering a comprehensive understanding and potential solutions. The core issue revolves around the absence of a parent-child inheritance relationship between ChatClientObservationContext and ToolCallingObservationContext during Flux streaming requests. This absence hinders the propagation of crucial indicators, such as spring.ai.chat.client.conversation.id, which is vital for tracking conversations. This article aims to explore the root cause of this problem and provide potential solutions for Spring AI developers.
Understanding the Problem: Streaming Tool Calls in Spring AI
When working with Spring AI and streaming requests, the ChatClientObservationContext and ToolCallingObservationContext do not maintain a parent-child relationship. This is likely due to the multithreaded nature of Flux streams. The absence of this relationship creates a challenge: the ChatClientObservationContext holds an essential indicator, the spring.ai.chat.client.conversation.id, which is crucial for tracking and managing conversations. Ideally, this ID should be accessible within the ToolCallingObservationContext to maintain context throughout the tool call process. However, in Spring AI version 1.1.0, this propagation doesn't occur automatically, creating a gap in observation data. Understanding the nuances of this issue is crucial for developers aiming to build robust and context-aware AI applications with Spring. The key to addressing this lies in finding a way to bridge the gap between the chat context and the tool call context within the streaming environment.
The Significance of spring.ai.chat.client.conversation.id
The spring.ai.chat.client.conversation.id serves as a unique identifier for each conversation, enabling developers to trace the flow of interactions and maintain context across multiple exchanges. When a tool call is made within a conversation, it's essential to associate that tool call with the correct conversation ID. This ensures that the tool's actions are correctly attributed and that the overall conversation history remains coherent. Without this ID, it becomes challenging to analyze the behavior of tool calls within specific conversations, potentially hindering debugging and performance optimization efforts. Therefore, ensuring the availability of the conversation ID within the ToolCallingObservationContext is paramount for building comprehensive observability into Spring AI applications.
Contrasting Behavior: Streaming vs. Call Requests
Interestingly, this issue is specific to Flux streaming requests. In contrast, when using the call request method, a parent-child relationship does exist between ChatClientObservationContext and ToolCallingObservationContext. This allows developers to easily access the parent ChatClientObservationContext and retrieve the spring.ai.chat.client.conversation.id. This discrepancy highlights the complexities introduced by asynchronous streaming and the need for a tailored solution. The synchronous nature of the call request simplifies context propagation, while the asynchronous nature of Flux streams requires a more deliberate approach to ensure context is maintained across different stages of processing. This difference in behavior underscores the importance of understanding the underlying execution model when designing observability solutions for Spring AI applications.
Code Example and Analysis
Let's examine the provided code snippet to understand the problem in more detail.
public static ChatClientObservationContext findParentClientContext(Observation.ContextView ctx) {
if (ctx == null) {
return null;
}
try {
ObservationView current = ctx.getParentObservation();
while (current != null) {
Observation.ContextView parentCtx = current.getContextView();
if (parentCtx instanceof ChatClientObservationContext clientCtx) {
return clientCtx;
}
current = parentCtx.getParentObservation();
}
}catch (Throwable ignore) {
}
return null;
}
public class ToolObservationHandler implements ObservationHandler<ToolCallingObservationContext> {
@Override
public void onStop(ToolCallingObservationContext context) {
ChatClientObservationContext clientCtx = findParentClientContext(context);
// note: for flux streaming request, clientCtx will always be null
if (clientCtx != null) {
String conversationId = Optional.ofNullable(
clientCtx.getHighCardinalityKeyValue(
ChatClientObservationDocumentation.HighCardinalityKeyNames.CHAT_CLIENT_CONVERSATION_ID.asString()))
.map(KeyValue::getValue)
.orElse("");
}
}
}
// flux streaming request
public Flux<String> flux(String message, Long chatId) {
AtomicBoolean hasSentSeparator = new AtomicBoolean(false);
return chatClient
.prompt(promptService.getDefault())
.user(message)
.toolCallbacks(toolCallbackProvider.getToolCallbacks())
.tools(localToolsService)
.advisors(a -> a.param(ChatMemory.CONVERSATION_ID, "abc-1"))
.stream()
.content().contextWrite(ctx -> ctx.put(ChatMemory.CONVERSATION_ID, "abc-1"));
}
// `call` request
public String chat(String message, Long chatId) {
return chatClient
.prompt(promptService.getDefault())
.user(message)
.toolCallbacks(toolCallbackProvider.getToolCallbacks())
.tools(localToolsService)
.advisors(a -> a.param(ChatMemory.CONVERSATION_ID, "abc-1"))
.call()
.content();
}
The findParentClientContext method attempts to traverse the observation context hierarchy to find the parent ChatClientObservationContext. However, as noted in the comments, this method returns null for Flux streaming requests. This is because the expected parent-child relationship is absent. The ToolObservationHandler relies on this method to retrieve the conversation ID, which consequently fails for streaming scenarios. The code clearly demonstrates the disparity between streaming and call requests, highlighting the core of the problem. The flux method, representing the streaming request, showcases how the conversation ID is set using contextWrite, but this context is not automatically propagated to the ToolCallingObservationContext. In contrast, the chat method, representing the call request, implicitly propagates the context due to the inherent parent-child relationship between the observation contexts.
Analyzing the ToolObservationHandler
The ToolObservationHandler is designed to capture observation events related to tool calls. The onStop method is triggered when a tool call completes. Within this method, the code attempts to retrieve the ChatClientObservationContext using the findParentClientContext method. As we've established, this retrieval fails for Flux streaming requests, resulting in a null clientCtx. Consequently, the conversation ID cannot be extracted, leading to a loss of contextual information. This highlights the critical need for a mechanism to propagate the conversation ID to the ToolCallingObservationContext in streaming scenarios. Without this mechanism, it becomes challenging to correlate tool call events with specific conversations, hindering debugging and analysis.
Examining the Flux Streaming Request
The flux method demonstrates how a Flux stream is used to handle streaming requests. The contextWrite operator is used to attach the conversation ID to the context of the stream. However, this context is not automatically propagated to the ToolCallingObservationContext. This is a key point of the issue. The stream operates asynchronously, and the context is not implicitly carried over to the tool call execution. This necessitates a more explicit mechanism for context propagation. The stream() method initiates the asynchronous processing, and the subsequent tool calls occur within this asynchronous context, making it challenging to maintain the context established at the beginning of the stream.
Potential Solutions and Workarounds
Given the problem's nature, several approaches can be considered to address the missing context propagation in Flux streaming requests. Let's explore some potential solutions and workarounds.
1. Explicitly Propagating Context via Reactor Context
One approach involves explicitly propagating the conversation ID through the Reactor Context. This can be achieved by accessing the context within the tool call execution and manually passing the ID. This method ensures that the conversation ID is available within the ToolCallingObservationContext, even in the absence of a direct parent-child relationship. However, this approach requires modifying the tool call execution logic to access and propagate the context, which can be cumbersome.
2. Custom Observation Convention
Another approach is to create a custom ObservationConvention that captures the conversation ID from the ChatClientObservationContext and attaches it to the ToolCallingObservationContext. This requires implementing a custom convention that is aware of the conversation ID and can propagate it appropriately. This approach offers a more centralized and reusable solution, as the context propagation logic is encapsulated within the custom convention. However, it requires a deeper understanding of Spring's observation framework and the creation of custom components.
3. Utilizing ThreadLocal
A less recommended but potentially viable workaround is to use a ThreadLocal variable to store the conversation ID. Before initiating the tool call, the ID can be stored in the ThreadLocal, and then retrieved within the ToolCallingObservationContext. This approach is generally discouraged due to the potential for thread-related issues and context leakage. However, in certain scenarios, it might offer a quick and temporary solution. It's crucial to exercise caution when using ThreadLocal and ensure proper cleanup to avoid unintended side effects.
4. Spring AI Enhancement
The most robust solution would be an enhancement within Spring AI itself to automatically propagate the necessary context between ChatClientObservationContext and ToolCallingObservationContext in streaming scenarios. This would involve changes within the Spring AI framework to recognize and handle this context propagation automatically. This approach would provide the most seamless and maintainable solution for developers. However, it requires contributing to the Spring AI project or requesting this feature from the Spring AI team.
Conclusion
The issue of missing context propagation between ChatClientObservationContext and ToolCallingObservationContext in Spring AI Flux streaming requests presents a challenge for developers seeking comprehensive observability. While workarounds exist, such as explicitly propagating context or using custom observation conventions, the ideal solution lies in a Spring AI enhancement that automates this process. By understanding the nuances of the problem and exploring the potential solutions, developers can ensure that tool calls are correctly associated with their respective conversations, leading to more robust and insightful AI applications. Remember to always prioritize solutions that promote maintainability and clarity in your codebase.
For more information on Spring AI and related topics, visit the official Spring AI documentation. This resource provides valuable insights and guidance for building AI-powered applications with Spring.
