implementing-chat-streaming
Skill124 starsChanged 7 months agoMITView on GitHub
Provides SSE streaming patterns for the chat API and frontend. Use when implementing or modifying chat streaming, handling SSE events, or troubleshooting message flow between frontend and backend.
In this repository20 other files it gives its agents.
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- committing-codeSkill
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The file
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1 rule. About 0 are common, 0 are distinctive, and 1 is very specific to this project.
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- Distinctive
- Very specific
- Very specific: line 92
If user cancels: CHAT_CANCEL_STREAM sets status to idle.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Chat Streaming Implementation
Backend: SSE Endpoint
app.MapPost("/api/chat/stream", async (
ChatRequest request,
AgentFrameworkService agentService,
HttpContext httpContext,
CancellationToken cancellationToken) =>
{
httpContext.Response.Headers.Append("Content-Type", "text/event-stream");
httpContext.Response.Headers.Append("Cache-Control", "no-cache");
var conversationId = request.ConversationId
?? await agentService.CreateConversationAsync(request.Message, cancellationToken);
// Send conversation ID first
await httpContext.Response.WriteAsync(
$"data: {{\"type\":\"conversationId\",\"conversationId\":\"{conversationId}\"}}\n\n",
cancellationToken);
await httpContext.Response.Body.FlushAsync(cancellationToken);
// Stream chunks
await foreach (var chunk in agentService.StreamMessageAsync(
conversationId, request.Message, request.ImageDataUris, cancellationToken))
{
var json = JsonSerializer.Serialize(new { type = "chunk", content = chunk });
await httpContext.Response.WriteAsync($"data: {json}\n\n", cancellationToken);
await httpContext.Response.Body.FlushAsync(cancellationToken);
}
await httpContext.Response.WriteAsync("data: {\"type\":\"done\"}\n\n", cancellationToken);
})
.RequireAuthorization("RequireChatScope");Backend: IAsyncEnumerable Service
Actual return type: IAsyncEnumerable<StreamChunk> (not raw strings)
Why direct SDK? Uses ProjectResponsesClient directly because we need typed access to MCP approvals, file search quotes, and citation annotations. See .github/skills/researching-azure-ai-sdk/SKILL.md for full rationale.
public async IAsyncEnumerable<StreamChunk> StreamMessageAsync(
string conversationId,
string message,
List<string>? imageDataUris = null,
[EnumeratorCancellation] CancellationToken cancellationToken = default)
{
ObjectDisposedException.ThrowIf(_disposed, this);
// Stream response - yields StreamChunk with text deltas OR annotations
await foreach (var update in responsesClient.CreateResponseStreamingAsync(...))
{
if (update is StreamingResponseOutputTextDeltaUpdate deltaUpdate)
{
yield return StreamChunk.Text(deltaUpdate.Delta);
}
else if (update is StreamingResponseOutputItemDoneUpdate itemDoneUpdate)
{
var annotations = ExtractAnnotations(itemDoneUpdate.Item, fileSearchQuotes);
if (annotations.Count > 0)
{
yield return StreamChunk.WithAnnotations(annotations);
}
}
}
}StreamChunk model (backend/WebApp.Api/Models/StreamChunk.cs):
IsText/TextDelta- Text contentHasAnnotations/Annotations- Citation metadata
Frontend: Action Flow
CHAT_SEND_MESSAGE
→ CHAT_ADD_ASSISTANT_MESSAGE
→ CHAT_START_STREAM
→ (repeat CHAT_STREAM_CHUNK)
→ CHAT_STREAM_ANNOTATIONS (optional, for citations)
→ CHAT_STREAM_COMPLETE (with usage metrics)If user cancels: CHAT_CANCEL_STREAM sets status to idle.
Frontend: ChatService Pattern
See: frontend/src/services/ChatService.ts
Key patterns:
- AbortController for cancellation
- EventSource or fetch with ReadableStream
- Parse SSE
data:lines - Dispatch actions for each event type
Image Validation
Backend limits (see AzureAIAgentService.cs):
- Max 5 images per request
- Max 5MB per image (decoded)
- Allowed:
image/png,image/jpeg,image/gif,image/webp
Frontend limits (see frontend/src/utils/fileAttachments.ts):
- Same limits with user-friendly error messages
- Toast notifications for validation feedback
Project-Specific: Full Endpoint Implementation
app.MapPost("/api/chat/stream", async (
ChatRequest request,
AgentFrameworkService agentService,
HttpContext httpContext,
IHostEnvironment env,
CancellationToken cancellationToken) =>
{
httpContext.Response.Headers.Append("Content-Type", "text/event-stream");
httpContext.Response.Headers.Append("Cache-Control", "no-cache");
var conversationId = request.ConversationId
?? await agentService.CreateConversationAsync(request.Message, cancellationToken);
await httpContext.Response.WriteAsync(
$"data: {{\"type\":\"conversationId\",\"conversationId\":\"{conversationId}\"}}\n\n",
cancellationToken);
await httpContext.Response.Body.FlushAsync(cancellationToken);
await foreach (var chunk in agentService.StreamMessageAsync(
conversationId, request.Message, request.ImageDataUris, cancellationToken))
{
var json = System.Text.Json.JsonSerializer.Serialize(new { type = "chunk", content = chunk });
await httpContext.Response.WriteAsync($"data: {json}\n\n", cancellationToken);
await httpContext.Response.Body.FlushAsync(cancellationToken);
}
await httpContext.Response.WriteAsync("data: {\"type\":\"done\"}\n\n", cancellationToken);
})
.RequireAuthorization("RequireChatScope")
.WithName("StreamChatMessage");Project-Specific: Service Implementation
See: backend/WebApp.Api/Services/AgentFrameworkService.cs
Key patterns in StreamMessageAsync:
- Disposal guard before processing
- Multi-modal message support (text + image data URIs)
IAsyncEnumerable<StreamChunk>with[EnumeratorCancellation]StreamingResponseOutputTextDeltaUpdatefor text contentStreamingResponseOutputItemDoneUpdatefor annotations- Collects file search quotes via
FileSearchCallResponseItemfor citation context - Usage captured from
StreamingResponseCompletedUpdate
Project-Specific: Frontend State Flow
CHAT_SEND_MESSAGE
→ CHAT_ADD_ASSISTANT_MESSAGE
→ CHAT_START_STREAM
→ (repeat CHAT_STREAM_CHUNK)
→ CHAT_STREAM_ANNOTATIONS (optional, for citations)
→ CHAT_STREAM_COMPLETE (with usage: promptTokens, completionTokens, totalTokens, duration)Cancel: CHAT_CANCEL_STREAM sets status to idle and re-enables input.
Error: CHAT_ERROR with AppError containing message, optional retry action, timestamp.
SSE Event Types
| Event Type | Payload | Description |
conversationId | { conversationId: string } | Sent first for new conversations |
chunk | { content: string } | Text delta from agent response |
annotations | { annotations: [...] } | Citations (uri_citation, file_citation, etc.) |
usage | { duration, promptTokens, completionTokens, totalTokens } | Token metrics |
done | {} | Stream complete |
error | { message: string } | Error occurred |
Project-Specific: Dev Logging
Each state change prints (dev only):
🔄 [HH:MM:SS] ACTION_TYPE
Action: { … }
Changes: { field: before → after }Related Skills
- writing-csharp-code - Backend coding standards and AgentFrameworkService patterns
- writing-typescript-code - Frontend React patterns and ChatService implementation
- troubleshooting-authentication - Token acquisition for authenticated streaming
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