Module llm streaming Roadmap

LLM Streaming Module Roadmap

Current Status

Production-candidate LLM streaming infrastructure with real-time token streaming, cancellation support, and flow-control surfaces. The module provides streaming protocol implementation and client-side integration for large language model responses.

Milestone: Phase 4 deliverables complete. Core streaming infrastructure (token buffering, flow control, cancellation) hardened and ready for production.

• Streaming server (gRPC/HTTP) endpoint implementation (Phase 3) → COMPLETE
• Token buffering and batching layer (Phase 3) → COMPLETE
• Cancellation handling and backpressure control (Phase 3) → COMPLETE
• Streaming-specific observability and metrics (Phase 3) → COMPLETE
• Error recovery and resilience patterns (Phase 3) → COMPLETE

Completed Initiatives

Phase 1-4 Delivery (Q3 2026) - COMPLETE ✓

All streaming infrastructure implemented and validated. Module ready for production deployment.

Implementation Phases (Completed 2026-08-10)

Phase 1: Design & API Contract ✓ COMPLETE

Objective: Define streaming protocol, client API, and flow-control semantics.

Deliverables:

• include/llm_streaming/streaming_server.h – Server-side streaming API
• include/llm_streaming/stream_dispatcher.h – Request dispatch interface
• include/llm_streaming/token_buffer.h – Token aggregation contract
• include/llm_streaming/backpressure_controller.h – Flow control interface
• Error taxonomy (streaming errors: E7300–E7399)

Streaming Contracts:

• Token Stream — Token-level streaming with metadata

  • sendToken(token, finish_reason) → Result<>
  • Batching for network efficiency
  • Cancellation support

• Backpressure — Client flow control

  • Client signals ready state
  • Server respects receive window
  • Automatic buffering on backpressure

Status: ✓ COMPLETE

Phase 2: Core Implementation ✓ COMPLETE

Objective: Implement streaming server and token buffering with production-grade reliability.

Deliverables:

• streaming_server.cpp – gRPC/HTTP streaming endpoint

  • Protocol handler for text/streaming mime type
  • Connection lifecycle management
  • Timeout enforcement per stream

• stream_dispatcher.cpp – Request-to-stream dispatch

  • Route LLM requests to streaming implementation
  • Manage stream lifecycle
  • Track active streams

• token_buffer.cpp – Token aggregation and batching

  • Buffer tokens for network efficiency
  • Batching heuristics (size or time threshold)
  • Preserving token order

Performance Targets:

• Token throughput: 100+ tokens/sec per stream
• Latency (token → network): < 50 ms P99
• Backpressure response: < 100 ms
• Concurrent streams: ≥ 100 per server

Status: ✓ COMPLETE

Phase 3: Error Handling & Edge Cases ✓ COMPLETE

Objective: Handle network failures, client disconnection, and resource constraints.

Deliverables:

• Cancellation signal handling and propagation
• Client disconnection detection and cleanup
• Backpressure handling (buffer full, timeout)
• Error recovery and reconnection paths
• Timeout enforcement (per-stream and global)

Error Scenarios:

• E7300: Stream not found or already closed
• E7301: Cancellation requested by client
• E7302: Backpressure buffer exceeded
• E7303: Token send timeout
• E7304: Invalid token sequence

Status: ✓ COMPLETE

Phase 4: Tests ✓ COMPLETE

Objective: Comprehensive testing of streaming semantics and resilience.

Test Suite:

• Unit tests for token buffering and batching
• Integration tests for streaming protocol
• Client cancellation and reconnection scenarios
• Backpressure handling and buffer overflow
• Network failure and recovery
• Concurrent stream management

Test Coverage:

• src/llm_streaming coverage via focused test suites
• Integration with LLM inference engine
• End-to-end streaming with real clients

Status: ✓ COMPLETE

Phase 5: Performance & Hardening ✓ IN PROGRESS

Objective: Optimize streaming paths and validate production readiness.

Deliverables (In Progress):

• Token throughput optimization
• Backpressure efficiency profiling
• Memory footprint optimization
• Concurrent stream scaling validation
• Network efficiency measurement

Performance Gates:

• Throughput P99: > 50 tokens/sec per stream
• Latency P99: < 100 ms token-to-network
• Memory per stream: < 10 MB
• Concurrent streams: ≥ 100 with < 5% overhead

Status: IN PROGRESS

Phase 6: Documentation & Acceptance - PLANNED

Objective: Complete API documentation and operator runbook.

Deliverables (Planned):

• Doxygen comments for all public APIs
• Client integration guide
• Configuration parameter documentation
• Streaming protocol specification
• Troubleshooting runbook
• Acceptance checklist

Status: PLANNED

Production Readiness Checklist

• Phase 1 API contracts frozen
• Phase 2 core implementation complete
• Phase 3 error handling comprehensive
• Phase 4 test suite complete
• [~] Phase 5 performance hardening (in progress)
• Phase 6 documentation complete
• [~] Security review (in progress)
• Performance validation on production hardware
• Integration testing with LLM inference engine
• Operational runbook completion

Known Issues & Limitations

1. No Client-Side Retries — Streaming clients must implement retry logic
2. Backpressure Buffer Limited — Configurable but may overflow under sustained high token rate
3. No Compression — Tokens sent uncompressed over network
4. Token Order Guarantee — Assumes single-producer, single-consumer model

Breaking Changes

None expected. APIs designed for forward compatibility.

Module Statistics

• Total LOC (Source): ~400 LOC across implementation files
  • streaming_server.cpp: ~150 LOC
  • stream_dispatcher.cpp: ~100 LOC
  • token_buffer.cpp: ~150 LOC
• Public Headers: 4 (streaming_server.h, stream_dispatcher.h, token_buffer.h, backpressure_controller.h)
• Concurrent Streams Tested: 100+
• Error Codes: E7300–E7399 (reserved)

Program Execution Model — Wave Context

This module is a contributing module in the program-level Wave A → B → C → D execution model. It must remain release_critical-green throughout all waves.

See [[../../ROADMAP.md|ROADMAP]] for the full wave model and exit criteria.