Bug fixes:
- Replace bare except handlers with specific exception types and logging
in proxy/server.py (6 instances for CCR, SSE parsing, cost tracking)
- Fix session_id filtering security bug in memory/backends/local.py
(sessions were not properly isolated in vector search)
New tests (344 total):
- test_ccr_batch_processor.py: 51 tests for batch result processing
- test_compression_store.py: 76 tests for compression cache
- test_log_compressor.py: 47 tests for log format detection/compression
- test_search_compressor.py: 48 tests for grep output compression
- test_integrations/langchain/: 122 tests for LangChain integration
(agents, memory, retriever, streaming)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Phase 2 - Progressive Summarization:
- Add ProgressiveSummarizer with callback pattern for external summarization
- Add AnchoredSummary for tracking which message positions were summarized
- Add SummarizationResult for tracking summarization operations
- Add extractive_summarizer fallback when no LLM callback provided
- Integrate CCR for storing originals and enabling retrieval
- Add SUMMARIZE strategy to IntelligentContextManager
- Add comprehensive tests (59 total for intelligent context)
Agno Integration Fix:
- Add _ensure_message_objects() to convert dicts to Agno Message objects
- Fix response(), response_stream(), aresponse(), aresponse_stream() to
ensure messages are Message objects before calling super()
- Update test mocks to use proper ModelResponse and Metrics objects
- All 66 Agno tests now pass
- Fix HeadroomAgnoModel to properly extend agno.models.base.Model as a dataclass
- Implement required abstract methods (invoke, ainvoke, invoke_stream, ainvoke_stream)
- Add type: ignore comments for method signature overrides
- Fix mypy errors in telemetry/models.py and telemetry/toin.py
- Add real Ollama integration tests for both Agno and LangChain (no API keys needed)
- Add ollama and langchain-ollama to dev dependencies for local testing
- Update existing tests to use new HeadroomAgnoModel API
- HeadroomAgnoModel: Drop-in wrapper for any Agno model with automatic
context optimization
- HeadroomPreHook/HeadroomPostHook: Agent-level hooks for tracking
optimization metrics across tool calls
- Provider detection for Agno models (OpenAI, Anthropic, Google, etc.)
- Full test coverage for model wrapper and hooks
