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Release History

[0.3.0b1] (Unreleased)

Features Added

  • Write-time in-place deduplication: near-duplicate memories fold into the existing record (same id, newer content) instead of creating a new doc. See PR:#26
  • Reconciliation now resolves contradictions only, soft-deleting the loser with superseded_by; get_memory_history() walks that chain. See PR:#26

Bugs Fixed

  • Fixed a re-extraction loop that re-extracted the whole conversation every cycle (turns were never stamped extracted_at when vector dedup was on). See PR:#26

Other Changes

  • Reworked the extraction prompt (anti-inference, preserve specifics, topic-grouped memories) and simplified the schema to fact/episodic with fixed fact categories. See PR:#26
  • Token-bounded extraction batches with per-batch failure isolation; embedding inputs truncated to the model token budget. See PR:#26

[0.2.0b3] (2026-07-08)

Features Added

  • A custom user-agent can now be supplied via the new user_agent constructor argument on CosmosMemoryClient and AsyncCosmosMemoryClient. The toolkit's own user-agent (azsdk-python-cosmos-agent-memory/<version>) is always sent to Azure Cosmos DB so usage can be tracked; when a custom value is provided it is prefixed and the toolkit's user-agent is suffixed behind it ("<custom> <toolkit>"). See PR:#30
  • Per-turn processing cadence can now be set in-process via the new cadence_thresholds constructor argument on CosmosMemoryClient and AsyncCosmosMemoryClient, instead of only through environment variables. Pass a mapping keyed by the same names as the env vars (e.g. FACT_EXTRACTION_EVERY_N, DEDUP_EVERY_N, THREAD_SUMMARY_EVERY_N, USER_SUMMARY_EVERY_N); any key not present falls back to the environment/defaults, and None preserves today's env-only behavior. See PR:#29

[0.2.0b2] (2026-07-01)

Features Added

  • Embeddings and chat clients can now be injected via the new embeddings_client and chat_client constructor arguments on CosmosMemoryClient and AsyncCosmosMemoryClient. See PR:#27

[0.2.0b1] (2026-06-30)

Features Added

  • Raw conversation turns can now be embedded and vector-searched. Set enable_turn_embeddings=True (env ENABLE_TURN_EMBEDDINGS) to generate an embedding when each turn is written, then call search_turns() (sync and async, on both the client and store) to semantically search the raw turn log. See PR:#22

Other Changes

  • The memories container's vector index type is now configurable instead of being hard-coded to diskANN. Set it via the vector_index_type argument to create_memory_store(...) or the AI_FOUNDRY_EMBEDDING_VECTOR_INDEX_TYPE environment variable. See PR:#24
  • ai_foundry_endpoint now accepts a project-scoped Azure AI Foundry URL (https://<resource>.services.ai.azure.com/api/projects/<name>) in addition to the account-level inference endpoint. See PR:#23

[0.1.0b2] (2026-06-03)

Bugs Fixed

  • Hardened memory extraction: stops emitting phantom/synthesized facts the user never asserted, stops extracting facts from [assistant]: turns, stops re-processing already-extracted turns (which previously produced reversed CONTRADICT decisions and meta-facts like "X is contradicted by Y"), and stops storing near-duplicate episodic memories for the same scope. Episodic memories also now embed the actual content instead of a boilerplate "intent recorded" string. See PR:#20
  • Fixed add_cosmos + process_now silently bypassing the cadence subsystem: cadence env vars (THREAD_SUMMARY_EVERY_N, FACT_EXTRACTION_EVERY_N, USER_SUMMARY_EVERY_N, etc.) had no effect, and procedural / user-summary synthesis never ran. add_cosmos now triggers cadence on turn writes; process_now now runs the full 5-step pipeline on the in-process processor.See PR:#20

Other Changes

  • ProcessThreadResult gains procedural and user_summary fields. extract_memories returns a dropped_episodic_count for monitoring LLM-extraction quality.See PR:#20

[0.1.0b1] — 2026-06-01

Initial public preview release.

This is a beta release. The public surface may evolve in backward-incompatible ways before the 1.0.0 general-availability cut. Pin a specific version when integrating.

Added

  • Sync (CosmosMemoryClient) and async (AsyncCosmosMemoryClient) clients for storing, retrieving, and transforming agent memories backed by Azure Cosmos DB.
  • Typed memory record hierarchy (Pydantic): TurnRecord, FactRecord, EpisodicRecord, ProceduralRecord, ThreadSummaryRecord, UserSummaryRecord.
  • Vector + full-text + hybrid search over memories with metadata filters, tag filters, and per-type scoping.
  • Built-in memory processing pipeline: fact extraction, thread/user summarization, procedural-memory synthesis, contradiction handling, and deduplication — all driven by versioned .prompty prompts.
  • Two processor backends: InProcessProcessor (default, runs in your application process) and DurableFunctionProcessor (offloads work to a sibling Azure Function app via Cosmos DB change feed).
  • One-command azd up deployment that provisions Cosmos DB (with vector + full-text search enabled), Azure AI Foundry (chat + embedding deployments), Azure Function app (Flex Consumption), Storage, App Insights, and the User-Assigned Managed Identity wiring all of it together.
  • Focused exception hierarchy: AgentMemoryError, ConfigurationError, ValidationError, CosmosNotConnectedError, CosmosOperationError, MemoryNotFoundError, MemoryTypeMismatchError, LLMError.
  • Structured JSON logging via azure.cosmos.agent_memory.logging (configure_logging, JsonFormatter).

Package layout

  • Distribution name: azure-cosmos-agent-memory (PyPI)
  • Import path: azure.cosmos.agent_memory