DSPy History

https://dspy.ai/api/primitives/History/

dspy.History primitive — typed field holding messages: list[dict] that slots into any Signature . No persistent memory of its own; purely a structured context-injection contract. DSPy's optimisation loop (MIPRO, BootstrapFewShot) treats historical turns as trainable few-shot structure.

Active · Verified 2026-10-22 · fresh as of 2026-10-22 · 45 cited facts, 6 with a third-party source · 2 recorded changes · Suggest a correction

At a glance

Tier
T3
Latest release
not applicable — not OSS fix
License
MIT repo fix
Freshness
2026-10-22 fix
Layer
agent-infra repo fix
Licensing
open-source repo fix
Deployment locus
local vendor fix
Platform vs product
platform vendor fix
SDK languages
python vendor fix

Memory taxonomy

storage
kv
retrieval
injection
persistence
session
update
read-only
unit
document
governance
inspectable
conflict
n/a

When to use

Optimised for: typed Signature-field history primitive

Anti-fit: not for non-DSPy programs

Pros & cons

Pros

Typed programming model means memory composes cleanly with prompts and optimizers.

Cons

DSPy's broader adoption is still emerging; more research-tilted than production-tilted.

Claims & capabilities

Open source. Official Mem0+DSPy tutorial.

Technical surface

API surface
not applicable — research paper
Backend storage
not applicable — research paper
Deployment
Both (OSS self-hosted; dspy.ai cloud services if applicable)
Embedding model
not applicable — research paper
Multi-tenancy
not applicable — research paper
MCP
searched not found
A2A
not supported
OpenTelemetry
via adapter — Arize Phoenix

Similar systems

Other framework-embedded memory in the catalog, ranked by inbound references.

  • Spring AI ChatMemory T3

    Wraps conversation memory behind an Advisor abstraction. MessageWindowChatMemory default 20-msg sliding window (preserves system messages); pluggable ChatMemoryRepository backends (in-memory, JDBC, Cassandra, Neo4j). Memory injected as cross-cutting concern at the ChatClient level.

  • Flowise Memory T1

    Discontinued: Flowise (acquired by Workday, Aug 2025) was sunset in 2026 — code freeze 2026-07-29, GitHub repo archived 2026-08-13, end of life 2026-08-31. Was a visual LangChain canvas with LangChain-native memory nodes (Buffer, Buffer Window, Conversation Summary Buffer) backed by an internal chat_message DB table; Buffer Window kept the last K interactions, Summary Buffer compressed older turns while keeping recent ones verbatim.

  • LangGraph Persistence T2

    Distinct from LangMem. Built-in checkpointer saves graph state per super-step (short-term, thread-scoped). Store System adds long-term hierarchical key-value memory across threads with optional vector search + TTL. Postgres / Mongo / Redis stores for production.

  • AutoGen Memory T2

    AutoGen's memory layer: ListMemory chronological context plus teachable agents that vectorise corrections; integrates with Mem0/Zep rather than building deep memory natively. Microsoft AutoGen is in maintenance mode (community managed, bug and security fixes only), and Microsoft points new projects to Microsoft Agent Framework.

  • CrewAI Memory T2

    Memory subsystem inside the CrewAI orchestration framework; integrates with Mem0 for the long-term tier.

  • Hermes Agent memory (Nous Research) T3

    Nous Research's open-source self-improving agent keeps an agent-curated MEMORY.md/USER.md notebook injected at session start, full-text (FTS5) search over past sessions that returns raw messages without LLM summarisation, and optional Honcho user modelling. one of the most-starred agent projects of 2026.

Sources (44 cited facts, 6 third-party)

Each fact links to the page it came from; the badge says who published it (how to read sources).

What changed

Changes to this record's lifecycle, licence, release, pricing and hosting facts, from the catalog's git history. Subscribe (Atom)

  1. 2026-10-23
    • Funding / ownership “Stanford NLP academic project (Hazy Research group); Omar Khattab also affiliated with Databricks; dspy.ai commerci…” → “Stanford NLP academic project (Hazy Research group); Omar Khattab also affiliated with Databricks” source
    #223
  2. 2026-10-22
    • License “not applicable — not OSS” → “MIT” source
    #195

Related systems

References (1)

  • Mem0 integrates with — Official Mem0+DSPy tutorial.