dinomem-crewai

CrewAI integration for DinoMem. Ships two pre-built tools that match the shape of CrewAI's built-in RecallMemoryTool / RememberTool — agents get hybrid retrieval (semantic + keyword + graph), multi-agent scoping, and Postgres-native storage with one config object.

pip install dinomem-crewai

Quick start

from crewai import Agent, Crew, Task
from dinomem_crewai import DinoMemConfig, create_dinomem_tools

config = DinoMemConfig(
    api_key="sk-...",
    agent_id="support-bot",
    scope="team",         # optional default
)

support = Agent(
    role="Support specialist",
    goal="Help customers and remember what they prefer.",
    backstory="...",
    tools=create_dinomem_tools(config),
)

crew = Crew(agents=[support], tasks=[Task(...)])
crew.kickoff()

The agent now has two tools — Search memory and Save to memory — that hit DinoMem instead of the local LanceDB/Mem0 default.

Tools

Both match CrewAI's built-in shape (name, description, args_schema), so agents pick them automatically — you don't have to retrain on tool descriptions.

Helpers (without tools)

For custom flows — pre-search before a task starts, post-extract facts after a run, etc.:

from dinomem_crewai import add_memory, recall_memories, search_memories

await_text = recall_memories("what does this customer prefer?", config)
# → "Relevant memories...\n- (score=0.85) ..."

hits = search_memories("escalation policy", config)
# → list[MemoryHit]

add_memory("Customer prefers email over phone.", config)

Config reference

Comparison

CrewAI's built-in memory uses LanceDB (or Mem0 if configured). This package gives you DinoMem's Postgres-native, multi-agent-aware memory layer through the same tool interface — no Memory rewrite, no separate storage layer.

License

Apache-2.0