65 lines
1.9 KiB
Markdown
65 lines
1.9 KiB
Markdown
# Memora
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**Long-term memory for AI agents.**
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AI assistants forget everything between sessions. Memora fixes that with a memory system that handles temporal reasoning, entity connections, and personality-aware responses.
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## Why Memora?
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- **Temporal queries** — "What did Alice do last spring?" requires more than vector search
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- **Entity connections** — Knowing "Alice works at Google" + "Google is in Mountain View" = "Alice works in Mountain View"
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- **Agent opinions** — Agents form and recall beliefs with confidence scores
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- **Personality** — Big Five traits influence how agents process and respond to information
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## 5-Minute Setup
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### 1. Start the server
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```bash
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# Clone and start with Docker
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git clone https://github.com/anthropics/memora.git
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cd memora/docker
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./start.sh
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```
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Server runs at `http://localhost:8080`
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### 2. Install the Python client
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```bash
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pip install memora-client
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```
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### 3. Use it
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```python
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from memora_client import Memora
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client = Memora(base_url="http://localhost:8080")
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# Store memories
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client.store(agent_id="my-agent", content="Alice works at Google")
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client.store(agent_id="my-agent", content="Bob prefers Python over JavaScript")
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# Search memories
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results = client.search(agent_id="my-agent", query="What does Alice do?")
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for r in results:
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print(f"{r['text']} ({r['weight']:.2f})")
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# Generate personality-aware responses
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answer = client.think(agent_id="my-agent", query="Tell me about Alice")
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print(answer["text"])
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```
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## Documentation
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Full documentation: [memora-docs](./memora-docs)
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- [Architecture](./memora-docs/docs/developer/architecture.md) — How ingestion, storage, and retrieval work
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- [Python Client](./memora-docs/docs/sdks/python.md) — Full API reference
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- [API Reference](./memora-docs/docs/api-reference/index.md) — REST API endpoints
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- [Personality](./memora-docs/docs/developer/personality.md) — Big Five traits and opinion formation
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## License
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MIT
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