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@@ -51,6 +51,22 @@ From PyPI
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pip install altk-evolve
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```
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**Optional Backend Dependencies:**
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The default filesystem backend uses simple text matching and requires no additional dependencies. For semantic vector similarity search, install one of these backends:
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For PostgreSQL with pgvector support (recommended for production):
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```bash
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uv sync --extra pgvector
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```
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For Milvus support (optimized for large-scale vector search):
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```bash
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uv sync --extra milvus
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```
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See the [Backend Configuration Guide](docs/guides/backend-configuration.md) for detailed comparison and setup instructions.
-`create_entity(content: str, entity_type: str, metadata: str | None, enable_conflict_resolution: bool)`: Create a single entity in the namespace.
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-`delete_entity(entity_id: str)`: Delete a specific entity by its ID.
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### Filter Migration Note
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Entity search filters reserve bare keys for top-level schema columns only: `id`, `type`, `content`, and `created_at`.
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If you need to filter on JSON metadata, use the `metadata.<key>` form. For example, use `filters={"type": "trajectory", "metadata.task_id": "123"}` instead of `filters={"type": "trajectory", "task_id": "123"}`.
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Existing integrations that stored custom fields in entity metadata should update filter writers to add the `metadata.` prefix for those keys.
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## Features
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-**Proactive**: Learns how to recognize problems and their solutions, and generates guidelines that get automatically applied to new tasks.
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-**Conflict Resolution**: Update existing guidelines when new information contradicts them.
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If you’re experimenting with Evolve or exploring on‑the‑job learning for agents, feel free to open an issue or discussion to share use cases, ideas, or feedback.
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See the [Contributing Guide](CONTRIBUTING.md) to understand our development process, or how to submit changes, report bugs, or propose features.
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See the [Contributing Guide](CONTRIBUTING.md) to understand our development process, or how to submit changes, report bugs, or propose features.
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