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Code formatting (#2153)

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Dev Khant
2025-01-16 12:33:56 +05:30
committed by GitHub
parent e12273c7cb
commit a4b085553a
4 changed files with 33 additions and 37 deletions
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docs/components/vectordbs/dbs/pgvector.mdx
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@@ -30,7 +30,7 @@ Here's the parameters available for configuring pgvector:
| Parameter | Description | Default Value |
| --- | --- | --- |
| `dbname` | The name of the database | `postgres` |
| `dbname` | The name of the | `postgres` |
| `collection_name` | The name of the collection | `mem0` |
| `embedding_model_dims` | Dimensions of the embedding model | `1536` |
| `user` | User name to connect to the database | `None` |

2
docs/features.mdx
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@@ -44,8 +44,6 @@ Mem0's memory implementation for Large Language Models (LLMs) offers several adv
- **Entity Relationships**: Mem0 can understand and relate entities across different interactions, unlike RAG which retrieves information from static documents. This leads to a deeper understanding of context and relationships.
- **Recency, Relevancy, and Decay**: Mem0 uses custom search algorithms to prioritize recent interactions and gradually forgets outdated information, ensuring the memory remains relevant and up-to-date for more accurate responses.
- **Contextual Continuity**: Mem0 retains information across sessions, maintaining continuity in conversations and interactions, which is essential for long-term engagement applications like virtual companions or personalized learning assistants.
- **Adaptive Learning**: Mem0 improves its personalization based on user interactions and feedback, making the memory more accurate and tailored to individual users over time.