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docs: Removed MemGPT (#1577)

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Signed-off-by: Anush008 <anushshetty90@gmail.com>
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Anush
2025-04-16 21:34:51 +05:30
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qdrant-landing/content/documentation/frameworks/_index.md
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title: Frameworks title: Frameworks
weight: 20 weight: 20
partition: build partition: build
aliases: ["/documentation/frameworks/memgpt/"]
--- ---
## Framework Integrations ## Framework Integrations
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| [Mastra](/documentation/frameworks/mastra/) | Typescript framework to build AI applications and features quickly. | | [Mastra](/documentation/frameworks/mastra/) | Typescript framework to build AI applications and features quickly. |
| [Mirror Security](/documentation/frameworks/mirror-security/) | Python framework for vector encryption and access control. | | [Mirror Security](/documentation/frameworks/mirror-security/) | Python framework for vector encryption and access control. |
| [Mem0](/documentation/frameworks/mem0/) | Self-improving memory layer for LLM applications, enabling personalized AI experiences. | | [Mem0](/documentation/frameworks/mem0/) | Self-improving memory layer for LLM applications, enabling personalized AI experiences. |
| [MemGPT](/documentation/frameworks/memgpt/) | System to build LLM agents with long term memory & custom tools |
| [Neo4j GraphRAG](/documentation/frameworks/neo4j-graphrag/) | Package to build graph retrieval augmented generation (GraphRAG) applications using Neo4j and Python. | | [Neo4j GraphRAG](/documentation/frameworks/neo4j-graphrag/) | Package to build graph retrieval augmented generation (GraphRAG) applications using Neo4j and Python. |
| [Pandas-AI](/documentation/frameworks/pandas-ai/) | Python library to query/visualize your data (CSV, XLSX, PostgreSQL, etc.) in natural language | | [Pandas-AI](/documentation/frameworks/pandas-ai/) | Python library to query/visualize your data (CSV, XLSX, PostgreSQL, etc.) in natural language |
| [Ragbits](/documentation/frameworks/ragbits/) | Python package that offers essential "bits" for building powerful Retrieval-Augmented Generation (RAG) applications. | | [Ragbits](/documentation/frameworks/ragbits/) | Python package that offers essential "bits" for building powerful Retrieval-Augmented Generation (RAG) applications. |
qdrant-landing/content/documentation/frameworks/memgpt.md
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title: MemGPT
---
# MemGPT
[MemGPT](https://memgpt.ai/) is a system that enables LLMs to manage their own memory and overcome limited context windows to
- Create perpetual chatbots that learn about you and change their personalities over time.
- Create perpetual chatbots that can interface with large data stores.
Qdrant is available as a storage backend in MemGPT for storing and semantically retrieving data.
## Usage
#### Installation
To install the required dependencies, install `pymemgpt` with the `qdrant` extra.
```sh
pip install 'pymemgpt[qdrant]'
```
You can configure MemGPT to use either a Qdrant server or an in-memory instance with the `memgpt configure` command.
#### Configuring the Qdrant server
When you run `memgpt configure`, go through the prompts as described in the [MemGPT configuration documentation](https://memgpt.readme.io/docs/config).
After you address several `memgpt` questions, you come to the following `memgpt` prompts:
```console
? Select storage backend for archival data: qdrant
? Select Qdrant backend: server
? Enter the Qdrant instance URI (Default: localhost:6333): https://xyz-example.eu-central.aws.cloud.qdrant.io
```
You can set an API key for authentication using the `QDRANT_API_KEY` environment variable.
#### Configuring an in-memory instance
```console
? Select storage backend for archival data: qdrant
? Select Qdrant backend: local
```
The data is persisted at the default MemGPT storage directory.
## Further Reading
- [MemGPT Examples](https://github.com/cpacker/MemGPT/tree/main/examples)
- [MemGPT Documentation](https://memgpt.readme.io/docs/index).