| Name | memories-dev JSON |
| Version |
2.0.0
JSON |
| download |
| home_page | https://memories.dev |
| Summary | A Python package for managing and processing earth observation data |
| upload_time | 2025-02-18 17:40:56 |
| maintainer | None |
| docs_url | None |
| author | Memories-dev |
| requires_python | <3.14.0,>=3.9 |
| license | Apache License
Version 2.0, January 2004
http://www.apache.org/licenses/
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|
| keywords |
earth observation
data processing
memory management
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
torch
transformers
pillow
requests
pyyaml
python-dotenv
tqdm
pyarrow
mercantile
mapbox-vector-tile
pyproj
pystac
redis
nltk
diffusers
langchain
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duckdb
shapely
geopy
folium
rtree
aiohttp
fsspec
cryptography
pyjwt
pystac-client
planetary-computer
fastapi
netCDF4
earthengine-api
sentinelhub
typing-extensions
pydantic
uvicorn
python-multipart
landsatxplore
sentinelsat
osmnx
py6s
opencv-python
matplotlib
numpy
pandas
ipywidgets
scikit-learn
rasterio
geopandas
albumentations
faiss-cpu
sentence-transformers
xarray
dask
accelerate
scipy
noise
torch-scatter
torch-sparse
torch-cluster
torch-geometric
faiss-gpu
cupy-cuda12x
cudf
cuspatial
torch
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torchaudio
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torch-sparse
torch-cluster
torch-geometric
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pytest-timeout
black
flake8
mypy
isort
pre-commit
sphinx
sphinx-rtd-theme
sphinx-autodoc-typehints
nbsphinx
pandoc
|
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| coveralls test coverage |
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|
<div align="center">
# memories.dev
**Collective Memory for AGI**
[](https://memories-dev.readthedocs.io/index.html)
[](LICENSE)
[](https://www.python.org/downloads/)
[](https://github.com/psf/black)
[](https://github.com/Vortx-AI/memories-dev/releases/tag/v1.1.8)
[](https://discord.com/invite/7qAFEekp)
<a href="https://www.producthunt.com/posts/memories-dev?embed=true&utm_source=badge-featured&utm_medium=badge&utm_souce=badge-memories-dev" target="_blank"><img src="https://api.producthunt.com/widgets/embed-image/v1/featured.svg?post_id=879661&theme=light&t=1739530783374" alt="memories.dev - Collective AGI Memory | Product Hunt" style="width: 250px; height: 54px;" width="250" height="54" /></a>
</div>
## Overview
memories.dev is a memory infrastructure for providing real-world context to AI models during inference. It processes, indexes, and serves location-tagged intelligence ("memories") from multiple data sources including satellite imagery, climate sensors, and urban development metrics. These memories enhance AI models' understanding and reasoning capabilities with real-world context.
## System Architecture
## Quick Start
```python
from memories.models.load_model import LoadModel
from memories.core.memory import MemoryStore
from memories.agents.agent import Agent
# Initialize with advanced models
load_model = LoadModel(
use_gpu= True
model_provider= "deepseek-ai" #"deepseek" or "openai"
deployment_type= "local" #"local" or "api"
model_name= "deepseek-r1-zero" #"deepseek-r1-zero" or "gpt-4o" or "deepseek-coder-3.1b-base" or "gpt-4o-mini"
#api_key= #"your-api-key" optional for api deployment
)
# Create Earth memories
memory_store = MemoryStore()
memories = memory_store.create_memories(
model = load_model,
location=(37.7749, -122.4194), # San Francisco coordinates
time_range=("2024-01-01", "2024-02-01"),
artifacts={
"satellite": ["sentinel-2", "landsat8"],
"landuse": ["osm","overture"]
}
)
# Generate synthetic data
synthetic_data = vx.generate_synthetic(
base_location=(37.7749, -122.4194),
scenario="urban_development",
time_steps=10,
climate_factors=True
)
# AGI reasoning with memories
insights = Agent(
query="Analyze urban development patterns and environmental impact",
context_memories=memories,
synthetic_scenarios=synthetic_data
)
```
## Installation
### Basic Installation
```bash
pip install memories-dev
```
### Python Version Compatibility
The package supports Python versions 3.9 through 3.13. Dependencies are automatically adjusted based on your Python version to ensure compatibility.
### Installation Options
#### 1. CPU-only Installation (Default)
```bash
pip install memories-dev
```
#### 2. GPU Support Installation
For CUDA 11.8:
```bash
pip install memories-dev[gpu]
```
For different CUDA versions, install PyTorch manually first:
```bash
# For CUDA 12.1
pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu121
# Then install the package
pip install memories-dev[gpu]
```
#### 3. Development Installation
For contributing to the project:
```bash
pip install memories-dev[dev]
```
#### 4. Documentation Tools
For building documentation:
```bash
pip install memories-dev[docs]
```
### Version-specific Dependencies
The package automatically handles version-specific dependencies based on your Python version:
- Python 3.9: Compatible with older versions of key packages
- Python 3.10-3.11: Standard modern package versions
- Python 3.12-3.13: Latest package versions with improved performance
### Common Issues and Solutions
1. **Shapely Version Conflicts**
- For Python <3.13: Uses Shapely 1.7.0-1.8.5
- For Python ≥3.13: Uses Shapely 2.0+
2. **GPU Dependencies**
- CUDA toolkit must be installed separately
- PyTorch Geometric packages are installed from wheels matching your CUDA version
3. **Package Conflicts**
If you encounter dependency conflicts:
```bash
pip install --upgrade pip
pip install memories-dev --no-deps
pip install -r requirements.txt
```
### Development Setup
1. Clone the repository:
```bash
git clone https://github.com/Vortx-AI/memories-dev.git
cd memories-dev
```
2. Create a virtual environment:
```bash
python -m venv venv
source venv/bin/activate # Linux/Mac
# or
.\venv\Scripts\activate # Windows
```
3. Install development dependencies:
```bash
pip install -e .[dev]
```
4. Install pre-commit hooks:
```bash
pre-commit install
```
## 🔄 Workflows
### Memory Formation Pipeline
```mermaid
graph LR
%% Node Styles
classDef input fill:#e3f2fd,stroke:#1565c0,stroke-width:2px
classDef process fill:#f3e5f5,stroke:#6a1b9a,stroke-width:2px
classDef storage fill:#e8f5e9,stroke:#2e7d32,stroke-width:2px
%% Input Nodes
I1(("📡 Raw Data")):::input
I2(("🛰️ Satellite")):::input
I3(("🌡️ Sensors")):::input
%% Processing Nodes
P1["🔄 Preprocessing"]:::process
P2["⚡ Feature Extraction"]:::process
P3["🧠 Memory Formation"]:::process
%% Storage Nodes
S1[("💾 Vector Store")]:::storage
S2[("📊 Time Series DB")]:::storage
S3[("🗺️ Spatial Index")]:::storage
%% Flow
I1 & I2 & I3 --> P1
P1 --> P2
P2 --> P3
P3 --> S1 & S2 & S3
```
### Query Pipeline
```mermaid
graph TD
%% Node Styles
classDef query fill:#fff3e0,stroke:#e65100,stroke-width:2px
classDef memory fill:#f3e5f5,stroke:#6a1b9a,stroke-width:2px
classDef output fill:#e8f5e9,stroke:#2e7d32,stroke-width:2px
%% Query Flow
Q1["🔍 Query Request"]:::query
Q2["📍 Location Filter"]:::query
Q3["⏱️ Time Filter"]:::query
%% Memory Operations
M1["🧠 Memory Lookup"]:::memory
M2["🔄 Context Assembly"]:::memory
M3["⚡ Real-time Update"]:::memory
%% Output Generation
O1["📊 Results"]:::output
O2["📝 Analysis"]:::output
O3["🔄 Synthesis"]:::output
%% Connections
Q1 --> Q2 & Q3
Q2 & Q3 --> M1
M1 --> M2 --> M3
M3 --> O1 & O2 & O3
```
### Agent System
```mermaid
graph TD
%% Node Styles
classDef agent fill:#fff3e0,stroke:#e65100,stroke-width:2px
classDef memory fill:#f3e5f5,stroke:#6a1b9a,stroke-width:2px
classDef task fill:#e3f2fd,stroke:#1565c0,stroke-width:2px
%% Agent Components
subgraph "🤖 Agent System"
A1["🧠 Reasoning Engine"]:::agent
A2["🔄 Memory Integration"]:::agent
A3["📊 Analysis Engine"]:::agent
end
%% Memory Access
subgraph "💾 Memory Access"
M1["📥 Retrieval"]:::memory
M2["🔄 Update"]:::memory
M3["🔍 Query"]:::memory
end
%% Task Processing
subgraph "📋 Tasks"
T1["📊 Analysis"]:::task
T2["🔄 Synthesis"]:::task
T3["📝 Reporting"]:::task
end
%% Connections
A1 --> M1 & M2 & M3
M1 & M2 & M3 --> A2
A2 --> A3
A3 --> T1 & T2 & T3
```
### Memory Architecture
```mermaid
graph TD
%% Styles
classDef store fill:#e1f5fe,stroke:#01579b,stroke-width:2px;
classDef cache fill:#f3e5f5,stroke:#4a148c,stroke-width:2px;
classDef index fill:#fff3e0,stroke:#e65100,stroke-width:2px;
%% Memory Store
subgraph Store[Memory Store]
V[Vector Store]
T[Time Series DB]
S[Spatial Index]
end
%% Cache System
subgraph Cache[Cache Layers]
L1[L1 Cache - Memory]
L2[L2 Cache - SSD]
L3[L3 Cache - Distributed]
end
%% Index System
subgraph Index[Index Types]
I1[Spatial Index]
I2[Temporal Index]
I3[Semantic Index]
end
%% Flow
V & T & S --> L1
L1 --> L2 --> L3
L3 --> I1 & I2 & I3
%% Styles
class V,T,S store;
class L1,L2,L3 cache;
class I1,I2,I3 index;
```
### Data Flow
```mermaid
graph LR
%% Styles
classDef input fill:#e1f5fe,stroke:#01579b,stroke-width:2px;
classDef process fill:#f3e5f5,stroke:#4a148c,stroke-width:2px;
classDef output fill:#e8f5e9,stroke:#1b5e20,stroke-width:2px;
%% Pipeline
I[Raw Data] --> P1[Preprocessing]
P1 --> P2[Feature Extraction]
P2 --> P3[Memory Formation]
P3 --> P4[Memory Storage]
P4 --> P5[Memory Retrieval]
P5 --> O[AI Integration]
%% Styles
class I input;
class P1,P2,P3,P4,P5 process;
class O output;
```
## 📚 Module Dependencies
```mermaid
graph TD
%% Node Styles
classDef core fill:#e3f2fd,stroke:#1565c0,stroke-width:2px
classDef dep fill:#fff3e0,stroke:#e65100,stroke-width:2px
classDef util fill:#f3e5f5,stroke:#6a1b9a,stroke-width:2px
%% Core Modules
C1["🧠 Memory Core"]:::core
C2["🤖 Agent Core"]:::core
C3["📡 Data Core"]:::core
%% Dependencies
D1["📊 NumPy/Pandas"]:::dep
D2["🔥 PyTorch"]:::dep
D3["🗄️ Vector Store"]:::dep
D4["🌐 Network Utils"]:::dep
%% Utilities
U1["⚙️ Config"]:::util
U2["📝 Logging"]:::util
U3["✅ Validation"]:::util
%% Connections
D1 & D2 --> C1
D3 --> C1 & C2
D4 --> C3
U1 --> C1 & C2 & C3
U2 --> C1 & C2 & C3
U3 --> C1 & C2 & C3
```
## Usage
See our [documentation](https://docs.memories.dev) for detailed usage instructions and examples.
## License
This project is licensed under the Apache License 2.0 - see the [LICENSE](LICENSE) file for details.
## Contributing
Please read [CONTRIBUTING.md](CONTRIBUTING.md) for details on our code of conduct and the process for submitting pull requests.
## Support
- Documentation: https://docs.memories.dev
- Issues: https://github.com/Vortx-AI/memories-dev/issues
- Discussions: https://github.com/Vortx-AI/memories-dev/discussions
- Discord Community: [Join us on Discord](https://discord.com/invite/7qAFEekp)
---
<div align="center">
<p align="center">Built with 💜 by the memories.dev team</p>
<p align="center">
<a href="https://discord.com/invite/7qAFEekp">Discord</a> •
</p>
</div>
Raw data
{
"_id": null,
"home_page": "https://memories.dev",
"name": "memories-dev",
"maintainer": null,
"docs_url": null,
"requires_python": "<3.14.0,>=3.9",
"maintainer_email": "Memories-dev <hello@memories.dev>",
"keywords": "earth observation, data processing, memory management",
"author": "Memories-dev",
"author_email": "Memories-dev <hello@memories.dev>",
"download_url": "https://files.pythonhosted.org/packages/48/4b/59e630c9b8ec2ecf7af933f15e256a867b3663e70e617348e7620a2c6718/memories_dev-2.0.0.tar.gz",
"platform": null,
"description": "<div align=\"center\">\n\n# memories.dev\n\n\n**Collective Memory for AGI**\n\n[](https://memories-dev.readthedocs.io/index.html)\n[](LICENSE)\n[](https://www.python.org/downloads/)\n[](https://github.com/psf/black)\n[](https://github.com/Vortx-AI/memories-dev/releases/tag/v1.1.8)\n[](https://discord.com/invite/7qAFEekp)\n\n\n\n<a href=\"https://www.producthunt.com/posts/memories-dev?embed=true&utm_source=badge-featured&utm_medium=badge&utm_souce=badge-memories-dev\" target=\"_blank\"><img src=\"https://api.producthunt.com/widgets/embed-image/v1/featured.svg?post_id=879661&theme=light&t=1739530783374\" alt=\"memories.dev - Collective AGI Memory | Product Hunt\" style=\"width: 250px; height: 54px;\" width=\"250\" height=\"54\" /></a>\n\n</div>\n\n## Overview\n\nmemories.dev is a memory infrastructure for providing real-world context to AI models during inference. It processes, indexes, and serves location-tagged intelligence (\"memories\") from multiple data sources including satellite imagery, climate sensors, and urban development metrics. These memories enhance AI models' understanding and reasoning capabilities with real-world context.\n\n\n\n## System Architecture\n\n## Quick Start\n\n```python\nfrom memories.models.load_model import LoadModel\nfrom memories.core.memory import MemoryStore\nfrom memories.agents.agent import Agent\n\n\n# Initialize with advanced models\nload_model = LoadModel(\n use_gpu= True \n model_provider= \"deepseek-ai\" #\"deepseek\" or \"openai\"\n deployment_type= \"local\" #\"local\" or \"api\"\n model_name= \"deepseek-r1-zero\" #\"deepseek-r1-zero\" or \"gpt-4o\" or \"deepseek-coder-3.1b-base\" or \"gpt-4o-mini\"\n #api_key= #\"your-api-key\" optional for api deployment\n)\n\n# Create Earth memories\nmemory_store = MemoryStore()\n\nmemories = memory_store.create_memories(\n model = load_model,\n location=(37.7749, -122.4194), # San Francisco coordinates\n time_range=(\"2024-01-01\", \"2024-02-01\"),\n artifacts={\n \"satellite\": [\"sentinel-2\", \"landsat8\"],\n \"landuse\": [\"osm\",\"overture\"]\n }\n)\n\n\n# Generate synthetic data\nsynthetic_data = vx.generate_synthetic(\n base_location=(37.7749, -122.4194),\n scenario=\"urban_development\",\n time_steps=10,\n climate_factors=True\n)\n\n# AGI reasoning with memories\ninsights = Agent(\n query=\"Analyze urban development patterns and environmental impact\",\n context_memories=memories,\n synthetic_scenarios=synthetic_data\n)\n```\n\n## Installation\n\n### Basic Installation\n\n```bash\npip install memories-dev\n```\n\n### Python Version Compatibility\n\nThe package supports Python versions 3.9 through 3.13. Dependencies are automatically adjusted based on your Python version to ensure compatibility.\n\n### Installation Options\n\n#### 1. CPU-only Installation (Default)\n```bash\npip install memories-dev\n```\n\n#### 2. GPU Support Installation\nFor CUDA 11.8:\n```bash\npip install memories-dev[gpu]\n```\n\nFor different CUDA versions, install PyTorch manually first:\n```bash\n# For CUDA 12.1\npip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu121\n\n# Then install the package\npip install memories-dev[gpu]\n```\n\n#### 3. Development Installation\nFor contributing to the project:\n```bash\npip install memories-dev[dev]\n```\n\n#### 4. Documentation Tools\nFor building documentation:\n```bash\npip install memories-dev[docs]\n```\n\n### Version-specific Dependencies\n\nThe package automatically handles version-specific dependencies based on your Python version:\n\n- Python 3.9: Compatible with older versions of key packages\n- Python 3.10-3.11: Standard modern package versions\n- Python 3.12-3.13: Latest package versions with improved performance\n\n### Common Issues and Solutions\n\n1. **Shapely Version Conflicts**\n - For Python <3.13: Uses Shapely 1.7.0-1.8.5\n - For Python \u22653.13: Uses Shapely 2.0+\n\n2. **GPU Dependencies**\n - CUDA toolkit must be installed separately\n - PyTorch Geometric packages are installed from wheels matching your CUDA version\n\n3. **Package Conflicts**\n If you encounter dependency conflicts:\n ```bash\n pip install --upgrade pip\n pip install memories-dev --no-deps\n pip install -r requirements.txt\n ```\n\n### Development Setup\n\n1. Clone the repository:\n```bash\ngit clone https://github.com/Vortx-AI/memories-dev.git\ncd memories-dev\n```\n\n2. Create a virtual environment:\n```bash\npython -m venv venv\nsource venv/bin/activate # Linux/Mac\n# or\n.\\venv\\Scripts\\activate # Windows\n```\n\n3. Install development dependencies:\n```bash\npip install -e .[dev]\n```\n\n4. Install pre-commit hooks:\n```bash\npre-commit install\n```\n\n## \ud83d\udd04 Workflows\n\n### Memory Formation Pipeline\n\n```mermaid\ngraph LR\n %% Node Styles\n classDef input fill:#e3f2fd,stroke:#1565c0,stroke-width:2px\n classDef process fill:#f3e5f5,stroke:#6a1b9a,stroke-width:2px\n classDef storage fill:#e8f5e9,stroke:#2e7d32,stroke-width:2px\n \n %% Input Nodes\n I1((\"\ud83d\udce1 Raw Data\")):::input\n I2((\"\ud83d\udef0\ufe0f Satellite\")):::input\n I3((\"\ud83c\udf21\ufe0f Sensors\")):::input\n \n %% Processing Nodes\n P1[\"\ud83d\udd04 Preprocessing\"]:::process\n P2[\"\u26a1 Feature Extraction\"]:::process\n P3[\"\ud83e\udde0 Memory Formation\"]:::process\n \n %% Storage Nodes\n S1[(\"\ud83d\udcbe Vector Store\")]:::storage\n S2[(\"\ud83d\udcca Time Series DB\")]:::storage\n S3[(\"\ud83d\uddfa\ufe0f Spatial Index\")]:::storage\n \n %% Flow\n I1 & I2 & I3 --> P1\n P1 --> P2\n P2 --> P3\n P3 --> S1 & S2 & S3\n```\n\n### Query Pipeline\n\n```mermaid\ngraph TD\n %% Node Styles\n classDef query fill:#fff3e0,stroke:#e65100,stroke-width:2px\n classDef memory fill:#f3e5f5,stroke:#6a1b9a,stroke-width:2px\n classDef output fill:#e8f5e9,stroke:#2e7d32,stroke-width:2px\n\n %% Query Flow\n Q1[\"\ud83d\udd0d Query Request\"]:::query\n Q2[\"\ud83d\udccd Location Filter\"]:::query\n Q3[\"\u23f1\ufe0f Time Filter\"]:::query\n \n %% Memory Operations\n M1[\"\ud83e\udde0 Memory Lookup\"]:::memory\n M2[\"\ud83d\udd04 Context Assembly\"]:::memory\n M3[\"\u26a1 Real-time Update\"]:::memory\n \n %% Output Generation\n O1[\"\ud83d\udcca Results\"]:::output\n O2[\"\ud83d\udcdd Analysis\"]:::output\n O3[\"\ud83d\udd04 Synthesis\"]:::output\n\n %% Connections\n Q1 --> Q2 & Q3\n Q2 & Q3 --> M1\n M1 --> M2 --> M3\n M3 --> O1 & O2 & O3\n```\n\n\n### Agent System\n\n```mermaid\ngraph TD\n %% Node Styles\n classDef agent fill:#fff3e0,stroke:#e65100,stroke-width:2px\n classDef memory fill:#f3e5f5,stroke:#6a1b9a,stroke-width:2px\n classDef task fill:#e3f2fd,stroke:#1565c0,stroke-width:2px\n\n %% Agent Components\n subgraph \"\ud83e\udd16 Agent System\"\n A1[\"\ud83e\udde0 Reasoning Engine\"]:::agent\n A2[\"\ud83d\udd04 Memory Integration\"]:::agent\n A3[\"\ud83d\udcca Analysis Engine\"]:::agent\n end\n\n %% Memory Access\n subgraph \"\ud83d\udcbe Memory Access\"\n M1[\"\ud83d\udce5 Retrieval\"]:::memory\n M2[\"\ud83d\udd04 Update\"]:::memory\n M3[\"\ud83d\udd0d Query\"]:::memory\n end\n\n %% Task Processing\n subgraph \"\ud83d\udccb Tasks\"\n T1[\"\ud83d\udcca Analysis\"]:::task\n T2[\"\ud83d\udd04 Synthesis\"]:::task\n T3[\"\ud83d\udcdd Reporting\"]:::task\n end\n\n %% Connections\n A1 --> M1 & M2 & M3\n M1 & M2 & M3 --> A2\n A2 --> A3\n A3 --> T1 & T2 & T3\n```\n\n### Memory Architecture\n\n```mermaid\ngraph TD\n %% Styles\n classDef store fill:#e1f5fe,stroke:#01579b,stroke-width:2px;\n classDef cache fill:#f3e5f5,stroke:#4a148c,stroke-width:2px;\n classDef index fill:#fff3e0,stroke:#e65100,stroke-width:2px;\n\n %% Memory Store\n subgraph Store[Memory Store]\n V[Vector Store]\n T[Time Series DB]\n S[Spatial Index]\n end\n\n %% Cache System\n subgraph Cache[Cache Layers]\n L1[L1 Cache - Memory]\n L2[L2 Cache - SSD]\n L3[L3 Cache - Distributed]\n end\n\n %% Index System\n subgraph Index[Index Types]\n I1[Spatial Index]\n I2[Temporal Index]\n I3[Semantic Index]\n end\n\n %% Flow\n V & T & S --> L1\n L1 --> L2 --> L3\n L3 --> I1 & I2 & I3\n\n %% Styles\n class V,T,S store;\n class L1,L2,L3 cache;\n class I1,I2,I3 index;\n```\n\n\n### Data Flow\n\n```mermaid\ngraph LR\n %% Styles\n classDef input fill:#e1f5fe,stroke:#01579b,stroke-width:2px;\n classDef process fill:#f3e5f5,stroke:#4a148c,stroke-width:2px;\n classDef output fill:#e8f5e9,stroke:#1b5e20,stroke-width:2px;\n\n %% Pipeline\n I[Raw Data] --> P1[Preprocessing]\n P1 --> P2[Feature Extraction]\n P2 --> P3[Memory Formation]\n P3 --> P4[Memory Storage]\n P4 --> P5[Memory Retrieval]\n P5 --> O[AI Integration]\n\n %% Styles\n class I input;\n class P1,P2,P3,P4,P5 process;\n class O output;\n```\n## \ud83d\udcda Module Dependencies\n\n```mermaid\ngraph TD\n %% Node Styles\n classDef core fill:#e3f2fd,stroke:#1565c0,stroke-width:2px\n classDef dep fill:#fff3e0,stroke:#e65100,stroke-width:2px\n classDef util fill:#f3e5f5,stroke:#6a1b9a,stroke-width:2px\n\n %% Core Modules\n C1[\"\ud83e\udde0 Memory Core\"]:::core\n C2[\"\ud83e\udd16 Agent Core\"]:::core\n C3[\"\ud83d\udce1 Data Core\"]:::core\n\n %% Dependencies\n D1[\"\ud83d\udcca NumPy/Pandas\"]:::dep\n D2[\"\ud83d\udd25 PyTorch\"]:::dep\n D3[\"\ud83d\uddc4\ufe0f Vector Store\"]:::dep\n D4[\"\ud83c\udf10 Network Utils\"]:::dep\n\n %% Utilities\n U1[\"\u2699\ufe0f Config\"]:::util\n U2[\"\ud83d\udcdd Logging\"]:::util\n U3[\"\u2705 Validation\"]:::util\n\n %% Connections\n D1 & D2 --> C1\n D3 --> C1 & C2\n D4 --> C3\n U1 --> C1 & C2 & C3\n U2 --> C1 & C2 & C3\n U3 --> C1 & C2 & C3\n```\n\n## Usage\n\nSee our [documentation](https://docs.memories.dev) for detailed usage instructions and examples.\n\n## License\n\nThis project is licensed under the Apache License 2.0 - see the [LICENSE](LICENSE) file for details.\n\n## Contributing\n\nPlease read [CONTRIBUTING.md](CONTRIBUTING.md) for details on our code of conduct and the process for submitting pull requests.\n\n## Support\n\n- Documentation: https://docs.memories.dev\n- Issues: https://github.com/Vortx-AI/memories-dev/issues\n- Discussions: https://github.com/Vortx-AI/memories-dev/discussions\n- Discord Community: [Join us on Discord](https://discord.com/invite/7qAFEekp)\n\n---\n\n<div align=\"center\">\n\n\n<p align=\"center\">Built with \ud83d\udc9c by the memories.dev team</p>\n\n<p align=\"center\">\n<a href=\"https://discord.com/invite/7qAFEekp\">Discord</a> \u2022\n</p>\n</div>\n\n",
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