memories.dev is a high-performance 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.
from memories_dev.memories_dev import memories_dev
from memories_dev.memories.earth_memory import EarthMemoryStore
from memories_dev.agents.agent import Agent
# Initialize with advanced models
vx = Vortx(
models={
"reasoning": deepseek-coder-small,
"vision": deepseek-vision-small
},
use_gpu=True
)
# Create Earth memories
memory_store = EarthMemoryStore()
memories = memory_store.create_memories(
location=(37.7749, -122.4194),
time_range=("2020-01-01", "2024-01-01"),
modalities=["satellite", "climate", "social"]
)
# 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
)# Basic installation (Coming Soon)
pip install memories-dev
# With GPU support (Coming Soon)
pip install memories-dev[gpu]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
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
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
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;
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;
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
- Global Points of Interest Database
- Global Places Database
- Cadastral Data & Digital Elevation Models
- Census & Demographics
- Satellite Data:
- ESA Sentinel-1 & 2
- NASA Landsat 7/8
- Custom data source integration
- Real-time memory synthesis during model inference
- Context-aware AI reasoning
- Multi-modal memory fusion
- Temporal pattern analysis
- Location-aware intelligence
- Privacy-preserving memory access
- Python 3.9+
- 16GB RAM
- 4+ CPU cores
- 20GB storage
- 32GB RAM
- 8+ CPU cores
- NVIDIA GPU (8GB+ VRAM)
- 50GB SSD storage
- Enhanced Language Models: Provide real-world context during inference
- Report Generation: Create detailed reports with location-specific insights
- Trend Analysis: Analyze temporal patterns with historical context
- Impact Assessment: Evaluate environmental and urban development impacts
- Decision Support: Aid decision-making with contextual intelligence
We welcome contributions! See our Contributing Guide for:
- Development Setup
- Code Style Guidelines
- Testing Requirements
- PR Process
Apache License 2.0 - See LICENSE for details.
Empowering AI with Real-World Context
