“Transcendental-Programmer” commited on
Commit
4932e02
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1 Parent(s): 632f510

FEAT: Init project structure and basic config

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  build/
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  # Environments
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  .env
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- # JetBrains specific template is maintained in a separate JetBrains.gitignore that can
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- # be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
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- # and can be added to the global gitignore or merged into this file. For a more nuclear
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- # option (not recommended) you can uncomment the following to ignore the entire idea folder.
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- #.idea/
 
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+ # Python
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  __pycache__/
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  *.py[cod]
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  *$py.class
 
 
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  *.so
 
 
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  .Python
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  build/
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  develop-eggs/
 
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  sdist/
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  var/
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  wheels/
 
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  *.egg-info/
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  .installed.cfg
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  *.egg
 
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+ # Virtual Environment
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+ venv/
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+ ENV/
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+
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+ # IDEs
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+ .idea/
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+ .vscode/
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+ *.swp
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+ *.swo
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+ # Jupyter Notebook
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+ .ipynb_checkpoints
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+ # Distribution / packaging
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+ .Python
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+ build/
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+ .installed.cfg
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+ *.egg
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  # Unit test / coverage reports
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  htmlcov/
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  .tox/
 
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  .coverage
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  .coverage.*
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  .cache
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  nosetests.xml
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  coverage.xml
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  *.cover
 
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  .hypothesis/
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  # Environments
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  .env
 
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  env.bak/
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  venv.bak/
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+ ideas.md
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+ plan.md
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
README.md CHANGED
@@ -1,2 +1,35 @@
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- # FinFedRAG-Financial-Federated-RAG
2
- FinFedRAG: A privacy-preserving framework that combines federated learning and RAG to generate synthetic financial data. It enables secure collaborative model training across institutions while maintaining data privacy and regulatory compliance.
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ # Federated Learning for Privacy-Preserving Financial Data Generation with RAG Integration
2
+
3
+ This project implements a federated learning framework combined with a Retrieval-Augmented Generation (RAG) system to generate privacy-preserving synthetic financial data.
4
+
5
+ ## Features
6
+
7
+ - Federated Learning using TensorFlow Federated
8
+ - Privacy-preserving data generation using VAE/GAN
9
+ - RAG integration for enhanced data quality
10
+ - Secure Multi-Party Computation (SMPC)
11
+ - Differential Privacy implementation
12
+ - Kubernetes-based deployment
13
+ - Comprehensive monitoring and logging
14
+
15
+ ## Installation
16
+
17
+ ```bash
18
+ pip install -r requirements.txt
19
+ ```
20
+
21
+ ## Usage
22
+
23
+ [Add usage instructions here]
24
+
25
+ ## Project Structure
26
+
27
+ [Add project structure description here]
28
+
29
+ ## License
30
+
31
+ MIT
32
+
33
+ ## Contributing
34
+
35
+ [Add contributing guidelines here]
config/client_config.yaml ADDED
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1
+ # client_config.yaml configuration
2
+
3
+ client:
4
+ # Data configuration
5
+ data:
6
+ batch_size: 32
7
+ shuffle_buffer: 1000
8
+ input_dim: 32
9
+
10
+ # Model configuration
11
+ model:
12
+ type: "feedforward"
13
+ hidden_dims: [128, 64]
14
+ activation: "relu"
15
+
16
+ # Training configuration
17
+ training:
18
+ local_epochs: 5
19
+ learning_rate: 0.001
20
+
21
+ monitoring:
22
+ log_level: "INFO"
23
+
config/logging_config.yaml ADDED
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+ version: 1
2
+ formatters:
3
+ detailed:
4
+ format: '%(asctime)s - %(name)s - %(levelname)s - %(message)s'
5
+ handlers:
6
+ console:
7
+ class: logging.StreamHandler
8
+ level: INFO
9
+ formatter: detailed
10
+ stream: ext://sys.stdout
11
+ file:
12
+ class: logging.FileHandler
13
+ level: INFO
14
+ formatter: detailed
15
+ filename: logs/federated_learning.log
16
+ loggers:
17
+ '': # Root logger
18
+ level: INFO
19
+ handlers: [console, file]
config/server_config.yaml ADDED
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1
+ # server_config.yaml configuration
2
+
3
+ server:
4
+ # Federated learning configuration
5
+ federated:
6
+ min_clients: 1
7
+ rounds: 10
8
+ sample_fraction: 0.8
9
+
10
+ # Aggregation configuration
11
+ aggregation:
12
+ method: "fedavg"
13
+ weighted: true
14
+
15
+ # Monitoring configuration
16
+ monitoring:
17
+ log_level: "INFO"
18
+
dir_structure.md ADDED
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1
+ # Directory Structure
2
+
3
+ ```
4
+ federated-rag-financial/
5
+ ├── .github/
6
+ │ └── workflows/
7
+ │ └── ci.yml
8
+ ├── .gitignore
9
+ ├── docker/
10
+ │ ├── Dockerfile.client
11
+ │ ├── Dockerfile.server
12
+ │ └── docker-compose.yml
13
+ ├── kubernetes/
14
+ │ ├── deployments/
15
+ │ │ ├── client.yaml
16
+ │ │ ├── server.yaml
17
+ │ │ └── rag.yaml
18
+ │ └── services/
19
+ │ └── service.yaml
20
+ ├── src/
21
+ │ ├── __init__.py
22
+ │ ├── client/
23
+ │ │ ├── __init__.py
24
+ │ │ ├── data_handler.py
25
+ │ │ └── model.py
26
+ │ ├── server/
27
+ │ │ ├── __init__.py
28
+ │ │ ├── aggregator.py
29
+ │ │ └── coordinator.py
30
+ │ ├── rag/
31
+ │ │ ├── __init__.py
32
+ │ │ ├── retriever.py
33
+ │ │ └── generator.py
34
+ │ ├── models/
35
+ │ │ ├── __init__.py
36
+ │ │ ├── vae.py
37
+ │ │ └── gan.py
38
+ │ └── utils/
39
+ │ ├── __init__.py
40
+ │ ├── privacy.py
41
+ │ └── metrics.py
42
+ ├── tests/
43
+ │ ├── __init__.py
44
+ │ ├── test_client.py
45
+ │ ├── test_server.py
46
+ │ └── test_rag.py
47
+ ├── docs/
48
+ │ ├── api/
49
+ │ ├── guides/
50
+ │ └── index.md
51
+ ├── notebooks/
52
+ │ ├── data_exploration.ipynb
53
+ │ └── model_evaluation.ipynb
54
+ ├── config/
55
+ │ ├── client_config.yaml
56
+ │ └── server_config.yaml
57
+ ├── requirements.txt
58
+ ├── setup.py
59
+ └── README.md
60
+ ```
docker/Dockerfile.client ADDED
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+ FROM python:3.8-slim
2
+
3
+ WORKDIR /app
4
+
5
+ # Install system dependencies
6
+ RUN apt-get update && \
7
+ apt-get install -y --no-install-recommends \
8
+ build-essential \
9
+ && rm -rf /var/lib/apt/lists/*
10
+
11
+ # Copy requirements and install Python dependencies
12
+ COPY requirements.txt .
13
+ RUN pip install --no-cache-dir -r requirements.txt
14
+
15
+ # Copy source code
16
+ COPY src/ src/
17
+ COPY config/ config/
18
+
19
+ # Set environment variables
20
+ ENV PYTHONPATH=/app
21
+ ENV CONFIG_PATH=/app/config/client_config.yaml
22
+
23
+ # Run the client
24
+ CMD ["python", "-m", "src.client.model"]
docker/Dockerfile.server ADDED
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+ FROM python:3.8-slim
2
+
3
+ WORKDIR /app
4
+
5
+ # Install system dependencies
6
+ RUN apt-get update && \
7
+ apt-get install -y --no-install-recommends \
8
+ build-essential \
9
+ && rm -rf /var/lib/apt/lists/*
10
+
11
+ # Copy requirements and install Python dependencies
12
+ COPY requirements.txt .
13
+ RUN pip install --no-cache-dir -r requirements.txt
14
+
15
+ # Copy source code
16
+ COPY src/ src/
17
+ COPY config/ config/
18
+
19
+ # Set environment variables
20
+ ENV PYTHONPATH=/app
21
+ ENV CONFIG_PATH=/app/config/server_config.yaml
22
+
23
+ # Expose ports for API and monitoring
24
+ EXPOSE 8000 8001
25
+
26
+ # Run the server
27
+ CMD ["python", "-m", "src.server.coordinator"]
docker/docker-compose.yml ADDED
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+ version: '3.8'
2
+
3
+ services:
4
+ fl-server:
5
+ build:
6
+ context: ..
7
+ dockerfile: docker/Dockerfile.server
8
+ ports:
9
+ - "8000:8000"
10
+ - "8001:8001"
11
+ volumes:
12
+ - ../config:/app/config
13
+ environment:
14
+ - PYTHONPATH=/app
15
+ - CONFIG_PATH=/app/config/server_config.yaml
16
+ networks:
17
+ - fl-network
18
+
19
+ fl-client:
20
+ build:
21
+ context: ..
22
+ dockerfile: docker/Dockerfile.client
23
+ depends_on:
24
+ - fl-server
25
+ volumes:
26
+ - ../config:/app/config
27
+ environment:
28
+ - PYTHONPATH=/app
29
+ - CONFIG_PATH=/app/config/client_config.yaml
30
+ - SERVER_HOST=fl-server
31
+ - SERVER_PORT=8000
32
+ networks:
33
+ - fl-network
34
+ deploy:
35
+ replicas: 3
36
+
37
+ networks:
38
+ fl-network:
39
+ driver: bridge
40
+
docs/index.md ADDED
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1
+ # Federated Learning for Privacy-Preserving Financial Data Generation
2
+
3
+ ## Overview
4
+ This documentation covers the implementation and usage of a federated learning system for generating synthetic financial data with privacy preservation using RAG (Retrieval-Augmented Generation).
5
+
6
+ ## Quick Start
7
+ - [Installation Guide](guides/installation.md)
8
+ - [Usage Guide](guides/usage.md)
9
+ - [API Reference](api/index.md)
10
+ - [Project Planning](guides/planning.md)
11
+
12
+ ## Architecture
13
+ The system consists of three main components:
14
+ 1. Federated Learning Framework
15
+ 2. Privacy-Preserving Data Generation
16
+ 3. RAG Integration
17
+
18
+ ## Components
19
+ - Client Implementation
20
+ - Server Coordination
21
+ - RAG System
22
+ - Privacy Management
23
+ - Data Handling
24
+
25
+ ## Contributing
26
+ Please read our [Contributing Guidelines](guides/contributing.md) for details on submitting pull requests.
27
+
28
+ ## License
29
+ This project is licensed under the MIT License - see the LICENSE file for details.
30
+
requirements.txt ADDED
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1
+ # Core ML frameworks
2
+ tensorflow>=2.6.0
3
+ tensorflow-federated
4
+ torch>=1.9.0
5
+ transformers
6
+
7
+ # Data processing
8
+ pandas>=1.3.0
9
+ numpy>=1.19.0
10
+ scikit-learn
11
+
12
+ # RAG components
13
+ elasticsearch
14
+ faiss-cpu
15
+
16
+ # Privacy and security
17
+ tensorflow-privacy
18
+ pysyft
19
+
20
+ # API and web
21
+ flask
22
+ fastapi
23
+ uvicorn
24
+
25
+ # Testing and development
26
+ pytest
27
+ black
28
+ flake8
29
+ isort
30
+
31
+ # Documentation
32
+ sphinx
33
+ sphinx-rtd-theme
34
+
35
+ # Additional requirements
36
+ pyyaml>=5.4.1
src/__init__.py ADDED
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+ """__init__.py module."""
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+
src/client/__init__.py ADDED
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+ """__init__.py module."""
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+
src/models/__init__.py ADDED
@@ -0,0 +1,2 @@
 
 
 
1
+ """__init__.py module."""
2
+
src/rag/__init__.py ADDED
@@ -0,0 +1,2 @@
 
 
 
1
+ """__init__.py module."""
2
+
src/server/__init__.py ADDED
@@ -0,0 +1,2 @@
 
 
 
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+ """__init__.py module."""
2
+
src/utils/__init__.py ADDED
@@ -0,0 +1,2 @@
 
 
 
1
+ """__init__.py module."""
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+
tests/__init__.py ADDED
@@ -0,0 +1,2 @@
 
 
 
1
+ """__init__.py module."""
2
+