refactor: dimension_reduction operator

operators/dimension_reduction/README.md

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+# Dimension Reduction Operator
+
+## Description
+
+The `Dimension Reduction` operator reduces the dimensionality of high-dimensional embeddings using t-SNE and UMAP algorithms. It supports reducing embeddings to 2D or 3D for visualization and analysis purposes while preserving the most important structural information.
+
+## Model Information
+
+- **t-SNE**: t-Distributed Stochastic Neighbor Embedding for non-linear dimensionality reduction
+- **UMAP**: Uniform Manifold Approximation and Projection for scalable dimension reduction
+- **Vector Size**: Configurable (typically 2-3 dimensions for visualization)
+- **Usage**: Reduces high-dimensional embeddings to lower dimensions for visualization, clustering, and analysis
+
+## Dependencies
+
+- scikit-learn >= 1.6.1
+- numpy >= 1.26,<2.2.0
+- umap-learn >= 0.5.0
+
+## How to Run the Tests
+
+1. Ensure that you are in the root directory of the `feluda` project.
+2. Install dependencies (in your virtual environment):
+
+   ```bash
+   uv pip install "./operators/dimension_reduction"
+   uv pip install "feluda[dev]"
+   ```
+
+3. Run the tests:
+
+   ```bash
+   pytest operators/dimension_reduction/test.py
+   ```
+
+## Usage
+
+```python
+from operators.dimension_reduction.dimension_reduction import DimensionReduction
+
+# Initialize with t-SNE
+operator = DimensionReduction("tsne", {
+    "n_components": 2,
+    "perplexity": 2,
+    "random_state": 42
+})
+
+# Prepare input data
+input_data = [
+    {"payload": "sample_1", "embedding": [1.0, 2.0, 3.0, 4.0, 5.0]},
+    {"payload": "sample_2", "embedding": [2.0, 3.0, 4.0, 5.0, 6.0]},
+    {"payload": "sample_3", "embedding": [3.0, 4.0, 5.0, 6.0, 7.0]}
+]
+
+
+# Run dimension reduction
+result = operator.run(input_data)
+
+# Access results
+for item in result:
+    print(f"Payload: {item['payload']}")
+    print(f"Reduced embedding: {item['reduced_embedding']}")
+```

operators/dimension_reduction/__init__.py

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+from .dimension_reduction import DimensionReduction
+
+__all__ = ["DimensionReduction"]