initial

Author: NavodSporoDev

.gitignore

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+venv
+build
+dist
+*.egg-info
+.env
+
+*.swp
+*.swo
+
+# By default do not include these files for version control
+# Override this by using 'git add -f'
+*.wav
+*.mp3

LICENSE

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+MIT License
+
+Copyright (c) 2025 Navod Peiris
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

README.md

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+<p align="center">
+  <img src="graphsense.png" />
+</p>
+
+<p align="center">
+    <a href="./LICENSE"><img src="https://img.shields.io/github/license/NavodPeiris/graphsense"></a>
+    <a href="https://github.com/NavodPeiris/graphsense/releases"><img src="https://img.shields.io/github/v/release/NavodPeiris/graphsense?color=ffa"></a>
+    <a href="support os"><img src="https://img.shields.io/badge/os-linux%2C%20win%2C%20mac-pink.svg"></a>
+    <a href=""><img src="https://img.shields.io/badge/python-3.8+-aff.svg"></a>
+    <a href="https://github.com/NavodPeiris/graphsense/issues"><img src="https://img.shields.io/github/issues/NavodPeiris/graphsense?color=9cc"></a>
+    <a href="https://github.com/NavodPeiris/graphsense/stargazers"><img src="https://img.shields.io/github/stars/NavodPeiris/graphsense?color=ccf"></a>
+    <a href="https://pypi.org/project/graphsense/"><img src="https://static.pepy.tech/badge/graphsense"></a>
+    
+</p>
+
+
+### Requirements
+
+* Python 3.8 or greater
+
+
+### installation:
+```
+pip install graphsense
+```
+
+
+### Training example:
+
+```
+from graphsense import GraphSense
+
+g = GraphSense()
+
+g.line_completion(input_path="code_files", output_path="output")
+
+```
+
+### Inference example:
+
+```
+from graphsense import GraphSense
+
+g = GraphSense()
+
+g.load_model("output/graph_embeddings.model")
+next = g.infer("def factorial(n):")
+
+print("next item predicted: ", next)
+```
+
+### Performance Comparison with gpt2_medium finetuned model
+Dataset used to train models: https://github.com/TheAlgorithms/Python 
+#### gpt2_medium finetuned model
+```
+input: def factorial(n)  
+output: return 1 if n == 1 else n * factorial(n - 1)   
+model size: 1.44GB   
+avg inference time: 10.3302 seconds  
+CPU Usage: 8.3%  
+Memory Usage: 68.54 MB  
+```
+
+#### graph embedding model 
+```
+input: def factorial(n)  
+output: return 1 if n == 1 else n * factorial(n - 1)   
+model size: 13.2MB
+avg inference time: 2.1870 seconds  
+CPU Usage: 0.2%
+Memory Usage: 4.54 MB  
+```