An advanced AI-powered solution enhances network diagnostics by leveraging large language models (LLMs). The system intelligently parses various types of device logs, including structured and unstructured data, to identify patterns and anomalies. It provides actionable insights and recommendations to help diagnose and resolve network issues efficiently. This solution simplifies the complexity of log analysis, enabling quicker and more accurate problem detection and resolution.
Python 3.11.9 or Higher (Recommended)
Create an account on groq cloud and get a Groq API Key
Create a google account and get a Google API Key
All The Modules/Libraries Used in the Project can be installed using requirements.txt
- streamlit~=1.35.0
- langchain~=0.2.1
- python-dotenv~=1.0.1
- langchain-groq~=0.1.4
- langchain-community~=0.2.1
- faiss-cpu~=1.8.0
- langchain-google-genai~=1.0.6
- Intialize a Git Repository.
git init- Clone the Current Git Repository.
git clone https://github.com/k-arthik-r/ai_powered_log_parsing_tool.git- Navigate to the root Directory of the project and Create a python virtual environment.
python -m venv venv
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Activate the Environment:
- for Powershell
.\venv\Scripts\Activate.ps1
- for CommandPrompt
.\venv\Scripts\activate.bat
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Install all the Modules Present in requirements
pip install -r requirements.txt- paste your google and groq API keys inside .env file in the root directory. Here
GOOGLE_API_KEY = <paste your google api key here>
GROQ_API_KEY = <paste your groq api key here>- run your application using,
streamlit run app.py-
Start your Docker Engine.
-
Open your Terminal (Power shell or Comand Prompt).
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Pull the Application Docker Image from the Docker Hub:
docker pull karthikclgid/ai-powered-log-parsing-tool:latest
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Run the Docker Image:
docker run -p 8501:8501 karthikclgid/ai-powered-log-parsing-tool:latest
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The Application will start its Execution.
The complete details of the Project Implementation is provided in Project Report
