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You will get a RAG: LLM-WebToGraph (Docker compose [streamlit +FAST API])

Praveen S.Status: Offline
Praveen S.
Preview imagePreview imagePreview image

Let a pro handle the details

Buy Other AI & Machine Learning services from Praveen, priced and ready to go.
Praveen S.Status: Offline
Praveen S.
Preview imagePreview imagePreview image

Let a pro handle the details

Buy Other AI & Machine Learning services from Praveen, priced and ready to go.

Project details

You will get a powerful RAG that harnesses the capabilities of Langchain and OpenAI's Language Models (LLMs) to scrape data from various sources on the web, transforming it into a structured knowledge graph. This knowledge graph is then populated into a Neo4j Aura Database, providing an efficient way to store, query, and retrieve information using cipher queries and LLMs. With the synergy of Langchain, OpenAI LLMs, and Neo4j, this project offers a robust knowledge management and retrieval solution.
AI Development Type
Deep Learning, Knowledge Representation, Model Tuning
AI Tools
Amazon SageMaker, Azure Machine Learning, Chainer, Deeplearning4j, MLflow, PyTorch
AI Development Language
Python

What's included $250

These options are included with the project scope.

$250
  • Delivery Time 7 days
  • Number of Revisions 2
    • AI Model Integration
    • Detailed Code Comments
    • Knowledge Graph
    • Model Documentation
    • Source Code
    • Taxonomy
Optional add-ons You can add these on the next page.
Fast 5 Days Delivery
+$250
Additional Revision
+$100
Praveen S.Status: Offline

About Praveen

Praveen S.Status: Offline
Machine Learning Engineer (NLP)
Montreal, Canada - 9:46 pm local time
I am a machine-learning enthusiast who enjoys problem-solving and building machine-learning pipelines. I am responsible for designing and implementing algorithms and models, selecting appropriate datasets, and optimizing models for performance. My experience includes training and fine-tuning deep learning models for NLP and computer vision pipelines on cloud-based platforms like AWS and GCP. I collaborate with cross-functional teams to integrate models into production systems and provide ongoing maintenance and support. I am passionate about leveraging the latest technologies and tools to build scalable and efficient machine-learning pipelines that can solve complex business problems.

Steps for completing your project

After purchasing the project, send requirements so Praveen can start the project.

Delivery time starts when Praveen receives requirements from you.

Praveen works on your project following the steps below.

Revisions may occur after the delivery date.

Planning

Gather client requirements and define project scope. Create a proposal and sign an agreement.

Development

Set up development environment. Develop web scraping and data transformation modules. Integrate with Neo4j Aura Database. Build a FastAPI-based health check API. Develop a Streamlit web application.

Review the work, release payment, and leave feedback to Praveen.