LangChain + Qdrant – AI Retriever Chain with Contextual Prompting (Docker + Python) - $200

LangChain + Qdrant – AI Retriever Chain with Contextual Prompting (Docker + Python)

We are seeking a developer with proven experience in implementing LangChain retriever chains using Qdrant as a vector database, fully containerized with Docker.

This is a real production task, not a test or sample project. All deliverables will be manually verified before approval. If you have not previously deployed LangChain with Qdrant, please do not apply.
Required Tasks:

Build a retriever pipeline using LangChain and Qdrant, fully Dockerized.

Implement contextual prompting with fallback and memory chaining.

Accept inputs via a lightweight REST API (FastAPI or Flask).

Provide a working demo, test data, and documentation.

Technology Stack (Mandatory):

Python

LangChain

Qdrant

Docker

GitHub for final delivery

REST API implementation (FastAPI or Flask)

Delivery Requirements:

All deliverables must be submitted via GitHub, with complete README.md.

Must include Docker setup, test data, and fully functional retriever chain.

Code must be clean, modular, and ready for integration.

Final payment will only be released after full delivery and manual review.

Budget:

Fixed price: 200 to 250 USD
Do not bid above this range.
Application Instructions:

Do not send generic proposals.

Include the phrase “LangChain + Qdrant real use” in your bid to confirm you read and understood the brief.

Only developers with real-world implementation experience should apply.

Upon completion, full intellectual property rights must be transferred to the client. The code may not be reused, resold, or repackaged.