Agentic

🧠 Agentic AI Feature Planner – Architecture & Flow 📌 Overview

The Agentic AI Feature Planner is a LangChain-based multi-agent system designed to transform raw project input and feedback into structured planning documents. It empowers product teams, UX researchers, and designers to derive meaningful plans from unstructured ideas.

🏗 System Architecture

Frontend: Streamlit UI with gradient styling and tab-based visualization for each agent's output.

Agents: Five LangChain agents coordinated sequentially, each performing a specialized task.

RAG Component: Uses FAISS-based vector store to retrieve contextual knowledge from PDFs.

LLM Backend: Google Gemini 2.0 Flash model integrated using LangChain.

⚙️ Agentic Flow

Agent 1 – Project Context Interpreter Extracts project objectives, target audience, and expected outcomes.

Agent 2 – User Journey Analyzer Identifies user roles, intentions, and key tasks from context + RAG documents.

Agent 3 – Task Plan Generator Converts goals into backend, frontend, and API tasks.

Agent 4 – User Action Mapper Maps tasks to real-world user-facing actions and flows.

Agent 5 – Planner Refiner Refines all results using mentor/peer feedback and outputs the final plan.

🔁 Pipeline Flow Summary

User enters project brief + optional feedback

Agents execute one after another in a pipeline

Each agent’s raw output is shown on its respective tab

Final refined plan is displayed as readable text in the main tab

Built With

• gemini
• langchain
• python
• rag
• vectordb