# shravanshidruk16/innomatics-research-labs-advanced-genai-internship-february-2026 architecture

> Architecture diagram of the GitHub repository shravanshidruk16/innomatics-research-labs-advanced-genai-internship-february-2026, generated by GitDiagram from its file tree, README and a sample of source files (last updated 2026-06-21). It is an AI-made overview: check details against the source.

- Interactive diagram: https://gitdiagram.com/shravanshidruk16/innomatics-research-labs-advanced-genai-internship-february-2026
- Repository: https://github.com/shravanshidruk16/innomatics-research-labs-advanced-genai-internship-february-2026

## Overview

1. **Repository shape**
   This is a **multi-project internship workspace**, not a single application. Each top-level folder is a largely independent deliverable: FastAPI assignments, LangChain experiments, an NLP set of tasks, a RAG customer-support assistant, and a hackathon dataset project.

2. **Primary boundary: project isolation**
   The repo is organized by **topic and submission**, so architecture is best drawn as several separate subsystems rather than one shared platform. Most projects have their own code, data, and artifacts, with limited evidence of cross-project dependencies.

3. **RAG Major Project – Customer Support Assistant**
   This is the clearest end-to-end production-style system. The `app/` package is split into distinct pipeline stages: **ingestion**, **retrieval**, **routing**, **LLM orchestration**, **workflow graph**, and **human-in-the-loop escalation**. The presence of `vectorstore/` and a `knowledge_base.pdf` indicates a document-grounded assistant built on indexed knowledge.

4. **RAG data flow**
   The likely flow is: **PDF knowledge base → loader → chunker → embedder → persisted vector store (Chroma) → retriever → routing/workflow → LLM response**. The `hitl/escalation.py` module suggests a fallback path where uncertain or sensitive queries are escalated instead of answered directly.

5. **RAG architecture boundary**
   The main architectural split is between **offline ingestion/indexing** and **online query handling**. Ingestion creates the vector store artifacts under `vectorstore/`, while runtime code in `main.py`, `graph/workflow.py`, `retrieval/retriever.py`, and `routing/router.py` serves user requests and decides response strategy.

6. **LangChain Assignment 3**
   This folder is a smaller, modular LLM pipeline focused on **resume-job matching**. The code is structured into `chains/` and `prompts/`, with `main.py` orchestrating execution over input text files such as `job_description.txt`, `strong_resume.txt`, `average_resume.txt`, and `weak_resume.txt`.

7. **LangChain data flow**
   The pipeline appears to follow a staged analysis pattern: **extract information → match resume to job → score fit → explain result**. The separate prompt files and chain files indicate a design where each LLM step is independently defined and then composed in the main script.

8. **FastAPI major project**
   `Final Major Project - FastAPI/Online_Course_Platform_FastAPI/` is a standalone web/API application for an **online course platform**. The core split is between `main.py` for application entry/API routing, `models.py` for domain/data structures, and `frontend.py` for UI or client-side integration. `assets/` and the generated HTML file suggest a packaged demo or report alongside the app code.

9. **FastAPI assignments**
   `IN226039402_FASTAPI/Assignment_1` through `Assignment_5` are separate learning exercises, each with its own `main.py`, HTML export, and images. These are best treated as **independent FastAPI practice modules** rather than parts of one shared system.

10. **NLP and data projects**
   The `NLP/` folder contains notebook-driven experiments plus `task3.py`, with datasets for Kindle and IMDb reviews. The `Entrance Test - Hackathon/` folder contains notebooks and a generated CSV dataset for food delivery. These are **analysis/modeling workspaces**, not app backends.

11. **Python programming notebooks**
   `Python Programming/` is a sequence of weekly notebook exercises. This area is instructional rather than system-oriented, and it does not appear to feed the major projects directly.

12. **Supporting artifacts**
   The repo includes generated deliverables, HTML exports, PDFs, images, datasets, and a Chroma persistence directory. These artifacts matter architecturally because they show the projects are **documented, reproducible exercises with persisted retrieval state** rather than purely transient notebook experiments.

Main entry points: [`Langchain/Assignment_3/main.py`](https://github.com/shravanshidruk16/innomatics-research-labs-advanced-genai-internship-february-2026/blob/main/Langchain/Assignment_3/main.py) (Orchestrator), [`Final Major Project - FastAPI/Online_Course_Platform_FastAPI`](https://github.com/shravanshidruk16/innomatics-research-labs-advanced-genai-internship-february-2026/tree/HEAD/Final%20Major%20Project%20-%20FastAPI/Online_Course_Platform_FastAPI) (Course App), [`RAG MAJOR PROJECT - CUSTOMER SUPPORT ASSISTANT/app`](https://github.com/shravanshidruk16/innomatics-research-labs-advanced-genai-internship-february-2026/tree/HEAD/RAG%20MAJOR%20PROJECT%20-%20CUSTOMER%20SUPPORT%20ASSISTANT/app) (Support Assistant), [`RAG MAJOR PROJECT - CUSTOMER SUPPORT ASSISTANT/app/routing/router.py`](https://github.com/shravanshidruk16/innomatics-research-labs-advanced-genai-internship-february-2026/blob/HEAD/RAG%20MAJOR%20PROJECT%20-%20CUSTOMER%20SUPPORT%20ASSISTANT/app/routing/router.py) (Router)

## Diagram (Mermaid)

```mermaid
flowchart TD

subgraph group_g_fastapi["FastAPI"]
  node_fastapi_major["Course App<br/>FastAPI app"]
  node_fastapi_main["App API<br/>entrypoint<br/>[main.py]"]
  node_fastapi_models["Models<br/>domain schema<br/>[models.py]"]
  node_fastapi_frontend["Frontend<br/>client layer<br/>[frontend.py]"]
  node_fastapi_assignments["Practice Set<br/>exercise bundle"]
end

subgraph group_g_langchain["LangChain"]
  node_langchain_major["Resume Matcher<br/>LangChain pipeline"]
  node_langchain_main["Orchestrator<br/>pipeline entrypoint<br/>[main.py]"]
  node_langchain_extract["Extract<br/>chain"]
  node_langchain_match["Match<br/>chain<br/>[matching_chain.py]"]
  node_langchain_score["Score<br/>chain<br/>[scoring_chain.py]"]
  node_langchain_explain["Explain<br/>chain"]
end

subgraph group_g_rag["RAG Assistant"]
  node_rag_major["Support Assistant<br/>RAG system"]
  node_rag_loader["Loader<br/>ingestion stage<br/>[loader.py]"]
  node_rag_chunker["Chunker<br/>ingestion stage<br/>[chunker.py]"]
  node_rag_embedder["Embedder<br/>ingestion stage<br/>[embedder.py]"]
  node_rag_retriever["Retriever<br/>retrieval stage<br/>[retriever.py]"]
  node_rag_router["Router<br/>decision stage<br/>[router.py]"]
  node_rag_workflow["Workflow<br/>orchestration graph<br/>[workflow.py]"]
  node_rag_llm["LLM Core<br/>generation stage<br/>[llm.py]"]
  node_rag_hitl["Escalation<br/>HITL fallback<br/>[escalation.py]"]
end

subgraph group_g_nlp["NLP"]
  node_nlp_workspace["NLP Lab<br/>analysis workspace"]
  node_nlp_task3["Task 3<br/>script<br/>[task3.py]"]
end

subgraph group_g_python["Python Programming"]
  node_python_workspace["Python Weeks<br/>notebook set"]
end

subgraph group_g_hackathon["Hackathon"]
  node_hackathon_workspace["Food Dataset<br/>data prep workspace"]
end

subgraph group_g_support["Supporting Artifacts"]
  node_rag_data["Knowledge Base<br/>source document<br/>[knowledge_base.pdf]"]
  node_rag_store[("Vector Store<br/>persistent index")]
  node_hackathon_dataset["Food CSV<br/>generated dataset"]
end

node_repo_root["Internship WS<br/>mono-repo"]

node_repo_root -->|"contains"| node_fastapi_major
node_repo_root -->|"contains"| node_fastapi_assignments
node_repo_root -->|"contains"| node_langchain_major
node_repo_root -->|"contains"| node_rag_major
node_repo_root -->|"contains"| node_nlp_workspace
node_repo_root -->|"contains"| node_python_workspace
node_repo_root -->|"contains"| node_hackathon_workspace
node_fastapi_major -->|"entrypoint"| node_fastapi_main
node_fastapi_major -->|"defines"| node_fastapi_models
node_fastapi_major -->|"integrates"| node_fastapi_frontend
node_langchain_major -->|"orchestrates"| node_langchain_main
node_langchain_main -->|"runs"| node_langchain_extract
node_langchain_main -->|"runs"| node_langchain_match
node_langchain_main -->|"runs"| node_langchain_score
node_langchain_main -->|"runs"| node_langchain_explain
node_rag_major -->|"offline ingest"| node_rag_loader
node_rag_loader -->|"prepares"| node_rag_chunker
node_rag_chunker -->|"indexes"| node_rag_embedder
node_rag_embedder -->|"persists"| node_rag_store
node_rag_major -->|"online runtime"| node_rag_workflow
node_rag_workflow -->|"routes"| node_rag_router
node_rag_router -->|"retrieves"| node_rag_retriever
node_rag_retriever -->|"grounds"| node_rag_llm
node_rag_router -->|"escalates"| node_rag_hitl
node_rag_workflow -->|"generates"| node_rag_llm
node_rag_major -->|"sources"| node_rag_data
node_nlp_workspace -->|"includes"| node_nlp_task3
node_hackathon_workspace -->|"produces"| node_hackathon_dataset

click node_fastapi_major "https://github.com/shravanshidruk16/innomatics-research-labs-advanced-genai-internship-february-2026/tree/main/Final Major Project - FastAPI/Online_Course_Platform_FastAPI"
click node_fastapi_main "https://github.com/shravanshidruk16/innomatics-research-labs-advanced-genai-internship-february-2026/blob/main/Final Major Project - FastAPI/Online_Course_Platform_FastAPI/main.py"
click node_fastapi_models "https://github.com/shravanshidruk16/innomatics-research-labs-advanced-genai-internship-february-2026/blob/main/Final Major Project - FastAPI/Online_Course_Platform_FastAPI/models.py"
click node_fastapi_frontend "https://github.com/shravanshidruk16/innomatics-research-labs-advanced-genai-internship-february-2026/blob/main/Final Major Project - FastAPI/Online_Course_Platform_FastAPI/frontend.py"
click node_fastapi_assignments "https://github.com/shravanshidruk16/innomatics-research-labs-advanced-genai-internship-february-2026/tree/main/IN226039402_FASTAPI"
click node_langchain_major "https://github.com/shravanshidruk16/innomatics-research-labs-advanced-genai-internship-february-2026/tree/main/Langchain/Assignment_3"
click node_langchain_main "https://github.com/shravanshidruk16/innomatics-research-labs-advanced-genai-internship-february-2026/blob/main/Langchain/Assignment_3/main.py"
click node_langchain_extract "https://github.com/shravanshidruk16/innomatics-research-labs-advanced-genai-internship-february-2026/blob/main/Langchain/Assignment_3/chains/extraction_chain.py"
click node_langchain_match "https://github.com/shravanshidruk16/innomatics-research-labs-advanced-genai-internship-february-2026/blob/main/Langchain/Assignment_3/chains/matching_chain.py"
click node_langchain_score "https://github.com/shravanshidruk16/innomatics-research-labs-advanced-genai-internship-february-2026/blob/main/Langchain/Assignment_3/chains/scoring_chain.py"
click node_langchain_explain "https://github.com/shravanshidruk16/innomatics-research-labs-advanced-genai-internship-february-2026/blob/main/Langchain/Assignment_3/chains/explanation_chain.py"
click node_rag_major "https://github.com/shravanshidruk16/innomatics-research-labs-advanced-genai-internship-february-2026/tree/main/RAG MAJOR PROJECT - CUSTOMER SUPPORT ASSISTANT/app"
click node_rag_loader "https://github.com/shravanshidruk16/innomatics-research-labs-advanced-genai-internship-february-2026/blob/main/RAG MAJOR PROJECT - CUSTOMER SUPPORT ASSISTANT/app/ingestion/loader.py"
click node_rag_chunker "https://github.com/shravanshidruk16/innomatics-research-labs-advanced-genai-internship-february-2026/blob/main/RAG MAJOR PROJECT - CUSTOMER SUPPORT ASSISTANT/app/ingestion/chunker.py"
click node_rag_embedder "https://github.com/shravanshidruk16/innomatics-research-labs-advanced-genai-internship-february-2026/blob/main/RAG MAJOR PROJECT - CUSTOMER SUPPORT ASSISTANT/app/ingestion/embedder.py"
click node_rag_retriever "https://github.com/shravanshidruk16/innomatics-research-labs-advanced-genai-internship-february-2026/blob/main/RAG MAJOR PROJECT - CUSTOMER SUPPORT ASSISTANT/app/retrieval/retriever.py"
click node_rag_router "https://github.com/shravanshidruk16/innomatics-research-labs-advanced-genai-internship-february-2026/blob/main/RAG MAJOR PROJECT - CUSTOMER SUPPORT ASSISTANT/app/routing/router.py"
click node_rag_workflow "https://github.com/shravanshidruk16/innomatics-research-labs-advanced-genai-internship-february-2026/blob/main/RAG MAJOR PROJECT - CUSTOMER SUPPORT ASSISTANT/app/graph/workflow.py"
click node_rag_llm "https://github.com/shravanshidruk16/innomatics-research-labs-advanced-genai-internship-february-2026/blob/main/RAG MAJOR PROJECT - CUSTOMER SUPPORT ASSISTANT/app/llm/llm.py"
click node_rag_hitl "https://github.com/shravanshidruk16/innomatics-research-labs-advanced-genai-internship-february-2026/blob/main/RAG MAJOR PROJECT - CUSTOMER SUPPORT ASSISTANT/app/hitl/escalation.py"
click node_rag_data "https://github.com/shravanshidruk16/innomatics-research-labs-advanced-genai-internship-february-2026/blob/main/RAG MAJOR PROJECT - CUSTOMER SUPPORT ASSISTANT/data/knowledge_base.pdf"
click node_rag_store "https://github.com/shravanshidruk16/innomatics-research-labs-advanced-genai-internship-february-2026/tree/main/RAG MAJOR PROJECT - CUSTOMER SUPPORT ASSISTANT/vectorstore"
click node_nlp_workspace "https://github.com/shravanshidruk16/innomatics-research-labs-advanced-genai-internship-february-2026/tree/main/NLP"
click node_nlp_task3 "https://github.com/shravanshidruk16/innomatics-research-labs-advanced-genai-internship-february-2026/blob/main/NLP/task3.py"
click node_python_workspace "https://github.com/shravanshidruk16/innomatics-research-labs-advanced-genai-internship-february-2026/tree/main/Python Programming"
click node_hackathon_workspace "https://github.com/shravanshidruk16/innomatics-research-labs-advanced-genai-internship-february-2026/tree/main/Entrance Test - Hackathon"
click node_hackathon_dataset "https://github.com/shravanshidruk16/innomatics-research-labs-advanced-genai-internship-february-2026/blob/main/Entrance Test - Hackathon/final_food_delivery_dataset.csv"

classDef toneNeutral fill:#f8fafc,stroke:#334155,stroke-width:1.5px,color:#0f172a
classDef toneBlue fill:#dbeafe,stroke:#2563eb,stroke-width:1.5px,color:#172554
classDef toneAmber fill:#fef3c7,stroke:#d97706,stroke-width:1.5px,color:#78350f
classDef toneMint fill:#dcfce7,stroke:#16a34a,stroke-width:1.5px,color:#14532d
classDef toneRose fill:#ffe4e6,stroke:#e11d48,stroke-width:1.5px,color:#881337
classDef toneIndigo fill:#e0e7ff,stroke:#4f46e5,stroke-width:1.5px,color:#312e81
classDef toneTeal fill:#ccfbf1,stroke:#0f766e,stroke-width:1.5px,color:#134e4a
class node_fastapi_major,node_fastapi_main,node_fastapi_models,node_fastapi_frontend,node_fastapi_assignments,node_rag_data,node_rag_store,node_hackathon_dataset toneBlue
class node_langchain_major,node_langchain_main,node_langchain_extract,node_langchain_match,node_langchain_score,node_langchain_explain toneAmber
class node_rag_major,node_rag_loader,node_rag_chunker,node_rag_embedder,node_rag_retriever,node_rag_router,node_rag_workflow,node_rag_llm,node_rag_hitl toneMint
class node_nlp_workspace,node_nlp_task3 toneRose
class node_python_workspace toneIndigo
class node_hackathon_workspace toneTeal
class node_repo_root toneNeutral
```

## Components

### FastAPI

Independent FastAPI practice and final project deliverables.

- [Course App](https://github.com/shravanshidruk16/innomatics-research-labs-advanced-genai-internship-february-2026/tree/HEAD/Final%20Major%20Project%20-%20FastAPI/Online_Course_Platform_FastAPI): FastAPI app · Standalone online course platform project. · `Final Major Project - FastAPI/Online_Course_Platform_FastAPI`
- [App API](https://github.com/shravanshidruk16/innomatics-research-labs-advanced-genai-internship-february-2026/blob/HEAD/Final%20Major%20Project%20-%20FastAPI/Online_Course_Platform_FastAPI/main.py): entrypoint · Main FastAPI application entry and route wiring. · `Final Major Project - FastAPI/Online_Course_Platform_FastAPI/main.py`
- [Models](https://github.com/shravanshidruk16/innomatics-research-labs-advanced-genai-internship-february-2026/blob/HEAD/Final%20Major%20Project%20-%20FastAPI/Online_Course_Platform_FastAPI/models.py): domain schema · Data structures and domain models for the course platform. · `Final Major Project - FastAPI/Online_Course_Platform_FastAPI/models.py`
- [Frontend](https://github.com/shravanshidruk16/innomatics-research-labs-advanced-genai-internship-february-2026/blob/HEAD/Final%20Major%20Project%20-%20FastAPI/Online_Course_Platform_FastAPI/frontend.py): client layer · UI/client integration layer for the project demo. · `Final Major Project - FastAPI/Online_Course_Platform_FastAPI/frontend.py`
- [Practice Set](https://github.com/shravanshidruk16/innomatics-research-labs-advanced-genai-internship-february-2026/tree/main/IN226039402_FASTAPI): exercise bundle · Separate FastAPI learning assignments with their own entrypoints. · `IN226039402_FASTAPI`

### LangChain

Resume-job matching pipeline built from chained LLM steps.

- [Resume Matcher](https://github.com/shravanshidruk16/innomatics-research-labs-advanced-genai-internship-february-2026/tree/main/Langchain/Assignment_3): LangChain pipeline · Modular resume-to-job matching workflow. · `Langchain/Assignment_3`
- [Orchestrator](https://github.com/shravanshidruk16/innomatics-research-labs-advanced-genai-internship-february-2026/blob/main/Langchain/Assignment_3/main.py): pipeline entrypoint · Main script that composes the extraction, matching, scoring, and explanation stages. · `Langchain/Assignment_3/main.py`
- [Extract](https://github.com/shravanshidruk16/innomatics-research-labs-advanced-genai-internship-february-2026/blob/main/Langchain/Assignment_3/chains/extraction_chain.py): chain · Information extraction chain for job and resume content. · `Langchain/Assignment_3/chains/extraction_chain.py`
- [Match](https://github.com/shravanshidruk16/innomatics-research-labs-advanced-genai-internship-february-2026/blob/main/Langchain/Assignment_3/chains/matching_chain.py): chain · Comparison chain for resume-job alignment. · `Langchain/Assignment_3/chains/matching_chain.py`
- [Score](https://github.com/shravanshidruk16/innomatics-research-labs-advanced-genai-internship-february-2026/blob/main/Langchain/Assignment_3/chains/scoring_chain.py): chain · Fit scoring chain for ranking the resume against the job description. · `Langchain/Assignment_3/chains/scoring_chain.py`
- [Explain](https://github.com/shravanshidruk16/innomatics-research-labs-advanced-genai-internship-february-2026/blob/main/Langchain/Assignment_3/chains/explanation_chain.py): chain · Explanation chain for summarizing the match result. · `Langchain/Assignment_3/chains/explanation_chain.py`

### RAG Assistant

Customer support assistant with offline indexing and online retrieval/orchestration.

- [Support Assistant](https://github.com/shravanshidruk16/innomatics-research-labs-advanced-genai-internship-february-2026/tree/HEAD/RAG%20MAJOR%20PROJECT%20-%20CUSTOMER%20SUPPORT%20ASSISTANT/app): RAG system · Customer support assistant built around indexed knowledge and workflow control. · `RAG MAJOR PROJECT - CUSTOMER SUPPORT ASSISTANT/app`
- [Loader](https://github.com/shravanshidruk16/innomatics-research-labs-advanced-genai-internship-february-2026/blob/HEAD/RAG%20MAJOR%20PROJECT%20-%20CUSTOMER%20SUPPORT%20ASSISTANT/app/ingestion/loader.py): ingestion stage · Loads the source knowledge base for indexing. · `RAG MAJOR PROJECT - CUSTOMER SUPPORT ASSISTANT/app/ingestion/loader.py`
- [Chunker](https://github.com/shravanshidruk16/innomatics-research-labs-advanced-genai-internship-february-2026/blob/HEAD/RAG%20MAJOR%20PROJECT%20-%20CUSTOMER%20SUPPORT%20ASSISTANT/app/ingestion/chunker.py): ingestion stage · Splits documents into retrieval-friendly chunks. · `RAG MAJOR PROJECT - CUSTOMER SUPPORT ASSISTANT/app/ingestion/chunker.py`
- [Embedder](https://github.com/shravanshidruk16/innomatics-research-labs-advanced-genai-internship-february-2026/blob/HEAD/RAG%20MAJOR%20PROJECT%20-%20CUSTOMER%20SUPPORT%20ASSISTANT/app/ingestion/embedder.py): ingestion stage · Creates embeddings and prepares persisted vector data. · `RAG MAJOR PROJECT - CUSTOMER SUPPORT ASSISTANT/app/ingestion/embedder.py`
- [Retriever](https://github.com/shravanshidruk16/innomatics-research-labs-advanced-genai-internship-february-2026/blob/HEAD/RAG%20MAJOR%20PROJECT%20-%20CUSTOMER%20SUPPORT%20ASSISTANT/app/retrieval/retriever.py): retrieval stage · Retrieves relevant knowledge base chunks from the vector store. · `RAG MAJOR PROJECT - CUSTOMER SUPPORT ASSISTANT/app/retrieval/retriever.py`
- [Router](https://github.com/shravanshidruk16/innomatics-research-labs-advanced-genai-internship-february-2026/blob/HEAD/RAG%20MAJOR%20PROJECT%20-%20CUSTOMER%20SUPPORT%20ASSISTANT/app/routing/router.py): decision stage · Selects response strategy based on query intent and confidence. · `RAG MAJOR PROJECT - CUSTOMER SUPPORT ASSISTANT/app/routing/router.py`
- [Workflow](https://github.com/shravanshidruk16/innomatics-research-labs-advanced-genai-internship-february-2026/blob/HEAD/RAG%20MAJOR%20PROJECT%20-%20CUSTOMER%20SUPPORT%20ASSISTANT/app/graph/workflow.py): orchestration graph · Coordinates the online query path across retrieval, LLM use, and escalation. · `RAG MAJOR PROJECT - CUSTOMER SUPPORT ASSISTANT/app/graph/workflow.py`
- [LLM Core](https://github.com/shravanshidruk16/innomatics-research-labs-advanced-genai-internship-february-2026/blob/HEAD/RAG%20MAJOR%20PROJECT%20-%20CUSTOMER%20SUPPORT%20ASSISTANT/app/llm/llm.py): generation stage · LLM wrapper used for grounded responses and workflow decisions. · `RAG MAJOR PROJECT - CUSTOMER SUPPORT ASSISTANT/app/llm/llm.py`
- [Escalation](https://github.com/shravanshidruk16/innomatics-research-labs-advanced-genai-internship-february-2026/blob/HEAD/RAG%20MAJOR%20PROJECT%20-%20CUSTOMER%20SUPPORT%20ASSISTANT/app/hitl/escalation.py): HITL fallback · Human-in-the-loop path for uncertain or sensitive queries. · `RAG MAJOR PROJECT - CUSTOMER SUPPORT ASSISTANT/app/hitl/escalation.py`

### NLP

Notebook-driven text analysis experiments and one script task.

- [NLP Lab](https://github.com/shravanshidruk16/innomatics-research-labs-advanced-genai-internship-february-2026/tree/main/NLP): analysis workspace · Notebook-based NLP experiments and a script task. · `NLP`
- [Task 3](https://github.com/shravanshidruk16/innomatics-research-labs-advanced-genai-internship-february-2026/blob/main/NLP/task3.py): script · Standalone NLP script among notebook experiments. · `NLP/task3.py`

### Python Programming

Weekly notebook exercises for core Python practice.

- [Python Weeks](https://github.com/shravanshidruk16/innomatics-research-labs-advanced-genai-internship-february-2026/tree/HEAD/Python%20Programming): notebook set · Weekly Python programming exercises. · `Python Programming`

### Hackathon

Dataset creation workspace for a food delivery data exercise.

- [Food Dataset](https://github.com/shravanshidruk16/innomatics-research-labs-advanced-genai-internship-february-2026/tree/HEAD/Entrance%20Test%20-%20Hackathon): data prep workspace · Hackathon-style notebook flow that creates a dataset artifact. · `Entrance Test - Hackathon`

### Supporting Artifacts

Generated documents, datasets, images, and persisted vector store state.

- [Knowledge Base](https://github.com/shravanshidruk16/innomatics-research-labs-advanced-genai-internship-february-2026/blob/HEAD/RAG%20MAJOR%20PROJECT%20-%20CUSTOMER%20SUPPORT%20ASSISTANT/data/knowledge_base.pdf): source document · PDF source document used to build the assistant's indexed knowledge. · `RAG MAJOR PROJECT - CUSTOMER SUPPORT ASSISTANT/data/knowledge_base.pdf`
- [Vector Store](https://github.com/shravanshidruk16/innomatics-research-labs-advanced-genai-internship-february-2026/tree/HEAD/RAG%20MAJOR%20PROJECT%20-%20CUSTOMER%20SUPPORT%20ASSISTANT/vectorstore): persistent index · Chroma persistence backing retrieval at runtime. · `RAG MAJOR PROJECT - CUSTOMER SUPPORT ASSISTANT/vectorstore`
- [Food CSV](https://github.com/shravanshidruk16/innomatics-research-labs-advanced-genai-internship-february-2026/blob/HEAD/Entrance%20Test%20-%20Hackathon/final_food_delivery_dataset.csv): generated dataset · Generated food delivery dataset output. · `Entrance Test - Hackathon/final_food_delivery_dataset.csv`

### Other components

- **Internship WS**: mono-repo · Top-level internship workspace containing several largely independent deliverables.

## Connections

- Internship WS → Course App: contains · Workspace includes a standalone FastAPI final project.
- Internship WS → Practice Set: contains · Workspace includes multiple FastAPI practice assignments.
- Internship WS → Resume Matcher: contains · Workspace includes a modular LangChain assignment.
- Internship WS → Support Assistant: contains · Workspace includes the RAG customer support system.
- Internship WS → NLP Lab: contains · Workspace includes NLP notebooks and script tasks.
- Internship WS → Python Weeks: contains · Workspace includes weekly Python exercises.
- Internship WS → Food Dataset: contains · Workspace includes dataset creation notebooks.
- Course App → App API: entrypoint · Application starts from the FastAPI main module.
- Course App → Models: defines · Domain models support the API layer.
- Course App → Frontend: integrates · Frontend/client integration sits beside the API.
- Resume Matcher → Orchestrator: orchestrates · Main script composes the pipeline stages.
- Orchestrator → Extract: runs · First stage extracts structured information.
- Orchestrator → Match: runs · Next stage compares resume and job description.
- Orchestrator → Score: runs · Scoring stage ranks fit quality.
- Orchestrator → Explain: runs · Explanation stage summarizes the result.
- Support Assistant → Loader: offline ingest · Assistant begins with source document loading.
- Loader → Chunker: prepares · Loaded document is chunked for indexing.
- Chunker → Embedder: indexes · Chunks are embedded for vector retrieval.
- Embedder → Vector Store: persists · Embeddings are stored in Chroma persistence.
- Support Assistant → Workflow: online runtime · Runtime query handling is coordinated by the workflow graph.
- Workflow → Router: routes · Workflow first decides the handling path.
- Router → Retriever: retrieves · Knowledge-grounded path queries the vector store.
- Retriever → LLM Core: grounds · Retrieved context is passed to the LLM.
- Router → Escalation: escalates · Uncertain or sensitive requests go to human-in-the-loop escalation.
- Workflow → LLM Core: generates · LLM produces the final response in the workflow.
- Support Assistant → Knowledge Base: sources · The PDF knowledge base seeds ingestion.
- NLP Lab → Task 3: includes · NLP workspace includes a standalone script among notebook tasks.
- Food Dataset → Food CSV: produces · Dataset creation notebooks generate the CSV artifact.