fix: corriger le type de projet de 'Personal Project' à 'Academic Project'

content/projects/nlp-hr-onboarding.md

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+---
+slug: nlp-hr-onboarding
+title: Intelligent HR Onboarding Assistant
+type: Academic Project
+description: Intelligent HR onboarding assistant using RAG, LangChain agents, and MistralAI embeddings to help new employees navigate company policies, employee directory, and administrative tasks. 
+shortDescription: An AI-powered assistant for streamlining HR onboarding processes and improving new hire experience.
+publishedAt: 2026-03-13
+readingTime: 3
+favorite: false
+status: Completed
+tags:
+  - Python
+  - NLP
+  - LangChain
+  - RAG
+icon: i-ph-robot-duotone
+---
+
+**NLP Project — Master M2**  
+*Authors: Arthur DANJOU, Aksscel Meh-Rik, Moritz von SIEMENS*
+
+::BackgroundTitle{title="Project Overview"}
+::
+
+The **Intelligent HR Onboarding Assistant** is a conversational AI system designed to guide new employees during their first week at **TechCorp**. It combines retrieval-augmented generation, tool-using agents, and conversational memory to provide accurate and actionable HR support.
+
+The assistant can answer policy questions, retrieve employee information, schedule internal meetings, and prepare leave requests from natural-language prompts.
+
+::BackgroundTitle{title="Key Features"}
+::
+
+- **Semantic HR policy search** powered by a RAG pipeline.
+- **Employee directory lookup** from structured JSON records.
+- **Meeting scheduling tools** integrated through LangChain.
+- **Automated leave request workflow** from chat instructions.
+- **Sliding-window memory** to keep multi-turn context coherent.
+- **Interactive Gradio UI** with visible agent actions and tool calls.
+
+::BackgroundTitle{title="Architecture"}
+::
+
+```
+┌──────────────────────────────────────────────────────────┐
+│           HR Onboarding Assistant — TechCorp            │
+│                                                         │
+│  📝 System prompts (LangChain LCEL)                     │
+│  🧠 Sliding window conversational memory                │
+│  🔧 Tools:                                              │
+│     ├── 🔍 Knowledge base search (RAG)                  │
+│     ├── 👤 Employee directory                           │
+│     ├── 📅 Meeting scheduling                           │
+│     ├── 🏖️ Leave request submission                     │
+│     └── 🕐 Current date and time                        │
+│  🔄 ReAct loop: reason → act → observe                  │
+│  📊 MistralAI Embeddings + Qdrant Vector Store          │
+└──────────────────────────────────────────────────────────┘
+```
+
+::BackgroundTitle{title="Prerequisites"}
+::
+
+- Python ≥ 3.13
+- MistralAI API key
+
+::BackgroundTitle{title="Installation"}
+::
+
+1. **Clone the repository**
+   ```bash
+   git clone <repository-url>
+   cd NLP-Intelligent-HR-Onboarding-Assistant-with-RAG-and-LangChain
+   ```
+
+2. **Install dependencies**
+   ```bash
+   uv sync
+   ```
+
+3. **Configure MistralAI API key**
+   
+   Set the environment variable:
+   ```bash
+   export MISTRAL_API_KEY="your_api_key"
+   ```
+
+::BackgroundTitle{title="Usage"}
+::
+
+### Run the Jupyter notebook
+
+```bash
+jupyter notebook projet.ipynb
+```
+
+Execute cells sequentially to:
+1. Analyze tokenization of HR documents
+2. Create the Qdrant vector database
+3. Initialize the ReAct agent
+4. Run demonstrations
+5. Launch the Gradio interface (runs on `http://127.0.0.1:7860`)
+
+### Data structure
+
+```
+data/
+├── entreprise.md    # HR knowledge base (leave policy, remote work, etc.)
+└── employés.json    # TechCorp employee directory
+```
+
+::BackgroundTitle{title="Learning Modules"}
+::
+
+| TP | Concept | Usage |
+|:---|:--------|:------|
+| **TP1** | Embeddings | Document vectorization and cosine similarity retrieval |
+| **TP2** | BPE Tokenization | Token-cost analysis with FR/EN comparison |
+| **TP3** | LLM + LangChain | ChatMistralAI setup, prompts, and LCEL chains |
+| **TP4** | Agents + Memory | `@tool` usage, ReAct orchestration, sliding-window memory |
+| **TP5** | RAG + Gradio | Qdrant indexing, semantic retrieval, interactive UI |
+
+::BackgroundTitle{title="Technologies"}
+::
+
+- **LangChain**: LLM orchestration framework
+- **MistralAI**: LLM inference and embeddings (`mistral-embed`)
+- **Qdrant**: In-memory vector database
+- **Gradio**: Interactive web interface
+- **tiktoken**: BPE tokenization analysis
+- **pandas**: Employee data manipulation
+
+::BackgroundTitle{title="Main Dependencies"}
+::
+
+```
+langchain>=1.2.11
+langchain-mistralai>=1.1.1
+langchain-qdrant>=1.1.0
+gradio>=6.9.0
+tiktoken>=0.12.0
+pandas>=3.0.1
+```
+
+::BackgroundTitle{title="Example Prompts"}
+::
+
+- "How many days of annual leave do I have?"
+- "What is the remote work policy?"
+- "Give me Claire Petit's contact information"
+- "Schedule a meeting with the Data Science team tomorrow at 2pm"
+- "I want to request leave from January 15th to 20th"
+
+::BackgroundTitle{title="Authors"}
+::
+
+- **Arthur DANJOU**
+- **Axelle MERIC**
+- **Moritz von SIEMENS**
+
+*Project completed as part of the Natural Language Processing course — Master M2*