1 Smart Chatbot PFE

Project Overview

• Conceive and implement a conversational assistant capable of understanding complex user queries and automatising appointment scheduling.
• Multilingual system requirements with support for i18n and integration with Google Translate API to handle multiple languages and regional variants.

Responsibilities & Tasks

• Design the NLP pipeline (intent/entity recognition, preprocessing) using spaCy and transformer embeddings (BERT) and implement dialogue management with Rasa.
• Build backend APIs in Python with FastAPI, connect to MongoDB for conversation/session storage, and implement integrations with Google Dialogflow and Calendly for scheduling.

Technical Stack & Integrations

• NLP: spaCy, BERT; Dialogue: Rasa; Backend: Python, FastAPI.
• Integrations: Google Dialogflow, Calendly; Database: MongoDB; Multilingual: i18n patterns and Google Translate API.

Deliverables & Expectations

• A working conversational assistant prototype that understands complex queries and can automatically book appointments via Calendly (or equivalent) through integrated flows.
• Documentation including architecture, API endpoints, data schemas in MongoDB, testing strategy, and instructions to run the system locally.

How to Apply

• To apply, send your application to issam@code-reason.com referencing the project title in the subject line.
• Suggested email subject: "Application — Smart Chatbot PFE" and include your CV, a short cover letter, and any relevant project links or code samples.