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Psychology Chatbot

Real-world project · AICTE-aligned · AI-graded · Audit-ready certificate

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About this project

Psychology Chatbot

Objective: Create an AI-powered chatbot to support users with psychological queries and mental health awareness.

Context: In India, access to mental health resources is limited, and stigma often prevents people from seeking help. A psychology chatbot can provide accessible, anonymous support and information, bridging gaps in mental health care.

What you'll build: You'll design a chatbot using Python with NLP libraries (NLTK, spaCy) and frameworks like Dialogflow or Rasa for conversational intelligence and sentiment analysis. The project includes ethical conversation flow design, integration of psychological support models, and a user-friendly web interface built with Flask or Django, storing interactions securely in MongoDB or Firebase.

Deliverables: Functional psychology chatbot, web interface, codebase, and a report on ethical considerations and system evaluation.

Milestones

No submission required for this milestone.

2. Research on Psychological Interaction Models & Ethics

5 marks 2d

Summarize at least three psychological interaction models relevant to chatbot counseling and outline key ethical considerations, including privacy and user safety. Submit a concise report (2-3 pages) with citations. Done means your report clearly links models and ethics to chatbot design, demonstrating understanding of psychological and ethical foundations.

3. Chatbot Conversation Flow Design

5 marks 3d

Draft a detailed conversation flow diagram for common user scenarios (e.g., stress, anxiety, general support), including greeting, escalation, and fallback paths. Submit the diagram (using a tool like draw.io or Lucidchart) and a brief explanation (max 1 page). Done means flows are logical, cover edge cases, and reflect psychological best practices.

4. NLP and Sentiment Analysis Module Development

5 marks 5d

Develop and submit code for an NLP module that recognizes user intents and performs basic sentiment analysis on input text. Include a README explaining model choices and sample input/output. Done means your module accurately classifies at least five intents and detects positive, negative, and neutral sentiments in test cases.

5. Chatbot Engine Integration (Dialogflow / Rasa)

5 marks 5d

Integrate your conversation flow and NLP module into a Dialogflow or Rasa chatbot engine. Submit configuration files, integration scripts, and a demo video (2-3 minutes) showing the chatbot handling at least three distinct conversation paths. Done means the engine processes user input, triggers correct flows, and responds appropriately.

6. Interface Development (Web/Mobile)

5 marks 5d

Design and implement a simple web or mobile interface for users to interact with the chatbot. Submit source code, screenshots, and a brief user guide. Done means users can send/receive messages, view conversation history, and the interface is functional and visually clear.

7. Beta Testing with Simulated Scenarios

10 marks 5d

Conduct beta testing with at least five simulated user scenarios covering various emotional states and intents. Submit a test report summarizing each scenario, chatbot responses, and any issues found. Done means your report demonstrates thorough testing, identifies limitations, and suggests improvements.

8. Deployment and Feedback Collection

15 marks 5d

Deploy your chatbot on a public or test server and collect feedback from at least three real users. Submit deployment instructions, user feedback summaries, and a reflection on improvements made post-feedback. Done means your chatbot is accessible, feedback is documented, and you show evidence of iterative refinement.

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Upcoming sessions

Session	Window	Enrolled
Psychology Chatbot	11 Jun 2026 to 10 Jun 2028	0

Skills you'll learn

Natural Language Processing (NLP)Chatbot Development (rule-based and AI-based)Sentiment AnalysisEthical AI UsageUI/UX DesignMental Health Awareness (basic level)

Tools used

Python with NLTK / spaCy for NLP Dialogflow / Rasa for chatbot development Flask/Django (for web interface) MongoDB / Firebase (to store conversations) TensorFlow (for training sentiment analysis models) GitHubPostman

Prerequisites

Python programming Basic understanding of psychology and emotional intelligence Experience with chatbot frameworks (like Rasa or Dialogflow) Knowledge of NLP models and concepts

Available mentors

Priyang Kumar

Free

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Psychology Chatbot

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Psychology Chatbot

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