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Local Single-Agent Mode\n\nA locally running Llama 3 model served through Ollama acts as a private\nmental health companion. A custom system prompt provides behavioural\nconstraints and safety instructions.\n\n2. Multi-Agent Mode\n\nThe system separates responsibilities between two agents:\n\nEmotion & Safety Analyzer --- analyzes the user's emotional\nstate, intensity, and potential safety risks.\n\nEmpathetic Support Assistant --- generates a warm and supportive\nresponse using the analysis.\n\nCrewAI orchestrates the agents sequentially, while Flask exposes the\nchatbot through HTTP endpoints.\n\n3. n8n Workflow\n\nThe n8n implementation uses a webhook-driven workflow:\n\nWebhook → Edit Fields → Emotion Analyzer → Support Advisor → Respond to Webhook\n\nProject Structure\n\nMental-Health-Support-Chatbot/\n├── bot.py\n├── Modelfile\n├── app.py\n├── templates/\n├── static/\n├── n8n/\n└── README.md\n\nThe exact project structure may vary depending on the implementation\nand files included in the repository.\n\nGetting Started\n\nPrerequisites\n\nMake sure you have:\n\nPython 3.10 or 3.11\n\nOllama\n\nLlama 3 model\n\nRequired Python packages\n\nn8n (if using the workflow implementation)\n\nGoogle Gemini API key (for the Gemini-based response layer)\n\nRun Ollama\n\nCreate the custom local model using the provided Modelfile:\n\nollama create mental-agent -f ./Modelfile\n\nVerify the model:\n\nollama list\n\nInstall Python Dependencies\n\npip install -r requirements.txt\n\nConfigure Environment Variables\n\nCreate a .env file and add your API credentials locally.\n\nDo not commit API keys, passwords, or other secrets to GitHub.\n\nRun the Application\n\npython app.py\n\nThe Flask application will start locally and can be accessed through the\ndisplayed local URL.\n\nSafety & Disclaimer\n\nThis project is intended to provide conversational emotional support and\nis not a replacement for professional mental health care, diagnosis,\ntherapy, or emergency services.\n\nThe safety mechanisms implemented in the project are basic and\nrule-based and have not been clinically validated. Users experiencing an\nemergency or immediate danger should contact appropriate emergency\nservices or qualified professionals.\n\nFuture Scope\n\nSecure user authentication and progress tracking\n\nFine-tuning on specialised therapeutic datasets\n\nVoice input and multimodal analysis\n\nImproved clinical escalation mechanisms\n\nMulti-language support\n\nRAG-based knowledge grounding\n\nExpanded safety evaluation and validation\n\nAuthor\n\nAnmol Tiwari\n\nMCA --- ABES Engineering College\n\nLicense\n\nThis project is developed for academic and educational purposes.\n=======\n# Mental-health-bot\nAI-powered Mental Health Support Chatbot built with Ollama, Llama 3, CrewAI, LangChain, Gemini API, Flask, and n8n. 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