PHP remains an excellent choice for AI chatbots — especially when integrating with WhatsApp, Slack, or custom web widgets. The key is designing a clean conversation pipeline.
Architecture Overview
- Webhook endpoint — receives user messages
- Session store — Redis or database for conversation history
- LLM provider — OpenAI, Anthropic, or local models via Ollama
- Response formatter — markdown to plain text, buttons, or cards
Context & Memory
Trim conversation history to fit token limits. Store system prompts separately and inject relevant user metadata (name, plan tier) on each request.
RAG for Accurate Answers
Retrieval-Augmented Generation lets bots answer from your docs: chunk content, embed with an API, store vectors, and retrieve top matches before prompting the LLM.
Production Tips
- Cache frequent FAQ answers to cut API costs.
- Add fallback messages when the model times out.
- Monitor hallucinations with human review queues for sensitive domains.