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Veröffentlicht July 5, 202410 Min. Lesezeit

Integrating AI into React Applications

Practical patterns for integrating OpenAI, LangChain, and vector databases into React and Next.js applications without over-engineering.

AIReactLangChainOpenAI

The AI Hype vs. Reality

Not every app needs AI. But when AI genuinely improves the user experience, here's how to integrate it cleanly.

Streaming Responses with React

For chat interfaces, streaming is essential for perceived performance:

const response = await openai.chat.completions.create({
  model: 'gpt-4',
  messages,
  stream: true,

for await (const chunk of response) { const delta = chunk.choices[0]?.delta?.content ?? ''; setMessage(prev => prev + delta); } ```

RAG Pipelines

For domain-specific knowledge, RAG (Retrieval-Augmented Generation) beats fine-tuning in most cases:

  1. Embed your documents with OpenAI embeddings
  2. Store vectors in Pinecone or FAISS
  3. Retrieve relevant context at query time
  4. Pass context + query to the LLM

Conclusion

Start simple, measure impact, then add complexity only where it matters.