Our customer onboarding chatbot built on OpenAI's API is hallucinating refund policies today, so how do I implement strict system prompts and retrieval augmented generation to fix it?
Download run
Fan-out diagram
The searches the AI actually ran for this prompt.
SEED QUERY
Our customer onboarding chatbot built on OpenAI's API is hallucinating refund policies today, so how do I implement strict system prompts and retrieval augmented generation to fix it?
1 real search · 1 real-search pass
OpenAI API documentation Responses API file search vector stores retrieval prompt engineering hallucinations structured outputs 2026Google ↗
OBSERVEDOther / navigational
Badge and edge weight = share of passes that produced the query. Hover a query for its intent and routing format.
Query classes
Google's semantic query class for every sub-query: what kind of answer each search is after, simulated vs real.
ChatGPT real searches (1)
Classes come from the query-classifier (a local Laya model). 1 of 1 calls are low-confidence (under 50%) — hover a query in the table to see its confidence.
Searches and sources
ChatGPT1 real searches · gpt-6
OpenAI API documentation Responses API file search vector stores retrieval prompt engineering hallucinations structured outputs 2026 Google ↗
- Assistants migration guide · platform.openai.com
- Create a model response · developers.openai.com