RAGFlow is a leading open-source Retrieval-Augmented Generation (RAG) engine that fuses cutting-edge RAG with Agent capabilities to create a superior context layer for LLMs
fix(go-models): harden 302.AI driver requests (#15289)
## Summary - Harden the 302.AI model driver request validation and response parsing paths. - Add focused tests for chat request mode, model listing, malformed provider responses, and input validation. ## What changed - Validate API keys, model names, rerank queries, ASR file paths, OCR inputs, parse URLs, task IDs, and model-list IDs before use. - Keep chat and streaming methods from accepting conflicting `stream` values in request payloads. - Send `ListModels` as a bodyless GET and parse the response with typed JSON structs instead of unchecked assertions. - Remove raw SSE event logging from stream handling. ## Why The driver could panic or send inconsistent requests when optional config fields were nil, empty, malformed, or contradicted the method path. This keeps provider-driver behavior explicit while preserving the existing supported 302.AI flows. Closes #14736
O
oktofeesh committed
8468227a1ab4ba8c66ba33c6c83b2b5ac7773b5d
Parent: 0694b4a
Committed by GitHub <noreply@github.com>
on 5/28/2026, 5:33:01 AM