Unverified50% confidenceFactExact time
在 Langfuse 中追踪被组织为层次化的 Span 结构，顶层 Trace 代表一次完整的用户请求，下面可嵌套 Generation Span、Tool Span、Retrieval Span 等子 Span
1
Sources
50%
Confidence
Long-term
Relevance
8/20/2026
First Seen
Sources
Related Claims
UnverifiedTools such as LangSmith, Langfuse, and Weights & Biases Weave provide structured trace storage, where each trace contains a Span tree structure recording inputs, outputs, latency, token consumption, and metadata.66% similarUnverifiedThe complete RAG pipeline includes an offline phase (document parsing → text chunking → Embedding vectorization → writing to a vector database) and an online phase (user query → query vectorization → vector retrieval → recalled document reranking → Prompt construction → LLM response generation).65% similarUnverifiedLLM tracing tools such as LangSmith, LangFuse, and Arize Phoenix can capture the Prompt/Completion pairs, tool call chains, and token consumption for each inference.64% similarVerifiedThe RAG architecture is divided into a retrieval stage and a generation stage; the retrieval stage uses vector databases (such as Chroma, Pinecone, and Milvus) to recall relevant text segments via cosine similarity.64% similarVerifiedLangSmith provides Trace tracking capabilities, recording the input and output, latency, and token consumption of every LLM call.63% similar
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