FlowiseAI/Flowise · error · Error

${e}

Error message

${e}

What it means

Generic catch-all in the Pinecone (LlamaIndex) node wrapping `VectorStoreIndex.fromDocuments`. Any failure during LlamaIndex index construction (embedding, Pinecone write, service context error) is re-thrown as `new Error(e)`, losing the original stack.

Source

Thrown at packages/components/nodes/vectorstores/Pinecone/Pinecone_LlamaIndex.ts:156

            for (let i = 0; i < flattenDocs.length; i += 1) {
                if (flattenDocs[i] && flattenDocs[i].pageContent) {
                    finalDocs.push(new LCDocument(flattenDocs[i]))
                }
            }

            const llamadocs: Document[] = []
            for (const doc of finalDocs) {
                llamadocs.push(new Document({ text: doc.pageContent, metadata: doc.metadata }))
            }

            const serviceContext = serviceContextFromDefaults({ llm: model, embedModel: embeddings })
            const storageContext = await storageContextFromDefaults({ vectorStore: pcvs })

            try {
                await VectorStoreIndex.fromDocuments(llamadocs, { serviceContext, storageContext })
                return { numAdded: finalDocs.length, addedDocs: finalDocs }
            } catch (e) {
                throw new Error(e)
            }
        }
    }

    async init(nodeData: INodeData, _: string, options: ICommonObject): Promise<any> {
        const indexName = nodeData.inputs?.pineconeIndex as string
        const pineconeNamespace = nodeData.inputs?.pineconeNamespace as string
        const pineconeMetadataFilter = nodeData.inputs?.pineconeMetadataFilter
        const embeddings = nodeData.inputs?.embeddings as BaseEmbedding
        const model = nodeData.inputs?.model
        const topK = nodeData.inputs?.topK as string
        const k = topK ? parseFloat(topK) : 4

        const credentialData = await getCredentialData(nodeData.credential ?? '', options)
        const pineconeApiKey = getCredentialParam('pineconeApiKey', credentialData, nodeData)

        const obj: PineconeParams = {
            indexName,

View on GitHub (pinned to abe4a8601a)

Solutions

1. Inspect the flattened message for the LlamaIndex/Pinecone underlying error.
2. Confirm `model` and `embeddings` are LlamaIndex-compatible `BaseEmbedding`/LLM instances.
3. Verify Pinecone API key, index, and that the index dimension matches `embedModel`.
4. Re-wrap preserving the original error (see fix).

Example fix

// before
} catch (e) {
    throw new Error(e)
}
// after — preserve cause
} catch (e) {
    throw e instanceof Error ? e : new Error(String(e))
}

// preflight: ensure LlamaIndex-compatible embed model + matching dimension
if (!embeddings || typeof (embeddings as any).getTextEmbedding !== 'function') {
  throw new Error('embeddings must be a LlamaIndex BaseEmbedding')
}
const dim = (await (embeddings as any).getTextEmbedding('test')).length
if (indexDimension && dim !== indexDimension) throw new Error(`dim ${dim} != index ${indexDimension}`)

function isLlamaIndexEmbedding(v: unknown): boolean {
  return typeof v === 'object' && v !== null && typeof (v as any).getTextEmbedding === 'function'
}

try {
  await VectorStoreIndex.fromDocuments(llamadocs, { serviceContext, storageContext })
} catch (e) {
  throw e instanceof Error ? e : new Error(`LlamaIndex Pinecone index build failed: ${String(e)}`)
}

When it happens

Trigger: Pinecone client/auth failure; embedding model error; service context misconfiguration (missing llm/embedModel); dimension mismatch between embedModel and the Pinecone index; network failure to Pinecone.

Common situations: Mixing LlamaIndex and LangChain embedding types; Pinecone serverless region mismatch; API key expired; embedding model returns a dimension different from the index.

Related errors

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AI-assisted analysis of FlowiseAI/Flowise@abe4a8601a (2026-08-12). Data as JSON: /api/errors/d8e23dec05583ed2. Report an issue: GitHub.