What data for this category looks like
Electronic component research and investment data mainly comes from four sources: original manufacturer public datasheets, industry association standardized parameter libraries, vertical e-commerce supply ledgers, and securities firm research and investment selection analysis reports. Update rhythm fluctuates with original manufacturer new product launches, supply cycle adjustments, and industry research report updates. No fixed cycle exists. Single documents are mostly multi-page PDFs or structured tables. Core fields include component model, package type, rated voltage, rated current, operating temperature range, pin definitions, alternative models, and more. Units include volts, amps, degrees Celsius, pin count and other professional measurement identifiers.
What constraints do these characteristics impose on deployment and upgrade
The multi-source heterogeneous format of electronic component data requires the deployment phase to adapt to multiple parsing engines for PDF, Excel, web pages, and other formats. The lack of a fixed update rhythm requires the upgrade link to support incremental synchronization tasks. This avoids redundant data from full re-scanning. The multi-field, multi-unit structure requires unit normalization and field standardization during the preprocessing phase. This prevents confusion in vector database storage dimensions. The long document characteristic requires segment configuration to balance contextual relevance. This avoids breaking the semantic integrity of associated parameters such as pins and voltage.
How to set configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
PARSE_FILE_TIMEOUT_SECONDS | 900 seconds | Electronic component manufacturer datasheets are mostly multi-page professional documents with long parsing times, avoiding interrupting the parsing process due to timeout |
UPLOAD_FILE_MAX_SIZE | 2000 MB | Supports batch uploading of multiple manufacturer datasheet collection packages to meet the large-scale document import needs of research and investment teams |
chunk_size | 800–1200 characters | Matches the length of the core parameter section of a single parameter document, avoiding splitting associated fields such as pins and voltage to ensure retrieval context integrity |
RECALL_TOP_N | Top 8 entries | Meets the needs of multi-dimensional parameter comparison for research and investment, while controlling context length to avoid exceeding model processing limits |
SIMILARITY_THRESHOLD | 0.72–0.85 | Balances parameter matching accuracy and alternative model recall range. Too low will introduce irrelevant component models, while too high will miss valid alternative solutions |
VLLM_WORKER_NUM | 4–6 workers | Adapts to the load of concurrent processing of multiple document parsing and retrieval requests, avoiding resource exhaustion on a single node |
The parameter values provided on this page are common starting point recommendations for configuration. Actual values are affected by material form, data volume and business rules. Specific issues require specific analysis, and it is recommended to test on your own samples before finalizing settings.
Three Common Mistakes
- Symptom: After configuring an Ollama local model, a
model not founderror is returned during retrieval. Cause: The model access address and provider parameters were not correctly configured in.env.local, resulting in channel verification failure. - Symptom: After vLLM deployment, concurrent query speed is slow and single-request responses time out. Cause: The
max_batch_sizeandVLLM_WORKER_NUMparameters were not adjusted, failing to adapt to the long context processing load after parsing electronic component documents. - Symptom: After batch uploading electronic component datasheets, some documents show a
Parsing failedstatus. Cause: A reasonablePARSE_FILE_TIMEOUT_SECONDSparameter was not set, and a short duration cannot complete full parsing of multi-page professional documents.
How to Confirm Configuration Is Correct
- Upload a standard electronic component datasheet, and verify that the parsed fields include core business information, with field mapping matching preset rules.
- Initiate a parameter comparison query, and verify that the matching degree of returned results falls within the preset threshold range, with no obvious irrelevant models mixed in.
- Start a multi-concurrent query task, and verify that the vLLM interface response time meets business expectations, with no continuous timeout errors.
- Check the vector database connection logs, and confirm there are no abnormal records such as dimension mismatches or connection interruptions.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-14.