Deployment and Upgrade for Securities Research Report Retrieval

Securities research report data primarily comes from licensed securities firm research institutes and public industry research disclosure channels.

What this category of data looks like

Securities research report data primarily comes from licensed securities firm research institutes and public industry research disclosure channels. Update frequency fluctuates with trading days: released frequently during trading days, with significantly fewer updates on non-trading days. Each document’s structure includes sections such as title, core logic, industry and individual stock fundamental data, valuation calculations, risk warnings, etc. Fields include issuing institution, release date, covered targets, rating, target price (unit: yuan). Some documents embed structured tables and charts, with content lengths mostly ranging from thousands to tens of thousands of characters.

What constraints do these characteristics impose during deployment and upgrade

The high-frequency update nature of research reports requires configuring incremental index synchronization tasks during deployment to avoid excessive computing resource usage from full reindexing. The long-text structure requires configuring context window thresholds adapted to the length of financial research reports, and the parsing link must support embedded structured tables and chart content. Fields contain clear financial quantitative indicators, requiring support for precise filtering by fields such as release date and rating during retrieval, with corresponding metadata indexes configured during deployment. The upgrade link requires synchronized updates to research report parsing rules to adapt to format adjustments in newly released reports and avoid parsing errors.

How to set configurations

Configuration ItemRecommended ValueRationale
PARSE_FILE_TIMEOUT_SECONDS600 secondsIndividual research reports have long lengths, and the parsing process needs to handle embedded charts and text; the timeout period must be adapted to long document parsing
maxContext8000–16000 charactersThe core content of research reports mostly falls within the thousands-of-characters range, adapted to splicing retrieved long-context research report segments
RECALL_TOP_KTop 10–15 resultsResearch reports have high information density; too many retrieved results will introduce irrelevant content, while too few will fail to cover core viewpoints
UPLOAD_FILE_MAX_SIZE1000 MBReasonable upper limit for single research report collections or batch upload scenarios, avoiding excessive storage usage from a single upload
SCHEDULER_INTERVAL300 secondsResearch reports have high update frequency; the scheduled synchronization interval must balance timeliness and resource usage
SIMILARITY_THRESHOLD0.75–0.85Semantic similarity of financial terms is high; the threshold must be higher than general scenarios to filter low-relevance retrieved results

The parameter values provided on this page are common recommended starting points 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 using locally relevant sample data before finalizing settings.

Three common mistakes

  • Phenomenon: A 503 status code is returned when calling the interface after deployment, and GPU memory exhaustion errors occur during concurrent access. Cause: Concurrent GPU memory quotas are not calculated based on the context requirements of long research reports, and the single-card concurrency threshold of general large models is directly applied.
  • Phenomenon: The container fails to start with an INITIALROOT password verification failure, and the management backend cannot be logged into. Cause: The `INITIALROOT` environment variable in docker-compose.yml is not configured correctly, or the variable value contains special characters that are not escaped.
  • Phenomenon: Parsing timeouts or process crashes occur during batch research report uploads. Cause: PARSE_FILE_TIMEOUT_SECONDS and concurrent upload thread counts are not adjusted based on hardware specifications, exceeding the computing and storage carrying capacity of the device.

How to confirm configurations are correct

  • Execute a single research report parsing task, verify that the parsed fields include core metadata such as issuing institution and target price, and adjust corresponding parameters until the task completes successfully.
  • Initiate multiple concurrent retrieval requests, monitor hardware resource usage, and adjust concurrent thread counts and retrieval configurations until resource usage matches hardware specifications.
  • Trigger a scheduled synchronization task, check whether research reports released in the corresponding time period are added to the vector database, and adjust synchronization interval parameters to match the update rhythm.
  • Enter professional financial search terms, verify the relevance and timeliness of retrieved results, and adjust the similarity threshold until results meet expectations.

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.