What this category's data looks like
Feed industry investment research data mainly comes from public data released by industry associations, market interfaces of commodity exchanges, internal production ledgers of feed enterprises, and feed safety standard documents issued by the Ministry of Agriculture and Rural Affairs.
There are three update schedules: spot market data is updated daily, industry monthly reports are updated every 10 days, and standard documents are updated every six months.
Three types of document structures are used:
- Structured raw material quotation tables, with fields including variety, origin, release date, quotation and others
- Unstructured industry research reports, including supply and demand analysis and policy interpretation content
- Structured raw material test data, with fields including batch, test item, indicator value, unit and others
Units vary across different data types, including yuan/ton, mg/kg, g/kg and others.
What constraints do these characteristics impose on the database and operations link
High-frequency updated spot market data generates a large number of write requests. Separate storage partitions must be created to avoid resource competition with low-frequency updated standard documents and research report data.
Multi-dimensional associated data requires cross-table indexes to support fast queries of quotations, test results and industry analysis for the same variety across different cycles.
Document lengths vary widely: some entries are only a few lines of quotation information, while others can be dozens of pages of research reports. Flexible sharding rules are needed to balance storage efficiency and query speed.
Multi-source data synchronization requires handling issues such as interface fluctuations and format differences. Retry and format verification mechanisms must be configured to prevent data loss or cleaning errors.
Additionally, changes to some standard documents will affect full investment research logic. Historical versions must be retained for traceback and verification.
How to set the configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
PARSE_FILE_TIMEOUT_SECONDS | 900 seconds | Feed industry research reports vary widely in length, with the longest reaching dozens of pages. Parsing takes a long time. This configuration prevents task interruptions mid-run |
RECALL_CHUNK_SIZE | 800–1200 characters | Covers the sharding needs of both short feed raw material quotation entries and long research report paragraphs, balances recall accuracy and query efficiency |
RERANK_TOP_N | Top 8 entries | Feed industry investment research data includes multi-dimensional associated entries. A sufficient number of candidate results must be recalled before reranking to avoid missing key information |
REDIS_MAX_MEMORY | 16000 MB | High-frequency updated market data caching occupies significant memory. This configuration prevents service interruptions caused by cache overflow |
DB_SYNC_RETRY_TIMES | 3 retries | Interface fluctuations may occur during multi-source data synchronization. Multiple retries reduce the probability of data loss |
MAX_CONTEXT_LENGTH | 12000 characters | Feed industry investment research requires association of multiple historical reports and real-time market data. This length covers common context requirements |
The parameter values provided on this page are common starting points for configuration. Actual values are affected by material form, data volume and business rules. Specific issues require specific analysis. It is recommended to test on your own samples before finalizing settings.
Three common misconfigurations
- Phenomenon: After starting a rerank task, service video memory usage continues to rise until it is exhausted, then begins to occupy system memory. Cause: No reasonable upper limit is configured for
RERANK_TOP_N, and no automatic video memory release mechanism is enabled. Excessive candidate results occupy too many computing resources. - Phenomenon: After the client closes the SSE connection, conversation records are not written to the database, and empty fields are displayed during queries. Cause: Synchronous write mode is not configured. The default asynchronous write mode causes data to fail to persist when the connection is interrupted.
- Phenomenon: After starting the Docker container, MongoDB connection fails, and the log shows an authentication error. Cause: The
MONGODB_AUTH_SOURCEparameter is not configured correctly, and the MongoDB port inside the container is not mapped to the host machine. External connections cannot access the database.
How to confirm configurations are correct
- Upload long documents of the corresponding category, check that no timeout errors appear in parsing tasks, and confirm that the timeout configuration matches the actual time required for document processing.
- Initiate a conversation that includes multi-dimensional associated data, check the number of reranked entries in the returned results, and confirm that they match the configured recall and reranking rules.
- Manually terminate a data synchronization task, check that complete synchronized data is retained in the database, and confirm that the retry configuration is effective.
- View service logs and database connection logs, confirm that there are no authentication errors or connection timeout errors, and verify that the configuration parameters match system resource conditions.
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.