What the data for this category looks like
Game financial report analysis data is sourced from quarterly public financial report announcements of listed game manufacturers, and compliant third-party game operation data APIs. Two update schedules are used: quarterly core financial reports are updated every 3 months, while monthly operating revenue and user data are updated each calendar month. Individual financial report documents include fields such as segment revenue breakdowns, active user scale, paying user scale, revenue amounts for each game category, and R&D investment amounts. Most field units are ten thousand RMB and person-times.
What constraints these characteristics impose on deployment and upgrade
Game financial report data sources include public financial report documents and third-party operation data APIs. Update cycles differ between quarterly and monthly frequencies, and fields include multi-category revenue breakdowns. During deployment, multi-source data synchronization tasks must be configured. Update cycles for full quarterly financial reports and incremental monthly operation data must be differentiated, and mixed parsing of structured tables and unstructured documents must be supported. During upgrade, existing parsing rules must be compatible, while dynamic adjustments to game manufacturers’ financial report formats must be supported. This avoids parsing failures caused by minor format changes. Additionally, indexing for multi-category fields must be adapted to multi-dimensional vector storage configurations, to prevent dimension mismatch issues during data retrieval.
How to set the configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Game financial report PDFs include multi-page revenue breakdowns and operation data tables, with longer parsing times than general documents |
UPLOAD_FILE_MAX_SIZE | 50 MB | Individual quarterly consolidated financial report PDFs typically do not exceed 50 MB, supporting batch upload requirements |
CHUNK_SIZE | 800–1200 characters | Game financial report fields mostly contain long-text revenue breakdowns. Excessively long segments reduce retrieval accuracy, while excessively short segments increase the number of retrieval requests |
RECALL_TOP_K | Top 8 entries | Correlated data in game financial reports mostly consists of same-category revenue or user data. Too many recalled entries introduce irrelevant information |
VECTOR_STORE_DIMENSION | 1536 | Output dimension of general text embedding models, adapted to text encoding requirements for game financial report fields |
FILE_STORAGE_PATH | /data/fastgpt/game_finance | Specify a dedicated storage directory during private deployment, to facilitate distinguishing game financial report data from other business data |
The parameter values provided on this page are standard recommended starting points for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require individual analysis. It is recommended to test on your own samples before finalizing settings.
Three common mistakes
- Phenomenon: Syntax errors occur when accessing the deployed page using outdated browsers such as 360 Speed Browser, and the interface fails to load normally. Cause: FastGPT 4.8.7 and later versions use ES2020 syntax to compile front-end code by default, and outdated browsers do not support some syntax features of this version.
- Phenomenon: A
permission deniederror occurs when starting a private deployment, and the specified data directory cannot be accessed. Cause: The user group of the FastGPT process has not been added to the access whitelist of the data directory, or the directory permission configuration is incorrect. - Phenomenon: Normal inference requests cannot be initiated after connecting to ollama, and the interface returns a connection timeout error. Cause: The local access address and port of ollama have not been configured correctly, or the firewall blocks the communication port between FastGPT and ollama.
How to confirm the configuration is complete
- Upload a test game financial report PDF, check if the parsed text fragments include core fields such as revenue breakdowns and user data, and verify that the fields match the content of the uploaded file.
- View scheduled task logs, confirm that quarterly and monthly data synchronization tasks are automatically triggered according to the preset cycle, with no execution failure records.
- Access the FastGPT file storage directory, confirm that the uploaded game financial report files are stored according to the specified path, with no permission errors.
- Initiate a query based on game financial report data, check if the returned retrieval results include revenue or user data matching the query keywords, and that the number of results conforms to the preset recall configuration.
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.