What data for this category looks like
Data sources for general mixed research report retrieval include publicly available research reports from securities firm research institutes, statistical bulletins from industry associations, periodic announcements of listed companies, and third-party industry databases. Update frequency aligns with the following schedule: real-time synchronization with the release of individual research reports, quarterly updates for industry bulletins, and updates tied to financial reporting cycles for periodic reports. Document structure includes fields such as research report title, issuing institution, release date, core viewpoints, data charts, industry ratings, target price, and more. Units include RMB, percentage, industry classification codes, and other standard units. The length of individual documents varies widely, ranging from several thousand characters to tens of thousands of characters.
What constraints these characteristics impose on multi-turn dialogue and prompting
Research reports contain a large volume of professional terms, structured data, and charts. In multi-turn dialogue, context details such as issuing institution and release date must be retained to avoid confusion between similar reports from different cycles. Research reports have numerous specialized fields, so prompts must clearly specify target extraction fields; otherwise, precise matching of user professional queries cannot be achieved. Real-time updated research report data requires multi-turn dialogue to support dynamic recall of the latest content, so prompts must include trigger logic for real-time retrieval. The long-document characteristic requires limiting the length of multi-turn context to avoid overflow and loss of key information.
How to set configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxContext | 8000–12000 characters | The length of individual general mixed research reports varies widely. Retaining sufficient context helps avoid loss of key professional information |
recall_top_k | Top 8–12 entries | Research report data has a large volume. Too many recalled results will exceed the context window, while too few will fail to cover relevant reports |
chunk_size | 1500–2000 characters | Research reports contain charts and specialized paragraphs. Segment length is adjusted to fit semantic relevance and avoid disrupting professional logic |
maxConversationHistory | Top 3–5 turns | Research report queries usually focus on a single scenario. Excessive conversation history will interfere with the accuracy of current retrieval |
PARSE_FILE_TIMEOUT_SECONDS | 120 seconds | Research reports contain a large number of charts and tables, which take longer to parse. The timeout period must be extended to avoid parsing failures |
similarity_threshold | 0.75–0.85 | Research reports have a high proportion of professional terms. A threshold that is too low will introduce irrelevant content, while a threshold that is too high will miss relevant reports |
The parameter values provided on this page are common starting points for configuration setup. Actual values are affected by material format, data volume, and business rules. Specific issues require case-by-case analysis. It is recommended to test on your own samples before finalizing settings.
Three common mistakes
- Phenomenon: When debugging a locally deployed model, the interface shows a successful call but the returned content does not meet expectations. The actual used model is a non-specified cloud model. Cause: The access address and authentication key of the local model were not bound in the LLM configuration, and the option to automatically fall back to the default model was enabled.
- Phenomenon: When uploading research report data in long JSON format, the system returns a parsing failure prompt. Cause: The
UPLOAD_FILE_MAX_SIZEandchunk_sizeparameters were not adjusted. The default configuration limits the character cap for single files and single segments, which cannot accommodate long JSON content. - Phenomenon: Subsequent questions in multi-turn dialogue cannot associate previously mentioned research report content, and retrieval results do not match. Cause: The
maxConversationHistoryparameter was not set. The default retained conversation history is too short, leading to loss of context.
How to confirm correct configuration
- Enter the application debugging interface, enter a query containing specific research report keywords, check if the returned results include matching research report fields, and adjust the similarity threshold until the results meet expectations.
- Upload a single long research report, check the parsing progress and results, adjust the segment length and timeout time to ensure successful parsing and complete content.
- Initiate consecutive multi-turn questions, check if the system retains research report information from previous conversations, adjust the context window and the number of retained history entries to ensure correct context association.
- After binding the local model, select the model in the debugging interface to initiate a question, check if the returned results use the specified model, and confirm that the access configuration is correct.
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.