What the data for this category looks like
Research report retrieval data sources include public research reports from securities firms, public investment research documents from mutual funds, and industry analysis reports released by industry associations. Update follows a fixed rhythm: daily updates for securities firm morning briefings and industry weekly reports, weekly updates for in-depth research reports, and monthly updates for industry panoramic reports. Each individual document uses a standard structure, including fields such as title, publishing institution, release time, core viewpoints, industry tracking data, and target ratings. Unit specifications are as follows: "report pages" uses pages as the unit, "number of covered targets" uses units as the unit, and "release time" uses a standard date format.
Constraints Imposed on Multi-turn Dialogue and Prompt Engineering
Individual research report documents have long length and rich fields. Multi-turn dialogue must accurately associate specific field information within a single report to avoid confusion across reports. Frequently updated data sources require prompts to explicitly prioritize the latest released report content, to prevent referencing outdated information. Multi-turn follow-up scenarios require retaining the report identifier and core field context from the current session, to ensure subsequent questions directly link to previously mentioned research report content. The mixed structure of structured fields and unstructured text in research reports requires prompts to clearly distinguish between data fields and analytical viewpoints, to avoid generating incorrect associations.
Configuration Settings
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
maxContext | First 8–12 session context entries | Research report content has long length; excessive context will occupy the model window. 8-12 entries can cover the association needs of multi-turn follow-ups without exceeding the context limits of conventional models |
promptTemplate | "Please answer user questions based on the following research report content: {context}. User question: {question}. Strictly match the field names and numerical units in the research report." | Research reports have structured fields; explicitly requiring prompts to match fields can avoid generating incorrect associations |
relevanceThreshold | 0.75–0.85 | Research report content is professional and fields are scattered. A threshold that is too low will retrieve irrelevant reports, while a threshold that is too high will miss relevant content. 0.75-0.85 balances retrieval precision and coverage |
rerankTopN | First 5–7 retrieved results | Research reports come from diverse sources and have large volumes. Taking the top 5-7 entries after reranking ensures core relevant reports are included in the context, while controlling the character count of single-round input |
contextWindowSize | 6000–8000 characters | Individual research report text can reach tens of thousands of characters. Setting this parameter truncates retrieved context to a reasonable range that the model can process |
completionReason | Enable field pass-through | Used to transmit the current session's retrieval scope during multi-turn conversations, ensuring subsequent questions can directly link to the specified research reports |
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 case-by-case analysis. It is recommended to test on your own samples before finalizing settings.
Three Common Configuration Mistakes
- Phenomenon: In FastGPT 4.10.0, after configuring
maxContextto 30 entries, the conversation details only display 2 context entries, and replies cannot associate with context. Cause: ThecontextWindowSizeparameter was not configured synchronously. The session context was forcibly truncated by the model input window, retaining only the most recent 2 entries. - Phenomenon: The
completionReasonfield value of the AI dialogue node cannot be referenced in the workflow. Cause: The "Pass completion reason" configuration item of the AI dialogue node was not enabled. This field is not written to the session storage context by default. - Phenomenon: Field names with spaces in research reports cannot be correctly identified when the prompt contains spaces. Cause: The prompt did not use half-width quotation marks to wrap space-containing field identifiers, causing the model to fail to accurately match structured fields.
How to Verify Correct Configuration
- Initiate a targeted question for a single specified research report, check whether the reply content strictly matches the fields and values in the report, to confirm that the prompt configuration is effective.
- Initiate two or more related follow-up questions, check whether the conversation details retain the context information from previous questions, to confirm that the
maxContextconfiguration meets expectations. - Trigger the loop verification logic, check whether the workflow can trigger secondary retrieval or end the conversation based on the classification judgment results, to confirm that the
enableLoopconfiguration is correct. - View the vector retrieval logs, check whether the number of retrieved results matches the configurations of
rerankTopNandrelevanceThreshold, to confirm that the retrieval configuration is effective.
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.