What the Data for This Category Looks Like
The data for this category mainly comes from internal party building learning platforms of communication tower operation enterprises, party building learning materials issued by superior party committees, and party building practice documents combined with tower operation and maintenance scenarios. Updates follow a set rhythm: current learning points are updated monthly, and party building case sets paired with frontline operation and maintenance are updated quarterly. Each document has a standard structure: title, publishing entity, publishing date, content classification tags, and main text. Some documents include additional associated fields such as site number and team location. These fields are used to match the learning needs of specific operation and maintenance teams.
Constraints on Knowledge Base Retrieval and Recall
Data includes associated fields such as site number and team location. This requires the retrieval link to support targeted filtering based on these metadata, to avoid returning irrelevant party building content across teams or regions. Monthly updated learning points and quarterly updated practice cases require the knowledge base recall link to support incremental synchronization configuration, to avoid loading expired content. Documents have content classification tags. This requires retrieval to filter results by dimensions such as theoretical learning and post practice, to match party building learning scenario needs. Some documents have long text structures. This requires the recall link to accurately split long texts and retain context information of associated fields, to ensure the relevance of retrieval results.
Configuration Settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
similarity | 0.72–0.80 | Party building learning content is mostly standardized theoretical text. This range filters low-correlation generic content while retaining targeted points that fit the scenario. |
limit | Top 8 entries | For the party building learning scenario of tower teams, recalling 8 entries at a time covers the weekly learning points for the team, avoiding information overload. |
searchMode | hybrid | Balances keyword matching and semantic recall, adapting to precise expressions of party building theory and scenario association of practice cases. |
usingReRank | Enabled | Performs secondary sorting on recall results, prioritizing content strongly related to the party building learning theme, and resolving redundancy issues from semantic recall. |
datasetSearchUsingExtensionQuery | Enabled | Generates extended query terms based on the original question, covering synonymous expressions common in party building learning, such as associative matching between "three meetings and one lesson" and "branch meeting system". |
collectionIds | Bind the corresponding party building knowledge base collection ID | Only retrieve party building knowledge bases exclusive to the communication tower scenario, to avoid mixing in party building content from other categories. |
Three Common Misconfigurations
- Phenomenon: Retrieval results mix in party building content from other industries, such as learning materials from education or healthcare fields. Cause: The
collectionIdsof the exclusive party building knowledge base are not bound, so the retrieval scope covers all party building datasets. - Phenomenon: When calling an AI model with internet access, only party building content within the knowledge base is returned, and the latest policy information cannot be supplemented. Cause: The application's retrieval mode is fixed to knowledge base-only retrieval, and cross-source retrieval configuration is not enabled, so the model cannot call external data.
- Phenomenon: Retrieval results are not sorted by timeliness, and older party building learning materials appear first. Cause: The
usingReRankreordering function is not enabled, and metadata filtering based on publishing date is not configured, leading to insufficient timeliness of recall results.
How to Confirm the Configuration Is Correct
- Enter the FastGPT knowledge base management page, check if the bound
collectionIdsonly include party building knowledge base collections for the communication tower scenario, to confirm the retrieval scope is correct. - Submit a test question such as "Party building learning points for XX team", check if the returned results include associated documents for the corresponding team, to verify that the metadata filtering function is working.
- View the retrieval logs, confirm that the number of recall results matches the configuration of the
limitparameter, and that the reordering function has performed secondary sorting on the results. - Test the internet retrieval scenario, submit a question that requires the latest party building policies, confirm that the model can return externally supplemented content, to verify that the cross-source retrieval configuration is working.
The values provided are common starting points and should be evaluated against the reader's own samples.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-28.