HTTP Interfaces and External Systems for Advertising and

What the data for this category looks like

Data sources include internal advertising placement ledgers of financial institutions, third-party financial advertising monitoring databases, public reports from industry marketing associations, and financial brand media resource quotation documents. Update cadence: Latest placement data is synced weekly, full industry research reports are released monthly. Document structures are mostly multi-chapter nested, including modules such as placement channel share, budget allocation, audience profile, and ROI analysis. Fields include placement platform name, budget amount (unit: ten thousand yuan), impressions (unit: times), conversions (unit: units). Some documents include nested sub-channel detailed data.

What constraints these characteristics impose on HTTP interfaces and external systems

Multi-chapter nested document structures require interfaces to support segmented recall and nested content parsing, to avoid returning full-page long text that exceeds the model context window. Fields include nested sub-channel data, so interface parameters must support field filtering at specified levels to reduce redundant data transmission. Weekly updated real-time placement data requires interfaces to be configured with short-cycle cache refresh mechanisms, and support incremental sync interfaces to reduce pull load. Documents include numerical fields with units, so interfaces must retain original units and numerical precision when returning data, to avoid unit conversion errors. Authentication rules vary across different data sources, so interfaces need to adapt to multiple sets of authentication logic to connect with internal ledgers and third-party monitoring platforms.

How to Configure Settings

Configuration Item	Suggested Value	Rationale
`max_recall_count`	`Top 10-15 entries`	Advertising and marketing research reports have long individual content; excessive recall will exceed the model context window
`similarity_threshold`	`0.75-0.85`	Most fields in advertising and marketing data are structured numerical values; too low a threshold will introduce irrelevant channel data
`refresh_interval`	`3600 seconds`	Real-time placement data is updated weekly; hourly caching balances timeliness and interface load
`field_filter_rules`	`Filter by placement platform, budget amount, impressions`	Advertising and marketing research reports have high field redundancy; specifying core fields reduces interface transmission volume
`parse_chunk_size`	`800-1200 characters`	Multi-chapter nested structures require moderate segment length to ensure context coherence
`external_auth_token`	`Assign independent tokens per data source`	Authentication rules differ across third-party advertising data sources; independent tokens reduce cross-source call risks

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 case-by-case analysis, and it is recommended to test on your own samples before finalizing settings.

Three Common Misconfigurations

Calling the HTTP interface returns empty results. The cause is that field_filter_rules is not configured. The interface returns a large number of non-core redundant fields in the advertising research report, which exceeds the model context window and is truncated to empty.
After upgrading from 4.8.17 to 4.8.18, historical knowledge base content cannot be retrieved. The cause is that strict_field_match is enabled by default after the upgrade, and the field names of the original advertising and marketing research reports have case differences, resulting in matching failures.
Calling the interface returns a 400 error with a parameter format error prompt. The cause is that the unit parameter of the budget amount is not passed as required by the data source. The values of advertising and marketing data must be attached with unit identifiers such as ten thousand yuan/yuan; failure to specify will trigger parameter verification failure.

How to Verify Correct Configuration

Call the test interface with the specified advertising and marketing research report ID, check whether the returned results include the preset core fields, and the field units are consistent with the original data.
View the interface logs to confirm that the cache refresh cycle matches the refresh_interval configuration, and real-time data from the past hour has been synchronized successfully.
Simulate cross-data source calls, use authentication tokens from different third-party advertising data sources, and check whether the interface can normally pull corresponding data without authentication errors.
Adjust similarity_threshold to the boundary value, check whether the relevance of the returned results meets expectations, and there is no excessive irrelevant content.

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.