What the data for this category looks like
Film theater financing daily report data is sourced from film industry financing filing public platforms, official theater project financing announcements, and industrial park project declaration systems. Data is updated daily, covering all declared and public projects from the previous calendar day. The data uses a structured table format, including fields such as project name, production entity, financing amount, financing round, theater screening share, filing number, and update date. The unit for financing amount is ten thousand yuan, the unit for screening data is screenings, and filing numbers use a 16-character string format.
Constraints on multi-turn dialogue and prompt engineering
The structured multi-field format, daily full update cycle, and exclusive screening-linked attributes of film theater financing daily reports impose multiple constraints on multi-turn dialogue and prompt engineering configurations. First, the multi-field structure requires prompts to explicitly specify the range of fields to extract, to avoid outputting irrelevant information. Second, the daily full update feature requires multi-turn dialogue to retain historical query project identifiers and filtering conditions, to support cross-date associated queries. Third, the unit and format requirements for dedicated fields require prompts to enforce checks for the ten thousand yuan unit of financing amounts, the 16-character string format of filing numbers, and the screenings unit of screening data. Fourth, the attribute of screening-linked financing projects must be clearly distinguished from ordinary corporate financing in prompts, to avoid mixing up query results.
How to Configure Parameters
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxContext | 12000–18000 tokens | Film theater financing daily reports contain multiple fields and daily full datasets, this value range retains sufficient historical query context and project information |
history_turns | 5–8 turns | Film theater financing queries typically revolve around specific projects or production entities. 5-8 turns of historical dialogue covers associated query needs while avoiding context overload |
prompt_template | Fixed template specifying field extraction rules, unit checks, and screening-linked distinction | Clearly inform the model of required fields and unit formats, and distinguish between ordinary financing and financing projects tied to theater screenings |
token_count_display | Enabled | Meets the need to view separate token counts for AI dialogue input and output |
markdown_render | Enabled | Enables markdown-formatted prompts, outputs rendered formats instead of raw source text |
show_ai_dialog | Configured as needed | Can be disabled during tool calls to avoid redundant AI dialogue content output |
The parameter values provided on this page are conventional recommendations used as starting points for configuration. Actual values are affected by material form, data volume and business rules. Each situation requires separate analysis, and it is recommended to test against your own samples before finalizing.
Three Common Mistakes
- Phenomenon: Using markdown-optimized prompts results in output being markdown source code instead of rendered format. Cause: The
markdown_renderconfiguration item is not enabled, so the model only outputs the format defined in the prompt as plain text without triggering rendering logic. - Phenomenon: Tool call workflows include redundant AI dialogue intermediate content. Cause: The
show_ai_dialogconfiguration item is not disabled, and AI dialogue logs from the tool call process are retained by default. - Phenomenon: Historical film project information from previous queries cannot be directly referenced in multi-turn dialogue. Cause: The
history_turnsormaxContextparameters are not configured correctly, with too few historical dialogue turns or insufficient context window, causing historical information to be automatically truncated.
How to Verify Proper Configuration
- Initiate a test dialogue with multi-field queries, verify that output only covers the specified film theater financing daily report fields with no irrelevant information.
- Initiate a cross-date associated query, verify that the model can retain historical query project identifiers and filtering conditions, and correctly associate financing projects from different dates.
- Check the statistics area of the dialogue interface, verify that input and output token counts are displayed separately.
- Initiate a tool call test, verify that when
show_ai_dialogis configured to disabled, no redundant AI dialogue intermediate content is output.
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.