|
|
| Line 12: |
Line 12: |
| | <strong>Settings.txt</strong> | | | <strong>Settings.txt</strong> |
| |- | | |- |
| | CONFIG:OpenFDA-Vertex-V1.0 // identifies schema version | | | CONFIG:OpenFDA-Vertex-V1.0 // identifies schema version (readonly) |
| |https_url1:api.fda.gov/device/event.json? // openFDA api for source data
| | https_url1: // openFDA api for source data |
| |limit1:100
| | limit1: // limit of query results |
| |report_title:Complaint Reportability Assessment
| | report_title: // title of output report |
| |data1_fields: // data fields to be analyzed in MDR query results
| | data1_fields: // data fields to be analyzed in MDR query results |
| |KEYWORD1-SEARCH: // general keyword search terms (matched in any field)
| | KEYWORD1-SEARCH: // general keyword search terms (matched in any field) |
|
| |
|
| |SEARCH1-FIELDS:SEARCH1-TERMS // query search fields and terms
| | SEARCH1-FIELDS:SEARCH1-TERMS // query search fields and terms |
| |date_received:[20200101+TO+20240315]
| | date_received:[20200101+TO+20240315] |
| |device.device_report_product_code:(FMF)
| | device.device_report_product_code:(FMF) |
|
| |
|
| |SORT1-FIELD:SORT1-TERM // query results sorting
| | SORT1-FIELD:SORT1-TERM // query results sorting |
| |date_received:desc
| | date_received:desc |
|
| |
|
| |COUNT1-FIELD:COUNT1-TERM // query count field/term
| | COUNT1-FIELD:COUNT1-TERM // query count field/term |
|
| |
|
| |AI CONFIGURATION & PROMPTS:
| | AI CONFIGURATION & PROMPTS: |
| |// Prompt that summarizes the product problem
| | AI-ProblemSummaryPrompt: // Prompt that summarizes the product problem |
| |AI-ProblemSummaryPrompt:Describe the following product problem in a couple of sentences. Include essential details.
| | AI-CountSummaryPrompt: // Prompt that counts the instances of items |
| |// Prompt that counts the instances of items
| | AI-ProblemSimilarityPrompt: // Prompt that summarizes the problem similarity to a product problem |
| |AI-CountSummaryPrompt:List each unique item along with the count for each item.
| | AI-MDRSimilarityPrompt: // Prompt that analyzes the similarity between input problem and MAUDE results matching query criteria |
| |// Prompt that summarizes the problem similarity to a product problem
| | AI-ReportSummaryPrompt: // Prompt that summarizes the most similar problems |
| |AI-ProblemSimilarityPrompt:Analyze the similarity of this problem ({{problem_input}}) to the following problem. Use semantic similarity measurement. Present the result with the similarity score as a percentage followed by a concise explanation of the similarity score.
| | AI-WordsPerReport: // Number of words in each intermediate report (recommended: 1500, range: 100-5000). |
| |// Prompt that analyzes the similarity between input problem and MAUDE results matching query criteria
| | AI-ModelTemperature: // LLM Temperature index (recommended: 0.05, range: 0..1f) |
| |AI-MDRSimilarityPrompt:Match the most similar problem reports to this ({{problem_input}}). Include all important details. Include all reference numbers. Include the similarity scores as a percentage. Explain the similarities. Use semantic similarity measurements. Present results in descending similarity scores. For each matching result, include the matching report number followed by the similarity score followed by a brief description of the problem followed by an explanation of the similarities.
| | AI-ModelTopP: // LLM TOP_P index (recommended: 0.4, range: 0..1f) |
| |// Prompt that summarizes the most similar problems
| | AI-ModelTopK: // LLM TOP_K number of words for next word prediction (recommended: 10, range: 1-128) |
| |AI-ReportSummaryPrompt: List the top matching problem reports with the highest similarity scores. Include all details about the matching problems.
| | AI-ModelMaxOutputTokens: // LLM maximum output words (range: 1-2048) |
| |// Maximum number of words in each intermediate report.
| |
| |AI-WordsPerReport:1500
| |
| |// LLM Pro-Vision temperature index (0..1f)
| |
| |AI-ModelTemperature:0.05
| |
| |// LLM Pro-Vision TOP_P index (0..1f)
| |
| |AI-ModelTopP:0.4
| |
| |// LLM Pro-Vision TOP_K (Number of words for next word prediction)
| |
| |AI-ModelTopK:10
| |
| |// LLM Maximum output words (1..2048)
| |
| |AI-ModelMaxOutputTokens:2048
| |
| |} | | |} |
|
| |
|