Sample Files: AI-Complaint-Assistant for document

You can share your own app files on this page. Please include a brief description of your app files.

Reference files

File:ComplaintAssessmentDocument-Schema.zip

File:OpenFDA device search fields.xlsx

Settings.txt

CONFIG:OpenFDA-Vertex-V1.0 // identifies schema version (readonly)

https_url1: // openFDA api for source data

limit1: // limit of query results

report_title: // title of output report

data1_fields: // data fields to be analyzed in MDR query results

KEYWORD1-SEARCH: // general keyword search terms (matched in any field)

SEARCH1-FIELDS:SEARCH1-TERMS // query search fields and terms, see openFDA device_search_fields.xlsx for full details of searchable fields

date_received: // example field

device.device_report_product_code: // example field

SORT1-FIELD:SORT1-TERM // query results sorting date_received:desc

COUNT1-FIELD:COUNT1-TERM // query count field/term

AI-ProblemSummaryPrompt: // Prompt that summarizes the product problem

AI-CountSummaryPrompt: // Prompt that counts the instances of items

AI-ProblemSimilarityPrompt: // Prompt that summarizes the problem similarity to a product problem

AI-MDRSimilarityPrompt: // Prompt that analyzes the similarity between input problem and MAUDE results matching query criteria

AI-ReportSummaryPrompt: // Prompt that summarizes the most similar problems

AI-WordsPerReport: // Number of words in each intermediate report (recommended: 1500, range: 100-5000)

AI-ModelTemperature: // LLM Temperature index (recommended: 0.05, range: 0..1f)

AI-ModelTopP: // LLM TOP_P index (recommended: 0.4, range: 0..1f)

AI-ModelTopK: // LLM TOP_K number of words for next word prediction (recommended: 10, range: 1-128)

AI-ModelMaxOutputTokens: // LLM maximum output words (range: 1-2048)

Sample App Files

Media: Basic-Complaint-Assessment-for-document.zip Description: Settings includes filter on product code FMF and date range from 2020 to present. Prompts for matching top similar product problem codes and individual MAUDE reports using semantic similarity.