Sample Files: AI-Complaint-Assistant with prompt

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Reference files

File:ComplaintAssessmentPrompt-Schema.zip

File:OpenFDA device search fields.xlsx

Settings.txt CONFIG:OpenFDA-Vertex-V1.0 // identifies schema version https_url1:api.fda.gov/device/event.json? // openFDA api for source data limit1:100 report_title:Complaint Reportability Assessment 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 date_received:[20200101+TO+20240315] device.device_report_product_code:(FMF) SORT1-FIELD:SORT1-TERM // query results sorting date_received:desc COUNT1-FIELD:COUNT1-TERM // query count field/term AI CONFIGURATION & PROMPTS: // Prompt that summarizes the product problem AI-ProblemSummaryPrompt:Describe the following product problem in a couple of sentences. Include essential details. // Prompt that counts the instances of items AI-CountSummaryPrompt:List each unique item along with the count for each item. // Prompt that summarizes the problem similarity to a product problem AI-ProblemSimilarityPrompt:Analyze the similarity of this problem (Template: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. // Prompt that analyzes the similarity between input problem and MAUDE results matching query criteria AI-MDRSimilarityPrompt:Match the most similar problem reports to this (Template: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. // Prompt that summarizes the most similar problems AI-ReportSummaryPrompt: List the top matching problem reports with the highest similarity scores. Include all details about the matching problems. // 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

Sample App Files

Media: Basic-Complaint-Assessment-with-prompt.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.