Sample Files: AI-Complaint-Assistant with prompt: Difference between revisions

Sample Files: AI-Complaint-Assistant with prompt (edit)

Revision as of 20:28, 7 April 2024

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Waghanna

Bureaucrats, Interface administrators, Administrators

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-You can share your own app files on this page additional, please ensure you include a brief description of your app files.
+You can share your own app files on this page. Please include a brief description of your app files.
-[[Media: Sample-Complaint-Assessment-with-prompt.zip]]
+<blockquote>
-Description: Settings queries product code FMF and date range from 2020 to present, prompts for creating similarity scores with top matching MAUDE reports.
+'''''Reference files'''''
+[[File: ComplaintAssessmentPrompt-Schema.zip]]
+[[File: openFDA device_search_fields.xlsx]]
+<code>
+Settings.txt:
+CONFIG:OpenFDA-Vertex-V1.0   //identifies schema version
+Open FDA API Query specification:
+https_url1:api.fda.gov/device/event.json?
+limit1:100
+REPORT
+report_title:Complaint Reportability Assessment
+// Data fields analyzed in MDR query results
+data1_fields:product_problems, device.brand_name, patient.patient_problems, device.manufacturer_d_name, report_number, mdr_text.text
+// General keyword search terms (in any field)
+KEYWORD1-SEARCH:
+// Query search fields and terms
+SEARCH1-FIELDS:SEARCH1-TERMS
+date_received:[20200101+TO+20240315]
+device.device_report_product_code:(FMF)
+// Query results sorting
+SORT1-FIELD:SORT1-TERM
+date_received:desc
+// Query count field/term
+COUNT1-FIELD:COUNT1-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 ({{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 ({{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
+</code>
+</blockquote>
+==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.