runGptAnalysis now parses the results from assistant. Need to add prompt for data type

Author: Samantha Mathan

src/gpt-controller.ts

@@ -3,7 +3,7 @@ import { GPTModel } from "./enums";
 import { FileObject } from "openai/resources";
 import path, { resolve } from "path";
 import fs from "fs";
-import { AssistantBody, GPTResponse, ThreadMessage, GPTData } from "./types";
+import { AssistantBody, GPTResponse, ThreadMessage, GPTData, Testing, TestLocation } from "./types";
 import { prompt, questions } from "./prompts.data";
 import { threadId } from "worker_threads";
 
@@ -61,14 +61,42 @@ export class GPTController {
             await GPTController.client.beta.threads.messages.list(
               run.thread_id,
             );
+          var n = 1;
           for (const message of messages.data.reverse()) {
             // Need to check if the message content is text before parsing it
             if (message.content[0].type == "text") {
-              result = message.content[0].text.value; // TODO: parse this result, then verify with user or add to database
-              console.log(`${message.role} > ${result}`);
-              //console.log();
-              // TODO: push the parsed results to the threadResults as a GPTData object
-              threadResults.push();
+              result = message.content[0].text.value;
+              var resvalues: GPTData = {    // Initialize GPT data object
+                paper_name: "",
+                year: 0,
+                author: [],
+                part_no: "",
+                type: [],
+                manufacturer: "",
+                testing_location: "Terrestrial",
+                testing_type: "TID",
+                data_type: 0
+              }
+              // Every second message has the data values
+              if(n % 2 == 0) {
+                // console.log(`${message.role} > ${result}`);
+                let preres = result.split("ø").map((s) => s.replace("\n", ""));
+                // console.log(preres)
+                resvalues = {
+                  paper_name: preres[0],
+                  year: parseInt(preres[1]),
+                  author: preres[2].split(","),
+                  part_no: preres[3],
+                  type: preres[4].split("¶"),
+                  manufacturer: preres[5],
+                  testing_location: <TestLocation>preres[6],
+                  testing_type: <Testing>preres[7],     // TODO: this gives a list ("TID, TID, DD") sometimes so the cast may fail
+                  data_type: 0    // TODO: add a prompt to get data_type
+                };
+                console.log(resvalues)
+                threadResults.push(resvalues);
+              }
+              n++;
             }
           }
         } else {

src/prompts.data.ts

@@ -1,8 +1,11 @@
 export const questions = [
+  "What is the title of the paper",
+  "Which year was the paper published",
   "What are all of the author's names, in the format (J. Doe) in a list like this ['J. Doe', 'R. Austin']",
   "What is the Part No. or name if that is not available",
   'What is the type of part (eg, switching regulator), if there are multiple part numbers listed, list them all and seperate them with a "¶"',
   "Who is the manufacturer",
+  'What is the type of testing location: Respond to this question with "Terrestrial" for a terrestial testing location, or "Flight" for a flight testing location',
   'What type of testing was done: Respond to this question with "TID" for Total Ionizing Dose testing, "SEE" for heavy ion, proton, laser, or neutron testing, or "OTHER" if you are not completely 100% sure',
 ];
 

src/types.ts

@@ -53,7 +53,7 @@ export type GPTData = {
   year: number;
   author: string[];
   part_no: string;
-  type: string;
+  type: string[];
   manufacturer: string;
   testing_location: TestLocation;
   testing_type: Testing;