Add scenario editing modal, twitter sentiment seeding (#101)

* testing agi-eval benchmark * Add scenario modal editor * Add initial values to ScenarioEditorModal * Add seedTwitterSentiment.ts --------- Co-authored-by: Kyle Corbitt <kyle@corbt.com>
2023-08-01 01:26:43 -07:00
parent 6316eaae6d
commit 1fb428ef4a
11 changed files with 621 additions and 102 deletions
--- a/prisma/seedTwitterSentiment.ts
+++ b/prisma/seedTwitterSentiment.ts
@@ -0,0 +1,113 @@
+import { prisma } from "~/server/db";
+import dedent from "dedent";
+import fs from "fs";
+import { parse } from "csv-parse/sync";
+
+const defaultId = "11111111-1111-1111-1111-111111111112";
+
+await prisma.organization.deleteMany({
+  where: { id: defaultId },
+});
+
+// If there's an existing org, just seed into it
+const org =
+  (await prisma.organization.findFirst({})) ??
+  (await prisma.organization.create({
+    data: { id: defaultId },
+  }));
+
+type Scenario = {
+  text: string;
+  sentiment: string;
+  emotion: string;
+};
+
+const experimentName = `Twitter Sentiment Analysis`;
+const oldExperiment = await prisma.experiment.findFirst({
+  where: {
+    label: experimentName,
+    organizationId: org.id,
+  },
+});
+if (oldExperiment) {
+  await prisma.experiment.deleteMany({
+    where: { id: oldExperiment.id },
+  });
+}
+
+const experiment = await prisma.experiment.create({
+  data: {
+    id: oldExperiment?.id ?? undefined,
+    label: experimentName,
+    organizationId: org.id,
+  },
+});
+
+const content = fs.readFileSync("./prisma/datasets/validated_tweets.csv", "utf8");
+
+// eslint-disable-next-line @typescript-eslint/no-explicit-any
+const records: any[] = parse(content, { delimiter: ",", from_line: 2 });
+
+console.log("records", records);
+
+const scenarios: Scenario[] = records.map((row) => ({
+  text: row[0],
+  sentiment: row[1],
+  emotion: row[2],
+}));
+
+console.log("scenarios", scenarios.length);
+
+await prisma.testScenario.createMany({
+  data: scenarios.slice(0, 30).map((scenario, i) => ({
+    experimentId: experiment.id,
+    sortIndex: i,
+    variableValues: {
+      text: scenario.text,
+      sentiment: scenario.sentiment,
+      emotion: scenario.emotion,
+    },
+  })),
+});
+
+await prisma.templateVariable.createMany({
+  data: ["text", "sentiment", "emotion"].map((label) => ({
+    experimentId: experiment.id,
+    label,
+  })),
+});
+
+await prisma.promptVariant.createMany({
+  data: [
+    {
+      experimentId: experiment.id,
+      label: "Prompt Variant 1",
+      sortIndex: 0,
+      model: "gpt-3.5-turbo-0613",
+      modelProvider: "openai/ChatCompletion",
+      constructFnVersion: 1,
+      constructFn: dedent`
+          definePrompt("openai/ChatCompletion", {
+            model: "gpt-3.5-turbo-0613",
+            messages: [
+              {
+                role: "user",
+                content: \`Text: ${"$"}{scenario.text}\n\nRespond with the sentiment (negative|neutral|positive) and emotion (optimism|joy|anger|sadness) of the tweet in this format: "answer: <sentiment>-<emotion>".\`
+              }
+            ],
+            temperature: 0,
+          })`,
+    },
+  ],
+});
+
+await prisma.evaluation.createMany({
+  data: [
+    {
+      experimentId: experiment.id,
+      label: "Eval",
+      evalType: "CONTAINS",
+      value: "answer: {{sentiment}}-{{emotion}}",
+    },
+  ],
+});