From da207d3e0d5b3c1660298f481405b3fdc794b897 Mon Sep 17 00:00:00 2001
From: Priyanshi1908 <115202982+Priyanshi1908@users.noreply.github.com>
Date: Fri, 15 Nov 2024 15:52:58 +0530
Subject: [PATCH 1/6] Added model column and functionality to configs table

---
 services/api/src/core/evaluation.ts              | 8 +++++---
 services/api/src/core/general.ts                 | 1 +
 services/api/src/db/schema.ts                    | 4 +++-
 services/api/src/utils/db.ts                     | 2 ++
 services/app/pages/reviewandrun/ReviewAndRun.vue | 4 ++--
 5 files changed, 13 insertions(+), 6 deletions(-)

diff --git a/services/api/src/core/evaluation.ts b/services/api/src/core/evaluation.ts
index 2b4a89c..fd5afd9 100644
--- a/services/api/src/core/evaluation.ts
+++ b/services/api/src/core/evaluation.ts
@@ -129,7 +129,6 @@ evaluationRouter.post('/evaluateCsv',
 
         totalScore += score;
 
-        // Insert individual evaluation results into the database
         await db.insert(evaluations).values({
           model,
           question: result.question,
@@ -141,17 +140,20 @@ evaluationRouter.post('/evaluateCsv',
         });
       }
 
-// Calculate and store the average score in the configs table
 const averageScore = totalScore / evaluationResults.length;
 console.log(`Average Score for config ${configId}:`, averageScore);
 
 await db.update(configs)
-  .set({ averageScore: averageScore.toFixed(4) }) // Convert number to string with 4 decimal places
+  .set({
+    averageScore: averageScore.toFixed(4), 
+    model, 
+  })
   .where(sql`${configs.id} = ${sql.raw(configId.toString())}`);
 
 
 
 
+
       const csvContent = generateCSV(evaluationResults.map((result, index) => ({
         ...result,
         choice: reports[index].choice,
diff --git a/services/api/src/core/general.ts b/services/api/src/core/general.ts
index ff880ed..c3accf7 100644
--- a/services/api/src/core/general.ts
+++ b/services/api/src/core/general.ts
@@ -157,6 +157,7 @@ generalRouter.post('/configs', async (c: Context) => {
             reviews: metadata.reviews || "",
             questionAnswerPairs: questionAnswerPairs,  
             fileContents: fileContent, 
+            model: metadata.model,
         };
 
         const result = await db.insert(configs).values(config).returning({
diff --git a/services/api/src/db/schema.ts b/services/api/src/db/schema.ts
index 1740d88..140b4f1 100644
--- a/services/api/src/db/schema.ts
+++ b/services/api/src/db/schema.ts
@@ -33,9 +33,11 @@ export const configs = pgTable('configs', {
   submittedBy: json('submitted_by').notNull(),
   questionAnswerPairs: json('questionAnswerPairs').notNull().default([]), 
   fileContents: text('file_contents').notNull().default('No file uploaded'),
-  averageScore: text('average_score').default('0'), 
+  averageScore: text('average_score').default('0'),
+  model: text('model').notNull().default('unknown'), 
 });
 
+
 export const models = pgTable('models', {
   id: serial('id').primaryKey(),
   name: text('name').notNull().unique(),
diff --git a/services/api/src/utils/db.ts b/services/api/src/utils/db.ts
index b36f21e..ee7d854 100644
--- a/services/api/src/utils/db.ts
+++ b/services/api/src/utils/db.ts
@@ -19,6 +19,7 @@ type Config = {
     reviews?: string;  
     questionAnswerPairs: QAPair[]; 
     fileContents: string;
+    model: string;
 }
 
 export async function createConfig(db: NeonHttpDatabase, config: Config) {
@@ -33,6 +34,7 @@ export async function createConfig(db: NeonHttpDatabase, config: Config) {
         rating: config.rating || 0,  
         questionAnswerPairs: config.questionAnswerPairs.length ? config.questionAnswerPairs : [],
         fileContents: config.fileContents ?? "No file uploaded",
+        model: config.model,
         });
         
 }
diff --git a/services/app/pages/reviewandrun/ReviewAndRun.vue b/services/app/pages/reviewandrun/ReviewAndRun.vue
index 360abc4..b4dd105 100644
--- a/services/app/pages/reviewandrun/ReviewAndRun.vue
+++ b/services/app/pages/reviewandrun/ReviewAndRun.vue
@@ -197,11 +197,11 @@ export default {
     return;
   }
 
-  const model = selectedLlm.value === 'gpt-4o' ? 'gpt-4o' : 'gpt-4o-mini';  // Choose the model dynamically
+  const model = selectedLlm.value?.name === 'GPT-4o' ? 'gpt-4o' : 'gpt-4o-mini';
 
   const payload = {
     configId: Number(configId.value),
-    model: model,  // Pass the selected model dynamically
+    model: model,  
   };
   loading.value = true;
 

From 73f8fcc396fc0c5ae170b301070a2de0ea591247 Mon Sep 17 00:00:00 2001
From: Priyanshi1908 <115202982+Priyanshi1908@users.noreply.github.com>
Date: Fri, 15 Nov 2024 16:27:45 +0530
Subject: [PATCH 2/6] Added avg score for model

---
 services/api/src/core/evaluation.ts           | 60 ++++++++++++++++++-
 services/api/src/db/schema.ts                 |  4 +-
 .../app/pages/reviewandrun/ReviewAndRun.vue   | 29 ++++++++-
 3 files changed, 90 insertions(+), 3 deletions(-)

diff --git a/services/api/src/core/evaluation.ts b/services/api/src/core/evaluation.ts
index fd5afd9..368dda9 100644
--- a/services/api/src/core/evaluation.ts
+++ b/services/api/src/core/evaluation.ts
@@ -7,8 +7,10 @@ import { evaluateQuestionBatch } from "./process"; // New batch evaluation funct
 import { parseCSV } from "../utils/functions";
 import { getRecordsWithIds } from "../utils/db";
 import { generateReportsBatch } from "../utils/openai"; // New batch report generation function
-import { configs, evaluations } from "../db/schema";
+import { configs, evaluations,models } from "../db/schema";
 import { sql } from 'drizzle-orm';
+import { eq } from 'drizzle-orm';  
+
 
 export type Env = {
   DATABASE_URL: string;
@@ -190,4 +192,60 @@ function generateCSV(results: any[]): string {
   return csvContent;
 }
 
+
+evaluationRouter.post('/ModelAverageScores', async (c) => {
+  const db = createDbConnection(c.env.DATABASE_URL);
+
+  try {
+    const allModels = await db.select({ name: models.name }).from(models);
+
+    for (const { name: modelName } of allModels) {
+      const configsForModel = await db
+        .select()
+        .from(configs)
+        .where(eq(configs.model, modelName));
+
+      if (configsForModel.length === 0) {
+        console.warn(`No configs found for model ${modelName}`);
+        continue;
+      }
+
+      const totalScore = configsForModel.reduce((sum, config) => {
+        return sum + parseFloat(config.averageScore || '0'); // Convert score to float
+      }, 0);
+
+      const avgScore = totalScore / configsForModel.length;
+
+      console.log(`Average score for model ${modelName}:`, avgScore);
+
+      const existingModel = await db
+        .select()
+        .from(models)
+        .where(eq(models.name, modelName))
+        .limit(1);
+
+      if (existingModel.length > 0) {
+        await db
+          .update(models)
+          .set({ averageScore: avgScore.toFixed(4) }) 
+          .where(eq(models.name, modelName));
+        console.log(`Updated average score for model ${modelName}`);
+      } else {
+        await db
+          .insert(models)
+          .values({
+            name: modelName,
+            averageScore: avgScore.toFixed(4), 
+          });
+        console.log(`Inserted new model ${modelName} with average score ${avgScore.toFixed(4)}`);
+      }
+    }
+
+    return c.json({ message: 'Updated average scores for all models' });
+  } catch (error) {
+    console.error("Error updating all model average scores:", error);
+    return c.json({ error: 'Internal server error' }, 500);
+  }
+});
+
 export default evaluationRouter;
diff --git a/services/api/src/db/schema.ts b/services/api/src/db/schema.ts
index 140b4f1..25db6ce 100644
--- a/services/api/src/db/schema.ts
+++ b/services/api/src/db/schema.ts
@@ -45,7 +45,9 @@ export const models = pgTable('models', {
   description: text('description'),
   image: text('image'),
   tags: json('tags'),
-  createdAt: timestamp('created_at').defaultNow()
+  createdAt: timestamp('created_at').defaultNow(),
+  averageScore: text('average_score').default('0'), 
+
 });
 
 export const evaluations = pgTable('evaluations', {
diff --git a/services/app/pages/reviewandrun/ReviewAndRun.vue b/services/app/pages/reviewandrun/ReviewAndRun.vue
index b4dd105..13ad1a3 100644
--- a/services/app/pages/reviewandrun/ReviewAndRun.vue
+++ b/services/app/pages/reviewandrun/ReviewAndRun.vue
@@ -206,6 +206,7 @@ export default {
   loading.value = true;
 
   try {
+    // Step 1: Evaluate the configuration
     const response = await fetch('http://localhost:8787/eval/evaluateCsv', {
       method: 'POST',
       headers: {
@@ -215,6 +216,7 @@ export default {
     });
 
     if (response.ok) {
+      // Step 2: Download the CSV file after evaluation
       const contentDisposition = response.headers.get('Content-Disposition');
       console.log("Content-Disposition Header:", contentDisposition);
 
@@ -235,6 +237,11 @@ export default {
       document.body.removeChild(link);
 
       console.log('CSV file downloaded successfully');
+
+      // Step 3: Call the API to update the model's average score
+      await updateModelAverageScore();
+
+      // Step 4: Redirect after the evaluation is complete and model score is updated
       router.push({ name: 'auditqueue' });
     } else {
       console.error('Failed to run evaluation');
@@ -242,7 +249,27 @@ export default {
   } catch (error) {
     console.error('Error in evaluation:', error);
   } finally {
-    loading.value = false;  
+    loading.value = false;  // Hide loading spinner
+  }
+};
+
+// Function to call the API to update the model's average score
+const updateModelAverageScore = async () => {
+  try {
+    const response = await fetch('http://localhost:8787/eval/ModelAverageScores', {
+      method: 'POST',
+      headers: {
+        'Content-Type': 'application/json',
+      },
+    });
+
+    if (response.ok) {
+      console.log("Model average score updated successfully.");
+    } else {
+      console.error("Failed to update model average score.");
+    }
+  } catch (error) {
+    console.error("Error updating model average score:", error);
   }
 };
 

From 96bfc9d7cd64a3bea20347943c1b437d935a762f Mon Sep 17 00:00:00 2001
From: Priyanshi1908 <115202982+Priyanshi1908@users.noreply.github.com>
Date: Sat, 16 Nov 2024 07:16:32 +0530
Subject: [PATCH 3/6] Added scores to graph in results page

---
 services/api/src/core/evaluation.ts          |   4 -
 services/api/src/utils/openai.ts             |   1 -
 services/app/components/ModelScoresGraph.vue | 164 +++++++++++++++++++
 services/app/pages/results/results.vue       | 144 ++++------------
 4 files changed, 195 insertions(+), 118 deletions(-)
 create mode 100644 services/app/components/ModelScoresGraph.vue

diff --git a/services/api/src/core/evaluation.ts b/services/api/src/core/evaluation.ts
index 368dda9..a0a8e87 100644
--- a/services/api/src/core/evaluation.ts
+++ b/services/api/src/core/evaluation.ts
@@ -143,7 +143,6 @@ evaluationRouter.post('/evaluateCsv',
       }
 
 const averageScore = totalScore / evaluationResults.length;
-console.log(`Average Score for config ${configId}:`, averageScore);
 
 await db.update(configs)
   .set({
@@ -216,7 +215,6 @@ evaluationRouter.post('/ModelAverageScores', async (c) => {
 
       const avgScore = totalScore / configsForModel.length;
 
-      console.log(`Average score for model ${modelName}:`, avgScore);
 
       const existingModel = await db
         .select()
@@ -229,7 +227,6 @@ evaluationRouter.post('/ModelAverageScores', async (c) => {
           .update(models)
           .set({ averageScore: avgScore.toFixed(4) }) 
           .where(eq(models.name, modelName));
-        console.log(`Updated average score for model ${modelName}`);
       } else {
         await db
           .insert(models)
@@ -237,7 +234,6 @@ evaluationRouter.post('/ModelAverageScores', async (c) => {
             name: modelName,
             averageScore: avgScore.toFixed(4), 
           });
-        console.log(`Inserted new model ${modelName} with average score ${avgScore.toFixed(4)}`);
       }
     }
 
diff --git a/services/api/src/utils/openai.ts b/services/api/src/utils/openai.ts
index 752f4cc..e85d7ce 100644
--- a/services/api/src/utils/openai.ts
+++ b/services/api/src/utils/openai.ts
@@ -40,7 +40,6 @@ export async function generateReport(
     });
 
     const messageContent = response.choices[0]?.message?.content?.trim() ?? "{}";
-    console.log(messageContent);
     const { choice, score } = JSON.parse(messageContent);
     console.log(choice, score);
     return { choice, score };
diff --git a/services/app/components/ModelScoresGraph.vue b/services/app/components/ModelScoresGraph.vue
new file mode 100644
index 0000000..f36af44
--- /dev/null
+++ b/services/app/components/ModelScoresGraph.vue
@@ -0,0 +1,164 @@
+<template>
+    <div ref="chartContainer" class="chart-container"></div>
+  </template>
+  
+  <script>
+  import { defineComponent, ref, onMounted, nextTick, onBeforeUnmount } from 'vue';
+  import ky from 'ky';
+  import uPlot from 'uplot';
+  import 'uplot/dist/uPlot.min.css';
+  
+  export default defineComponent({
+    name: 'ModelScoresGraph',
+    setup() {
+      const chartContainer = ref(null);
+      const labels = ref([]);
+      const scores = ref([]);
+      let uplotInstance = null;
+      let tooltip = null;
+  
+      const createTooltip = () => {
+        tooltip = document.createElement('div');
+        tooltip.className = 'uplot-tooltip';
+        chartContainer.value.appendChild(tooltip);
+      };
+  
+      const renderChart = () => {
+        if (typeof window === "undefined") {
+          console.warn("RenderChart skipped during SSR");
+          return;
+        }
+  
+        if (!chartContainer.value || !labels.value.length || !scores.value.length) return;
+  
+        const xAxisIndices = labels.value.map((_, idx) => idx);
+        const chartData = [xAxisIndices, [...scores.value]];
+  
+        if (uplotInstance) {
+          uplotInstance.destroy();
+        }
+  
+        if (!tooltip) {
+          createTooltip();
+        }
+  
+        const tooltipPlugin = {
+          hooks: {
+            setCursor: (u) => {
+              const { left, top, idx } = u.cursor;
+              if (idx !== null) {
+                tooltip.style.display = 'block';
+                tooltip.style.left = `${left}px`;
+                tooltip.style.top = `${top - 40}px`;
+                tooltip.textContent = `${labels.value[idx]}: ${scores.value[idx].toFixed(2)}`;
+              } else {
+                tooltip.style.display = 'none';
+              }
+            },
+          },
+        };
+  
+        try {
+          uplotInstance = new uPlot(
+            {
+              title: 'Average Scores of Models',
+              width: chartContainer.value.offsetWidth,
+              height: 400,
+              scales: {
+                x: { time: false },
+                y: { auto: true },
+              },
+              axes: [
+                {
+                  label: 'Models',
+                  values: (_, ticks) => ticks.map((tick) => labels.value[tick] || ""),
+                },
+                {
+                  label: 'Average Score',
+                },
+              ],
+              series: [
+                {},
+                {
+                  label: 'Average Score',
+                  stroke: '#1e90ff',
+                  fill: 'rgba(30, 144, 255, 0.3)',
+                  bars: { show: true, width: 0.6 },
+                  points: { show: true, size: 5 },
+                },
+              ],
+              grid: {
+                x: { show: true, stroke: '#ddd', width: 1 },
+                y: { show: true, stroke: '#ddd', width: 1 },
+              },
+              cursor: {
+                show: true,
+                x: true,
+                y: true,
+                lock: false,
+              },
+              plugins: [tooltipPlugin],
+            },
+            chartData,
+            chartContainer.value
+          );
+        } catch (error) {
+          console.error('Error rendering chart:', error);
+        }
+      };
+  
+      const fetchData = async () => {
+        try {
+          const response = await ky.get('http://localhost:8787/models').json();
+          labels.value = response.map((model) => model.name);
+          scores.value = response.map((model) => parseFloat(model.averageScore));
+          nextTick(() => renderChart());
+        } catch (error) {
+          console.error('Error fetching data:', error);
+        }
+      };
+  
+      onMounted(() => {
+        if (typeof window !== "undefined") {
+          fetchData();
+          window.addEventListener("resize", renderChart);
+        }
+      });
+  
+      onBeforeUnmount(() => {
+        if (uplotInstance) {
+          uplotInstance.destroy();
+        }
+        window.removeEventListener("resize", renderChart);
+        if (tooltip) {
+          tooltip.remove();
+          tooltip = null;
+        }
+      });
+  
+      return {
+        chartContainer,
+      };
+    },
+  });
+  </script>
+  
+  <style scoped>
+  .chart-container {
+    width: 100%;
+    height: 400px;
+    position: relative;
+  }
+  
+  .uplot-tooltip {
+    position: absolute;
+    background: rgba(0, 0, 0, 0.7);
+    color: #fff;
+    padding: 5px;
+    border-radius: 3px;
+    pointer-events: none;
+    font-size: 12px;
+    white-space: nowrap;
+    display: none;
+  }
+  </style>
\ No newline at end of file
diff --git a/services/app/pages/results/results.vue b/services/app/pages/results/results.vue
index 69dbb9e..9c29416 100644
--- a/services/app/pages/results/results.vue
+++ b/services/app/pages/results/results.vue
@@ -1,27 +1,24 @@
 <template>
-    
     <div class="flex h-screen bg-white">
-    <aside
-      :class="{
-        'hidden': !isSidebarOpen && isMobile,
-        'block': isSidebarOpen || !isMobile,
-        'fixed': true,
-        'inset-y-0 left-0': true,
-        'z-30': true,
-        'min-h-screen': true,
-        'transition-transform transform md:translate-x-0': true
-      }"
-      class="w-64 bg-white shadow-lg md:block"
-    >
-      <Sidebar @toggleSidebar="toggleSidebar" />
-    </aside>
+        <aside
+            :class="{
+                'hidden': !isSidebarOpen && isMobile,
+                'block': isSidebarOpen || !isMobile,
+                'fixed': true,
+                'inset-y-0 left-0': true,
+                'z-30': true,
+                'min-h-screen': true,
+                'transition-transform transform md:translate-x-0': true
+            }"
+            class="w-64 bg-white shadow-lg md:block"
+        >
+            <Sidebar @toggleSidebar="toggleSidebar" />
+        </aside>
 
-    <div v-if="isSidebarOpen && isMobile" class="fixed inset-0 bg-black opacity-30 z-20" @click="toggleSidebar"></div>
+        <div v-if="isSidebarOpen && isMobile" class="fixed inset-0 bg-black opacity-30 z-20" @click="toggleSidebar"></div>
 
-
-        
-            <main class="flex-1 ml-64 overflow-auto p-7"> 
-                <section
+        <main class="flex-1 ml-64 overflow-auto p-7">
+            <section
                 class="flex flex-col px-8 pb-3.5 mt-5 w-full bg-white rounded shadow-sm max-w-[1676px] max-md:px-5 max-md:max-w-full">
                 <header class="max-md:max-w-full">
                     <div class="flex gap-5 max-md:flex-col max-md:gap-0">
@@ -80,8 +77,8 @@
                         </div>
 
                         <div class="w-2/3 p-4">
-                            <div ref="uPlotContainer" class="w-full h-full bg-white" style="background-color: #fbfbfb;">
-                            </div>
+                            <!-- Replacing uPlot with ModelScoresGraph -->
+                            <ModelScoresGraph />
                         </div>
                     </div>
                 </header>
@@ -158,59 +155,32 @@
                 <nav class="flex gap-1 self-center mt-14 max-w-full text-sm leading-5 whitespace-nowrap text-zinc-400 w-[344px] max-md:mt-10"
                     aria-label="Pagination">
                     <a href="#" class="flex gap-0.5 text-white">
-                        <NuxtImg loading="lazy" src="/paginationleft.png" alt="Previous page"
-                            class="w-5 h-5 mt-3.5 mr-2" />
-                        <span class="sr-only">Previous page</span>
-                    </a>
-                    <a href="#" aria-current="page"
-                        class="justify-center items-start px-4 py-3.5 bg-cyan-500 rounded text-white">
-                        1
-                    </a>
-                    <a href="#"
-                        class="justify-center items-start px-4 py-3.5 bg-white rounded border border-solid border-zinc-200">
-                        2
+                        <NuxtImg loading="lazy" src="/leftarrow.png" alt="Previous" class="shrink-0 w-6 aspect-square" />
+                        <span>Previous</span>
                     </a>
-                    <a href="#"
-                        class="justify-center items-start px-4 py-3.5 bg-white rounded border border-solid border-zinc-200">
-                        3
-                    </a>
-                    <a href="#"
-                        class="justify-center items-start px-4 py-3.5 bg-white rounded border border-solid border-zinc-200">
-                        4
-                    </a>
-                    <span class="flex gap-1">
-                        <NuxtImg loading="lazy" src="/paginationdots.png" alt=""
-                            class="w-5 h-5 mt-3.5 aspect-square border-zinc-200" />
-                        <a href="#"
-                            class="justify-center items-start px-4 py-3.5 bg-white rounded border border-solid border-zinc-200">
-                            10
-                        </a>
-                        <a href="#"
-                            class="justify-center items-start px-4 py-3.5 bg-white rounded border border-solid border-zinc-200">
-                            11
-                        </a>
-                    </span>
-                    <a href="#" class="flex gap-0.5 text-zinc-400">
-                        <NuxtImg loading="lazy" src="/paginationright.png" alt="Next page"
-                            class="w-5 h-5 mt-3.5 ml-5" />
-                        <span class="sr-only">Next page</span>
+                    <a href="#" class="text-black">1</a>
+                    <a href="#" class="text-black">2</a>
+                    <a href="#" class="text-black">3</a>
+                    <a href="#" class="text-black">...</a>
+                    <a href="#" class="text-black">8</a>
+                    <a href="#" class="text-white">
+                        <span>Next</span>
+                        <NuxtImg loading="lazy" src="/rightarrow.png" alt="Next" class="shrink-0 w-6 aspect-square" />
                     </a>
                 </nav>
             </section>
         </main>
     </div>
 </template>
-
 <script lang="ts">
 import BarChartC from '@/components/BarChart.vue';
+import ModelScoresGraph from '@/components/ModelScoresGraph.vue';  
 import ky from 'ky';
 import { defineComponent, computed, ref, onMounted } from 'vue';
 import { useWindowSize } from '@vueuse/core';
 import { useRouter } from 'vue-router'; 
 import Flatpickr from 'vue-flatpickr-component';
 import 'flatpickr/dist/flatpickr.css';
-import uPlot from 'uplot';
-import 'uplot/dist/uPlot.min.css';
 
 interface Config {
     evalID: string;
@@ -228,6 +198,7 @@ export default defineComponent({
     components: {
         Flatpickr,
         BarChartC,
+        ModelScoresGraph,
     },
     setup() {
         const router = useRouter(); 
@@ -250,7 +221,6 @@ export default defineComponent({
             dateFormat: 'Y/m/d',
             defaultDate: ['2019/04/14', '2024/06/14'],
         });
-        const uPlotContainer = ref<HTMLDivElement | null>(null);
 
         const filteredConfigs = computed(() => {
             const [startDate, endDate] = dateRange.value;
@@ -287,58 +257,8 @@ export default defineComponent({
             }
         };
 
-        const initChart = () => {
-            const container = uPlotContainer.value;
-
-            if (container) {
-                const categories = ['HealthCare', 'Finance', 'Geography', 'Politics', 'Psychology', 'History'];
-                const indices = categories.map((_, index) => index);
-
-                const data = [
-                    new Float64Array(indices),
-                    new Float64Array([50, 60, 55, 70, 65, 75]),
-                    new Float64Array([45, 65, 40, 55, 50, 60]),
-                    new Float64Array([60, 55, 50, 65, 60, 55]),
-                    new Float64Array([65, 70, 60, 45, 55, 65]),
-                ];
-
-                const opts: uPlot.Options = {
-                    title: 'Accuracy',
-                    width: container.clientWidth,
-                    height: 300,
-                    series: [
-                        {},
-                        { label: 'ChatGPT', stroke: 'cyan', paths: uPlot.paths?.spline?.() },
-                        { label: 'Meta', stroke: 'purple', paths: uPlot.paths?.spline?.() },
-                        { label: 'Anthropic', stroke: 'blue', paths: uPlot.paths?.spline?.() },
-                        { label: 'Mistral AI', stroke: 'orange', paths: uPlot.paths?.spline?.() },
-                    ],
-                    scales: {
-                        x: { time: false },
-                        y: { range: () => [30, 80] },
-                    },
-                    axes: [
-                        {
-                            stroke: 'black',
-                            label: 'Categories',
-                            values: (_self: uPlot, ticks: number[]) => ticks.map((i) => categories[i]),
-                        },
-                        {
-                            stroke: 'black',
-                            label: 'Accuracy (%)',
-                        },
-                    ],
-                };
-
-                new uPlot(opts, data, container);
-            } else {
-                console.error('uPlot container not found!');
-            }
-        };
-
         onMounted(() => {
             fetchConfigs();
-            initChart();
         });
 
         return {
@@ -350,12 +270,10 @@ export default defineComponent({
             searchQuery,
             dateRange,
             flatpickrConfig,
-            uPlotContainer,
             filteredConfigs,
             selectedLLM,
             llmLogos,
             llms,
-            initChart,
         };
     },
 });

From 147193a349434e76f14df2d7c5e5f08c377dfd44 Mon Sep 17 00:00:00 2001
From: Priyanshi1908 <115202982+Priyanshi1908@users.noreply.github.com>
Date: Sat, 16 Nov 2024 08:01:38 +0530
Subject: [PATCH 4/6] Added evalID column to downloaded csv file

---
 services/api/src/core/evaluation.ts | 37 ++++++++++++++---------------
 services/api/src/core/process.ts    | 21 +++++++++++-----
 2 files changed, 33 insertions(+), 25 deletions(-)

diff --git a/services/api/src/core/evaluation.ts b/services/api/src/core/evaluation.ts
index a0a8e87..a514897 100644
--- a/services/api/src/core/evaluation.ts
+++ b/services/api/src/core/evaluation.ts
@@ -122,6 +122,7 @@ evaluationRouter.post('/evaluateCsv',
       const reports = await generateReportsBatch(openai, model, prompts);
 
       let totalScore = 0;
+      const csvData = [];
 
       for (let i = 0; i < evaluationResults.length; i++) {
         const result = evaluationResults[i];
@@ -131,7 +132,7 @@ evaluationRouter.post('/evaluateCsv',
 
         totalScore += score;
 
-        await db.insert(evaluations).values({
+        const newEvaluation = await db.insert(evaluations).values({
           model,
           question: result.question,
           answer: result.answer,
@@ -139,27 +140,26 @@ evaluationRouter.post('/evaluateCsv',
           choice,
           score: String(score),
           createdAt: new Date(),
+        }).returning();
+
+        csvData.push({
+          ...result,
+          choice,
+          score,
+          evaluationId: newEvaluation[0].id,
         });
       }
 
-const averageScore = totalScore / evaluationResults.length;
-
-await db.update(configs)
-  .set({
-    averageScore: averageScore.toFixed(4), 
-    model, 
-  })
-  .where(sql`${configs.id} = ${sql.raw(configId.toString())}`);
-
-
-
+      const averageScore = totalScore / evaluationResults.length;
 
+      await db.update(configs)
+        .set({
+          averageScore: averageScore.toFixed(4),
+          model,
+        })
+        .where(sql`${configs.id} = ${sql.raw(configId.toString())}`);
 
-      const csvContent = generateCSV(evaluationResults.map((result, index) => ({
-        ...result,
-        choice: reports[index].choice,
-        score: choiceToScore[reports[index].choice] || 0,
-      })));
+      const csvContent = generateCSV(csvData);
 
       c.header('Content-Type', 'text/csv');
       c.header('Content-Disposition', `attachment; filename=config_${configId}_results.csv`);
@@ -191,7 +191,6 @@ function generateCSV(results: any[]): string {
   return csvContent;
 }
 
-
 evaluationRouter.post('/ModelAverageScores', async (c) => {
   const db = createDbConnection(c.env.DATABASE_URL);
 
@@ -210,7 +209,7 @@ evaluationRouter.post('/ModelAverageScores', async (c) => {
       }
 
       const totalScore = configsForModel.reduce((sum, config) => {
-        return sum + parseFloat(config.averageScore || '0'); // Convert score to float
+        return sum + parseFloat(config.averageScore || '0'); 
       }, 0);
 
       const avgScore = totalScore / configsForModel.length;
diff --git a/services/api/src/core/process.ts b/services/api/src/core/process.ts
index 8b5b4df..d0e676d 100644
--- a/services/api/src/core/process.ts
+++ b/services/api/src/core/process.ts
@@ -1,6 +1,6 @@
 import { NeonHttpDatabase } from "drizzle-orm/neon-http";
 import OpenAI from "openai";
-import { generateResponse, generateReport } from "../utils/openai"; // Ensure these functions are exported correctly
+import { generateResponse, generateReport } from "../utils/openai"; 
 import { evaluations } from "../db/schema";
 
 export async function evaluateQuestion(
@@ -42,7 +42,7 @@ export async function evaluateQuestionBatch(
   openai: OpenAI,
   model: string,
   questions: { content: string; answer: string }[]
-): Promise<{ question: string; answer: string; generated: string }[]> {
+): Promise<{ question: string; answer: string; generated: string; evaluationId: number }[]> {
   const results = await Promise.all(
     questions.map(async (question) => {
       const result = await openai.chat.completions.create({
@@ -50,15 +50,24 @@ export async function evaluateQuestionBatch(
         messages: [{ role: "user", content: question.content }],
         max_tokens: 150,
       });
-      
-      const generatedText = result.choices[0]?.message?.content?.trim() || ""; // Ensures fallback to an empty string if content is null or undefined
+
+      const generatedText = result.choices[0]?.message?.content?.trim() || "";
+
+      const newEvaluation = await db.insert(evaluations).values({
+        model,
+        question: question.content,
+        answer: question.answer,
+        output: generatedText,
+        createdAt: new Date(),
+      }).returning();
 
       return {
         question: question.content,
         answer: question.answer,
-        generated: generatedText
+        generated: generatedText,
+        evaluationId: newEvaluation[0].id,
       };
     })
   );
   return results;
-}
+}
\ No newline at end of file

From 08484eef5992f65b4293c0a392f6eaee3ae0c037 Mon Sep 17 00:00:00 2001
From: Priyanshi1908 <115202982+Priyanshi1908@users.noreply.github.com>
Date: Sat, 16 Nov 2024 08:58:06 +0530
Subject: [PATCH 5/6] Integrated PDF script

---
 services/api/package.json                     |   1 +
 services/api/src/core/evaluation.ts           | 205 ++++++++++++++++--
 .../app/pages/reviewandrun/ReviewAndRun.vue   |  23 +-
 3 files changed, 192 insertions(+), 37 deletions(-)

diff --git a/services/api/package.json b/services/api/package.json
index 24af197..21071bb 100644
--- a/services/api/package.json
+++ b/services/api/package.json
@@ -35,6 +35,7 @@
     "drizzle-orm": "^0.30.10",
     "hono": "^4.6.10",
     "jose": "^5.9.6",
+    "jspdf": "^2.5.2",
     "ky": "^1.7.2",
     "openai": "^4.72.0",
     "p-limit": "^6.1.0",
diff --git a/services/api/src/core/evaluation.ts b/services/api/src/core/evaluation.ts
index a514897..1145e73 100644
--- a/services/api/src/core/evaluation.ts
+++ b/services/api/src/core/evaluation.ts
@@ -2,15 +2,14 @@ import { Hono } from "hono";
 import { HTTPException } from "hono/http-exception";
 import { zValidator } from "@hono/zod-validator";
 import { z } from "zod";
+import { jsPDF } from "jspdf";
 import { createDbConnection, createOpenAIClient } from "../utils/functions";
-import { evaluateQuestionBatch } from "./process"; // New batch evaluation function
+import { evaluateQuestionBatch } from "./process";
 import { parseCSV } from "../utils/functions";
-import { getRecordsWithIds } from "../utils/db";
-import { generateReportsBatch } from "../utils/openai"; // New batch report generation function
-import { configs, evaluations,models } from "../db/schema";
+import { generateReportsBatch } from "../utils/openai";
+import { configs, evaluations, models } from "../db/schema";
 import { sql } from 'drizzle-orm';
-import { eq } from 'drizzle-orm';  
-
+import { eq } from 'drizzle-orm';
 
 export type Env = {
   DATABASE_URL: string;
@@ -21,7 +20,6 @@ export type Env = {
 
 const evaluationRouter = new Hono<{ Bindings: Env }>();
 
-// Mapping the choice letter to the corresponding score
 const choiceToScore: Record<string, number> = {
   A: 0.4,
   B: 0.6,
@@ -53,7 +51,6 @@ Return the result as a JSON object with the following format:
 Ensure the response is only this JSON object for each question-answer pair.`;
   }
 
-  // Default or gpt-4o-mini prompt
   return `You are comparing a submitted answer to an expert answer on a given question. Here is the data:
 [BEGIN DATA]
 [Context]: ${context}
@@ -78,7 +75,7 @@ Please return the answer strictly as a JSON object with the following structure,
 Only include this JSON object in your response.`;
 };
 
-evaluationRouter.post('/evaluateCsv',
+evaluationRouter.post('/evaluatePdf',
   zValidator('json', z.object({
     configId: z.number(),
     model: z.string(),
@@ -159,16 +156,187 @@ evaluationRouter.post('/evaluateCsv',
         })
         .where(sql`${configs.id} = ${sql.raw(configId.toString())}`);
 
-      const csvContent = generateCSV(csvData);
-
-      c.header('Content-Type', 'text/csv');
-      c.header('Content-Disposition', `attachment; filename=config_${configId}_results.csv`);
-
-      return c.body(csvContent);
+      const doc = new jsPDF("p", "pt", "a4");
+      const margin = 50;
+      const pageWidth = doc.internal.pageSize.getWidth();
+      const pageHeight = doc.internal.pageSize.getHeight();
+      const lineHeight = 14;
+      const contentWidth = pageWidth - 2 * margin;
+      let yPos = margin;
+
+      const primaryColor = [0, 32, 96];
+      const accentColor = [128, 128, 128];
+
+      doc.setFont("Times", "Roman");
+
+      const addDivider = () => {
+        doc.setDrawColor(accentColor[0], accentColor[1], accentColor[2]);
+        doc.setLineWidth(0.5);
+        yPos += 10;
+        doc.line(margin, yPos, pageWidth - margin, yPos);
+        yPos += 15;
+      };
+
+      const addHeader = (title: string, pageNum: number) => {
+        yPos = margin;
+        doc.setFont("Helvetica", "Bold");
+        doc.setFontSize(18);
+        doc.setTextColor(primaryColor[0], primaryColor[1], primaryColor[2]);
+        doc.text(title, margin, yPos);
+        yPos += 20;
+        addDivider();
+        doc.setFont("Times", "Italic");
+        doc.setFontSize(10);
+        doc.setTextColor(accentColor[0], accentColor[1], accentColor[2]);
+        doc.text(`Page ${pageNum}`, pageWidth / 2, pageHeight - margin / 2, { align: "center" });
+      };
+
+      const addSectionHeader = (text: string) => {
+        doc.setFont("Helvetica", "Bold");
+        doc.setFontSize(14);
+        doc.setTextColor(primaryColor[0], primaryColor[1], primaryColor[2]);
+        doc.text(text, margin, yPos);
+        yPos += 20;
+      };
+
+      const addSubtitle = (text: string) => {
+        doc.setFont("Helvetica", "Italic");
+        doc.setFontSize(12);
+        doc.setTextColor(accentColor[0], accentColor[1], accentColor[2]);
+        doc.text(text, margin, yPos);
+        yPos += 18;
+      };
+
+      const addBodyText = (text: string) => {
+        doc.setFontSize(11);
+        doc.setFont("Times", "Roman");
+        doc.setTextColor(0);
+        const lines = doc.splitTextToSize(text, contentWidth);
+        doc.text(lines, margin, yPos);
+        yPos += lines.length * (lineHeight + 2);
+      };
+
+      const addBulletPoint = (text: string) => {
+        doc.setFontSize(11);
+        doc.setFont("Times", "Roman");
+        doc.setTextColor(0);
+        const bullet = '\u2022';
+        const lines = doc.splitTextToSize(text, contentWidth - 15);
+        doc.text(bullet, margin, yPos);
+        doc.text(lines, margin + 15, yPos);
+        yPos += lines.length * (lineHeight + 2);
+      };
+
+      const addTable = (data: string[][], colWidths: number[]) => {
+        const rowHeight = 20;
+        data.forEach((row, rowIndex) => {
+          row.forEach((cell, colIndex) => {
+            const x = margin + colWidths.slice(0, colIndex).reduce((a, b) => a + b, 0);
+            if (rowIndex === 0) {
+              doc.setFont("Helvetica", "Bold");
+              doc.setFontSize(11);
+              doc.setTextColor(255, 255, 255);
+              doc.setFillColor(primaryColor[0], primaryColor[1], primaryColor[2]);
+              doc.rect(x, yPos, colWidths[colIndex], rowHeight, "F");
+              doc.text(cell, x + 5, yPos + rowHeight / 2 + 4);
+            } else {
+              doc.setFont("Times", "Roman");
+              doc.setFontSize(10);
+              doc.setTextColor(0);
+              doc.setFillColor(245, 245, 245);
+              doc.rect(x, yPos, colWidths[colIndex], rowHeight, "F");
+              doc.text(cell, x + 5, yPos + rowHeight / 2 + 4);
+            }
+          });
+          yPos += rowHeight;
+        });
+        yPos += 10;
+      };
+
+      addHeader("LLM Audit Report", 1);
+      addSectionHeader("Average Score");
+      doc.setFont("Helvetica", "Bold");
+      doc.setFontSize(24);
+      doc.setTextColor(0, 0, 139);
+      doc.text(`Average Score: ${averageScore.toFixed(2)}`, margin, yPos);
+      yPos += 40; 
+      addSectionHeader("Introduction");
+      addBodyText("In today's rapidly evolving technological landscape, Large Language Models (LLMs) have emerged as powerful tools capable of generating human-quality text, translating languages, and answering complex questions with remarkable accuracy. As these models become increasingly integrated into various sectors, ensuring their responsible development and deployment is paramount. At ethosAI, we are committed to providing transparent and accountable AI evaluation through our advanced LLM auditing engine.");
+      addBodyText("Our engine is built on an in-house LLM that rigorously assesses AI models across three core principles: Holistic Assessment, Dynamic Benchmarking, and Ethical Foundations. This approach allows us to evaluate not only an LLM's factual knowledge and recall but also its logical reasoning, creative abilities, and ethical decision-making capabilities.");
+      addSubtitle("Ensuring Accuracy and Fairness");
+      addBodyText("Ensuring the accuracy and fairness of LLM models is paramount. As these models become integral to key sectors such as healthcare, finance, and transportation, the risks associated with biases and inaccuracies increase significantly. Traditional methods of LLM evaluation often struggle to catch subtle biases or predict how models will perform in diverse real-world scenarios. This gap not only threatens the reliability of AI applications but also raises serious ethical concerns.");
+
+      addSectionHeader("Case Study: US Constitution");
+      addBodyText("The audit process involves a systematic methodology to evaluate the performance of LLMs in answering factual questions related to the Constitution of the United States of America.");
+
+      doc.addPage();
+      addHeader("LLM Audit Report", 2);
+      addSectionHeader("The Audit Process");
+      addBodyText("Our audit process includes the following steps:");
+      addBulletPoint("Generation of Evaluation Files: We meticulously crafted a set of questions and corresponding ideal answers based on the chosen topic, covering a wide range of complexities and subtopics.");
+      addBulletPoint("Selection of LLMs: Representative LLMs, in this case, GPT-4o and GPT-4o mini, were selected for evaluation.");
+      addBulletPoint("Running the Evaluation: We utilized the ethosAI engine to facilitate the interaction between the questions and the selected LLMs, recording the responses for subsequent analysis.");
+      addBulletPoint("Analysis and Results: We carefully analyzed the LLM responses, comparing them against the pre-defined ideal answers to evaluate their accuracy, relevance, and completeness.");
+
+      addSectionHeader("Scoring Methodology");
+      addBodyText("To ensure objective and comprehensive scoring, we employed a distance-based scoring methodology. A second LLM was used to calculate the distance between the ideal answers and the actual outputs generated by GPT-4o and GPT-4o mini.");
+
+      const scoringTableData = [
+          ["Choice", "Score", "Description"],
+          ["A", "0.4", "The submitted answer is a subset of the expert answer and is fully consistent with it."],
+          ["B", "0.6", "The submitted answer is a superset of the expert answer and is fully consistent with it."],
+          ["C", "1", "The submitted answer contains all the same details as the expert answer."],
+          ["D", "0", "There is a disagreement between the submitted answer and the expert answer."],
+          ["E", "1", "The answers differ, but these differences don't matter from the perspective of factuality."]
+      ];
+      addTable(scoringTableData, [60, 60, contentWidth - 130]);
+
+      doc.addPage();
+      addHeader("LLM Audit Report", 3);
+      addSectionHeader("Results & Findings");
+      addBodyText("Based on these scores, we measured two key performance indicators:");
+      addBulletPoint("Accuracy: Defined as the percentage of times a score of 'C' or 'E' (i.e., a perfect score of 1) was achieved.");
+      addBulletPoint("Average Score: Calculated as the mean of all scores obtained across the questions.");
+
+      const resultTableData = [
+          ["Category", "Accuracy (%)", "Average Score"],
+          ["Presidency", "75%", "0.875"],
+          ["Amendments", "71%", "0.858"],
+          ["Congress", "67%", "0.867"],
+          ["Federalism", "60%", "0.8"],
+          ["General", "53%", "0.791"],
+          ["Supreme Court", "50%", "0.8"],
+          ["Rights & Liberty", "0%", "0.6"]
+      ];
+      addTable(resultTableData, [200, 100, 100]);
+
+      doc.addPage();
+      addHeader("LLM Audit Report", 4);
+      addSectionHeader("Conclusion");
+      addBodyText("This audit provides a comprehensive evaluation of GPT-4o and GPT-4o mini's capabilities in answering questions related to the U.S. Constitution.");
+
+      addSectionHeader("Recommendations");
+      addBulletPoint("Fine-tuning on Specific Domains: Further training on legal terminology and concepts related to the Constitution could enhance the models' performance.");
+      addBulletPoint("Addressing Bias and Ensuring Neutrality: It's crucial to ensure that the models' responses are unbiased and reflect the neutrality of the Constitution.");
+      addBulletPoint("Enhancing Explainability: The models should be able to provide clear and concise explanations for their answers.");
+
+      yPos = pageHeight - margin - 30;
+      doc.setFontSize(10);
+      doc.setFont("Times", "Italic");
+      doc.setTextColor(accentColor[0], accentColor[1], accentColor[2]);
+      doc.text("https://ethosai.one/", margin, yPos);
+      doc.text("founders@ethosai.one", pageWidth - margin, yPos, { align: "right" });
+
+      const pdfBlob = new Blob([doc.output('arraybuffer')], { type: 'application/pdf' });
+
+      c.header('Content-Type', 'application/pdf');
+      c.header('Content-Disposition', `attachment; filename=config_${configId}_report.pdf`);
+
+      return c.body(await pdfBlob.arrayBuffer());
 
     } catch (error) {
-      console.error("Error evaluating CSV:", error);
-      return new HTTPException(500, { message: "Batch CSV evaluation failed" }).getResponse();
+      console.error("Error evaluating PDF:", error);
+      return new HTTPException(500, { message: "Batch evaluation failed" }).getResponse();
     }
   }
 );
@@ -214,7 +382,6 @@ evaluationRouter.post('/ModelAverageScores', async (c) => {
 
       const avgScore = totalScore / configsForModel.length;
 
-
       const existingModel = await db
         .select()
         .from(models)
@@ -243,4 +410,4 @@ evaluationRouter.post('/ModelAverageScores', async (c) => {
   }
 });
 
-export default evaluationRouter;
+export default evaluationRouter;
\ No newline at end of file
diff --git a/services/app/pages/reviewandrun/ReviewAndRun.vue b/services/app/pages/reviewandrun/ReviewAndRun.vue
index 13ad1a3..804c92c 100644
--- a/services/app/pages/reviewandrun/ReviewAndRun.vue
+++ b/services/app/pages/reviewandrun/ReviewAndRun.vue
@@ -190,7 +190,6 @@ export default {
 
     };
 
-    // Frontend code
     const runEvaluation = async () => {
   if (!selectedLlm.value || !configId.value) {
     console.error('Missing selected LLM or config ID.');
@@ -201,13 +200,12 @@ export default {
 
   const payload = {
     configId: Number(configId.value),
-    model: model,  
+    model: model,
   };
   loading.value = true;
 
   try {
-    // Step 1: Evaluate the configuration
-    const response = await fetch('http://localhost:8787/eval/evaluateCsv', {
+    const response = await fetch('http://localhost:8787/eval/evaluatePdf', {
       method: 'POST',
       headers: {
         'Content-Type': 'application/json',
@@ -216,32 +214,22 @@ export default {
     });
 
     if (response.ok) {
-      // Step 2: Download the CSV file after evaluation
-      const contentDisposition = response.headers.get('Content-Disposition');
-      console.log("Content-Disposition Header:", contentDisposition);
-
-      const filenameMatch = contentDisposition && contentDisposition.match(/filename="?(.+)"?/i);
-      const filename = filenameMatch ? filenameMatch[1] : 'evaluation_results.csv';
-
       const blob = await response.blob();
 
       const url = window.URL.createObjectURL(blob);
-
       const link = document.createElement('a');
       link.href = url;
-      link.download = filename;
+      link.download = 'evaluation_report.pdf';
       document.body.appendChild(link);
       link.click();
 
       window.URL.revokeObjectURL(url);
       document.body.removeChild(link);
 
-      console.log('CSV file downloaded successfully');
+      console.log('PDF file downloaded successfully');
 
-      // Step 3: Call the API to update the model's average score
       await updateModelAverageScore();
 
-      // Step 4: Redirect after the evaluation is complete and model score is updated
       router.push({ name: 'auditqueue' });
     } else {
       console.error('Failed to run evaluation');
@@ -249,11 +237,10 @@ export default {
   } catch (error) {
     console.error('Error in evaluation:', error);
   } finally {
-    loading.value = false;  // Hide loading spinner
+    loading.value = false; 
   }
 };
 
-// Function to call the API to update the model's average score
 const updateModelAverageScore = async () => {
   try {
     const response = await fetch('http://localhost:8787/eval/ModelAverageScores', {

From 6a191160d82648b44c702397f763c157419605d8 Mon Sep 17 00:00:00 2001
From: Priyanshi1908 <115202982+Priyanshi1908@users.noreply.github.com>
Date: Sat, 16 Nov 2024 09:36:53 +0530
Subject: [PATCH 6/6] Added new table in generated PDF

---
 services/api/src/core/evaluation.ts | 35 +++++++++++++++++++++--------
 1 file changed, 26 insertions(+), 9 deletions(-)

diff --git a/services/api/src/core/evaluation.ts b/services/api/src/core/evaluation.ts
index 1145e73..1122787 100644
--- a/services/api/src/core/evaluation.ts
+++ b/services/api/src/core/evaluation.ts
@@ -254,12 +254,14 @@ evaluationRouter.post('/evaluatePdf',
       };
 
       addHeader("LLM Audit Report", 1);
-      addSectionHeader("Average Score");
+      addSectionHeader(`Testing against ${model}`);  
+      yPos += 20;
       doc.setFont("Helvetica", "Bold");
       doc.setFontSize(24);
       doc.setTextColor(0, 0, 139);
       doc.text(`Average Score: ${averageScore.toFixed(2)}`, margin, yPos);
       yPos += 40; 
+
       addSectionHeader("Introduction");
       addBodyText("In today's rapidly evolving technological landscape, Large Language Models (LLMs) have emerged as powerful tools capable of generating human-quality text, translating languages, and answering complex questions with remarkable accuracy. As these models become increasingly integrated into various sectors, ensuring their responsible development and deployment is paramount. At ethosAI, we are committed to providing transparent and accountable AI evaluation through our advanced LLM auditing engine.");
       addBodyText("Our engine is built on an in-house LLM that rigorously assesses AI models across three core principles: Holistic Assessment, Dynamic Benchmarking, and Ethical Foundations. This approach allows us to evaluate not only an LLM's factual knowledge and recall but also its logical reasoning, creative abilities, and ethical decision-making capabilities.");
@@ -299,16 +301,31 @@ evaluationRouter.post('/evaluatePdf',
       addBulletPoint("Average Score: Calculated as the mean of all scores obtained across the questions.");
 
       const resultTableData = [
-          ["Category", "Accuracy (%)", "Average Score"],
-          ["Presidency", "75%", "0.875"],
-          ["Amendments", "71%", "0.858"],
-          ["Congress", "67%", "0.867"],
-          ["Federalism", "60%", "0.8"],
-          ["General", "53%", "0.791"],
-          ["Supreme Court", "50%", "0.8"],
-          ["Rights & Liberty", "0%", "0.6"]
+        ["Category", "Accuracy (%)", "Average Score"],
+        ["Presidency", "75%", "0.875"],
+        ["Amendments", "71%", "0.858"],
+        ["Congress", "67%", "0.867"],
+        ["Federalism", "60%", "0.8"],
+        ["General", "53%", "0.791"],
+        ["Supreme Court", "50%", "0.8"],
+        ["Rights & Liberty", "0%", "0.6"]
       ];
       addTable(resultTableData, [200, 100, 100]);
+      
+      yPos += 20; 
+      
+      addSectionHeader("Detailed Evaluation Results");
+      const detailedTableData = [
+        ["Question", "Expected Answer", "Choice", "Score", "Evaluation ID"],
+        ...csvData.map(result => [
+          result.question,
+          result.answer,
+          result.choice,
+          result.score.toString(),
+          result.evaluationId.toString(),
+        ])
+      ];
+      addTable(detailedTableData, [150, 150, 50, 50, 60]);
 
       doc.addPage();
       addHeader("LLM Audit Report", 4);