Refactor calculating score. Add sort node for vanity

agent/agent.ts

@@ -9,6 +9,7 @@ import { ragasMetrics } from "./nodes/ragasMetrics";
 import { produceRanking } from "./nodes/produceRanking";
 import { createModelNode } from "./nodes/model";
 import { loopEndConditional } from "./conditionals/loop_end";
+import { sort } from "./nodes/sort";
 
 const triggerEventToolNode = createToolNode(triggerEventToolsByName);
 
@@ -34,6 +35,7 @@ const agent = new StateGraph(MessagesState)
   .addNode("relationModel", relationModel)
   
   .addNode(produceRanking.name, produceRanking)
+  .addNode(sort.name, sort)
   
   .addEdge(START, normalizationSetup.name)
   .addEdge(normalizationSetup.name, "normalisationModel")
@@ -52,7 +54,9 @@ const agent = new StateGraph(MessagesState)
   .addEdge("relationModel", produceRanking.name)
 
   // @ts-expect-error
-  .addConditionalEdges(produceRanking.name, loopEndConditional, [verificationSetup.name, END])
+  .addConditionalEdges(produceRanking.name, loopEndConditional, [verificationSetup.name, sort.name])
+  
+  .addEdge(sort.name, END)
 
   .compile();
 

agent/conditionals/loop_end.ts

@@ -7,7 +7,7 @@ export const loopEndConditional: ConditionalEdgeRouter<typeof MessagesState, Str
     const triggerEventsIndex = state.proposedTriggerEventIndex;
 
     if (triggerEventsIndex == triggerEvents.length-1) {
-      return END
+      return "sort"
     }
     else {
       return "verificationSetup"

agent/nodes/produceRanking.ts

@@ -2,49 +2,59 @@ import { GraphNode } from "@langchain/langgraph";
 import { MessagesState } from "../state";
 import { BaseMessage } from "@langchain/core/messages";
 
-type Priority = keyof typeof mapping;
+//TODO: Each of these might need different weights
+const keys = ["CONFIDENCE", "RAGAS", "RELATION"];
 
 const mapping = {
   VERYHIGH: 1.0,
   HIGH: 0.75,
   MEDIUM: 0.5,
   LOW: 0.25,
-  VERYLOW: 0.0
+  VERYLOW: 0.0,
 } as const;
 
-function mapResponse(value: string): number {
-  const upper = value.toUpperCase() as Priority;
+type Priority = keyof typeof mapping;
 
-  if (upper in mapping) {
-    return mapping[upper];
-  }
+function mapResponse(value: string | undefined | null): number {
+  if (!value) return 0;
 
-  return 0;
+  const trimmed = value.trim();
+  const num = parseFloat(trimmed);
+
+  // If number, return it
+  if (!isNaN(num)) return num;
+
+  // Otherwise, map to value
+  const upper = trimmed.toUpperCase() as Priority;
+  return mapping[upper] ?? 0;
 }
 
 function getLastMessageContaining(
   messages: BaseMessage[],
   searchString: string
-): string {
+): string | null {
   for (let i = messages.length - 1; i >= 0; i--) {
     const content = messages[i].content;
     if (typeof content === "string" && content.includes(searchString)) {
       return content;
     }
   }
-  return "";
+  return null;
 }
 
 export const produceRanking: GraphNode<typeof MessagesState> = async (state) => {
-  //TODO: what should these weights be
-  let conf = getLastMessageContaining(state.messages, "CONFIDENCE")?.split(":")[1] //TODO: we can better error handle here
-  let ragas = getLastMessageContaining(state.messages, "RAGAS")?.split(":")[1] //TODO: we can genericify this too surely
-  let rel = getLastMessageContaining(state.messages, "RELATION")?.split(":")[1]
+  // Extract and map values
+  const values = keys.map((key) => {
+    const msg = getLastMessageContaining(state.messages, key);
+    const part = msg?.split(":").at(1);
+    return mapResponse(part);
+  });
 
-  let result = mapResponse(conf) * Number.parseFloat(ragas) * mapResponse(rel)
+  // Multiply!
+  const result = values.reduce((acc, val) => acc * val, 1);
 
-  let current = state.proposedTriggerEvent;
+  const current = state.proposedTriggerEvent;
   current[state.proposedTriggerEventIndex].score = result;
 
-  return  { proposedTriggerEvent: current };
+  return { proposedTriggerEvent: current };
 };

agent/nodes/ragasMetrics.ts

@@ -8,8 +8,6 @@ export const ragasMetrics: GraphNode<typeof MessagesState> = async (state) => {
   const answer = state.proposedTriggerEvent[state.proposedTriggerEventIndex].Event
   const contexts = state.proposedTriggerEvent[state.proposedTriggerEventIndex].context?.split("^^^") ?? []
   
-  console.log(contexts)
-  
   const results = await evaluateWithRagas({question, answer, contexts})
   
   return {

agent/nodes/sort.ts

@@ -0,0 +1,20 @@
+import { GraphNode } from "@langchain/langgraph";
+import { MessagesState } from "../state";
+import { AIMessage } from "@langchain/core/messages";
+export const sort: GraphNode<typeof MessagesState> = async (state) => {
+  //not sure which will be better from API, just do both
+
+  let current = state.proposedTriggerEvent;
+  current.sort((a, b) => ((b.score as number) ?? 0) - ((a.score as number) ?? 0));
+
+
+  const displayVersion = current.map((item) => ({
+    event: item.Event,
+    reasoningWhyRelevant: item.ReasoningWhyRelevant,
+    score: item.score ?? 0,
+  }));
+
+  let message = new AIMessage(JSON.stringify(displayVersion))
+
+  return { proposedTriggerEvent: current, messages: [message] };
+};

agent/state.ts

@@ -1,12 +1,6 @@
 import {
-  StateGraph,
   StateSchema,
   MessagesValue,
-  ReducedValue,
-  GraphNode,
-  ConditionalEdgeRouter,
-  START,
-  END,
 } from "@langchain/langgraph";
 import { z } from "zod/v4";
 
@@ -17,7 +11,7 @@ export const ProposedTriggerEvent = z.object({
   Url: z.url(),
   IsItselfDisinformation: z.boolean(),
   context: z.string().optional(),
-  score: z.number().optional
+  score: z.number().optional()
 })
 
 export const ProposedTriggerEventArray = z.array(ProposedTriggerEvent);