Refactor/new prompts

custom-guidelines-pseudocode.txt

@@ -0,0 +1,11 @@
+if session_notes: 
+	custom_guidelines = get_cg("aklsdjfkljasdf", "fasdfasdjf")
+else:
+
+	custom_guidelines = get_cg("aklsdjfkljasdf")
+
+get_cg(general_guidelines, session_notes = "") -> str:
+ return custom_guidelines
+
+
+systemp = f"{custom-guidelines}"

src/client/app/api/journal/save/route.js

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+import { NextResponse } from 'next/server';
+
+export async function POST(req) {
+  try {
+    const { userId, text, id } = await req.json();
+
+    // No vectorization here! Just send the raw text to Python.
+    const res = await fetch('http://localhost:5001/upsert', {
+      method: 'POST',
+      headers: { 'Content-Type': 'application/json' },
+      body: JSON.stringify({
+        user_id: userId,
+        text: text,
+        id: id
+      })
+    });
+
+    return NextResponse.json(await res.json());
+  } catch (err) {
+    return NextResponse.json({ error: err.message }, { status: 500 });
+  }
+}

src/client/app/api/journal/summary/route.js

@@ -0,0 +1,50 @@
+import { NextResponse } from 'next/server';
+import { pipeline } from '@xenova/transformers';
+
+export async function POST(req) {
+  try {
+    const { userId, topic } = await req.json();
+
+    // 1. Generate the Vector locally on your CPU
+    const pipe = await pipeline('feature-extraction', 'Xenova/all-MiniLM-L6-v2');
+    const output = await pipe(topic, { pooling: 'mean', normalize: true });
+    const vector = Array.from(output.data);
+
+    // 2. Fetch relevant entries from your Python Bridge
+    const actianRes = await fetch('http://localhost:5001/search', {
+      method: 'POST',
+      headers: { 'Content-Type': 'application/json' },
+      body: JSON.stringify({ 
+        vector: vector, 
+        user_id: userId 
+      }),
+    });
+
+    const entries = await actianRes.json();
+
+    // Combine the retrieved logs into one "context" string
+    const context = entries.map(e => e.text).join("\n---\n");
+
+    // 3. Send to Ollama for the final summary
+    const ollamaRes = await fetch('http://localhost:11434/api/generate', {
+      method: 'POST',
+      headers: { 'Content-Type': 'application/json' },
+      body: JSON.stringify({
+        model: "llama3",
+        prompt: `Based on these journal entries:\n${context}\n\nSummarize the user's day regarding "${topic}" in one concise sentence.`,
+        stream: false
+      }),
+    });
+
+    const final = await ollamaRes.json();
+
+    return NextResponse.json({ 
+      summary: final.response,
+      rawContext: context 
+    });
+
+  } catch (error) {
+    console.error("Pipeline Error:", error);
+    return NextResponse.json({ error: "Check if Bridge and Ollama are running" }, { status: 500 });
+  }
+}

src/client/app/api/therapy/chat/route.js

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+export async function POST(req) {
+  const { userId, message, transcript, evidence, agenda } = await req.json();
+
+  const res = await fetch('http://localhost:5001/agent/run_session', {
+    method: 'POST',
+    headers: { 'Content-Type': 'application/json' },
+    body: JSON.stringify({
+        user_id: userId,
+        message: message,
+        transcript: transcript, // Pass history back to Python
+        evidence: evidence,      // Pass evidence back to Python
+	agenda: agenda
+    })
+  });
+
+  if (!res.ok) throw new Error("Bridge failed");
+
+  const data = await res.json();
+  return Response.json({
+    reply: data.therapy_response,
+    fullTranscript: data.full_transcript
+  });
+}

src/client/app/api/therapy/chat_stream/route.js

@@ -0,0 +1,19 @@
+export async function POST(req) {
+  const body = await req.json();
+
+  const res = await fetch('http://localhost:5001/agent/chat_stream', {
+    method: 'POST',
+    headers: { 'Content-Type': 'application/json' },
+    body: JSON.stringify(body),
+  });
+
+  if (!res.ok) return new Response("Bridge Connection Failed", { status: 500 });
+
+  return new Response(res.body, {
+    headers: {
+      'Content-Type': 'text/event-stream',
+      'Cache-Control': 'no-cache',
+      'Connection': 'keep-alive',
+    },
+  });
+}

src/client/app/api/therapy/end/route.js

@@ -0,0 +1,23 @@
+export async function POST(req) {
+  try {
+    const body = await req.json();
+
+    const res = await fetch('http://localhost:5001/agent/end_session', {
+      method: 'POST',
+      headers: { 'Content-Type': 'application/json' },
+      body: JSON.stringify({
+          user_id: body.userId,
+          transcript: body.transcript,
+          evidence: body.evidence,
+	  agenda: body.agenda
+      })
+    });
+
+    if (!res.ok) throw new Error("Bridge failed");
+
+    const data = await res.json();
+    return Response.json(data);
+  } catch (err) {
+    return Response.json({ error: err.message }, { status: 500 });
+  }
+}

src/client/app/api/therapy/start/route.js

@@ -0,0 +1,21 @@
+import { NextResponse } from 'next/server';
+
+export async function POST(req) {
+  const { userId, userNotes } = await req.json(); // Capture userNotes
+
+  const res = await fetch('http://localhost:5001/agent/start', {
+    method: 'POST',
+    headers: { 'Content-Type': 'application/json' },
+    body: JSON.stringify({ 
+      user_id: userId, 
+      user_notes: userNotes // Pass it to Flask
+    })
+  });
+
+  const data = await res.json();
+  return NextResponse.json({
+    openingMessage: data.food_for_thought,
+    evidenceFound: data.evidence,
+    agenda: data.agenda // Pass the generated agenda back to the frontend
+  });
+}

src/client/app/components/ExerciseList.js

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+"use client";
+import { useState } from 'react';
+import GuidedExercise from './GuidedExercise';
+
+export default function ExerciseList({ exercises }) {
+  const [activeExercise, setActiveExercise] = useState(null);
+
+  if (activeExercise) {
+    return (
+      <GuidedExercise
+        title={activeExercise.title}
+        script={activeExercise.content}
+        onExit={() => setActiveExercise(null)}
+      />
+    );
+  }
+
+  return (
+    <div className="grid grid-cols-1 md:grid-cols-3 gap-4">
+      {exercises.map((ex, i) => (
+        <div key={i} className="p-6 border rounded-2xl bg-white shadow-sm hover:shadow-md transition-shadow flex flex-col justify-between">
+          <div>
+            <span className={`text-xs font-bold px-2 py-1 rounded-full ${
+              ex.type === 'interactive' ? "bg-purple-100 text-purple-600" : "bg-blue-100 text-blue-600"
+            }`}>
+              {ex.type}
+            </span>
+            <h3 className="text-xl font-bold mt-4">{ex.title}</h3>
+            <p className="text-gray-600 mt-2 text-sm line-clamp-3">{ex.content}</p>
+          </div>
+
+          <button
+            onClick={() => ex.type === 'interactive' ? setActiveExercise(ex) : alert(ex.content)}
+            className="mt-6 w-full py-3 rounded-xl font-bold bg-gray-900 text-white hover:bg-black transition-colors"
+          >
+            {ex.type === 'interactive' ? "Start Guided Session" : "View Instructions"}
+          </button>
+        </div>
+      ))}
+    </div>
+  );
+}

src/client/app/components/GuidedExercise.js

@@ -0,0 +1,68 @@
+"use client";
+import { useState, useEffect } from 'react';
+
+export default function GuidedExercise({ title, script, onExit }) {
+  // Split the script by our special token
+  const sentences = script.split("[BREAK]").map(s => s.trim()).filter(s => s);
+  const [index, setIndex] = useState(0);
+  const [isPlaying, setIsPlaying] = useState(false);
+
+  const speak = (text) => {
+    // Stop any existing speech
+    window.speechSynthesis.cancel();
+
+    const utterance = new SpeechSynthesisUtterance(text);
+    utterance.rate = 0.9; // Slightly slower for therapy
+
+    utterance.onend = () => {
+      setIsPlaying(false);
+      // Auto-advance the index so the UI highlights the next sentence
+      if (index < sentences.length - 1) {
+        setIndex(prev => prev + 1);
+      }
+    };
+
+    window.speechSynthesis.speak(utterance);
+    setIsPlaying(true);
+  };
+
+  return (
+    <div className="fixed inset-0 bg-white z-50 flex flex-col items-center justify-center p-6">
+      <button onClick={onExit} className="absolute top-6 right-6 text-gray-400 hover:text-black">✕ Close</button>
+
+      <div className="max-w-2xl w-full text-center">
+        <span className="text-blue-500 font-bold uppercase tracking-widest text-xs">Guided Session</span>
+        <h2 className="text-3xl font-bold mt-2 mb-12">{title}</h2>
+
+        {/* The Karaoke Display */}
+        <div className="space-y-6 mb-12 text-2xl leading-relaxed">
+          {sentences.map((s, i) => (
+            <p key={i} className={`transition-all duration-500 ${
+              i === index ? "text-black font-medium scale-105" : "text-gray-200"
+            }`}>
+              {s}
+            </p>
+          ))}
+        </div>
+
+        {/* Control Button */}
+        <button
+          onClick={() => isPlaying ? window.speechSynthesis.cancel() : speak(sentences[index])}
+          className={`w-20 h-20 rounded-full flex items-center justify-center shadow-xl transition-all ${
+            isPlaying ? "bg-red-500" : "bg-green-600 hover:scale-110"
+          } text-white`}
+        >
+          {isPlaying ? (
+            <div className="flex gap-1"><div className="w-2 h-6 bg-white"></div><div className="w-2 h-6 bg-white"></div></div>
+          ) : (
+            <span className="text-3xl ml-1">▶</span>
+          )}
+        </button>
+
+        <p className="mt-6 text-gray-400 text-sm italic">
+          {index === sentences.length - 1 && !isPlaying ? "Exercise Complete" : "Press play to continue"}
+        </p>
+      </div>
+    </div>
+  );
+}