low-level experimental epistemic intelligence

api_server.py

@@ -5,6 +5,11 @@ import requests
 from fastapi import FastAPI, Request
 from pydantic import BaseModel
 from fastapi.middleware.cors import CORSMiddleware
+from fastapi.responses import HTMLResponse
+from fastapi.staticfiles import StaticFiles
+from fastapi.responses import FileResponse
+from fastapi import BackgroundTasks
+
 from core.conversation_manager import ConversationState
 from core.conversation_engine import handle_turn
 
@@ -13,13 +18,11 @@ from core.input_classifier import is_meaningful_input
 from core.memory_store import save_state, load_state # session persistence handling
 from core.conversation_manager import from_dict # to have the retrieved conversation in DICT/JSON converted to ConversationState Object
 
-from fastapi.responses import HTMLResponse
-from fastapi.staticfiles import StaticFiles
-from fastapi.responses import FileResponse
-
-from fastapi import BackgroundTasks
 from agents.epistemic_agent import epistemic_response
 
+from core.epistemic.profile_manager import update_global_profile
+from core.epistemic.epistemic_cross import cross_session_analysis
+
 # CREATE APP FIRST
 app = FastAPI()
 
@@ -225,6 +228,26 @@ def chat(req: ChatRequest, background_tasks: BackgroundTasks):
     # -----------------------------
     output = handle_turn(state, message)
 
+     
+    # ---- (EXPERIMENTAL) LOW-LEVEL CROSS-SESSION EPISTEMIC INTELLIGENCE/ANALYSIS ----
+    
+    # -------------------------------
+    # UPDATE GLOBAL PROFILE
+    # -------------------------------
+    state.session_id = session_id  # ensure attached
+    session_record = update_global_profile(state)
+
+    # -------------------------------
+    # EPISTEMIC CROSS-SESSION
+    # -------------------------------
+    epistemic_text = cross_session_analysis(session_record)
+
+    # attach to response
+    output["witness_updates"] = {
+        "epistemic": epistemic_text
+    }
+    # ---- (EXPERIMENTAL) LOW-LEVEL CROSS-SESSION EPISTEMIC INTELLIGENCE/ANALYSIS - End ----
+
     # -----------------------------------------
     # SAVE STATE AFTER EVERY TURN (PERSISTENCE)
     # -----------------------------------------

core/epistemic/epistemic_cross.py

@@ -0,0 +1,57 @@
+
+# ./core/epistemic/epistemic_cross.py
+
+from core.profile_store import load_profile
+
+
+def cross_session_analysis(current_session):
+
+    profile = load_profile()
+
+    past = profile["sessions"][:-1]  # exclude current
+
+    if not past:
+        return "No prior sessions to compare."
+
+    # -------------------------
+    # PATTERN DETECTION
+    # -------------------------
+    repeated = []
+
+    for s in past:
+        overlap = set(s["themes"]) & set(current_session["themes"])
+        if len(overlap) >= 1:
+            repeated.extend(list(overlap))
+
+    repeated = list(set(repeated))
+
+    # -------------------------
+    # DEPTH TREND
+    # -------------------------
+    prev_depth = past[-1]["depth"]
+    curr_depth = current_session["depth"]
+
+    if curr_depth > prev_depth:
+        trend = "Growth detected (increasing depth)"
+    elif curr_depth < prev_depth:
+        trend = "Regression detected (reduced depth)"
+    else:
+        trend = "Stable level of engagement"
+
+    # -------------------------
+    # BUILD RESPONSE
+    # -------------------------
+    response = f"""
+CROSS-SESSION ANALYSIS:
+
+PATTERNS:
+{", ".join(repeated) if repeated else "No strong repetition detected"}
+
+TRAJECTORY:
+Previous depth: {prev_depth} → Current depth: {curr_depth}
+
+EVALUATION:
+{trend}
+"""
+
+    return response.strip()

core/epistemic/profile_manager.py

@@ -0,0 +1,81 @@
+
+# ./core/epistemic/profile_manager.py
+
+from core.profile_store import load_profile, save_profile
+
+
+# -------------------------------
+# BASIC THEME EXTRACTION (LIGHT)
+# -------------------------------
+def extract_themes(text):
+
+    keywords = {
+        "self-doubt": ["doubt", "not sure", "uncertain"],
+        "identity": ["who am i", "identity", "self"],
+        "fear": ["afraid", "fear", "anxiety"],
+        "avoidance": ["avoid", "escape", "ignore"],
+        "meaning": ["meaning", "purpose"],
+    }
+
+    detected = set()
+
+    text = text.lower()
+
+    for theme, words in keywords.items():
+        for w in words:
+            if w in text:
+                detected.add(theme)
+
+    return list(detected)
+
+
+# -------------------------------
+# DEPTH SCORING
+# -------------------------------
+def score_depth(text):
+
+    text = text.lower()
+
+    if "i feel" in text or "i am" in text:
+        return 4
+    elif "why" in text:
+        return 3
+    elif "what is" in text:
+        return 1
+    else:
+        return 2
+
+
+# -------------------------------
+# MAIN FUNCTION
+# -------------------------------
+def update_global_profile(state):
+
+    profile = load_profile()
+
+    # ---- collect client text ----
+    client_msgs = [
+        m["content"]
+        for m in state.history
+        if m["role"] == "client"
+    ]
+
+    full_text = " ".join(client_msgs)
+
+    themes = extract_themes(full_text)
+    depth = score_depth(full_text)
+
+    session_record = {
+        "session_id": state.session_id,
+        "themes": themes,
+        "depth": depth
+    }
+
+    profile["sessions"].append(session_record)
+
+    # merge global themes
+    profile["themes"] = list(set(profile["themes"] + themes))
+
+    save_profile(profile)
+
+    return session_record

core/epistemic/profile_store.py

@@ -0,0 +1,25 @@
+
+# ./core/epistemic/profile_store.py
+
+import os
+import json
+
+PROFILE_PATH = "/data/profile.json"
+
+
+def load_profile():
+    if not os.path.exists(PROFILE_PATH):
+        return {
+            "sessions": [],
+            "themes": []
+        }
+
+    with open(PROFILE_PATH, "r") as f:
+        return json.load(f)
+
+
+def save_profile(profile):
+    os.makedirs(os.path.dirname(PROFILE_PATH), exist_ok=True)
+
+    with open(PROFILE_PATH, "w") as f:
+        json.dump(profile, f, indent=2)