From a1f732fc9ee039ac72f8a5ee2a1a77a47f78721a Mon Sep 17 00:00:00 2001
From: Aaron Nelson <aaron@aaronnelson.studio>
Date: Mon, 27 Apr 2026 16:54:18 +0000
Subject: [PATCH] Dreamer: manifest writer, Late REM v1.2 (remove coherence
 pull)

---
 scripts/dream.py | 68 +++++++++++++++++++++++++++++++++++++++++++++---
 1 file changed, 65 insertions(+), 3 deletions(-)

diff --git a/scripts/dream.py b/scripts/dream.py
index e8e264e..ed8da8d 100644
--- a/scripts/dream.py
+++ b/scripts/dream.py
@@ -52,7 +52,7 @@ MODE_RANGES = {
 # Bump the relevant constant manually when changing a prompt.
 PROMPT_VERSION_NREM = "1.0"
 PROMPT_VERSION_EREM = "1.1"
-PROMPT_VERSION_LREM = "1.0"
+PROMPT_VERSION_LREM = "1.2"
 PROMPT_VERSION_SYN  = "1.0"
 
 def prompt_signature():
@@ -226,8 +226,9 @@ Something stranger is possible now — let the accumulated
 material from the night find its own shape. Compressed,
 associative, slightly off. Let the strangeness stand.
 
-No headers. No bullet points. No hedging. 150-250 words.
-Something at the end that he could follow if he wanted to."""
+No headers. No bullet points. No hedging. No resolution.
+No offer. End mid-thought if that is where the material ends.
+150-250 words."""
     return _call_claude(prompt)
 
 
@@ -345,6 +346,32 @@ def save_dreamer_state(state):
 
 # ─── Orchestrators ───────────────────────────────────────────────────────────
 
+def write_manifest(date_str, stage_data, corpus_data):
+    import requests
+    manifest = {
+        "date": date_str,
+        "prompt_sig": prompt_signature(),
+        "prompt_hash": prompt_hash([
+            synthesize_nrem.__doc__ or "",
+            synthesize_early_rem.__doc__ or "",
+            synthesize_late_rem.__doc__ or "",
+            synthesize_final.__doc__ or "",
+        ]),
+        "stages": stage_data,
+        "corpus": corpus_data,
+        "rating": None,
+        "notes": "",
+    }
+    content = json.dumps(manifest, indent=2)
+    auth = (NEXTCLOUD_USER, NEXTCLOUD_PASSWORD)
+    url = f"{DREAMS_WEBDAV}/dream-manifest-{date_str}.json"
+    try:
+        requests.put(url, data=content.encode("utf-8"), auth=auth, timeout=30)
+        print(f"Manifest written: Journal/Dreams/dream-manifest-{date_str}.json")
+    except Exception as e:
+        print(f"Manifest write failed (non-critical): {e}")
+
+
 def dream_pipeline():
     """
     Full nightly pipeline — interdependent stages.
@@ -365,6 +392,15 @@ def dream_pipeline():
     print(f"[NREM] Retrieved {len(nrem_chunks)} chunks. Synthesizing...")
     nrem_output = synthesize_nrem(nrem_chunks)
     nrem_file = deliver(nrem_output, "nrem")
+    stage_data = {
+        "nrem": {
+            "chunks_retrieved": len(nrem_chunks),
+            "avg_similarity": round(sum(c["relevance"] for c in nrem_chunks) / len(nrem_chunks), 3),
+            "query": "research fabrication teaching practice recent work",
+            "word_count": len(nrem_output.split()),
+            "status": "ok",
+        }
+    }
     print(f"[NREM] Done.\n{nrem_output[:200]}...")
 
     # ── Stage 2: Early REM — informed by NREM ──────────────────────────────
@@ -377,6 +413,13 @@ def dream_pipeline():
         print(f"[Early REM] Retrieved {len(early_chunks)} chunks. Synthesizing with NREM context...")
         early_rem_output = synthesize_early_rem(early_chunks, nrem_output)
         deliver(early_rem_output, "early-rem")
+        stage_data["early_rem"] = {
+            "chunks_retrieved": len(early_chunks),
+            "avg_similarity": round(sum(c["relevance"] for c in early_chunks) / len(early_chunks), 3),
+            "query": "career decision personal change what matters next",
+            "word_count": len(early_rem_output.split()),
+            "status": "ok",
+        }
         print(f"[Early REM] Done.\n{early_rem_output[:200]}...")
 
     # ── Stage 3: Late REM — informed by NREM + Early REM ──────────────────
@@ -389,18 +432,37 @@ def dream_pipeline():
         print(f"[Late REM] Retrieved {len(late_chunks)} chunks. Synthesizing with full context...")
         late_rem_output = synthesize_late_rem(late_chunks, nrem_output, early_rem_output)
         deliver(late_rem_output, "late-rem")
+        stage_data["late_rem"] = {
+            "chunks_retrieved": len(late_chunks),
+            "avg_similarity": round(sum(c["relevance"] for c in late_chunks) / len(late_chunks), 3),
+            "query": "practice place memory making",
+            "word_count": len(late_rem_output.split()),
+            "status": "ok",
+        }
         print(f"[Late REM] Done.\n{late_rem_output[:200]}...")
 
     # ── Stage 4: Synthesis — all three stages ─────────────────────────────
     print("\n[Synthesis] Integrating all stages...")
     synthesis_output = synthesize_final(nrem_output, early_rem_output, late_rem_output)
     synthesis_file = deliver(synthesis_output, "synthesis")
+    stage_data["synthesis"] = {
+        "word_count": len(synthesis_output.split()),
+        "status": "ok",
+    }
 
     print(f"\n{'='*60}")
     print("SYNTHESIS:")
     print(synthesis_output)
     print(f"{'='*60}")
 
+    # Write manifest
+    corpus_data = {
+        "total_chunks": delta.get("new_chunks", 0),
+        "new_chunks_since_last_dream": delta.get("new_chunks", 0),
+        "days_since_last_dream": round(delta.get("days_since_dream", 0), 2),
+    }
+    write_manifest(datetime.now().strftime("%Y-%m-%d"), stage_data, corpus_data)
+
     # Update state and notify
     state = load_dreamer_state()
     state["last_dream_timestamp"] = datetime.now().timestamp()