feat(library): add business + finance types, workspace_id, IngestJob

Adds two new content-type-aware library types — `business` for
proposals/marketing/strategy (used by the work-team agents) and `finance`
for statements/tax/market commentary (used by Garth). Each ships with
chunking config, embedding/reranker instructions, an LLM-context prompt
that forbids fabricating financial figures, and a vision prompt.

Adds a unique-indexed `workspace_id` property to `Library` so a node
can be scoped to a Daedalus workspace. Null means a global library;
non-null means workspace-scoped. Search Cypher (added in a later
commit) enforces the boundary.

Adds an `IngestJob` Django ORM model — separate from neomodel — that
tracks asynchronous ingestion lifecycle (Daedalus → S3 → Celery →
embedding pipeline) with idempotency on (library, source_ref, hash).
Migration 0001_initial creates the table.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

mnemosyne/library/models.py

@@ -1,11 +1,16 @@
 """
-Neo4j graph models for the Mnemosyne content library.
+Models for the Mnemosyne content library.
 
-All content data (libraries, collections, items, chunks, concepts, images)
-lives in Neo4j as a knowledge graph. These models use neomodel's StructuredNode
-OGM — they do NOT participate in Django's ORM or migrations.
+Most content (libraries, collections, items, chunks, concepts, images)
+lives in Neo4j as a knowledge graph via neomodel StructuredNode. These do
+NOT participate in Django's ORM or migrations.
+
+The IngestJob model at the bottom of this file is the exception: it tracks
+the lifecycle of asynchronous ingestion requests (file → embedding pipeline)
+in PostgreSQL via Django's ORM.
 """
 
+from django.db import models
 from neomodel import (
     ArrayProperty,
     DateTimeProperty,
@@ -50,8 +55,14 @@ class Library(StructuredNode):
     """
     Top-level container representing a content library.
 
-    Each library has a type (fiction, technical, music, film, art, journal)
-    that drives chunking strategy, embedding instructions, and LLM prompts.
+    Each library has a type (fiction, nonfiction, technical, music, film,
+    art, journal, business, finance) that drives chunking strategy,
+    embedding instructions, and LLM prompts.
+
+    A library may be either *global* (workspace_id is null — searchable
+    across the whole instance) or *workspace-scoped* (workspace_id set —
+    visible only to agents inside that Daedalus workspace). Scoping is
+    enforced structurally by every search query.
     """
 
     uid = UniqueIdProperty()
@@ -66,10 +77,16 @@ class Library(StructuredNode):
             "film": "Film",
             "art": "Art",
             "journal": "Journal",
+            "business": "Business",
+            "finance": "Finance",
         },
     )
     description = StringProperty(default="")
 
+    # Daedalus workspace UUID this library is scoped to. Null for global
+    # libraries. Unique-indexed so a workspace cannot have two libraries.
+    workspace_id = StringProperty(unique_index=True, required=False)
+
     # Content-type configuration
     chunking_config = JSONProperty(default={})
     embedding_instruction = StringProperty(default="")
@@ -270,3 +287,78 @@ class ImageEmbedding(StructuredNode):
 
     def __str__(self):
         return f"ImageEmbedding ({self.uid})"
+
+
+# --- Django ORM models (PostgreSQL) ---
+
+
+class IngestJob(models.Model):
+    """
+    Tracks the lifecycle of an asynchronous ingestion + embedding job.
+
+    Created when an external client (e.g. Daedalus) posts a file via the
+    REST ingest API. The Celery worker reads and updates this row as the
+    job moves through fetch / chunk / embed / graph stages.
+
+    Idempotency: a (library, source_ref, content_hash) triple uniquely
+    identifies a piece of content. A second POST with the same triple
+    returns the existing job; a POST with the same source_ref but a new
+    content_hash supersedes the prior Item.
+    """
+
+    STATUS_CHOICES = [
+        ("pending", "Pending"),
+        ("processing", "Processing"),
+        ("completed", "Completed"),
+        ("failed", "Failed"),
+    ]
+
+    id = models.CharField(max_length=64, primary_key=True)
+    item_uid = models.CharField(max_length=64, db_index=True, blank=True)
+    library_uid = models.CharField(max_length=64, db_index=True)
+    celery_task_id = models.CharField(max_length=255, blank=True)
+
+    status = models.CharField(
+        max_length=20,
+        choices=STATUS_CHOICES,
+        default="pending",
+        db_index=True,
+    )
+    progress = models.CharField(max_length=50, default="queued")
+    error = models.TextField(blank=True, null=True)
+    retry_count = models.PositiveIntegerField(default=0)
+
+    chunks_created = models.PositiveIntegerField(default=0)
+    concepts_extracted = models.PositiveIntegerField(default=0)
+    embedding_model = models.CharField(max_length=100, blank=True)
+
+    # The file's content hash (sha256). Used for idempotency: a second
+    # ingest with the same source_ref + same hash is a no-op; a second
+    # ingest with the same source_ref + different hash supersedes.
+    content_hash = models.CharField(max_length=64, db_index=True, blank=True)
+
+    # Where the file came from. For Daedalus: source="daedalus",
+    # source_ref="<workspace_id>/<file_id>".
+    source = models.CharField(max_length=50, default="")
+    source_ref = models.CharField(max_length=200, blank=True, db_index=True)
+    s3_key = models.CharField(max_length=500)
+
+    # Optional metadata carried forward to the Item node.
+    title = models.CharField(max_length=500, blank=True)
+    file_type = models.CharField(max_length=50, blank=True)
+    file_size = models.PositiveBigIntegerField(default=0)
+    collection_uid = models.CharField(max_length=64, blank=True)
+
+    created_at = models.DateTimeField(auto_now_add=True)
+    started_at = models.DateTimeField(null=True, blank=True)
+    completed_at = models.DateTimeField(null=True, blank=True)
+
+    class Meta:
+        ordering = ["-created_at"]
+        indexes = [
+            models.Index(fields=["status", "-created_at"]),
+            models.Index(fields=["source", "source_ref"]),
+        ]
+
+    def __str__(self):
+        return f"IngestJob {self.id} [{self.status}]"