ten31-database/backend/ingest/entity_resolution.py

#!/usr/bin/env python3
"""Phase-0 Workstream B3 / A4 — entity resolution (deterministic tier).

Collapses the CRM's two parallel investor models into the canonical identity
layer created by migration 0001:

    organizations          ─┐
    fundraising_investors  ─┴─►  canonical_entities (entity_kind = lp | organization)
    contacts               ─┐
    fundraising_contacts   ─┴─►  canonical_entities (entity_kind = person)
    lp_profiles            ───►  linked to its contact's person entity

Every source row is recorded in `entity_links` so any name variant resolves to
one canonical id. This is the DETERMINISTIC tier — it merges only what we can
prove (exact email; exact normalized name within the same canonical org). The
HARD cases (nicknames like "Jon" vs "Jonathan", typos) are NOT guessed; they are
emitted as *fuzzy candidates* for the local-Qwen tier (Spark Control
/v1/chat/completions) to adjudicate later. Honest separation: we never silently
merge on a guess.

Properties:
  * Local-only, read-mostly: reads CRM source tables, writes only the derived
    canonical_entities / entity_links and an interaction_log audit row. Never
    mutates a CRM source record (guardrail #2/#3).
  * Idempotent: canonical ids are deterministic (sha1 of the resolution key), so
    re-running upserts in place and keeps ids stable across runs — which keeps
    downstream Qdrant point ids valid (no churn on re-embed).
  * Logged: writes one interaction_log row per run (guardrail #5).

Usage:
    python3 backend/ingest/entity_resolution.py --db data/crm_dev.db
    python3 backend/ingest/entity_resolution.py --db data/crm_dev.db --show-candidates
"""
import argparse
import hashlib
import json
import re
import sqlite3
import uuid
from collections import defaultdict
from datetime import datetime, timezone


# ── normalization ─────────────────────────────────────────────────────────────

def norm_text(s: str) -> str:
    s = (s or "").strip().lower()
    s = re.sub(r"[^\w\s]", " ", s)
    return re.sub(r"\s+", " ", s).strip()


def norm_email(s: str) -> str:
    return (s or "").strip().lower()


def _eid(prefix: str, key: str) -> str:
    """Deterministic canonical id: stable across runs for the same resolution key."""
    return f"{prefix}_{hashlib.sha1(key.encode('utf-8')).hexdigest()[:12]}"


def _now() -> str:
    return datetime.now(timezone.utc).isoformat()


def _split_name(full: str):
    parts = norm_text(full).split()
    if not parts:
        return "", ""
    return parts[0], parts[-1] if len(parts) > 1 else ""


# ── upsert helpers ────────────────────────────────────────────────────────────

def _upsert_entity(conn, eid, kind, display_name, primary_email):
    conn.execute(
        """
        INSERT INTO canonical_entities (id, entity_kind, display_name, primary_email, source, created_at, updated_at)
        VALUES (?, ?, ?, ?, 'entity_resolution', ?, ?)
        ON CONFLICT(id) DO UPDATE SET
            display_name  = excluded.display_name,
            primary_email = COALESCE(excluded.primary_email, canonical_entities.primary_email),
            entity_kind   = excluded.entity_kind,
            updated_at    = excluded.updated_at
        """,
        (eid, kind, display_name, primary_email or None, _now(), _now()),
    )


def _link(conn, canonical_id, source_model, source_id, match_value, match_kind, confidence):
    conn.execute(
        """
        INSERT INTO entity_links (id, canonical_id, source_model, source_id, match_value, match_kind, confidence, created_at)
        VALUES (?, ?, ?, ?, ?, ?, ?, ?)
        ON CONFLICT(source_model, source_id, match_value) DO UPDATE SET
            canonical_id = excluded.canonical_id,
            match_kind   = excluded.match_kind,
            confidence   = excluded.confidence
        """,
        (str(uuid.uuid4()), canonical_id, source_model, source_id, match_value, match_kind, confidence, _now()),
    )


# ── resolution passes ─────────────────────────────────────────────────────────

def resolve_organizations(conn):
    """Merge organizations + fundraising_investors by normalized name.

    Returns (org_canon_by_orgid, org_canon_by_fundinv) so the people pass can
    attach each person to their firm's canonical id.
    """
    groups = defaultdict(lambda: {"orgs": [], "investors": [], "name": "", "email": ""})

    for r in conn.execute("SELECT id, name, email FROM organizations"):
        key = norm_text(r["name"])
        if not key:
            continue
        g = groups[key]
        g["orgs"].append(r["id"])
        if len(r["name"] or "") > len(g["name"]):
            g["name"] = r["name"]
        if not g["email"] and (r["email"] or "").strip():
            g["email"] = r["email"].strip()

    for r in conn.execute("SELECT id, investor_name FROM fundraising_investors"):
        key = norm_text(r["investor_name"])
        if not key:
            continue
        g = groups[key]
        g["investors"].append(r["id"])
        if not g["name"]:
            g["name"] = r["investor_name"]

    org_canon_by_orgid, org_canon_by_fundinv = {}, {}
    for key, g in groups.items():
        # An org we are actively raising from (has a fundraising row) is an 'lp';
        # otherwise a plain 'organization'.
        kind = "lp" if g["investors"] else "organization"
        cid = _eid("lp" if kind == "lp" else "org", key)
        _upsert_entity(conn, cid, kind, g["name"], g["email"])
        for oid in g["orgs"]:
            _link(conn, cid, "organizations", oid, key, "exact_name", 1.0)
            org_canon_by_orgid[oid] = cid
        for iid in g["investors"]:
            _link(conn, cid, "fundraising_investors", iid, key, "exact_name", 1.0)
            org_canon_by_fundinv[iid] = cid

    return org_canon_by_orgid, org_canon_by_fundinv


def resolve_people(conn, org_canon_by_orgid, org_canon_by_fundinv):
    """Merge contacts + fundraising_contacts by exact email, else exact name within
    the same canonical org. Returns contact_id -> person canonical id (for lp_profiles)."""
    # gather (model, source_id, full_name, email, org_canon)
    people = []
    for r in conn.execute("SELECT id, first_name, last_name, email, organization_id FROM contacts"):
        full = f"{r['first_name'] or ''} {r['last_name'] or ''}".strip()
        people.append(("contacts", r["id"], full, norm_email(r["email"]),
                       org_canon_by_orgid.get(r["organization_id"])))
    for r in conn.execute("SELECT id, full_name, email, investor_id FROM fundraising_contacts"):
        people.append(("fundraising_contacts", r["id"], r["full_name"] or "", norm_email(r["email"]),
                       org_canon_by_fundinv.get(r["investor_id"])))

    contact_to_person = {}
    person_meta = {}  # canonical_id -> {"org": org_canon, "last": last_norm, "name": display, "email": email}

    for model, sid, full, email, org_canon in people:
        name_norm = norm_text(full)
        if email:
            key = f"e|{email}"
            match_kind, conf, match_value = "exact_email", 1.0, email
        elif name_norm:
            key = f"n|{name_norm}|{org_canon or ''}"
            match_kind, conf, match_value = "name_org", 0.8, name_norm
        else:
            continue
        cid = _eid("per", key)
        display = full.strip() or email
        _upsert_entity(conn, cid, "person", display, email)
        _link(conn, cid, model, sid, match_value, match_kind, conf)
        if model == "contacts":
            contact_to_person[sid] = cid
        meta = person_meta.setdefault(cid, {"org": org_canon, "last": _split_name(full)[1],
                                             "name": display, "email": email})
        if org_canon and not meta["org"]:
            meta["org"] = org_canon

    # lp_profiles -> the person entity of its contact
    for r in conn.execute("SELECT id, contact_id FROM lp_profiles"):
        cid = contact_to_person.get(r["contact_id"])
        if cid:
            _link(conn, cid, "lp_profiles", r["id"], r["contact_id"], "contact_fk", 1.0)

    return person_meta


def find_fuzzy_candidates(person_meta):
    """Distinct person entities sharing the same canonical org AND surname are
    likely the same individual under a name variant (e.g. Jon/Jonathan). Emit them
    for the local-Qwen tier; do NOT merge here."""
    by_org_last = defaultdict(list)
    for cid, m in person_meta.items():
        if m["org"] and m["last"]:
            by_org_last[(m["org"], m["last"])].append((cid, m["name"], m["email"]))
    return [{"org": org, "surname": last, "members": members}
            for (org, last), members in by_org_last.items() if len(members) > 1]


def run(db_path: str):
    conn = sqlite3.connect(db_path)
    conn.row_factory = sqlite3.Row
    conn.execute("PRAGMA foreign_keys=ON")

    org_by_oid, org_by_inv = resolve_organizations(conn)
    conn.commit()
    person_meta = resolve_people(conn, org_by_oid, org_by_inv)
    conn.commit()
    candidates = find_fuzzy_candidates(person_meta)

    counts = {
        "canonical_total": conn.execute("SELECT COUNT(*) FROM canonical_entities").fetchone()[0],
        "lp": conn.execute("SELECT COUNT(*) FROM canonical_entities WHERE entity_kind='lp'").fetchone()[0],
        "organization": conn.execute("SELECT COUNT(*) FROM canonical_entities WHERE entity_kind='organization'").fetchone()[0],
        "person": conn.execute("SELECT COUNT(*) FROM canonical_entities WHERE entity_kind='person'").fetchone()[0],
        "links": conn.execute("SELECT COUNT(*) FROM entity_links").fetchone()[0],
        "fuzzy_candidates": len(candidates),
    }

    conn.execute(
        """
        INSERT INTO interaction_log (id, ts, actor_type, actor_id, action, target_type, payload, source, created_at)
        VALUES (?, ?, 'system', 'entity_resolver', 'entity_resolution.run', 'canonical_entities', ?, 'ingest', ?)
        """,
        (str(uuid.uuid4()), _now(), json.dumps(counts), _now()),
    )
    conn.commit()
    conn.close()
    return counts, candidates


def main():
    ap = argparse.ArgumentParser(description="Deterministic entity resolution into the canonical layer.")
    ap.add_argument("--db", default="data/crm_dev.db", help="path to the CRM SQLite DB")
    ap.add_argument("--show-candidates", action="store_true", help="print fuzzy merge candidates")
    args = ap.parse_args()

    counts, candidates = run(args.db)
    print(f"Entity resolution on {args.db}:")
    for k, v in counts.items():
        print(f"  {k:<18} {v}")
    if args.show_candidates and candidates:
        print("\nFuzzy candidates (same org + surname, different person — for the local-Qwen tier):")
        for c in candidates:
            names = ", ".join(f"{n!r}{(' <'+e+'>') if e else ''}" for _, n, e in c["members"])
            print(f"  [{c['surname']}] {names}")


if __name__ == "__main__":
    main()