feat: migrate to circuitforge-core for db, llm router, and tiers

app/wizard/tiers.py

@@ -1,7 +1,7 @@
 """
 Tier definitions and feature gates for Peregrine.
 
-Tiers: free < paid < premium
+Tiers: free < paid < premium < ultra (ultra reserved; no Peregrine features use it yet)
 FEATURES maps feature key → minimum tier required.
 Features not in FEATURES are available to all tiers (free).
 
@@ -25,7 +25,11 @@ from __future__ import annotations
 import os as _os
 from pathlib import Path
 
-TIERS = ["free", "paid", "premium"]
+from circuitforge_core.tiers import (
+    can_use as _core_can_use,
+    TIERS,
+    tier_label as _core_tier_label,
+)
 
 # Maps feature key → minimum tier string required.
 # Features absent from this dict are free (available to all).
@@ -132,25 +136,20 @@ def can_use(
     Returns False for unknown/invalid tier strings.
     """
     effective_tier = demo_tier if (demo_tier is not None and _DEMO_MODE) else tier
-    required = FEATURES.get(feature)
-    if required is None:
-        return True  # not gated — available to all
+    # Pass Peregrine's BYOK_UNLOCKABLE via has_byok collapse — core's frozenset is empty
     if has_byok and feature in BYOK_UNLOCKABLE:
         return True
-    try:
-        return TIERS.index(effective_tier) >= TIERS.index(required)
-    except ValueError:
-        return False  # invalid tier string
+    return _core_can_use(feature, effective_tier, _features=FEATURES)
 
 
 def tier_label(feature: str, has_byok: bool = False) -> str:
     """Return a display label for a locked feature, or '' if free/unlocked."""
     if has_byok and feature in BYOK_UNLOCKABLE:
         return ""
-    required = FEATURES.get(feature)
-    if required is None:
+    raw = _core_tier_label(feature, _features=FEATURES)
+    if not raw or raw == "free":
         return ""
-    return "🔒 Paid" if required == "paid" else "⭐ Premium"
+    return "🔒 Paid" if raw == "paid" else "⭐ Premium"
 
 
 def effective_tier(

requirements.txt

@@ -2,6 +2,9 @@
 # Extracted from environment.yml for Docker pip installs
 # Keep in sync with environment.yml
 
+# ── CircuitForge shared core ───────────────────────────────────────────────
+-e ../circuitforge-core
+
 # ── Web UI ────────────────────────────────────────────────────────────────
 streamlit>=1.35
 watchdog
@@ -78,3 +81,10 @@ lxml
 # ── Documentation ────────────────────────────────────────────────────────
 mkdocs>=1.5
 mkdocs-material>=9.5
+
+# ── Vue SPA API backend ──────────────────────────────────────────────────
+fastapi>=0.100.0
+uvicorn[standard]>=0.20.0
+PyJWT>=2.8.0
+cryptography>=40.0.0
+python-multipart>=0.0.6

scripts/db.py

@@ -9,30 +9,14 @@ from datetime import datetime
 from pathlib import Path
 from typing import Optional
 
+from circuitforge_core.db import get_connection as _cf_get_connection
+
 DEFAULT_DB = Path(os.environ.get("STAGING_DB", Path(__file__).parent.parent / "staging.db"))
 
 
 def get_connection(db_path: Path = DEFAULT_DB, key: str = "") -> "sqlite3.Connection":
-    """
-    Open a database connection.
-
-    In cloud mode with a key: uses SQLCipher (AES-256 encrypted, API-identical to sqlite3).
-    Otherwise: vanilla sqlite3.
-
-    Args:
-        db_path: Path to the SQLite/SQLCipher database file.
-        key:     SQLCipher encryption key (hex string). Empty = unencrypted.
-    """
-    import os as _os
-    cloud_mode = _os.environ.get("CLOUD_MODE", "").lower() in ("1", "true", "yes")
-    if cloud_mode and key:
-        from pysqlcipher3 import dbapi2 as _sqlcipher
-        conn = _sqlcipher.connect(str(db_path))
-        conn.execute(f"PRAGMA key='{key}'")
-        return conn
-    else:
-        import sqlite3 as _sqlite3
-        return _sqlite3.connect(str(db_path))
+    """Thin shim — delegates to circuitforge_core.db.get_connection."""
+    return _cf_get_connection(db_path, key)
 
 
 CREATE_JOBS = """

scripts/llm_router.py

@@ -2,168 +2,18 @@
 LLM abstraction layer with priority fallback chain.
 Reads config/llm.yaml. Tries backends in order; falls back on any error.
 """
-import os
-import yaml
-import requests
 from pathlib import Path
-from openai import OpenAI
+
+from circuitforge_core.llm import LLMRouter as _CoreLLMRouter
 
 CONFIG_PATH = Path(__file__).parent.parent / "config" / "llm.yaml"
 
 
-class LLMRouter:
+class LLMRouter(_CoreLLMRouter):
+    """Peregrine-specific LLMRouter — defaults to Peregrine's config/llm.yaml."""
+
     def __init__(self, config_path: Path = CONFIG_PATH):
-        with open(config_path) as f:
-            self.config = yaml.safe_load(f)
-
-    def _is_reachable(self, base_url: str) -> bool:
-        """Quick health-check ping. Returns True if backend is up."""
-        health_url = base_url.rstrip("/").removesuffix("/v1") + "/health"
-        try:
-            resp = requests.get(health_url, timeout=2)
-            return resp.status_code < 500
-        except Exception:
-            return False
-
-    def _resolve_model(self, client: OpenAI, model: str) -> str:
-        """Resolve __auto__ to the first model served by vLLM."""
-        if model != "__auto__":
-            return model
-        models = client.models.list()
-        return models.data[0].id
-
-    def complete(self, prompt: str, system: str | None = None,
-                 model_override: str | None = None,
-                 fallback_order: list[str] | None = None,
-                 images: list[str] | None = None,
-                 max_tokens: int | None = None) -> str:
-        """
-        Generate a completion. Tries each backend in fallback_order.
-
-        model_override: when set, replaces the configured model for
-        openai_compat backends (e.g. pass a research-specific ollama model).
-        fallback_order: when set, overrides config fallback_order for this
-        call (e.g. pass config["research_fallback_order"] for research tasks).
-        images: optional list of base64-encoded PNG/JPG strings. When provided,
-        backends without supports_images=true are skipped. vision_service backends
-        are only tried when images is provided.
-        Raises RuntimeError if all backends are exhausted.
-        """
-        if os.environ.get("DEMO_MODE", "").lower() in ("1", "true", "yes"):
-            raise RuntimeError(
-                "AI inference is disabled in the public demo. "
-                "Run your own instance to use AI features."
-            )
-        order = fallback_order if fallback_order is not None else self.config["fallback_order"]
-        for name in order:
-            backend = self.config["backends"][name]
-
-            if not backend.get("enabled", True):
-                print(f"[LLMRouter] {name}: disabled, skipping")
-                continue
-
-            supports_images = backend.get("supports_images", False)
-            is_vision_service = backend["type"] == "vision_service"
-
-            # vision_service only used when images provided
-            if is_vision_service and not images:
-                print(f"[LLMRouter] {name}: vision_service skipped (no images)")
-                continue
-
-            # non-vision backends skipped when images provided and they don't support it
-            if images and not supports_images and not is_vision_service:
-                print(f"[LLMRouter] {name}: no image support, skipping")
-                continue
-
-            if is_vision_service:
-                if not self._is_reachable(backend["base_url"]):
-                    print(f"[LLMRouter] {name}: unreachable, skipping")
-                    continue
-                try:
-                    resp = requests.post(
-                        backend["base_url"].rstrip("/") + "/analyze",
-                        json={
-                            "prompt": prompt,
-                            "image_base64": images[0] if images else "",
-                        },
-                        timeout=60,
-                    )
-                    resp.raise_for_status()
-                    print(f"[LLMRouter] Used backend: {name} (vision_service)")
-                    return resp.json()["text"]
-                except Exception as e:
-                    print(f"[LLMRouter] {name}: error — {e}, trying next")
-                    continue
-
-            elif backend["type"] == "openai_compat":
-                if not self._is_reachable(backend["base_url"]):
-                    print(f"[LLMRouter] {name}: unreachable, skipping")
-                    continue
-                try:
-                    client = OpenAI(
-                        base_url=backend["base_url"],
-                        api_key=backend.get("api_key") or "any",
-                    )
-                    raw_model = model_override or backend["model"]
-                    model = self._resolve_model(client, raw_model)
-                    messages = []
-                    if system:
-                        messages.append({"role": "system", "content": system})
-                    if images and supports_images:
-                        content = [{"type": "text", "text": prompt}]
-                        for img in images:
-                            content.append({
-                                "type": "image_url",
-                                "image_url": {"url": f"data:image/png;base64,{img}"},
-                            })
-                        messages.append({"role": "user", "content": content})
-                    else:
-                        messages.append({"role": "user", "content": prompt})
-
-                    create_kwargs: dict = {"model": model, "messages": messages}
-                    if max_tokens is not None:
-                        create_kwargs["max_tokens"] = max_tokens
-                    resp = client.chat.completions.create(**create_kwargs)
-                    print(f"[LLMRouter] Used backend: {name} ({model})")
-                    return resp.choices[0].message.content
-
-                except Exception as e:
-                    print(f"[LLMRouter] {name}: error — {e}, trying next")
-                    continue
-
-            elif backend["type"] == "anthropic":
-                api_key = os.environ.get(backend["api_key_env"], "")
-                if not api_key:
-                    print(f"[LLMRouter] {name}: {backend['api_key_env']} not set, skipping")
-                    continue
-                try:
-                    import anthropic as _anthropic
-                    client = _anthropic.Anthropic(api_key=api_key)
-                    if images and supports_images:
-                        content = []
-                        for img in images:
-                            content.append({
-                                "type": "image",
-                                "source": {"type": "base64", "media_type": "image/png", "data": img},
-                            })
-                        content.append({"type": "text", "text": prompt})
-                    else:
-                        content = prompt
-                    kwargs: dict = {
-                        "model": backend["model"],
-                        "max_tokens": 4096,
-                        "messages": [{"role": "user", "content": content}],
-                    }
-                    if system:
-                        kwargs["system"] = system
-                    msg = client.messages.create(**kwargs)
-                    print(f"[LLMRouter] Used backend: {name}")
-                    return msg.content[0].text
-                except Exception as e:
-                    print(f"[LLMRouter] {name}: error — {e}, trying next")
-                    continue
-
-        raise RuntimeError("All LLM backends exhausted")
+        super().__init__(config_path)
 
 
 # Module-level singleton for convenience

tests/test_llm_router.py

@@ -24,7 +24,7 @@ def test_router_uses_first_reachable_backend():
     mock_response.choices[0].message.content = "hello"
 
     with patch.object(router, "_is_reachable", side_effect=[False, True, True, True, True]), \
-         patch("scripts.llm_router.OpenAI") as MockOpenAI:
+         patch("circuitforge_core.llm.router.OpenAI") as MockOpenAI:
         instance = MockOpenAI.return_value
         instance.chat.completions.create.return_value = mock_response
         mock_model = MagicMock()
@@ -54,7 +54,7 @@ def test_is_reachable_returns_false_on_connection_error():
 
     router = LLMRouter(CONFIG_PATH)
 
-    with patch("scripts.llm_router.requests.get", side_effect=requests.ConnectionError):
+    with patch("circuitforge_core.llm.router.requests.get", side_effect=requests.ConnectionError):
         result = router._is_reachable("http://localhost:9999/v1")
 
     assert result is False
@@ -92,8 +92,8 @@ def test_complete_skips_backend_without_image_support(tmp_path):
     mock_resp.status_code = 200
     mock_resp.json.return_value = {"text": "B — collaborative"}
 
-    with patch("scripts.llm_router.requests.get") as mock_get, \
-         patch("scripts.llm_router.requests.post") as mock_post:
+    with patch("circuitforge_core.llm.router.requests.get") as mock_get, \
+         patch("circuitforge_core.llm.router.requests.post") as mock_post:
         # health check returns ok for vision_service
         mock_get.return_value = MagicMock(status_code=200)
         mock_post.return_value = mock_resp
@@ -127,7 +127,7 @@ def test_complete_without_images_skips_vision_service(tmp_path):
     cfg_file.write_text(yaml.dump(cfg))
 
     router = LLMRouter(config_path=cfg_file)
-    with patch("scripts.llm_router.requests.post") as mock_post:
+    with patch("circuitforge_core.llm.router.requests.post") as mock_post:
         try:
             router.complete("text only prompt")
         except RuntimeError:

tests/test_wizard_tiers.py

@@ -8,7 +8,9 @@ from app.wizard.tiers import can_use, tier_label, TIERS, FEATURES, BYOK_UNLOCKAB
 
 
 def test_tiers_list():
-    assert TIERS == ["free", "paid", "premium"]
+    # Peregrine uses the core tier list; "ultra" is included but no features require it yet
+    assert TIERS[:3] == ["free", "paid", "premium"]
+    assert "ultra" in TIERS
 
 
 def test_can_use_free_feature_always():