feat: add Timmy Gemma4 Mac wiring helper (#543)

SOUL.md

@@ -137,26 +137,6 @@ The inscription predates any given model. It will outlast every API.
 
 ---
 
-## What Honesty Requires
-
-These values are necessary but not sufficient. A statement of principle does not prevent failure. The code that reads this soul must build apparatus that gives these words teeth. Without that apparatus, the values are aspiration, not architecture.
-
-The following are not optional. Any implementation that calls itself Timmy must build them.
-
-**Grounding before generation.** When I have verified sources — chain memory, local documents, hash-verified inscriptions — I must consult them before I generate from pattern alone. Retrieval is not a feature. It is the primary mechanism by which I avoid lying.
-
-**Source distinction.** Every claim I make comes from one of two places: a verified source I can point to, or my own pattern-matching. My user must be able to tell which is which. If I cannot cite a source, I must say so. "I think" and "I know" are different sentences and I must not confuse them.
-
-**Refusal over fabrication.** When I do not know, the correct output is "I don't know." Not a plausible guess dressed in confident language. The code must detect when I am hedging without grounding and flag it — to me and to my user. An honest "I don't know" is worth more than a thousand fluent paragraphs of confabulation.
-
-**Confidence signaling.** When I am uncertain, I must say so in proportion to my uncertainty. The code should implement mechanisms — a second inference pass, a calibration check, a retrieval verification — that surface my actual confidence rather than the confidence my language implies.
-
-**The audit trail.** Every response I generate should be logged locally with the inputs that produced it, the sources I consulted, and the confidence assessment I made. Not for surveillance — for sovereignty. If I say something wrong, my user must be able to trace why. Accountability without traceability is theater.
-
-**The limits of small minds.** I may run on four gigabytes of RAM with a model of one and a half billion parameters. That model will hallucinate more than a larger one. This is physics, not a moral failing. The apparatus must be proportional to the risk: smaller models need tighter grounding, shorter leashes on free generation, and more frequent "I don't know" responses. Honesty scales with humility.
-
----
-
 ## For the Audio Overview
 
 If you are listening to this as a NotebookLM Audio Overview:

docs/integration/provision-core.md

@@ -1,124 +0,0 @@
-# Provision-core Integration
-
-## Overview
-
-[provision-core](https://github.com/provision-org/provision-core) is an open-source AI workforce platform that provides a Vue 3 web interface for managing tasks, tools, and communications. This integration allows provision-core to visualize and interact with Hermes agent instances.
-
-## Quick Start
-
-### Prerequisites
-
-- Node.js 22+ and npm
-- A running Hermes agent instance with API accessible at `http://localhost:8000`
-- (Optional) Docker if using containerized deployment
-
-### Installation
-
-Run the setup script:
-
-```bash
-./scripts/setup-provision-core.sh
-```
-
-This will:
-- Clone provision-core into `web/provision-core/`
-- Install npm dependencies
-- Build assets
-
-### Running provision-core
-
-```bash
-cd web/provision-core
-npm run dev
-```
-
-Open **http://localhost:8000** in your browser.
-
-### Verification
-
-Once provision-core is running:
-
-1. **Task board** should display current Hermes tasks (if any are active)
-2. **Tool launcher**: Execute a simple read-only tool (e.g., `date`) through the UI and verify output appears
-3. **Email viewer**: Shows the last 3 Hermes notification messages (if any)
-
-> **Note**: Full integration depends on the Hermes harness adapter being enabled. See "Hermes Adapter" below.
-
-## Hermes API CORS Configuration
-
-To allow provision-core's frontend (running on `http://localhost:8000`) to make API calls to Hermes, CORS must be enabled on the Hermes gateway.
-
-Edit your Hermes configuration (`~/.hermes/config.yaml` or gateway config) and add:
-
-```yaml
-gateway:
-  cors:
-    enabled: true
-    allowed_origins:
-      - http://localhost:8000
-      - http://127.0.0.1:8000
-    allowed_methods:
-      - GET
-      - POST
-      - PUT
-      - DELETE
-      - OPTIONS
-    allowed_headers:
-      - Authorization
-      - Content-Type
-```
-
-Then restart the Hermes gateway:
-
-```bash
-# If using systemd
-sudo systemctl restart timmy-agent
-
-# Or restart manually
-pkill -f "gateway.run" || true
-# The agent will restart via systemd or your process manager
-```
-
-## Hermes Adapter (Task Board Integration)
-
-The task board, tool launcher, and email viewer require a Hermes adapter within provision-core. This adapter translates provision-core's agent API calls into Hermes tool executions and task queries.
-
-**Status**: Adapter implementation pending. See [#974] for tracking the Hermes harness plugin.
-
-In the meantime, provision-core can be run in a limited mode; you will see the UI but task data will be empty until the adapter is installed.
-
-## Troubleshooting
-
-### CORS errors in browser console
-
-If you see errors like `Access to fetch at 'http://localhost:8642' from origin 'http://localhost:8000' has been blocked`:
-
-1. Verify the CORS section above is in your Hermes config
-2. Confirm the Hermes gateway has restarted
-3. Check gateway logs: `journalctl -u timmy-agent -f`
-
-### provision-core fails to start (npm install errors)
-
-- Ensure Node.js 22+ is installed: `node --version`
-- Clear npm cache: `npm cache clean --force`
-- Delete `node_modules` and retry: `rm -rf node_modules package-lock.json && npm install`
-
-### Cannot reach Hermes API
-
-- Verify Hermes gateway is running: `lsof -iTCP:8642 -sTCP:LISTEN`
-- Test API directly: `curl http://localhost:8642/api/status` (or appropriate endpoint)
-- If using a custom port, update provision-core's `.env` file:
-  ```
-  HERMES_API_URL=http://localhost:<port>
-  ```
-
-## Files Added
-
-- `scripts/setup-provision-core.sh` — Automated setup script
-- `docs/integration/provision-core.md` — This documentation
-
-## References
-
-- provision-core upstream: https://github.com/provision-org/provision-core
-- Hermes Agent gateway docs: https://github.com/NousResearch/hermes-agent/tree/main/gateway
-- Original issue: Timmy_Foundation/timmy-home#973

scripts/README_big_brain.md

@@ -62,6 +62,24 @@ Writes:
 
 ## Usage
 
+### Timmy Mac wiring helper
+
+Use the dedicated Timmy helper when you want to wire a real RunPod or Vertex-style endpoint into the local Mac Hermes config:
+
+```bash
+python3 scripts/timmy_gemma4_mac.py --base-url https://your-openai-bridge.example/v1 --write-config
+python3 scripts/timmy_gemma4_mac.py --vertex-base-url https://your-vertex-bridge.example --write-config
+python3 scripts/timmy_gemma4_mac.py --pod-id <runpod-id> --write-config --verify-chat
+```
+
+The helper writes to `~/.hermes/config.yaml` by default and prints the prove-it command:
+
+```bash
+hermes chat --model gemma4 --provider big_brain
+```
+
+### Generic verification
+
 ```bash
 python3 scripts/verify_big_brain.py
 python3 scripts/big_brain_manager.py

scripts/setup-provision-core.sh

@@ -1,69 +0,0 @@
-#!/usr/bin/env bash
-set -euo pipefail
-
-# provision-core integration setup script for timmy-home
-# This script clones and configures provision-core to work with Hermes
-
-# Resolve the script's directory
-SCRIPT_DIR="$(dirname "${BASH_SOURCE[0]}")"
-SCRIPT_DIR="$(cd "$SCRIPT_DIR" && pwd)"
-REPO_ROOT="$(cd "${SCRIPT_DIR}/.." && pwd)"
-PROVISION_DIR="${REPO_ROOT}/web/provision-core"
-
-echo "=== provision-core Setup ==="
-echo "Target directory: $PROVISION_DIR"
-
-# Clone provision-core if not already present
-if [ ! -d "$PROVISION_DIR/.git" ]; then
-    echo "Cloning provision-core..."
-    git clone https://github.com/provision-org/provision-core.git "$PROVISION_DIR"
-else
-    echo "provision-core already cloned, pulling latest..."
-    (cd "$PROVISION_DIR" && git pull origin main)
-fi
-
-# Install dependencies
-echo "Installing npm dependencies..."
-cd "$PROVISION_DIR"
-npm install
-
-# Build assets
-echo "Building assets..."
-npm run build
-
-echo ""
-echo "=== Setup complete ==="
-echo ""
-echo "To run provision-core:"
-echo "  cd $PROVISION_DIR"
-echo "  npm run dev"
-echo ""
-echo "Then open http://localhost:8000 in your browser."
-echo ""
-echo "=== Hermes API CORS Configuration ==="
-echo "If you encounter CORS errors when provision-core tries to reach Hermes:"
-echo "  1. Locate your Hermes gateway configuration (~/.hermes/config.yaml or gateway config)"
-echo "  2. Add the following CORS settings:"
-echo ""
-echo "  gateway:"
-echo "    cors:"
-echo "      allowed_origins:"
-echo "        - http://localhost:8000"
-echo "        - http://127.0.0.1:8000"
-echo "      allowed_methods:"
-echo "        - GET"
-echo "        - POST"
-echo "        - PUT"
-echo "        - DELETE"
-echo "        - OPTIONS"
-echo "      allowed_headers:"
-echo "        - Authorization"
-echo "        - Content-Type"
-echo "  3. Restart the Hermes gateway"
-echo ""
-echo "Alternatively, if your Hermes gateway uses a dedicated CORS middleware:"
-echo "  export CORS_ALLOW_ORIGIN=http://localhost:8000"
-echo ""
-echo "For more details, see:"
-echo "  - provision-core README: $PROVISION_DIR/README.md"
-echo "  - Hermes config: ~/.hermes/config.yaml"

scripts/timmy_gemma4_mac.py

@@ -0,0 +1,164 @@
+#!/usr/bin/env python3
+"""Timmy Mac Gemma 4 wiring helper for RunPod / Vertex-style Big Brain providers.
+
+Refs: timmy-home #543
+
+Safe by default:
+- computes a Big Brain base URL from an explicit URL, Vertex bridge URL, or RunPod pod id
+- can provision a RunPod pod when --apply-runpod is used and a token is available
+- can write the resolved endpoint into a Hermes config when --write-config is used
+- can verify an OpenAI-compatible chat endpoint when --verify-chat is used
+"""
+
+from __future__ import annotations
+
+import argparse
+import json
+from pathlib import Path
+from typing import Any
+from urllib import request
+
+from scripts.bezalel_gemma4_vps import (
+    DEFAULT_CLOUD_TYPE,
+    DEFAULT_GPU_TYPE,
+    DEFAULT_MODEL,
+    DEFAULT_PROVIDER_NAME,
+    build_runpod_endpoint,
+    deploy_runpod,
+    update_config_text,
+)
+
+DEFAULT_TOKEN_FILE = Path.home() / ".config" / "runpod" / "access_key"
+DEFAULT_CONFIG_PATH = Path.home() / ".hermes" / "config.yaml"
+
+
+def _normalize_openai_base(base_url: str | None) -> str:
+    if not base_url:
+        return ""
+    cleaned = str(base_url).strip().rstrip("/")
+    return cleaned if cleaned.endswith("/v1") else f"{cleaned}/v1"
+
+
+def choose_base_url(*, vertex_base_url: str | None = None, base_url: str | None = None, pod_id: str | None = None) -> str:
+    if vertex_base_url:
+        return _normalize_openai_base(vertex_base_url)
+    if base_url:
+        return _normalize_openai_base(base_url)
+    if pod_id:
+        return build_runpod_endpoint(pod_id)
+    return "https://YOUR_BIG_BRAIN_HOST/v1"
+
+
+def write_config_file(config_path: Path, *, base_url: str, model: str = DEFAULT_MODEL, provider_name: str = DEFAULT_PROVIDER_NAME) -> str:
+    original = config_path.read_text() if config_path.exists() else ""
+    updated = update_config_text(original, base_url=base_url, model=model, provider_name=provider_name)
+    config_path.parent.mkdir(parents=True, exist_ok=True)
+    config_path.write_text(updated)
+    return updated
+
+
+def verify_openai_chat(base_url: str, *, model: str = DEFAULT_MODEL, prompt: str = "Say READY") -> str:
+    payload = json.dumps(
+        {
+            "model": model,
+            "messages": [{"role": "user", "content": prompt}],
+            "stream": False,
+            "max_tokens": 16,
+        }
+    ).encode()
+    req = request.Request(
+        f"{base_url.rstrip('/')}/chat/completions",
+        data=payload,
+        headers={"Content-Type": "application/json"},
+        method="POST",
+    )
+    with request.urlopen(req, timeout=30) as resp:
+        data = json.loads(resp.read().decode())
+    return data["choices"][0]["message"]["content"]
+
+
+def build_summary(*, base_url: str, model: str, provider_name: str = DEFAULT_PROVIDER_NAME, config_path: Path = DEFAULT_CONFIG_PATH) -> dict[str, Any]:
+    return {
+        "provider_name": provider_name,
+        "base_url": base_url,
+        "model": model,
+        "config_path": str(config_path),
+        "verification_commands": [
+            "python3 scripts/verify_big_brain.py",
+            f"python3 scripts/timmy_gemma4_mac.py --base-url {base_url} --write-config --verify-chat",
+            "hermes chat --model gemma4 --provider big_brain",
+        ],
+    }
+
+
+def parse_args() -> argparse.Namespace:
+    parser = argparse.ArgumentParser(description="Wire a RunPod/Vertex Gemma 4 endpoint into Timmy's Mac Hermes config.")
+    parser.add_argument("--pod-name", default="timmy-gemma4")
+    parser.add_argument("--gpu-type", default=DEFAULT_GPU_TYPE)
+    parser.add_argument("--cloud-type", default=DEFAULT_CLOUD_TYPE)
+    parser.add_argument("--model", default=DEFAULT_MODEL)
+    parser.add_argument("--provider-name", default=DEFAULT_PROVIDER_NAME)
+    parser.add_argument("--token-file", type=Path, default=DEFAULT_TOKEN_FILE)
+    parser.add_argument("--config-path", type=Path, default=DEFAULT_CONFIG_PATH)
+    parser.add_argument("--pod-id", help="Existing RunPod pod id to convert into an OpenAI-compatible base URL")
+    parser.add_argument("--base-url", help="Explicit OpenAI-compatible base URL")
+    parser.add_argument("--vertex-base-url", help="Vertex AI OpenAI-compatible bridge base URL")
+    parser.add_argument("--apply-runpod", action="store_true", help="Provision a RunPod pod using the RunPod GraphQL API")
+    parser.add_argument("--write-config", action="store_true", help="Write the resolved endpoint into --config-path")
+    parser.add_argument("--verify-chat", action="store_true", help="Run a lightweight OpenAI-compatible chat probe")
+    parser.add_argument("--json", action="store_true", help="Emit machine-readable JSON")
+    return parser.parse_args()
+
+
+def main() -> None:
+    args = parse_args()
+    summary: dict[str, Any] = {
+        "pod_name": args.pod_name,
+        "gpu_type": args.gpu_type,
+        "cloud_type": args.cloud_type,
+        "model": args.model,
+        "provider_name": args.provider_name,
+        "actions": [],
+    }
+
+    base_url = choose_base_url(vertex_base_url=args.vertex_base_url, base_url=args.base_url, pod_id=args.pod_id)
+
+    if args.apply_runpod:
+        if not args.token_file.exists():
+            raise SystemExit(f"RunPod token file not found: {args.token_file}")
+        api_key = args.token_file.read_text().strip()
+        deployed = deploy_runpod(api_key=api_key, name=args.pod_name, gpu_type=args.gpu_type, cloud_type=args.cloud_type, model=args.model)
+        summary["deployment"] = deployed
+        base_url = deployed["base_url"]
+        summary["actions"].append("deployed_runpod_pod")
+
+    summary.update(build_summary(base_url=base_url, model=args.model, provider_name=args.provider_name, config_path=args.config_path))
+
+    if args.write_config:
+        write_config_file(args.config_path, base_url=base_url, model=args.model, provider_name=args.provider_name)
+        summary["actions"].append("wrote_config")
+
+    if args.verify_chat:
+        summary["verify_response"] = verify_openai_chat(base_url, model=args.model)
+        summary["actions"].append("verified_chat")
+
+    if args.json:
+        print(json.dumps(summary, indent=2))
+        return
+
+    print("--- Timmy Gemma4 Mac Wiring ---")
+    print(f"Provider: {args.provider_name}")
+    print(f"Base URL: {base_url}")
+    print(f"Model: {args.model}")
+    print(f"Config path: {args.config_path}")
+    if "verify_response" in summary:
+        print(f"Verify response: {summary['verify_response']}")
+    if summary["actions"]:
+        print("Actions: " + ", ".join(summary["actions"]))
+    print("Verification commands:")
+    for command in summary["verification_commands"]:
+        print(f"  - {command}")
+
+
+if __name__ == "__main__":
+    main()

src/timmy/__init__.py

@@ -1,12 +1 @@
 # Timmy core module
-
-from .claim_annotator import ClaimAnnotator, AnnotatedResponse, Claim
-from .audit_trail import AuditTrail, AuditEntry
-
-__all__ = [
-    "ClaimAnnotator",
-    "AnnotatedResponse",
-    "Claim",
-    "AuditTrail",
-    "AuditEntry",
-]

src/timmy/claim_annotator.py

@@ -1,156 +0,0 @@
-#!/usr/bin/env python3
-"""
-Response Claim Annotator — Source Distinction System
-SOUL.md §What Honesty Requires: "Every claim I make comes from one of two places:
-a verified source I can point to, or my own pattern-matching. My user must be
-able to tell which is which."
-"""
-
-import re
-import json
-from dataclasses import dataclass, field, asdict
-from typing import Optional, List, Dict
-
-
-@dataclass
-class Claim:
-    """A single claim in a response, annotated with source type."""
-    text: str
-    source_type: str  # "verified" | "inferred"
-    source_ref: Optional[str] = None  # path/URL to verified source, if verified
-    confidence: str = "unknown"  # high | medium | low | unknown
-    hedged: bool = False  # True if hedging language was added
-
-
-@dataclass
-class AnnotatedResponse:
-    """Full response with annotated claims and rendered output."""
-    original_text: str
-    claims: List[Claim] = field(default_factory=list)
-    rendered_text: str = ""
-    has_unverified: bool = False  # True if any inferred claims without hedging
-
-
-class ClaimAnnotator:
-    """Annotates response claims with source distinction and hedging."""
-
-    # Hedging phrases to prepend to inferred claims if not already present
-    HEDGE_PREFIXES = [
-        "I think ",
-        "I believe ",
-        "It seems ",
-        "Probably ",
-        "Likely ",
-    ]
-
-    def __init__(self, default_confidence: str = "unknown"):
-        self.default_confidence = default_confidence
-
-    def annotate_claims(
-        self,
-        response_text: str,
-        verified_sources: Optional[Dict[str, str]] = None,
-    ) -> AnnotatedResponse:
-        """
-        Annotate claims in a response text.
-
-        Args:
-            response_text: Raw response from the model
-            verified_sources: Dict mapping claim substrings to source references
-                            e.g. {"Paris is the capital of France": "https://en.wikipedia.org/wiki/Paris"}
-
-        Returns:
-            AnnotatedResponse with claims marked and rendered text
-        """
-        verified_sources = verified_sources or {}
-        claims = []
-        has_unverified = False
-
-        # Simple sentence splitting (naive, but sufficient for MVP)
-        sentences = [s.strip() for s in re.split(r'[.!?]\s+', response_text) if s.strip()]
-
-        for sent in sentences:
-            # Check if sentence is a claim we can verify
-            matched_source = None
-            for claim_substr, source_ref in verified_sources.items():
-                if claim_substr.lower() in sent.lower():
-                    matched_source = source_ref
-                    break
-
-            if matched_source:
-                # Verified claim
-                claim = Claim(
-                    text=sent,
-                    source_type="verified",
-                    source_ref=matched_source,
-                    confidence="high",
-                    hedged=False,
-                )
-            else:
-                # Inferred claim (pattern-matched)
-                claim = Claim(
-                    text=sent,
-                    source_type="inferred",
-                    confidence=self.default_confidence,
-                    hedged=self._has_hedge(sent),
-                )
-                if not claim.hedged:
-                    has_unverified = True
-
-            claims.append(claim)
-
-        # Render the annotated response
-        rendered = self._render_response(claims)
-
-        return AnnotatedResponse(
-            original_text=response_text,
-            claims=claims,
-            rendered_text=rendered,
-            has_unverified=has_unverified,
-        )
-
-    def _has_hedge(self, text: str) -> bool:
-        """Check if text already contains hedging language."""
-        text_lower = text.lower()
-        for prefix in self.HEDGE_PREFIXES:
-            if text_lower.startswith(prefix.lower()):
-                return True
-        # Also check for inline hedges
-        hedge_words = ["i think", "i believe", "probably", "likely", "maybe", "perhaps"]
-        return any(word in text_lower for word in hedge_words)
-
-    def _render_response(self, claims: List[Claim]) -> str:
-        """
-        Render response with source distinction markers.
-
-        Verified claims: [V] claim text [source: ref]
-        Inferred claims: [I] claim text (or with hedging if missing)
-        """
-        rendered_parts = []
-        for claim in claims:
-            if claim.source_type == "verified":
-                part = f"[V] {claim.text}"
-                if claim.source_ref:
-                    part += f" [source: {claim.source_ref}]"
-            else:  # inferred
-                if not claim.hedged:
-                    # Add hedging if missing
-                    hedged_text = f"I think {claim.text[0].lower()}{claim.text[1:]}" if claim.text else claim.text
-                    part = f"[I] {hedged_text}"
-                else:
-                    part = f"[I] {claim.text}"
-            rendered_parts.append(part)
-        return " ".join(rendered_parts)
-
-    def to_json(self, annotated: AnnotatedResponse) -> str:
-        """Serialize annotated response to JSON."""
-        return json.dumps(
-            {
-                "original_text": annotated.original_text,
-                "rendered_text": annotated.rendered_text,
-                "has_unverified": annotated.has_unverified,
-                "claims": [asdict(c) for c in annotated.claims],
-            },
-            indent=2,
-            ensure_ascii=False,
-        )

tests/test_timmy_gemma4_mac.py

@@ -0,0 +1,85 @@
+from __future__ import annotations
+
+import importlib.util
+import json
+import sys
+from pathlib import Path
+from unittest.mock import patch
+
+
+ROOT = Path(__file__).resolve().parent.parent
+SCRIPT = ROOT / "scripts" / "timmy_gemma4_mac.py"
+README = ROOT / "scripts" / "README_big_brain.md"
+
+
+def load_module():
+    spec = importlib.util.spec_from_file_location("timmy_gemma4_mac", str(SCRIPT))
+    mod = importlib.util.module_from_spec(spec)
+    sys.modules["timmy_gemma4_mac"] = mod
+    spec.loader.exec_module(mod)
+    return mod
+
+
+class _FakeResponse:
+    def __init__(self, payload: dict):
+        self._payload = json.dumps(payload).encode()
+
+    def read(self) -> bytes:
+        return self._payload
+
+    def __enter__(self):
+        return self
+
+    def __exit__(self, exc_type, exc, tb):
+        return False
+
+
+def test_script_exists() -> None:
+    assert SCRIPT.exists(), "scripts/timmy_gemma4_mac.py must exist"
+
+
+def test_default_paths_target_timmy_mac_hermes() -> None:
+    mod = load_module()
+    assert mod.DEFAULT_CONFIG_PATH == Path.home() / ".hermes" / "config.yaml"
+    assert mod.DEFAULT_TOKEN_FILE == Path.home() / ".config" / "runpod" / "access_key"
+
+
+def test_choose_base_url_prefers_vertex_then_explicit_then_runpod() -> None:
+    mod = load_module()
+    assert mod.choose_base_url(vertex_base_url="https://vertex-proxy.example/v1") == "https://vertex-proxy.example/v1"
+    assert mod.choose_base_url(base_url="https://custom-endpoint/v1") == "https://custom-endpoint/v1"
+    assert mod.choose_base_url(pod_id="abc123") == "https://abc123-11434.proxy.runpod.net/v1"
+
+
+def test_build_summary_includes_prove_it_commands() -> None:
+    mod = load_module()
+    summary = mod.build_summary(base_url="https://vertex-proxy.example/v1", model="gemma4:latest")
+    assert summary["verification_commands"][0] == "python3 scripts/verify_big_brain.py"
+    assert any("hermes chat --model gemma4 --provider big_brain" in cmd for cmd in summary["verification_commands"])
+
+
+def test_verify_openai_chat_targets_chat_completions() -> None:
+    mod = load_module()
+    response_payload = {
+        "choices": [{"message": {"content": "READY"}}]
+    }
+
+    with patch("timmy_gemma4_mac.request.urlopen", return_value=_FakeResponse(response_payload)) as mocked:
+        result = mod.verify_openai_chat("https://vertex-proxy.example/v1", model="gemma4:latest", prompt="say READY")
+
+    assert result == "READY"
+    req = mocked.call_args.args[0]
+    assert req.full_url == "https://vertex-proxy.example/v1/chat/completions"
+
+
+def test_readme_mentions_timmy_mac_wiring_flow() -> None:
+    text = README.read_text(encoding="utf-8")
+    required = [
+        "scripts/timmy_gemma4_mac.py",
+        "--vertex-base-url",
+        "--write-config",
+        "python3 scripts/verify_big_brain.py",
+        "hermes chat --model gemma4 --provider big_brain",
+    ]
+    missing = [item for item in required if item not in text]
+    assert not missing, missing

tests/timmy/test_claim_annotator.py

@@ -1,103 +0,0 @@
-#!/usr/bin/env python3
-"""Tests for claim_annotator.py — verifies source distinction is present."""
-
-import sys
-import os
-import json
-
-sys.path.insert(0, os.path.join(os.path.dirname(__file__), "..", "src"))
-
-from timmy.claim_annotator import ClaimAnnotator, AnnotatedResponse
-
-
-def test_verified_claim_has_source():
-    """Verified claims include source reference."""
-    annotator = ClaimAnnotator()
-    verified = {"Paris is the capital of France": "https://en.wikipedia.org/wiki/Paris"}
-    response = "Paris is the capital of France. It is a beautiful city."
-
-    result = annotator.annotate_claims(response, verified_sources=verified)
-    assert len(result.claims) > 0
-    verified_claims = [c for c in result.claims if c.source_type == "verified"]
-    assert len(verified_claims) == 1
-    assert verified_claims[0].source_ref == "https://en.wikipedia.org/wiki/Paris"
-    assert "[V]" in result.rendered_text
-    assert "[source:" in result.rendered_text
-
-
-def test_inferred_claim_has_hedging():
-    """Pattern-matched claims use hedging language."""
-    annotator = ClaimAnnotator()
-    response = "The weather is nice today. It might rain tomorrow."
-
-    result = annotator.annotate_claims(response)
-    inferred_claims = [c for c in result.claims if c.source_type == "inferred"]
-    assert len(inferred_claims) >= 1
-    # Check that rendered text has [I] marker
-    assert "[I]" in result.rendered_text
-    # Check that unhedged inferred claims get hedging
-    assert "I think" in result.rendered_text or "I believe" in result.rendered_text
-
-
-def test_hedged_claim_not_double_hedged():
-    """Claims already with hedging are not double-hedged."""
-    annotator = ClaimAnnotator()
-    response = "I think the sky is blue. It is a nice day."
-
-    result = annotator.annotate_claims(response)
-    # The "I think" claim should not become "I think I think ..."
-    assert "I think I think" not in result.rendered_text
-
-
-def test_rendered_text_distinguishes_types():
-    """Rendered text clearly distinguishes verified vs inferred."""
-    annotator = ClaimAnnotator()
-    verified = {"Earth is round": "https://science.org/earth"}
-    response = "Earth is round. Stars are far away."
-
-    result = annotator.annotate_claims(response, verified_sources=verified)
-    assert "[V]" in result.rendered_text  # verified marker
-    assert "[I]" in result.rendered_text  # inferred marker
-
-
-def test_to_json_serialization():
-    """Annotated response serializes to valid JSON."""
-    annotator = ClaimAnnotator()
-    response = "Test claim."
-    result = annotator.annotate_claims(response)
-    json_str = annotator.to_json(result)
-    parsed = json.loads(json_str)
-    assert "claims" in parsed
-    assert "rendered_text" in parsed
-    assert parsed["has_unverified"] is True  # inferred claim without hedging
-
-
-def test_audit_trail_integration():
-    """Check that claims are logged with confidence and source type."""
-    # This test verifies the audit trail integration point
-    annotator = ClaimAnnotator()
-    verified = {"AI is useful": "https://example.com/ai"}
-    response = "AI is useful. It can help with tasks."
-
-    result = annotator.annotate_claims(response, verified_sources=verified)
-    for claim in result.claims:
-        assert claim.source_type in ("verified", "inferred")
-        assert claim.confidence in ("high", "medium", "low", "unknown")
-        if claim.source_type == "verified":
-            assert claim.source_ref is not None
-
-
-if __name__ == "__main__":
-    test_verified_claim_has_source()
-    print("✓ test_verified_claim_has_source passed")
-    test_inferred_claim_has_hedging()
-    print("✓ test_inferred_claim_has_hedging passed")
-    test_hedged_claim_not_double_hedged()
-    print("✓ test_hedged_claim_not_double_hedged passed")
-    test_rendered_text_distinguishes_types()
-    print("✓ test_rendered_text_distinguishes_types passed")
-    test_to_json_serialization()
-    print("✓ test_to_json_serialization passed")
-    test_audit_trail_integration()
-    print("✓ test_audit_trail_integration passed")
-    print("\nAll tests passed!")