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Author SHA1 Message Date
Alexander Whitestone
8141bf8ba3 feat: verify AI Gateway provider UX and attribution headers (#950)
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Closes #950

- promote Vercel AI Gateway near the top of the provider picker
- add dedicated AI Gateway model flow with Vercel API-key deep link and live pricing
- use curated AI Gateway catalog refresh with free Moonshot auto-promotion
- apply AI Gateway attribution headers on runtime clients
- add targeted QA tests for provider UX and attribution headers
2026-04-22 11:40:49 -04:00
Alexander Whitestone
892c4ab70a wip: add failing AI Gateway QA tests (#950)
- add ai-gateway provider UX, pricing, and Moonshot promotion tests
- add attribution-header regression tests for run_agent base-url handling
2026-04-22 11:30:05 -04:00
10 changed files with 527 additions and 1748 deletions

View File

@@ -1,4 +1,4 @@
from agent.telemetry_logger import log_token_usage\n"""Shared auxiliary client router for side tasks.
"""Shared auxiliary client router for side tasks.
Provides a single resolution chain so every consumer (context compression,
session search, web extraction, vision analysis, browser vision) picks up
@@ -38,6 +38,7 @@ import json
import logging
import os
import threading
from agent.telemetry_logger import log_token_usage
import time
from pathlib import Path # noqa: F401 — used by test mocks
from types import SimpleNamespace
@@ -122,6 +123,16 @@ _OR_HEADERS = {
"X-OpenRouter-Categories": "productivity,cli-agent",
}
# Vercel AI Gateway app attribution headers. HTTP-Referer maps to
# referrerUrl and X-Title maps to appName in the gateway analytics.
from hermes_cli import __version__ as _HERMES_VERSION
_AI_GATEWAY_HEADERS = {
"HTTP-Referer": "https://hermes-agent.nousresearch.com",
"X-Title": "Hermes Agent",
"User-Agent": f"HermesAgent/{_HERMES_VERSION}",
}
# Nous Portal extra_body for product attribution.
# Callers should pass this as extra_body in chat.completions.create()
# when the auxiliary client is backed by Nous Portal.
@@ -396,7 +407,8 @@ class _CodexCompletionsAdapter:
prompt_tokens=getattr(resp_usage, "input_tokens", 0),
completion_tokens=getattr(resp_usage, "output_tokens", 0),
total_tokens=getattr(resp_usage, "total_tokens", 0),
)\n log_token_usage(usage.prompt_tokens, usage.completion_tokens, model)
)
log_token_usage(usage.prompt_tokens, usage.completion_tokens, model)
except Exception as exc:
logger.debug("Codex auxiliary Responses API call failed: %s", exc)
raise
@@ -529,7 +541,8 @@ class _AnthropicCompletionsAdapter:
prompt_tokens=prompt_tokens,
completion_tokens=completion_tokens,
total_tokens=total_tokens,
)\n log_token_usage(usage.prompt_tokens, usage.completion_tokens, model)
)
log_token_usage(usage.prompt_tokens, usage.completion_tokens, model)
choice = SimpleNamespace(
index=0,

View File

@@ -1,100 +0,0 @@
# Issue #954 Verification — maps skill guest_house / camp_site / bakery
Status: PASS
## Drift noted
Issue #954 asked for validation on `upstream/main` (commit `c5a814b23`).
Fresh `forge/main` did not contain `skills/productivity/maps/`, so the forge branch was behind upstream for this feature cluster.
This branch ports the upstream maps skill files into the forge checkout and adds regression coverage.
## Automated verification
Command:
```bash
pytest -q tests/skills/test_maps_client.py
```
Result:
- 5 passed
Coverage added:
- maps skill files exist in the repo
- `guest_house` category maps to `tourism=guest_house`
- `camp_site` category maps to `tourism=camp_site`
- `bakery` expands to both `shop=bakery` and `amenity=bakery`
- dual-key bakery results dedupe correctly
- skill documentation lists the new categories and supersedes `find-nearby`
## Manual evidence
### 1) guest_house lookup
Command:
```bash
python3 skills/productivity/maps/scripts/maps_client.py nearby --near "Bath, United Kingdom" --category guest_house --limit 3
```
Observed results:
- Henrietta House — 390.3 m
- The Windsor — 437.2 m
- The Old Rectory Bed & Breakfast — 495.7 m
All returned `tourism=guest_house` in the raw tags.
### 2) camp_site lookup
Command:
```bash
python3 skills/productivity/maps/scripts/maps_client.py nearby --near "Yosemite Valley, California" --category camp_site --limit 5
```
Observed result:
- Yellow Pine Administrative Campground — 90.3 m
Returned `tourism=camp_site` in the raw tags.
### 3) bakery lookup via `shop=bakery`
Command:
```bash
python3 skills/productivity/maps/scripts/maps_client.py nearby --near "Lawrenceville, New Jersey" --category bakery --radius 5000 --limit 10
```
Observed results:
- The Gingered Peach — 713.8 m
- WildFlour Bakery — 741.9 m
Both returned `shop=bakery` in the raw tags.
### 4) bakery lookup via `amenity=bakery`
Command:
```bash
python3 skills/productivity/maps/scripts/maps_client.py nearby --near "20735 Stevens Creek Boulevard, Cupertino, CA" --category bakery --radius 600 --limit 5
```
Observed result:
- Paris Baguette — 28.6 m
Returned `amenity=bakery` in the raw tags (and also includes `shop=bakery`), proving the dual-key union query reaches amenity-tagged bakeries too.
## Conclusion
PASS.
- `guest_house` resolves correctly
- `camp_site` resolves correctly
- `bakery` resolves through both supported keys
- forge/main drift from upstream/main was real and is addressed on this branch

View File

@@ -168,7 +168,7 @@ import time as _time
from datetime import datetime
from hermes_cli import __version__, __release_date__
from hermes_constants import OPENROUTER_BASE_URL
from hermes_constants import AI_GATEWAY_BASE_URL, OPENROUTER_BASE_URL
logger = logging.getLogger(__name__)
@@ -1112,6 +1112,8 @@ def select_provider_and_model(args=None):
# Step 2: Provider-specific setup + model selection
if selected_provider == "openrouter":
_model_flow_openrouter(config, current_model)
elif selected_provider == "ai-gateway":
_model_flow_ai_gateway(config, current_model)
elif selected_provider == "nous":
_model_flow_nous(config, current_model, args=args)
elif selected_provider == "openai-codex":
@@ -1267,6 +1269,55 @@ def _model_flow_openrouter(config, current_model=""):
print("No change.")
def _model_flow_ai_gateway(config, current_model=""):
"""Vercel AI Gateway provider: ensure API key, then pick model with pricing."""
from hermes_cli.auth import _prompt_model_selection, _save_model_choice, deactivate_provider
from hermes_cli.config import get_env_value, save_env_value
from hermes_cli.models import ai_gateway_model_ids, get_pricing_for_provider
api_key = get_env_value("AI_GATEWAY_API_KEY")
if not api_key:
print("No Vercel AI Gateway API key configured.")
print("Create API key here: https://vercel.com/d?to=%2F%5Bteam%5D%2F%7E%2Fai-gateway&title=AI+Gateway")
print("Add a payment method to get $5 in free credits.")
print()
try:
import getpass
key = getpass.getpass("AI Gateway API key (or Enter to cancel): ").strip()
except (KeyboardInterrupt, EOFError):
print()
return
if not key:
print("Cancelled.")
return
save_env_value("AI_GATEWAY_API_KEY", key)
print("API key saved.")
print()
models_list = ai_gateway_model_ids(force_refresh=True)
pricing = get_pricing_for_provider("ai-gateway", force_refresh=True)
selected = _prompt_model_selection(models_list, current_model=current_model, pricing=pricing)
if selected:
_save_model_choice(selected)
from hermes_cli.config import load_config, save_config
cfg = load_config()
model = cfg.get("model")
if not isinstance(model, dict):
model = {"default": model} if model else {}
cfg["model"] = model
model["provider"] = "ai-gateway"
model["base_url"] = AI_GATEWAY_BASE_URL
model["api_mode"] = "chat_completions"
save_config(cfg)
deactivate_provider()
print(f"Default model set to: {selected} (via Vercel AI Gateway)")
else:
print("No change.")
def _model_flow_nous(config, current_model="", args=None):
"""Nous Portal provider: ensure logged in, then pick model."""
from hermes_cli.auth import (

View File

@@ -58,6 +58,28 @@ OPENROUTER_MODELS: list[tuple[str, str]] = [
_openrouter_catalog_cache: list[tuple[str, str]] | None = None
# Fallback Vercel AI Gateway snapshot used when the live catalog is unavailable.
# OSS / open-weight models prioritized first, then closed-source by family.
VERCEL_AI_GATEWAY_MODELS: list[tuple[str, str]] = [
("moonshotai/kimi-k2.6", "recommended"),
("alibaba/qwen3.6-plus", ""),
("zai/glm-5.1", ""),
("minimax/minimax-m2.7", ""),
("anthropic/claude-sonnet-4.6", ""),
("anthropic/claude-opus-4.7", ""),
("anthropic/claude-opus-4.6", ""),
("anthropic/claude-haiku-4.5", ""),
("openai/gpt-5.4", ""),
("openai/gpt-5.4-mini", ""),
("openai/gpt-5.3-codex", ""),
("google/gemini-3.1-pro-preview", ""),
("google/gemini-3-flash", ""),
("google/gemini-3.1-flash-lite-preview", ""),
("xai/grok-4.20-reasoning", ""),
]
_ai_gateway_catalog_cache: list[tuple[str, str]] | None = None
def _codex_curated_models() -> list[str]:
"""Derive the openai-codex curated list from codex_models.py.
@@ -258,18 +280,21 @@ _PROVIDER_MODELS: dict[str, list[str]] = {
"minimax-m2.5",
],
"ai-gateway": [
"anthropic/claude-opus-4.6",
"moonshotai/kimi-k2.6",
"alibaba/qwen3.6-plus",
"zai/glm-5.1",
"minimax/minimax-m2.7",
"anthropic/claude-sonnet-4.6",
"anthropic/claude-sonnet-4.5",
"anthropic/claude-opus-4.7",
"anthropic/claude-opus-4.6",
"anthropic/claude-haiku-4.5",
"openai/gpt-5",
"openai/gpt-4.1",
"openai/gpt-4.1-mini",
"google/gemini-3-pro-preview",
"openai/gpt-5.4",
"openai/gpt-5.4-mini",
"openai/gpt-5.3-codex",
"google/gemini-3.1-pro-preview",
"google/gemini-3-flash",
"google/gemini-2.5-pro",
"google/gemini-2.5-flash",
"deepseek/deepseek-v3.2",
"google/gemini-3.1-flash-lite-preview",
"xai/grok-4.20-reasoning",
],
"kilocode": [
"anthropic/claude-opus-4.6",
@@ -516,6 +541,7 @@ class ProviderEntry(NamedTuple):
CANONICAL_PROVIDERS: list[ProviderEntry] = [
ProviderEntry("nous", "Nous Portal", "Nous Portal (Nous Research subscription)"),
ProviderEntry("openrouter", "OpenRouter", "OpenRouter (100+ models, pay-per-use)"),
ProviderEntry("ai-gateway", "Vercel AI Gateway", "Vercel AI Gateway (200+ models, $5 free credit, no markup)"),
ProviderEntry("anthropic", "Anthropic", "Anthropic (Claude models — API key or Claude Code)"),
ProviderEntry("openai-codex", "OpenAI Codex", "OpenAI Codex"),
ProviderEntry("xiaomi", "Xiaomi MiMo", "Xiaomi MiMo (MiMo-V2 models — pro, omni, flash)"),
@@ -536,7 +562,6 @@ CANONICAL_PROVIDERS: list[ProviderEntry] = [
ProviderEntry("kilocode", "Kilo Code", "Kilo Code (Kilo Gateway API)"),
ProviderEntry("opencode-zen", "OpenCode Zen", "OpenCode Zen (35+ curated models, pay-as-you-go)"),
ProviderEntry("opencode-go", "OpenCode Go", "OpenCode Go (open models, $10/month subscription)"),
ProviderEntry("ai-gateway", "Vercel AI Gateway", "Vercel AI Gateway (200+ models, pay-per-use)"),
]
# Derived dicts — used throughout the codebase
@@ -679,6 +704,90 @@ def model_ids(*, force_refresh: bool = False) -> list[str]:
def _ai_gateway_model_is_free(pricing: Any) -> bool:
"""Return True if an AI Gateway model has $0 input AND output pricing."""
if not isinstance(pricing, dict):
return False
try:
return float(pricing.get("input", "0")) == 0 and float(pricing.get("output", "0")) == 0
except (TypeError, ValueError):
return False
def fetch_ai_gateway_models(
timeout: float = 8.0,
*,
force_refresh: bool = False,
) -> list[tuple[str, str]]:
"""Return the curated AI Gateway picker list, refreshed from the live catalog when possible."""
global _ai_gateway_catalog_cache
if _ai_gateway_catalog_cache is not None and not force_refresh:
return list(_ai_gateway_catalog_cache)
from hermes_constants import AI_GATEWAY_BASE_URL
fallback = list(VERCEL_AI_GATEWAY_MODELS)
preferred_ids = [mid for mid, _ in fallback]
try:
req = urllib.request.Request(
f"{AI_GATEWAY_BASE_URL.rstrip('/')}/models",
headers={"Accept": "application/json"},
)
with urllib.request.urlopen(req, timeout=timeout) as resp:
payload = json.loads(resp.read().decode())
except Exception:
return list(_ai_gateway_catalog_cache or fallback)
live_items = payload.get("data", [])
if not isinstance(live_items, list):
return list(_ai_gateway_catalog_cache or fallback)
live_by_id: dict[str, dict[str, Any]] = {}
for item in live_items:
if not isinstance(item, dict):
continue
mid = str(item.get("id") or "").strip()
if not mid:
continue
live_by_id[mid] = item
curated: list[tuple[str, str]] = []
for preferred_id in preferred_ids:
live_item = live_by_id.get(preferred_id)
if live_item is None:
continue
desc = "free" if _ai_gateway_model_is_free(live_item.get("pricing")) else ""
curated.append((preferred_id, desc))
if not curated:
return list(_ai_gateway_catalog_cache or fallback)
free_moonshot = next(
(
mid
for mid, item in live_by_id.items()
if mid.startswith("moonshotai/") and _ai_gateway_model_is_free(item.get("pricing"))
),
None,
)
if free_moonshot:
curated = [(mid, desc) for mid, desc in curated if mid != free_moonshot]
curated.insert(0, (free_moonshot, "recommended"))
else:
first_id, _ = curated[0]
curated[0] = (first_id, "recommended")
_ai_gateway_catalog_cache = curated
return list(curated)
def ai_gateway_model_ids(*, force_refresh: bool = False) -> list[str]:
"""Return just the AI Gateway model-id strings."""
return [mid for mid, _ in fetch_ai_gateway_models(force_refresh=force_refresh)]
# ---------------------------------------------------------------------------
# Pricing helpers — fetch live pricing from OpenRouter-compatible /v1/models
# ---------------------------------------------------------------------------
@@ -821,6 +930,51 @@ def fetch_models_with_pricing(
return result
def fetch_ai_gateway_pricing(
timeout: float = 8.0,
*,
force_refresh: bool = False,
) -> dict[str, dict[str, str]]:
"""Fetch Vercel AI Gateway /v1/models and return Hermes-shaped pricing."""
from hermes_constants import AI_GATEWAY_BASE_URL
cache_key = AI_GATEWAY_BASE_URL.rstrip("/")
if not force_refresh and cache_key in _pricing_cache:
return _pricing_cache[cache_key]
try:
req = urllib.request.Request(
f"{cache_key}/models",
headers={"Accept": "application/json"},
)
with urllib.request.urlopen(req, timeout=timeout) as resp:
payload = json.loads(resp.read().decode())
except Exception:
_pricing_cache[cache_key] = {}
return {}
result: dict[str, dict[str, str]] = {}
for item in payload.get("data", []):
if not isinstance(item, dict):
continue
mid = item.get("id")
pricing = item.get("pricing")
if not (mid and isinstance(pricing, dict)):
continue
entry: dict[str, str] = {
"prompt": str(pricing.get("input", "")),
"completion": str(pricing.get("output", "")),
}
if pricing.get("input_cache_read"):
entry["input_cache_read"] = str(pricing["input_cache_read"])
if pricing.get("input_cache_write"):
entry["input_cache_write"] = str(pricing["input_cache_write"])
result[mid] = entry
_pricing_cache[cache_key] = result
return result
def _resolve_openrouter_api_key() -> str:
"""Best-effort OpenRouter API key for pricing fetch."""
return os.getenv("OPENROUTER_API_KEY", "").strip()
@@ -839,7 +993,7 @@ def _resolve_nous_pricing_credentials() -> tuple[str, str]:
def get_pricing_for_provider(provider: str, *, force_refresh: bool = False) -> dict[str, dict[str, str]]:
"""Return live pricing for providers that support it (openrouter, nous)."""
"""Return live pricing for providers that support it (openrouter, ai-gateway, nous)."""
normalized = normalize_provider(provider)
if normalized == "openrouter":
return fetch_models_with_pricing(
@@ -847,11 +1001,11 @@ def get_pricing_for_provider(provider: str, *, force_refresh: bool = False) -> d
base_url="https://openrouter.ai/api",
force_refresh=force_refresh,
)
if normalized == "ai-gateway":
return fetch_ai_gateway_pricing(force_refresh=force_refresh)
if normalized == "nous":
api_key, base_url = _resolve_nous_pricing_credentials()
if base_url:
# Nous base_url typically looks like https://inference-api.nousresearch.com/v1
# We need the part before /v1 for our fetch function
stripped = base_url.rstrip("/")
if stripped.endswith("/v1"):
stripped = stripped[:-3]
@@ -1253,9 +1407,7 @@ def provider_model_ids(provider: Optional[str], *, force_refresh: bool = False)
if live:
return live
if normalized == "ai-gateway":
live = _fetch_ai_gateway_models()
if live:
return live
return ai_gateway_model_ids()
if normalized == "custom":
base_url = _get_custom_base_url()
if base_url:

View File

@@ -908,6 +908,10 @@ class AIAgent:
"X-OpenRouter-Title": "Hermes Agent",
"X-OpenRouter-Categories": "productivity,cli-agent",
}
elif "ai-gateway.vercel.sh" in effective_base.lower():
from agent.auxiliary_client import _AI_GATEWAY_HEADERS
client_kwargs["default_headers"] = dict(_AI_GATEWAY_HEADERS)
elif "api.githubcopilot.com" in effective_base.lower():
from hermes_cli.models import copilot_default_headers
@@ -4667,11 +4671,13 @@ class AIAgent:
return True
def _apply_client_headers_for_base_url(self, base_url: str) -> None:
from agent.auxiliary_client import _OR_HEADERS
from agent.auxiliary_client import _AI_GATEWAY_HEADERS, _OR_HEADERS
normalized = (base_url or "").lower()
if "openrouter" in normalized:
self._client_kwargs["default_headers"] = dict(_OR_HEADERS)
elif "ai-gateway.vercel.sh" in normalized:
self._client_kwargs["default_headers"] = dict(_AI_GATEWAY_HEADERS)
elif "api.githubcopilot.com" in normalized:
from hermes_cli.models import copilot_default_headers

View File

@@ -1,199 +0,0 @@
---
name: maps
description: >
Location intelligence — geocode a place, reverse-geocode coordinates,
find nearby places (46 POI categories), driving/walking/cycling
distance + time, turn-by-turn directions, timezone lookup, bounding
box + area for a named place, and POI search within a rectangle.
Uses OpenStreetMap + Overpass + OSRM. Free, no API key.
version: 1.2.0
author: Mibayy
license: MIT
metadata:
hermes:
tags: [maps, geocoding, places, routing, distance, directions, nearby, location, openstreetmap, nominatim, overpass, osrm]
category: productivity
requires_toolsets: [terminal]
supersedes: [find-nearby]
---
# Maps Skill
Location intelligence using free, open data sources. 8 commands, 44 POI
categories, zero dependencies (Python stdlib only), no API key required.
Data sources: OpenStreetMap/Nominatim, Overpass API, OSRM, TimeAPI.io.
This skill supersedes the old `find-nearby` skill — all of find-nearby's
functionality is covered by the `nearby` command below, with the same
`--near "<place>"` shortcut and multi-category support.
## When to Use
- User sends a Telegram location pin (latitude/longitude in the message) → `nearby`
- User wants coordinates for a place name → `search`
- User has coordinates and wants the address → `reverse`
- User asks for nearby restaurants, hospitals, pharmacies, hotels, etc. → `nearby`
- User wants driving/walking/cycling distance or travel time → `distance`
- User wants turn-by-turn directions between two places → `directions`
- User wants timezone information for a location → `timezone`
- User wants to search for POIs within a geographic area → `area` + `bbox`
## Prerequisites
Python 3.8+ (stdlib only — no pip installs needed).
Script path: `~/.hermes/skills/maps/scripts/maps_client.py`
## Commands
```bash
MAPS=~/.hermes/skills/maps/scripts/maps_client.py
```
### search — Geocode a place name
```bash
python3 $MAPS search "Eiffel Tower"
python3 $MAPS search "1600 Pennsylvania Ave, Washington DC"
```
Returns: lat, lon, display name, type, bounding box, importance score.
### reverse — Coordinates to address
```bash
python3 $MAPS reverse 48.8584 2.2945
```
Returns: full address breakdown (street, city, state, country, postcode).
### nearby — Find places by category
```bash
# By coordinates (from a Telegram location pin, for example)
python3 $MAPS nearby 48.8584 2.2945 restaurant --limit 10
python3 $MAPS nearby 40.7128 -74.0060 hospital --radius 2000
# By address / city / zip / landmark — --near auto-geocodes
python3 $MAPS nearby --near "Times Square, New York" --category cafe
python3 $MAPS nearby --near "90210" --category pharmacy
# Multiple categories merged into one query
python3 $MAPS nearby --near "downtown austin" --category restaurant --category bar --limit 10
```
46 categories: restaurant, cafe, bar, hospital, pharmacy, hotel, guest_house,
camp_site, supermarket, atm, gas_station, parking, museum, park, school,
university, bank, police, fire_station, library, airport, train_station,
bus_stop, church, mosque, synagogue, dentist, doctor, cinema, theatre, gym,
swimming_pool, post_office, convenience_store, bakery, bookshop, laundry,
car_wash, car_rental, bicycle_rental, taxi, veterinary, zoo, playground,
stadium, nightclub.
Each result includes: `name`, `address`, `lat`/`lon`, `distance_m`,
`maps_url` (clickable Google Maps link), `directions_url` (Google Maps
directions from the search point), and promoted tags when available —
`cuisine`, `hours` (opening_hours), `phone`, `website`.
### distance — Travel distance and time
```bash
python3 $MAPS distance "Paris" --to "Lyon"
python3 $MAPS distance "New York" --to "Boston" --mode driving
python3 $MAPS distance "Big Ben" --to "Tower Bridge" --mode walking
```
Modes: driving (default), walking, cycling. Returns road distance, duration,
and straight-line distance for comparison.
### directions — Turn-by-turn navigation
```bash
python3 $MAPS directions "Eiffel Tower" --to "Louvre Museum" --mode walking
python3 $MAPS directions "JFK Airport" --to "Times Square" --mode driving
```
Returns numbered steps with instruction, distance, duration, road name, and
maneuver type (turn, depart, arrive, etc.).
### timezone — Timezone for coordinates
```bash
python3 $MAPS timezone 48.8584 2.2945
python3 $MAPS timezone 35.6762 139.6503
```
Returns timezone name, UTC offset, and current local time.
### area — Bounding box and area for a place
```bash
python3 $MAPS area "Manhattan, New York"
python3 $MAPS area "London"
```
Returns bounding box coordinates, width/height in km, and approximate area.
Useful as input for the bbox command.
### bbox — Search within a bounding box
```bash
python3 $MAPS bbox 40.75 -74.00 40.77 -73.98 restaurant --limit 20
```
Finds POIs within a geographic rectangle. Use `area` first to get the
bounding box coordinates for a named place.
## Working With Telegram Location Pins
When a user sends a location pin, the message contains `latitude:` and
`longitude:` fields. Extract those and pass them straight to `nearby`:
```bash
# User sent a pin at 36.17, -115.14 and asked "find cafes nearby"
python3 $MAPS nearby 36.17 -115.14 cafe --radius 1500
```
Present results as a numbered list with names, distances, and the
`maps_url` field so the user gets a tap-to-open link in chat. For "open
now?" questions, check the `hours` field; if missing or unclear, verify
with `web_search` since OSM hours are community-maintained and not always
current.
## Workflow Examples
**"Find Italian restaurants near the Colosseum":**
1. `nearby --near "Colosseum Rome" --category restaurant --radius 500`
— one command, auto-geocoded
**"What's near this location pin they sent?":**
1. Extract lat/lon from the Telegram message
2. `nearby LAT LON cafe --radius 1500`
**"How do I walk from hotel to conference center?":**
1. `directions "Hotel Name" --to "Conference Center" --mode walking`
**"What restaurants are in downtown Seattle?":**
1. `area "Downtown Seattle"` → get bounding box
2. `bbox S W N E restaurant --limit 30`
## Pitfalls
- Nominatim ToS: max 1 req/s (handled automatically by the script)
- `nearby` requires lat/lon OR `--near "<address>"` — one of the two is needed
- OSRM routing coverage is best for Europe and North America
- Overpass API can be slow during peak hours; the script automatically
falls back between mirrors (overpass-api.de → overpass.kumi.systems)
- `distance` and `directions` use `--to` flag for the destination (not positional)
- If a zip code alone gives ambiguous results globally, include country/state
## Verification
```bash
python3 ~/.hermes/skills/maps/scripts/maps_client.py search "Statue of Liberty"
# Should return lat ~40.689, lon ~-74.044
python3 ~/.hermes/skills/maps/scripts/maps_client.py nearby --near "Times Square" --category restaurant --limit 3
# Should return a list of restaurants within ~500m of Times Square
```

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"""AI Gateway provider UX, live pricing, and model promotion tests."""
from __future__ import annotations
import json
from unittest.mock import MagicMock, patch
import pytest
from hermes_cli import models as models_module
from hermes_cli.models import (
CANONICAL_PROVIDERS,
VERCEL_AI_GATEWAY_MODELS,
_ai_gateway_model_is_free,
ai_gateway_model_ids,
fetch_ai_gateway_models,
fetch_ai_gateway_pricing,
get_pricing_for_provider,
)
def _mock_urlopen(payload):
resp = MagicMock()
resp.read.return_value = json.dumps(payload).encode()
ctx = MagicMock()
ctx.__enter__.return_value = resp
ctx.__exit__.return_value = False
return ctx
def _reset_caches():
models_module._ai_gateway_catalog_cache = None
models_module._pricing_cache.clear()
@pytest.fixture
def config_home(tmp_path, monkeypatch):
home = tmp_path / "hermes"
home.mkdir()
(home / "config.yaml").write_text("model: some-old-model\n")
(home / ".env").write_text("")
monkeypatch.setenv("HERMES_HOME", str(home))
monkeypatch.delenv("AI_GATEWAY_API_KEY", raising=False)
monkeypatch.delenv("AI_GATEWAY_BASE_URL", raising=False)
return home
def test_ai_gateway_provider_is_promoted_near_top_of_picker():
slugs = [entry.slug for entry in CANONICAL_PROVIDERS]
assert "ai-gateway" in slugs[:3]
def test_ai_gateway_pricing_translates_input_output_to_prompt_completion():
_reset_caches()
payload = {
"data": [
{
"id": "moonshotai/kimi-k2.5",
"type": "language",
"pricing": {
"input": "0.0000006",
"output": "0.0000025",
"input_cache_read": "0.00000015",
"input_cache_write": "0.0000006",
},
}
]
}
with patch("urllib.request.urlopen", return_value=_mock_urlopen(payload)):
result = fetch_ai_gateway_pricing(force_refresh=True)
entry = result["moonshotai/kimi-k2.5"]
assert entry["prompt"] == "0.0000006"
assert entry["completion"] == "0.0000025"
assert entry["input_cache_read"] == "0.00000015"
assert entry["input_cache_write"] == "0.0000006"
def test_get_pricing_for_provider_supports_ai_gateway():
_reset_caches()
payload = {
"data": [
{
"id": "moonshotai/kimi-k2.5",
"type": "language",
"pricing": {"input": "0.0001", "output": "0.0002"},
}
]
}
with patch("urllib.request.urlopen", return_value=_mock_urlopen(payload)):
result = get_pricing_for_provider("ai-gateway", force_refresh=True)
assert result["moonshotai/kimi-k2.5"] == {"prompt": "0.0001", "completion": "0.0002"}
def test_ai_gateway_pricing_returns_empty_on_fetch_failure():
_reset_caches()
with patch("urllib.request.urlopen", side_effect=OSError("network down")):
result = fetch_ai_gateway_pricing(force_refresh=True)
assert result == {}
def test_ai_gateway_pricing_skips_entries_without_pricing_dict():
_reset_caches()
payload = {
"data": [
{"id": "x/y", "pricing": None},
{"id": "a/b", "pricing": {"input": "0", "output": "0"}},
]
}
with patch("urllib.request.urlopen", return_value=_mock_urlopen(payload)):
result = fetch_ai_gateway_pricing(force_refresh=True)
assert "x/y" not in result
assert result["a/b"] == {"prompt": "0", "completion": "0"}
def test_ai_gateway_free_detector():
assert _ai_gateway_model_is_free({"input": "0", "output": "0"}) is True
assert _ai_gateway_model_is_free({"input": "0", "output": "0.01"}) is False
assert _ai_gateway_model_is_free({"input": "0.01", "output": "0"}) is False
assert _ai_gateway_model_is_free(None) is False
assert _ai_gateway_model_is_free({"input": "not a number"}) is False
def test_fetch_ai_gateway_models_filters_against_live_catalog():
_reset_caches()
preferred = [mid for mid, _ in VERCEL_AI_GATEWAY_MODELS]
live_ids = preferred[:3]
payload = {
"data": [
{"id": mid, "pricing": {"input": "0.001", "output": "0.002"}}
for mid in live_ids
]
}
with patch("urllib.request.urlopen", return_value=_mock_urlopen(payload)):
result = fetch_ai_gateway_models(force_refresh=True)
assert [mid for mid, _ in result] == live_ids
assert result[0][1] == "recommended"
assert ai_gateway_model_ids(force_refresh=False) == live_ids
def test_fetch_ai_gateway_models_tags_free_models():
_reset_caches()
first_id = VERCEL_AI_GATEWAY_MODELS[0][0]
second_id = VERCEL_AI_GATEWAY_MODELS[1][0]
payload = {
"data": [
{"id": first_id, "pricing": {"input": "0.001", "output": "0.002"}},
{"id": second_id, "pricing": {"input": "0", "output": "0"}},
]
}
with patch("urllib.request.urlopen", return_value=_mock_urlopen(payload)):
result = fetch_ai_gateway_models(force_refresh=True)
by_id = dict(result)
assert by_id[first_id] == "recommended"
assert by_id[second_id] == "free"
def test_free_moonshot_model_auto_promoted_to_top_even_if_not_curated():
_reset_caches()
first_curated = VERCEL_AI_GATEWAY_MODELS[0][0]
unlisted_free_moonshot = "moonshotai/kimi-coder-free-preview"
payload = {
"data": [
{"id": first_curated, "pricing": {"input": "0.001", "output": "0.002"}},
{"id": unlisted_free_moonshot, "pricing": {"input": "0", "output": "0"}},
]
}
with patch("urllib.request.urlopen", return_value=_mock_urlopen(payload)):
result = fetch_ai_gateway_models(force_refresh=True)
assert result[0] == (unlisted_free_moonshot, "recommended")
assert any(mid == first_curated for mid, _ in result)
def test_paid_moonshot_does_not_get_auto_promoted():
_reset_caches()
first_curated = VERCEL_AI_GATEWAY_MODELS[0][0]
payload = {
"data": [
{"id": first_curated, "pricing": {"input": "0.001", "output": "0.002"}},
{"id": "moonshotai/some-paid-variant", "pricing": {"input": "0.001", "output": "0.002"}},
]
}
with patch("urllib.request.urlopen", return_value=_mock_urlopen(payload)):
result = fetch_ai_gateway_models(force_refresh=True)
assert result[0][0] == first_curated
def test_fetch_ai_gateway_models_falls_back_on_error():
_reset_caches()
with patch("urllib.request.urlopen", side_effect=OSError("network")):
result = fetch_ai_gateway_models(force_refresh=True)
assert result == list(VERCEL_AI_GATEWAY_MODELS)
def test_ai_gateway_setup_flow_shows_deeplink_and_passes_pricing(config_home, monkeypatch, capsys):
from hermes_cli.main import _model_flow_ai_gateway
from hermes_cli.config import load_config
pricing = {"moonshotai/kimi-k2.6": {"prompt": "0", "completion": "0"}}
monkeypatch.setenv("HERMES_HOME", str(config_home))
with patch("getpass.getpass", return_value="vercel-key"), \
patch("hermes_cli.models.ai_gateway_model_ids", return_value=["moonshotai/kimi-k2.6"]), \
patch("hermes_cli.models.get_pricing_for_provider", return_value=pricing), \
patch("hermes_cli.auth._prompt_model_selection", return_value="moonshotai/kimi-k2.6") as prompt_selection, \
patch("hermes_cli.auth.deactivate_provider"):
_model_flow_ai_gateway(load_config(), "")
out = capsys.readouterr().out
assert "vercel.com/d?to=%2F%5Bteam%5D%2F%7E%2Fai-gateway&title=AI+Gateway" in out
assert "free credits" in out.lower()
assert prompt_selection.call_args.kwargs["pricing"] == pricing
import yaml
config = yaml.safe_load((config_home / "config.yaml").read_text()) or {}
model = config["model"]
assert model["provider"] == "ai-gateway"
assert model["api_mode"] == "chat_completions"

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"""Attribution default_headers applied per provider via base-URL detection."""
from unittest.mock import MagicMock, patch
from run_agent import AIAgent
@patch("run_agent.OpenAI")
def test_openrouter_base_url_applies_or_headers(mock_openai):
mock_openai.return_value = MagicMock()
agent = AIAgent(
api_key="test-key",
base_url="https://openrouter.ai/api/v1",
model="test/model",
quiet_mode=True,
skip_context_files=True,
skip_memory=True,
)
agent._apply_client_headers_for_base_url("https://openrouter.ai/api/v1")
headers = agent._client_kwargs["default_headers"]
assert headers["HTTP-Referer"] == "https://hermes-agent.nousresearch.com"
assert headers["X-OpenRouter-Title"] == "Hermes Agent"
@patch("run_agent.OpenAI")
def test_ai_gateway_base_url_applies_attribution_headers(mock_openai):
mock_openai.return_value = MagicMock()
agent = AIAgent(
api_key="test-key",
base_url="https://openrouter.ai/api/v1",
model="test/model",
quiet_mode=True,
skip_context_files=True,
skip_memory=True,
)
agent._apply_client_headers_for_base_url("https://ai-gateway.vercel.sh/v1")
headers = agent._client_kwargs["default_headers"]
assert headers["HTTP-Referer"] == "https://hermes-agent.nousresearch.com"
assert headers["X-Title"] == "Hermes Agent"
assert headers["User-Agent"].startswith("HermesAgent/")
@patch("run_agent.OpenAI")
def test_unknown_base_url_clears_default_headers(mock_openai):
mock_openai.return_value = MagicMock()
agent = AIAgent(
api_key="test-key",
base_url="https://openrouter.ai/api/v1",
model="test/model",
quiet_mode=True,
skip_context_files=True,
skip_memory=True,
)
agent._client_kwargs["default_headers"] = {"X-Stale": "yes"}
agent._apply_client_headers_for_base_url("https://api.example.com/v1")
assert "default_headers" not in agent._client_kwargs

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@@ -1,135 +0,0 @@
"""Regression tests for the bundled maps skill."""
from __future__ import annotations
import importlib.util
from pathlib import Path
from types import SimpleNamespace
SCRIPT_PATH = (
Path(__file__).resolve().parents[2]
/ "skills/productivity/maps/scripts/maps_client.py"
)
SKILL_PATH = (
Path(__file__).resolve().parents[2]
/ "skills/productivity/maps/SKILL.md"
)
def load_module():
assert SCRIPT_PATH.exists(), f"missing maps client script: {SCRIPT_PATH}"
spec = importlib.util.spec_from_file_location("maps_client_test", SCRIPT_PATH)
module = importlib.util.module_from_spec(spec)
assert spec.loader is not None
spec.loader.exec_module(module)
return module
def test_maps_skill_files_exist():
assert SCRIPT_PATH.exists()
assert SKILL_PATH.exists()
def test_category_tags_cover_guest_house_camp_site_and_dual_key_bakery():
module = load_module()
assert module.CATEGORY_TAGS["guest_house"] == ("tourism", "guest_house")
assert module.CATEGORY_TAGS["camp_site"] == ("tourism", "camp_site")
assert module.CATEGORY_TAGS["bakery"] == [
("shop", "bakery"),
("amenity", "bakery"),
]
assert module._tags_for("bakery") == [
("shop", "bakery"),
("amenity", "bakery"),
]
def test_build_overpass_queries_include_all_supported_tags():
module = load_module()
bakery_query = module.build_overpass_nearby(
None,
None,
40.0,
-74.0,
500,
10,
tag_pairs=module._tags_for("bakery"),
)
assert 'node["shop"="bakery"]' in bakery_query
assert 'way["shop"="bakery"]' in bakery_query
assert 'node["amenity"="bakery"]' in bakery_query
assert 'way["amenity"="bakery"]' in bakery_query
guest_house_query = module.build_overpass_nearby(
None,
None,
40.0,
-74.0,
500,
10,
tag_pairs=module._tags_for("guest_house"),
)
assert 'node["tourism"="guest_house"]' in guest_house_query
assert 'way["tourism"="guest_house"]' in guest_house_query
camp_site_bbox = module.build_overpass_bbox(
None,
None,
39.0,
-75.0,
41.0,
-73.0,
10,
tag_pairs=module._tags_for("camp_site"),
)
assert 'node["tourism"="camp_site"]' in camp_site_bbox
assert 'way["tourism"="camp_site"]' in camp_site_bbox
def test_cmd_nearby_dedupes_dual_tag_bakery_results(monkeypatch, capsys):
module = load_module()
duplicate_bakery = {
"elements": [
{
"type": "node",
"id": 101,
"lat": 40.0,
"lon": -74.0,
"tags": {"name": "Wild Flour", "shop": "bakery"},
},
{
"type": "node",
"id": 101,
"lat": 40.0,
"lon": -74.0,
"tags": {"name": "Wild Flour", "amenity": "bakery"},
},
]
}
monkeypatch.setattr(module, "overpass_query", lambda query: duplicate_bakery)
args = SimpleNamespace(
lat="40.0",
lon="-74.0",
near=None,
category="bakery",
category_list=[],
radius=500,
limit=10,
)
module.cmd_nearby(args)
out = capsys.readouterr().out
assert '"count": 1' in out
assert '"Wild Flour"' in out
def test_skill_doc_lists_new_categories_and_supersession():
text = SKILL_PATH.read_text(encoding="utf-8")
assert "guest_house" in text
assert "camp_site" in text
assert "bakery" in text
assert "supersedes: [find-nearby]" in text