mirror of
https://github.com/NousResearch/hermes-agent.git
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`fetch_models_dev()` is on the hot path of every `AIAgent.__init__`
(via `context_compressor → get_model_context_length`). The previous
policy was "always try network first, only fall back to disk if
network fails," so every fresh `hermes chat` / `hermes gateway` /
batch / cron process paid 250-500 ms re-fetching a 2 MB JSON registry
that was already on disk from earlier runs.
Add a stage 2 between in-mem and network: if
`models_dev_cache.json` exists and its mtime is younger than the
existing `_MODELS_DEV_CACHE_TTL` (1 hour, same TTL the in-mem cache
already uses), load from disk and skip the network call.
The in-mem TTL is anchored to the disk file's age, so a 50-min-old
cache stays in-memory for only 10 more minutes — no surprise
extension of staleness window.
Invariants preserved:
- `force_refresh=True` still always hits the network and only falls
back to disk on failure (`hermes config refresh` semantics).
- Missing disk cache → fall through to network (first-ever run).
- Stale disk cache (mtime > TTL) → fall through to network.
- Negative file age (clock skew) → fall through to network.
- Network failure → existing stage-4 stale-disk fallback unchanged.
Measured impact (3-run medians, 9950X3D, fresh process per run):
fetch_models_dev cold: 256 → 17 ms (-93%)
hermes chat -q wall: 4.00 → 3.73 s (-7% median)
3.99 → 3.60 s (-10% min)
The chat-end-to-end win is bounded below by API latency variance, but
the fetch_models_dev microbenchmark is the cleanest signal: 239 ms
shaved off every fresh-process agent construction.
Win compounds with the previous perf PRs:
#22681 google_chat lazy-load
#22766 doctor parallel + IMDS off
#22790 gateway.platforms PEP 562
Tests: all 30 `tests/agent/test_models_dev.py` pass (added 4 new ones
covering the new disk-cache-first path, force_refresh override, stale
disk fallback, and missing-disk-cache fall-through). Full `tests/agent/`
suite: 2560 passed, 0 failed.
397 lines
15 KiB
Python
397 lines
15 KiB
Python
"""Tests for agent.models_dev — models.dev registry integration."""
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import json
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from unittest.mock import patch, MagicMock
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import pytest
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from agent.models_dev import (
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PROVIDER_TO_MODELS_DEV,
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_extract_context,
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fetch_models_dev,
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get_model_capabilities,
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lookup_models_dev_context,
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)
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SAMPLE_REGISTRY = {
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"anthropic": {
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"id": "anthropic",
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"name": "Anthropic",
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"models": {
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"claude-opus-4-6": {
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"id": "claude-opus-4-6",
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"limit": {"context": 1000000, "output": 128000},
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},
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"claude-sonnet-4-6": {
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"id": "claude-sonnet-4-6",
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"limit": {"context": 1000000, "output": 64000},
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},
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"claude-sonnet-4-0": {
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"id": "claude-sonnet-4-0",
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"limit": {"context": 200000, "output": 64000},
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},
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},
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},
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"github-copilot": {
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"id": "github-copilot",
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"name": "GitHub Copilot",
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"models": {
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"claude-opus-4.6": {
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"id": "claude-opus-4.6",
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"limit": {"context": 128000, "output": 32000},
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},
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},
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},
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"kilo": {
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"id": "kilo",
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"name": "Kilo Gateway",
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"models": {
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"anthropic/claude-sonnet-4.6": {
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"id": "anthropic/claude-sonnet-4.6",
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"limit": {"context": 1000000, "output": 128000},
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},
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},
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},
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"deepseek": {
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"id": "deepseek",
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"name": "DeepSeek",
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"models": {
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"deepseek-chat": {
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"id": "deepseek-chat",
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"limit": {"context": 128000, "output": 8192},
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},
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},
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},
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"audio-only": {
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"id": "audio-only",
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"models": {
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"tts-model": {
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"id": "tts-model",
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"limit": {"context": 0, "output": 0},
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},
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},
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},
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}
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class TestProviderMapping:
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def test_all_mapped_providers_are_strings(self):
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for hermes_id, mdev_id in PROVIDER_TO_MODELS_DEV.items():
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assert isinstance(hermes_id, str)
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assert isinstance(mdev_id, str)
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def test_known_providers_mapped(self):
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assert PROVIDER_TO_MODELS_DEV["anthropic"] == "anthropic"
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assert PROVIDER_TO_MODELS_DEV["copilot"] == "github-copilot"
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assert PROVIDER_TO_MODELS_DEV["stepfun"] == "stepfun"
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assert PROVIDER_TO_MODELS_DEV["kilocode"] == "kilo"
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assert PROVIDER_TO_MODELS_DEV["ai-gateway"] == "vercel"
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def test_unmapped_provider_not_in_dict(self):
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assert "nous" not in PROVIDER_TO_MODELS_DEV
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def test_openai_codex_mapped_to_openai(self):
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assert PROVIDER_TO_MODELS_DEV["openai"] == "openai"
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assert PROVIDER_TO_MODELS_DEV["openai-codex"] == "openai"
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class TestExtractContext:
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def test_valid_entry(self):
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assert _extract_context({"limit": {"context": 128000}}) == 128000
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def test_zero_context_returns_none(self):
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assert _extract_context({"limit": {"context": 0}}) is None
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def test_missing_limit_returns_none(self):
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assert _extract_context({"id": "test"}) is None
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def test_missing_context_returns_none(self):
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assert _extract_context({"limit": {"output": 8192}}) is None
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def test_non_dict_returns_none(self):
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assert _extract_context("not a dict") is None
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def test_float_context_coerced_to_int(self):
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assert _extract_context({"limit": {"context": 131072.0}}) == 131072
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class TestLookupModelsDevContext:
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@patch("agent.models_dev.fetch_models_dev")
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def test_exact_match(self, mock_fetch):
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mock_fetch.return_value = SAMPLE_REGISTRY
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assert lookup_models_dev_context("anthropic", "claude-opus-4-6") == 1000000
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@patch("agent.models_dev.fetch_models_dev")
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def test_case_insensitive_match(self, mock_fetch):
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mock_fetch.return_value = SAMPLE_REGISTRY
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assert lookup_models_dev_context("anthropic", "Claude-Opus-4-6") == 1000000
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@patch("agent.models_dev.fetch_models_dev")
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def test_provider_not_mapped(self, mock_fetch):
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mock_fetch.return_value = SAMPLE_REGISTRY
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assert lookup_models_dev_context("nous", "some-model") is None
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@patch("agent.models_dev.fetch_models_dev")
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def test_model_not_found(self, mock_fetch):
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mock_fetch.return_value = SAMPLE_REGISTRY
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assert lookup_models_dev_context("anthropic", "nonexistent-model") is None
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@patch("agent.models_dev.fetch_models_dev")
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def test_provider_aware_context(self, mock_fetch):
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"""Same model, different context per provider."""
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mock_fetch.return_value = SAMPLE_REGISTRY
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# Anthropic direct: 1M
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assert lookup_models_dev_context("anthropic", "claude-opus-4-6") == 1000000
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# GitHub Copilot: only 128K for same model
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assert lookup_models_dev_context("copilot", "claude-opus-4.6") == 128000
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@patch("agent.models_dev.fetch_models_dev")
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def test_zero_context_filtered(self, mock_fetch):
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mock_fetch.return_value = SAMPLE_REGISTRY
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# audio-only is not a mapped provider, but test the filtering directly
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data = SAMPLE_REGISTRY["audio-only"]["models"]["tts-model"]
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assert _extract_context(data) is None
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@patch("agent.models_dev.fetch_models_dev")
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def test_empty_registry(self, mock_fetch):
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mock_fetch.return_value = {}
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assert lookup_models_dev_context("anthropic", "claude-opus-4-6") is None
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class TestFetchModelsDev:
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@patch("agent.models_dev.requests.get")
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def test_fetch_success(self, mock_get):
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mock_resp = MagicMock()
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mock_resp.status_code = 200
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mock_resp.json.return_value = SAMPLE_REGISTRY
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mock_resp.raise_for_status = MagicMock()
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mock_get.return_value = mock_resp
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# Clear caches
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import agent.models_dev as md
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md._models_dev_cache = {}
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md._models_dev_cache_time = 0
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with patch.object(md, "_save_disk_cache"):
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result = fetch_models_dev(force_refresh=True)
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assert "anthropic" in result
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assert len(result) == len(SAMPLE_REGISTRY)
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@patch("agent.models_dev.requests.get")
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def test_fetch_failure_returns_stale_cache(self, mock_get):
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mock_get.side_effect = Exception("network error")
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import agent.models_dev as md
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md._models_dev_cache = SAMPLE_REGISTRY
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md._models_dev_cache_time = 0 # expired
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with patch.object(md, "_load_disk_cache", return_value=SAMPLE_REGISTRY):
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result = fetch_models_dev(force_refresh=True)
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assert "anthropic" in result
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@patch("agent.models_dev.requests.get")
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def test_in_memory_cache_used(self, mock_get):
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import agent.models_dev as md
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import time
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md._models_dev_cache = SAMPLE_REGISTRY
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md._models_dev_cache_time = time.time() # fresh
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result = fetch_models_dev()
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mock_get.assert_not_called()
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assert result == SAMPLE_REGISTRY
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@patch("agent.models_dev.requests.get")
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def test_fresh_disk_cache_skips_network(self, mock_get):
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"""When in-mem cache is empty but disk cache exists and is fresh by
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mtime (< TTL), fetch_models_dev returns disk data without ever
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making the network call.
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This is the cold-start fast path: every fresh process previously
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paid ~500 ms re-fetching a registry that was already on disk
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from an earlier run.
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"""
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import agent.models_dev as md
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# Empty in-mem cache so stage 1 doesn't short-circuit.
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md._models_dev_cache = {}
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md._models_dev_cache_time = 0
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with patch.object(md, "_disk_cache_age_seconds", return_value=60.0), \
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patch.object(md, "_load_disk_cache", return_value=SAMPLE_REGISTRY):
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result = fetch_models_dev()
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# The whole point: no network call.
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mock_get.assert_not_called()
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assert "anthropic" in result
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# In-mem cache populated so subsequent calls within the same
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# process stay on stage 1.
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assert md._models_dev_cache == SAMPLE_REGISTRY
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@patch("agent.models_dev.requests.get")
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def test_stale_disk_cache_falls_through_to_network(self, mock_get):
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"""When the disk cache is OLDER than TTL, we must hit the network
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(and only fall back to the stale disk data if network fails)."""
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import agent.models_dev as md
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md._models_dev_cache = {}
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md._models_dev_cache_time = 0
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mock_resp = MagicMock()
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mock_resp.status_code = 200
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mock_resp.json.return_value = SAMPLE_REGISTRY
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mock_resp.raise_for_status = MagicMock()
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mock_get.return_value = mock_resp
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# Disk cache exists but is older than the TTL — must NOT short-circuit.
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with patch.object(md, "_disk_cache_age_seconds",
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return_value=md._MODELS_DEV_CACHE_TTL + 60), \
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patch.object(md, "_load_disk_cache", return_value=SAMPLE_REGISTRY), \
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patch.object(md, "_save_disk_cache"):
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result = fetch_models_dev()
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mock_get.assert_called_once()
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assert "anthropic" in result
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@patch("agent.models_dev.requests.get")
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def test_force_refresh_skips_disk_cache(self, mock_get):
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"""force_refresh=True bypasses BOTH the in-mem cache AND the
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disk-cache fast path. Used by ``hermes config refresh`` and
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anywhere else the user explicitly asked for fresh data.
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"""
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import agent.models_dev as md
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md._models_dev_cache = {}
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md._models_dev_cache_time = 0
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mock_resp = MagicMock()
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mock_resp.status_code = 200
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mock_resp.json.return_value = SAMPLE_REGISTRY
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mock_resp.raise_for_status = MagicMock()
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mock_get.return_value = mock_resp
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# Disk cache is fresh, but force_refresh must override it.
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with patch.object(md, "_disk_cache_age_seconds", return_value=60.0), \
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patch.object(md, "_load_disk_cache", return_value=SAMPLE_REGISTRY), \
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patch.object(md, "_save_disk_cache"):
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result = fetch_models_dev(force_refresh=True)
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mock_get.assert_called_once()
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assert "anthropic" in result
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@patch("agent.models_dev.requests.get")
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def test_missing_disk_cache_falls_through_to_network(self, mock_get):
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"""If the disk cache file doesn't exist (first-ever run, or it
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was deleted), fall through cleanly to network."""
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import agent.models_dev as md
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md._models_dev_cache = {}
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md._models_dev_cache_time = 0
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mock_resp = MagicMock()
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mock_resp.status_code = 200
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mock_resp.json.return_value = SAMPLE_REGISTRY
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mock_resp.raise_for_status = MagicMock()
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mock_get.return_value = mock_resp
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with patch.object(md, "_disk_cache_age_seconds", return_value=None), \
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patch.object(md, "_save_disk_cache"):
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result = fetch_models_dev()
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mock_get.assert_called_once()
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assert "anthropic" in result
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# ---------------------------------------------------------------------------
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# get_model_capabilities — vision via modalities.input
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# ---------------------------------------------------------------------------
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CAPS_REGISTRY = {
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"google": {
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"id": "google",
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"models": {
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"gemma-4-31b-it": {
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"id": "gemma-4-31b-it",
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"attachment": False,
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"tool_call": True,
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"modalities": {"input": ["text", "image"]},
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"limit": {"context": 128000, "output": 8192},
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},
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"gemma-3-1b": {
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"id": "gemma-3-1b",
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"tool_call": True,
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"limit": {"context": 32000, "output": 8192},
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},
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"text-only-with-stale-attachment": {
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"id": "text-only-with-stale-attachment",
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"attachment": True,
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"tool_call": True,
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"modalities": {"input": ["text"]},
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"limit": {"context": 128000, "output": 8192},
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},
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},
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},
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"anthropic": {
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"id": "anthropic",
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"models": {
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"claude-sonnet-4": {
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"id": "claude-sonnet-4",
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"attachment": True,
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"tool_call": True,
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"limit": {"context": 200000, "output": 64000},
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},
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},
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},
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}
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class TestGetModelCapabilities:
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"""Tests for get_model_capabilities vision detection."""
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def test_vision_from_attachment_flag(self):
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"""Models with attachment=True and no modalities should report supports_vision=True."""
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with patch("agent.models_dev.fetch_models_dev", return_value=CAPS_REGISTRY):
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caps = get_model_capabilities("anthropic", "claude-sonnet-4")
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assert caps is not None
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assert caps.supports_vision is True
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def test_vision_from_modalities_input_image(self):
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"""Models with 'image' in modalities.input but attachment=False should
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still report supports_vision=True (the core fix in this PR)."""
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with patch("agent.models_dev.fetch_models_dev", return_value=CAPS_REGISTRY):
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caps = get_model_capabilities("google", "gemma-4-31b-it")
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assert caps is not None
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assert caps.supports_vision is True
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def test_text_only_modalities_override_stale_attachment_flag(self):
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"""Text-only modalities must win over stale attachment=True metadata."""
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with patch("agent.models_dev.fetch_models_dev", return_value=CAPS_REGISTRY):
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caps = get_model_capabilities("google", "text-only-with-stale-attachment")
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assert caps is not None
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assert caps.supports_vision is False
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def test_no_vision_without_attachment_or_modalities(self):
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"""Models with neither attachment nor image modality should be non-vision."""
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with patch("agent.models_dev.fetch_models_dev", return_value=CAPS_REGISTRY):
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caps = get_model_capabilities("google", "gemma-3-1b")
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assert caps is not None
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assert caps.supports_vision is False
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def test_modalities_non_dict_handled(self):
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"""Non-dict modalities field should not crash."""
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registry = {
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"google": {"id": "google", "models": {
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"weird-model": {
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"id": "weird-model",
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"modalities": "text", # not a dict
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"limit": {"context": 200000, "output": 8192},
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},
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}},
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}
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with patch("agent.models_dev.fetch_models_dev", return_value=registry):
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caps = get_model_capabilities("gemini", "weird-model")
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assert caps is not None
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assert caps.supports_vision is False
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def test_model_not_found_returns_none(self):
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"""Unknown model should return None."""
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with patch("agent.models_dev.fetch_models_dev", return_value=CAPS_REGISTRY):
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caps = get_model_capabilities("anthropic", "nonexistent-model")
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assert caps is None
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