Compare commits
1 Commits
| Author | SHA1 | Date | |
|---|---|---|---|
|
eeed075974 |
69
agent/context_snapshots.py
Normal file
69
agent/context_snapshots.py
Normal file
@@ -0,0 +1,69 @@
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"""First-class context snapshot artifacts for live runtime memory evaluation."""
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from __future__ import annotations
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import json
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import re
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from pathlib import Path
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from typing import Any
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from hermes_constants import get_hermes_home
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_SAFE_SEGMENT_RE = re.compile(r"[^A-Za-z0-9_.-]+")
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class ContextSnapshotRecorder:
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"""Write per-call prompt-composition artifacts for a Hermes session."""
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def __init__(self, session_id: str, *, enabled: bool = False, base_dir: str | Path | None = None):
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self.session_id = session_id or "session"
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self.enabled = bool(enabled)
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self.base_dir = Path(base_dir) if base_dir else get_hermes_home() / "reports" / "context_snapshots"
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@property
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def session_dir(self) -> Path:
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safe_session = _SAFE_SEGMENT_RE.sub("_", self.session_id).strip("._") or "session"
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return self.base_dir / safe_session
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def record_call(
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self,
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api_call_count: int,
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*,
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system_prompt: str,
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memory_provider_system_prompt: str = "",
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memory_prefetch_raw: str = "",
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memory_context_block: str = "",
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api_user_message: str = "",
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api_messages: list[dict[str, Any]] | None = None,
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metadata: dict[str, Any] | None = None,
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) -> Path | None:
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if not self.enabled:
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return None
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call_dir = self.session_dir / f"call_{api_call_count:03d}"
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call_dir.mkdir(parents=True, exist_ok=True)
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self._write_text(call_dir / "system_prompt.txt", system_prompt or "")
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self._write_text(call_dir / "memory_provider_system_prompt.txt", memory_provider_system_prompt or "")
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self._write_text(call_dir / "memory_prefetch_raw.txt", memory_prefetch_raw or "")
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self._write_text(call_dir / "memory_context_block.txt", memory_context_block or "")
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self._write_text(call_dir / "api_user_message.txt", api_user_message or "")
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self._write_json(call_dir / "api_messages.json", api_messages or [])
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self._write_json(
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call_dir / "metadata.json",
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{
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"session_id": self.session_id,
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"api_call_count": api_call_count,
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**(metadata or {}),
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},
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)
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return call_dir
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@staticmethod
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def _write_text(path: Path, content: str) -> None:
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path.write_text(content, encoding="utf-8")
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@staticmethod
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def _write_json(path: Path, payload: Any) -> None:
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path.write_text(json.dumps(payload, indent=2, ensure_ascii=False), encoding="utf-8")
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@@ -1,757 +1,194 @@
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[
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{
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"id": "screenshot_github_mark",
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"id": "screenshot_github_home",
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"url": "https://github.githubassets.com/images/modules/logos_page/GitHub-Mark.png",
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"category": "screenshot",
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"expected_keywords": [
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"github",
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"logo",
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"mark"
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],
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"expected_keywords": ["github", "logo", "mark"],
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"ground_truth_ocr": "",
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"expected_structure": {
|
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"min_length": 30,
|
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"min_sentences": 1,
|
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"has_numbers": false
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}
|
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"expected_structure": {"min_length": 30, "min_sentences": 1, "has_numbers": false}
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},
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{
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"id": "screenshot_github_social",
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"url": "https://github.githubassets.com/images/modules/site/social-cards.png",
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"category": "screenshot",
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"expected_keywords": [
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"github",
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"page",
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"web"
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],
|
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"ground_truth_ocr": "",
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"expected_structure": {
|
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"min_length": 30,
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"min_sentences": 1,
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"has_numbers": false
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}
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},
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{
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"id": "screenshot_github_code_search",
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"url": "https://github.githubassets.com/images/modules/site/features-code-search.png",
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"category": "screenshot",
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"expected_keywords": [
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"search",
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"code",
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"feature"
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],
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"ground_truth_ocr": "",
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"expected_structure": {
|
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"min_length": 30,
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"min_sentences": 1,
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"has_numbers": false
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}
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},
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{
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"id": "screenshot_terminal_capture",
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"url": "https://raw.githubusercontent.com/nicehash/nicehash-quick-start/main/images/nicehash-terminal.png",
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"category": "screenshot",
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"expected_keywords": [
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"terminal",
|
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"command",
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"output"
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],
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"ground_truth_ocr": "",
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"expected_structure": {
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"min_length": 30,
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"min_sentences": 1,
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"has_numbers": false
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}
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},
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{
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"id": "screenshot_http_404",
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"url": "https://http.cat/404.jpg",
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"category": "screenshot",
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"expected_keywords": [
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"404",
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"error",
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"cat"
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],
|
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"ground_truth_ocr": "",
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"expected_structure": {
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"min_length": 30,
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"min_sentences": 1,
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"has_numbers": false
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}
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},
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{
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"id": "screenshot_dummy_cli_01",
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"url": "https://dummyimage.com/1280x720/111827/f9fafb.png&text=Hermes+CLI+Session+01",
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"category": "screenshot",
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"expected_keywords": [
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"hermes",
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"cli",
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"session"
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],
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"ground_truth_ocr": "",
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"expected_structure": {
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"min_length": 30,
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"min_sentences": 1,
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"has_numbers": false
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}
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},
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{
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"id": "screenshot_dummy_cli_02",
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"url": "https://dummyimage.com/1280x720/0f172a/e2e8f0.png&text=Prompt+Cache+Dashboard",
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"category": "screenshot",
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"expected_keywords": [
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"prompt",
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"cache",
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"dashboard"
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],
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"ground_truth_ocr": "",
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"expected_structure": {
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"min_length": 30,
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"min_sentences": 1,
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"has_numbers": false
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}
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},
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{
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"id": "screenshot_dummy_ui_01",
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"url": "https://dummyimage.com/1280x720/1f2937/f3f4f6.png&text=Settings+Panel+Voice+Mode",
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"category": "screenshot",
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"expected_keywords": [
|
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"settings",
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"voice",
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"mode"
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],
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"ground_truth_ocr": "",
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"expected_structure": {
|
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"min_length": 30,
|
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"min_sentences": 1,
|
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"has_numbers": false
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}
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},
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{
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"id": "screenshot_dummy_ui_02",
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"url": "https://dummyimage.com/1280x720/334155/f8fafc.png&text=Browser+Vision+Preview",
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"category": "screenshot",
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"expected_keywords": [
|
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"browser",
|
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"vision",
|
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"preview"
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],
|
||||
"ground_truth_ocr": "",
|
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"expected_structure": {
|
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"min_length": 30,
|
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"min_sentences": 1,
|
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"has_numbers": false
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}
|
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},
|
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{
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"id": "screenshot_dummy_ui_03",
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"url": "https://dummyimage.com/1280x720/111827/ffffff.png&text=Tool+Call+Inspector",
|
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"category": "screenshot",
|
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"expected_keywords": [
|
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"tool",
|
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"call",
|
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"inspector"
|
||||
],
|
||||
"ground_truth_ocr": "",
|
||||
"expected_structure": {
|
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"min_length": 30,
|
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"min_sentences": 1,
|
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"has_numbers": false
|
||||
}
|
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},
|
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{
|
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"id": "diagram_flow_a",
|
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"url": "https://dummyimage.com/1200x800/f8fafc/0f172a.png&text=Flowchart+API+Gateway+Queue+Worker",
|
||||
"id": "diagram_mermaid_flow",
|
||||
"url": "https://mermaid.ink/img/pako:eNpdkE9PwzAMxb-K5VOl7gc7sAOIIDuAw9gptnRaSJLSJttQStmXs9LCH-ymBOI1ef_42U6cUSae4IkDxbAAWtB6siSZXVhjQTlgl1nigHg5fRBOzSfebopROCu_cytObSfgLSE1ANOeZWkO2IH5upZxYot8m1hqAdpD_63WRl0xdUG1jdl9kPiOb_EWk2JBtPaiKkF4eVIYgO0EtkW-RSgC4gJ6HJYRG1UNdN0HNVd0Bftjj7X8P92qPj-F8l8T3w",
|
||||
"category": "diagram",
|
||||
"expected_keywords": [
|
||||
"flowchart",
|
||||
"api",
|
||||
"worker"
|
||||
],
|
||||
"expected_keywords": ["flow", "diagram", "process"],
|
||||
"ground_truth_ocr": "",
|
||||
"expected_structure": {
|
||||
"min_length": 50,
|
||||
"min_sentences": 2,
|
||||
"has_numbers": false
|
||||
}
|
||||
"expected_structure": {"min_length": 50, "min_sentences": 2, "has_numbers": false}
|
||||
},
|
||||
{
|
||||
"id": "diagram_flow_b",
|
||||
"url": "https://dummyimage.com/1200x800/f1f5f9/0f172a.png&text=Architecture+Diagram+Database+Cache+Client",
|
||||
"category": "diagram",
|
||||
"expected_keywords": [
|
||||
"architecture",
|
||||
"diagram",
|
||||
"cache"
|
||||
],
|
||||
"id": "photo_random_1",
|
||||
"url": "https://picsum.photos/seed/vision1/400/300",
|
||||
"category": "photo",
|
||||
"expected_keywords": [],
|
||||
"ground_truth_ocr": "",
|
||||
"expected_structure": {
|
||||
"min_length": 50,
|
||||
"min_sentences": 2,
|
||||
"has_numbers": false
|
||||
}
|
||||
"expected_structure": {"min_length": 30, "min_sentences": 1, "has_numbers": false}
|
||||
},
|
||||
{
|
||||
"id": "diagram_uml_a",
|
||||
"url": "https://dummyimage.com/1200x800/e2e8f0/0f172a.png&text=Class+Diagram+User+Session+Message",
|
||||
"category": "diagram",
|
||||
"expected_keywords": [
|
||||
"class",
|
||||
"diagram",
|
||||
"session"
|
||||
],
|
||||
"id": "photo_random_2",
|
||||
"url": "https://picsum.photos/seed/vision2/400/300",
|
||||
"category": "photo",
|
||||
"expected_keywords": [],
|
||||
"ground_truth_ocr": "",
|
||||
"expected_structure": {
|
||||
"min_length": 50,
|
||||
"min_sentences": 2,
|
||||
"has_numbers": false
|
||||
}
|
||||
"expected_structure": {"min_length": 30, "min_sentences": 1, "has_numbers": false}
|
||||
},
|
||||
{
|
||||
"id": "diagram_uml_b",
|
||||
"url": "https://dummyimage.com/1200x800/cbd5e1/0f172a.png&text=Sequence+Diagram+Request+Response",
|
||||
"category": "diagram",
|
||||
"expected_keywords": [
|
||||
"sequence",
|
||||
"diagram",
|
||||
"response"
|
||||
],
|
||||
"id": "chart_simple_bar",
|
||||
"url": "https://quickchart.io/chart?c={type:'bar',data:{labels:['Q1','Q2','Q3','Q4'],datasets:[{label:'Revenue',data:[100,150,200,250]}]}}",
|
||||
"category": "chart",
|
||||
"expected_keywords": ["bar", "chart", "revenue"],
|
||||
"ground_truth_ocr": "",
|
||||
"expected_structure": {
|
||||
"min_length": 50,
|
||||
"min_sentences": 2,
|
||||
"has_numbers": false
|
||||
}
|
||||
"expected_structure": {"min_length": 50, "min_sentences": 2, "has_numbers": true}
|
||||
},
|
||||
{
|
||||
"id": "diagram_network_a",
|
||||
"url": "https://dummyimage.com/1200x800/ffffff/111827.png&text=Network+Nodes+Edges+Router",
|
||||
"category": "diagram",
|
||||
"expected_keywords": [
|
||||
"network",
|
||||
"node",
|
||||
"router"
|
||||
],
|
||||
"id": "chart_pie",
|
||||
"url": "https://quickchart.io/chart?c={type:'pie',data:{labels:['A','B','C'],datasets:[{data:[30,50,20]}]}}",
|
||||
"category": "chart",
|
||||
"expected_keywords": ["pie", "chart", "percentage"],
|
||||
"ground_truth_ocr": "",
|
||||
"expected_structure": {
|
||||
"min_length": 50,
|
||||
"min_sentences": 2,
|
||||
"has_numbers": false
|
||||
}
|
||||
},
|
||||
{
|
||||
"id": "diagram_network_b",
|
||||
"url": "https://dummyimage.com/1200x800/ffffff/1e293b.png&text=Service+Mesh+Proxy+Auth",
|
||||
"category": "diagram",
|
||||
"expected_keywords": [
|
||||
"service",
|
||||
"mesh",
|
||||
"auth"
|
||||
],
|
||||
"ground_truth_ocr": "",
|
||||
"expected_structure": {
|
||||
"min_length": 50,
|
||||
"min_sentences": 2,
|
||||
"has_numbers": false
|
||||
}
|
||||
},
|
||||
{
|
||||
"id": "diagram_state_machine",
|
||||
"url": "https://dummyimage.com/1200x800/f8fafc/334155.png&text=State+Machine+Idle+Run+Stop",
|
||||
"category": "diagram",
|
||||
"expected_keywords": [
|
||||
"state",
|
||||
"machine",
|
||||
"idle"
|
||||
],
|
||||
"ground_truth_ocr": "",
|
||||
"expected_structure": {
|
||||
"min_length": 50,
|
||||
"min_sentences": 2,
|
||||
"has_numbers": false
|
||||
}
|
||||
},
|
||||
{
|
||||
"id": "diagram_mind_map",
|
||||
"url": "https://dummyimage.com/1200x800/fefce8/1f2937.png&text=Mind+Map+Memory+Recall+Tools",
|
||||
"category": "diagram",
|
||||
"expected_keywords": [
|
||||
"mind",
|
||||
"memory",
|
||||
"tools"
|
||||
],
|
||||
"ground_truth_ocr": "",
|
||||
"expected_structure": {
|
||||
"min_length": 50,
|
||||
"min_sentences": 2,
|
||||
"has_numbers": false
|
||||
}
|
||||
},
|
||||
{
|
||||
"id": "diagram_pipeline",
|
||||
"url": "https://dummyimage.com/1200x800/ecfeff/155e75.png&text=Pipeline+Ingest+Rank+Summarize",
|
||||
"category": "diagram",
|
||||
"expected_keywords": [
|
||||
"pipeline",
|
||||
"ingest",
|
||||
"summarize"
|
||||
],
|
||||
"ground_truth_ocr": "",
|
||||
"expected_structure": {
|
||||
"min_length": 50,
|
||||
"min_sentences": 2,
|
||||
"has_numbers": false
|
||||
}
|
||||
"expected_structure": {"min_length": 50, "min_sentences": 2, "has_numbers": true}
|
||||
},
|
||||
{
|
||||
"id": "diagram_org_chart",
|
||||
"url": "https://dummyimage.com/1200x800/fdf2f8/831843.png&text=Org+Chart+Lead+Review+Ops",
|
||||
"url": "https://mermaid.ink/img/pako:eNpdkE9PwzAMxb-K5VOl7gc7sAOIIDuAw9gptnRaSJLSJttQStmXs9LCH-ymBOI1ef_42U6cUSae4IkDxbAAWtB6iuyIWyrLgXLALrPEAfFy-iCcmk-83RSjcFZ-51ac2k7AW0JqAKY9y9IcsAPzdS3jxBb5NrHUAraH_lutjbpi6oJqG7P7IPEd3-ItJsWCaO1FVYLw8qQwANsJbIt8i1AExAX0OCwjNqoa6LoPaq7oCvbHHmv5f7pVfX4K5b8mvg",
|
||||
"category": "diagram",
|
||||
"expected_keywords": [
|
||||
"org",
|
||||
"chart",
|
||||
"review"
|
||||
],
|
||||
"expected_keywords": ["organization", "hierarchy", "chart"],
|
||||
"ground_truth_ocr": "",
|
||||
"expected_structure": {
|
||||
"min_length": 50,
|
||||
"min_sentences": 2,
|
||||
"has_numbers": false
|
||||
}
|
||||
"expected_structure": {"min_length": 50, "min_sentences": 2, "has_numbers": false}
|
||||
},
|
||||
{
|
||||
"id": "photo_random_01",
|
||||
"url": "https://picsum.photos/seed/vision-bench-1/640/480",
|
||||
"id": "screenshot_terminal",
|
||||
"url": "https://raw.githubusercontent.com/nicehash/nicehash-quick-start/main/images/nicehash-terminal.png",
|
||||
"category": "screenshot",
|
||||
"expected_keywords": ["terminal", "command", "output"],
|
||||
"ground_truth_ocr": "",
|
||||
"expected_structure": {"min_length": 30, "min_sentences": 1, "has_numbers": false}
|
||||
},
|
||||
{
|
||||
"id": "photo_random_3",
|
||||
"url": "https://picsum.photos/seed/vision3/400/300",
|
||||
"category": "photo",
|
||||
"expected_keywords": [],
|
||||
"ground_truth_ocr": "",
|
||||
"expected_structure": {
|
||||
"min_length": 30,
|
||||
"min_sentences": 1,
|
||||
"has_numbers": false
|
||||
}
|
||||
"expected_structure": {"min_length": 30, "min_sentences": 1, "has_numbers": false}
|
||||
},
|
||||
{
|
||||
"id": "photo_random_02",
|
||||
"url": "https://picsum.photos/seed/vision-bench-2/640/480",
|
||||
"category": "photo",
|
||||
"expected_keywords": [],
|
||||
"ground_truth_ocr": "",
|
||||
"expected_structure": {
|
||||
"min_length": 30,
|
||||
"min_sentences": 1,
|
||||
"has_numbers": false
|
||||
}
|
||||
},
|
||||
{
|
||||
"id": "photo_random_03",
|
||||
"url": "https://picsum.photos/seed/vision-bench-3/640/480",
|
||||
"category": "photo",
|
||||
"expected_keywords": [],
|
||||
"ground_truth_ocr": "",
|
||||
"expected_structure": {
|
||||
"min_length": 30,
|
||||
"min_sentences": 1,
|
||||
"has_numbers": false
|
||||
}
|
||||
},
|
||||
{
|
||||
"id": "photo_random_04",
|
||||
"url": "https://picsum.photos/seed/vision-bench-4/640/480",
|
||||
"category": "photo",
|
||||
"expected_keywords": [],
|
||||
"ground_truth_ocr": "",
|
||||
"expected_structure": {
|
||||
"min_length": 30,
|
||||
"min_sentences": 1,
|
||||
"has_numbers": false
|
||||
}
|
||||
},
|
||||
{
|
||||
"id": "photo_random_05",
|
||||
"url": "https://picsum.photos/seed/vision-bench-5/640/480",
|
||||
"category": "photo",
|
||||
"expected_keywords": [],
|
||||
"ground_truth_ocr": "",
|
||||
"expected_structure": {
|
||||
"min_length": 30,
|
||||
"min_sentences": 1,
|
||||
"has_numbers": false
|
||||
}
|
||||
},
|
||||
{
|
||||
"id": "photo_random_06",
|
||||
"url": "https://picsum.photos/seed/vision-bench-6/640/480",
|
||||
"category": "photo",
|
||||
"expected_keywords": [],
|
||||
"ground_truth_ocr": "",
|
||||
"expected_structure": {
|
||||
"min_length": 30,
|
||||
"min_sentences": 1,
|
||||
"has_numbers": false
|
||||
}
|
||||
},
|
||||
{
|
||||
"id": "photo_random_07",
|
||||
"url": "https://picsum.photos/seed/vision-bench-7/640/480",
|
||||
"category": "photo",
|
||||
"expected_keywords": [],
|
||||
"ground_truth_ocr": "",
|
||||
"expected_structure": {
|
||||
"min_length": 30,
|
||||
"min_sentences": 1,
|
||||
"has_numbers": false
|
||||
}
|
||||
},
|
||||
{
|
||||
"id": "photo_random_08",
|
||||
"url": "https://picsum.photos/seed/vision-bench-8/640/480",
|
||||
"category": "photo",
|
||||
"expected_keywords": [],
|
||||
"ground_truth_ocr": "",
|
||||
"expected_structure": {
|
||||
"min_length": 30,
|
||||
"min_sentences": 1,
|
||||
"has_numbers": false
|
||||
}
|
||||
},
|
||||
{
|
||||
"id": "photo_random_09",
|
||||
"url": "https://picsum.photos/seed/vision-bench-9/640/480",
|
||||
"category": "photo",
|
||||
"expected_keywords": [],
|
||||
"ground_truth_ocr": "",
|
||||
"expected_structure": {
|
||||
"min_length": 30,
|
||||
"min_sentences": 1,
|
||||
"has_numbers": false
|
||||
}
|
||||
},
|
||||
{
|
||||
"id": "photo_random_10",
|
||||
"url": "https://picsum.photos/seed/vision-bench-10/640/480",
|
||||
"category": "photo",
|
||||
"expected_keywords": [],
|
||||
"ground_truth_ocr": "",
|
||||
"expected_structure": {
|
||||
"min_length": 30,
|
||||
"min_sentences": 1,
|
||||
"has_numbers": false
|
||||
}
|
||||
},
|
||||
{
|
||||
"id": "chart_bar_quarterly",
|
||||
"url": "https://quickchart.io/chart?c={type:'bar',data:{labels:['Q1','Q2','Q3','Q4'],datasets:[{label:'Revenue',data:[100,150,200,250]}]}}",
|
||||
"category": "chart",
|
||||
"expected_keywords": [
|
||||
"bar",
|
||||
"chart",
|
||||
"revenue"
|
||||
],
|
||||
"ground_truth_ocr": "",
|
||||
"expected_structure": {
|
||||
"min_length": 50,
|
||||
"min_sentences": 2,
|
||||
"has_numbers": true
|
||||
}
|
||||
},
|
||||
{
|
||||
"id": "chart_pie_market",
|
||||
"url": "https://quickchart.io/chart?c={type:'pie',data:{labels:['A','B','C'],datasets:[{data:[30,50,20]}]}}",
|
||||
"category": "chart",
|
||||
"expected_keywords": [
|
||||
"pie",
|
||||
"chart",
|
||||
"percentage"
|
||||
],
|
||||
"ground_truth_ocr": "",
|
||||
"expected_structure": {
|
||||
"min_length": 50,
|
||||
"min_sentences": 2,
|
||||
"has_numbers": true
|
||||
}
|
||||
},
|
||||
{
|
||||
"id": "chart_line_temp",
|
||||
"id": "chart_line",
|
||||
"url": "https://quickchart.io/chart?c={type:'line',data:{labels:['Jan','Feb','Mar','Apr'],datasets:[{label:'Temperature',data:[5,8,12,18]}]}}",
|
||||
"category": "chart",
|
||||
"expected_keywords": [
|
||||
"line",
|
||||
"chart",
|
||||
"temperature"
|
||||
],
|
||||
"expected_keywords": ["line", "chart", "temperature"],
|
||||
"ground_truth_ocr": "",
|
||||
"expected_structure": {
|
||||
"min_length": 50,
|
||||
"min_sentences": 2,
|
||||
"has_numbers": true
|
||||
}
|
||||
"expected_structure": {"min_length": 50, "min_sentences": 2, "has_numbers": true}
|
||||
},
|
||||
{
|
||||
"id": "chart_radar_skill",
|
||||
"id": "diagram_sequence",
|
||||
"url": "https://mermaid.ink/img/pako:eNpdkE9PwzAMxb-K5VOl7gc7sAOIIDuAw9gptnRaSJLSJttQStmXs9LCH-ymBOI1ef_42U6cUSae4IkDxbAAWtB6iuyIWyrLgXLALrPEAfFy-iCcmk-83RSjcFZ-51ac2k7AW0JqAKY9y9IcsAPzdS3jxBb5NrHUAraH_lutjbpi6oJqG7P7IPEd3-ItJsWCaO1FVYLw8qQwANsJbIt8i1AExAX0OCwjNqoa6LoPaq7oCvbHHmv5f7pVfX4K5b8mvg",
|
||||
"category": "diagram",
|
||||
"expected_keywords": ["sequence", "interaction", "message"],
|
||||
"ground_truth_ocr": "",
|
||||
"expected_structure": {"min_length": 50, "min_sentences": 2, "has_numbers": false}
|
||||
},
|
||||
{
|
||||
"id": "photo_random_4",
|
||||
"url": "https://picsum.photos/seed/vision4/400/300",
|
||||
"category": "photo",
|
||||
"expected_keywords": [],
|
||||
"ground_truth_ocr": "",
|
||||
"expected_structure": {"min_length": 30, "min_sentences": 1, "has_numbers": false}
|
||||
},
|
||||
{
|
||||
"id": "screenshot_webpage",
|
||||
"url": "https://github.githubassets.com/images/modules/site/social-cards.png",
|
||||
"category": "screenshot",
|
||||
"expected_keywords": ["github", "page", "web"],
|
||||
"ground_truth_ocr": "",
|
||||
"expected_structure": {"min_length": 30, "min_sentences": 1, "has_numbers": false}
|
||||
},
|
||||
{
|
||||
"id": "chart_radar",
|
||||
"url": "https://quickchart.io/chart?c={type:'radar',data:{labels:['Speed','Power','Defense','Magic'],datasets:[{label:'Hero',data:[80,60,70,90]}]}}",
|
||||
"category": "chart",
|
||||
"expected_keywords": [
|
||||
"radar",
|
||||
"chart",
|
||||
"skill"
|
||||
],
|
||||
"expected_keywords": ["radar", "chart", "skill"],
|
||||
"ground_truth_ocr": "",
|
||||
"expected_structure": {
|
||||
"min_length": 50,
|
||||
"min_sentences": 2,
|
||||
"has_numbers": true
|
||||
}
|
||||
"expected_structure": {"min_length": 50, "min_sentences": 2, "has_numbers": true}
|
||||
},
|
||||
{
|
||||
"id": "chart_stacked_cloud",
|
||||
"url": "https://quickchart.io/chart?c={type:'bar',data:{labels:['2022','2023','2024'],datasets:[{label:'Cloud',data:[100,150,200]},{label:'On-prem',data:[200,180,160]}]},options:{scales:{x:{stacked:true},y:{stacked:true}}}}",
|
||||
"category": "chart",
|
||||
"expected_keywords": [
|
||||
"stacked",
|
||||
"bar",
|
||||
"chart"
|
||||
],
|
||||
"id": "photo_random_5",
|
||||
"url": "https://picsum.photos/seed/vision5/400/300",
|
||||
"category": "photo",
|
||||
"expected_keywords": [],
|
||||
"ground_truth_ocr": "",
|
||||
"expected_structure": {
|
||||
"min_length": 50,
|
||||
"min_sentences": 2,
|
||||
"has_numbers": true
|
||||
}
|
||||
"expected_structure": {"min_length": 30, "min_sentences": 1, "has_numbers": false}
|
||||
},
|
||||
{
|
||||
"id": "chart_area_growth",
|
||||
"url": "https://quickchart.io/chart?c={type:'line',data:{labels:['W1','W2','W3','W4'],datasets:[{label:'Growth',data:[10,15,18,24],fill:true}]}}",
|
||||
"category": "chart",
|
||||
"expected_keywords": [
|
||||
"line",
|
||||
"growth",
|
||||
"chart"
|
||||
],
|
||||
"id": "diagram_class",
|
||||
"url": "https://mermaid.ink/img/pako:eNpdkE9PwzAMxb-K5VOl7gc7sAOIIDuAw9gptnRaSJLSJttQStmXs9LCH-ymBOI1ef_42U6cUSae4IkDxbAAWtB6iuyIWyrLgXLALrPEAfFy-iCcmk-83RSjcFZ-51ac2k7AW0JqAKY9y9IcsAPzdS3jxBb5NrHUAraH_lutjbpi6oJqG7P7IPEd3-ItJsWCaO1FVYLw8qQwANsJbIt8i1AExAX0OCwjNqoa6LoPaq7oCvbHHmv5f7pVfX4K5b8mvg",
|
||||
"category": "diagram",
|
||||
"expected_keywords": ["class", "object", "attribute"],
|
||||
"ground_truth_ocr": "",
|
||||
"expected_structure": {
|
||||
"min_length": 50,
|
||||
"min_sentences": 2,
|
||||
"has_numbers": true
|
||||
}
|
||||
"expected_structure": {"min_length": 50, "min_sentences": 2, "has_numbers": false}
|
||||
},
|
||||
{
|
||||
"id": "chart_scatter_eval",
|
||||
"url": "https://quickchart.io/chart?c={type:'scatter',data:{datasets:[{label:'Runs',data:[{x:1,y:70},{x:2,y:75},{x:3,y:82}]}]}}",
|
||||
"category": "chart",
|
||||
"expected_keywords": [
|
||||
"scatter",
|
||||
"chart",
|
||||
"runs"
|
||||
],
|
||||
"ground_truth_ocr": "",
|
||||
"expected_structure": {
|
||||
"min_length": 50,
|
||||
"min_sentences": 2,
|
||||
"has_numbers": true
|
||||
}
|
||||
},
|
||||
{
|
||||
"id": "chart_horizontal_bar",
|
||||
"url": "https://quickchart.io/chart?c={type:'bar',data:{labels:['UI','OCR','Docs'],datasets:[{label:'Score',data:[88,76,91]}]},options:{indexAxis:'y'}}",
|
||||
"category": "chart",
|
||||
"expected_keywords": [
|
||||
"bar",
|
||||
"score",
|
||||
"ocr"
|
||||
],
|
||||
"ground_truth_ocr": "",
|
||||
"expected_structure": {
|
||||
"min_length": 50,
|
||||
"min_sentences": 2,
|
||||
"has_numbers": true
|
||||
}
|
||||
},
|
||||
{
|
||||
"id": "chart_bubble_usage",
|
||||
"url": "https://quickchart.io/chart?c={type:'bubble',data:{datasets:[{label:'Latency',data:[{x:1,y:120,r:8},{x:2,y:95,r:6},{x:3,y:180,r:10}]}]}}",
|
||||
"category": "chart",
|
||||
"expected_keywords": [
|
||||
"bubble",
|
||||
"latency",
|
||||
"chart"
|
||||
],
|
||||
"ground_truth_ocr": "",
|
||||
"expected_structure": {
|
||||
"min_length": 50,
|
||||
"min_sentences": 2,
|
||||
"has_numbers": true
|
||||
}
|
||||
},
|
||||
{
|
||||
"id": "chart_doughnut_devices",
|
||||
"id": "chart_doughnut",
|
||||
"url": "https://quickchart.io/chart?c={type:'doughnut',data:{labels:['Desktop','Mobile','Tablet'],datasets:[{data:[60,30,10]}]}}",
|
||||
"category": "chart",
|
||||
"expected_keywords": [
|
||||
"doughnut",
|
||||
"chart",
|
||||
"device"
|
||||
],
|
||||
"expected_keywords": ["doughnut", "chart", "device"],
|
||||
"ground_truth_ocr": "",
|
||||
"expected_structure": {
|
||||
"min_length": 50,
|
||||
"min_sentences": 2,
|
||||
"has_numbers": true
|
||||
}
|
||||
"expected_structure": {"min_length": 50, "min_sentences": 2, "has_numbers": true}
|
||||
},
|
||||
{
|
||||
"id": "ocr_text_01",
|
||||
"url": "https://dummyimage.com/1200x320/ffffff/000000.png&text=Hermes+OCR+Alpha+01",
|
||||
"category": "ocr",
|
||||
"expected_keywords": [
|
||||
"hermes",
|
||||
"ocr"
|
||||
],
|
||||
"ground_truth_ocr": "Hermes OCR Alpha 01",
|
||||
"expected_structure": {
|
||||
"min_length": 10,
|
||||
"min_sentences": 1,
|
||||
"has_numbers": true
|
||||
}
|
||||
"id": "photo_random_6",
|
||||
"url": "https://picsum.photos/seed/vision6/400/300",
|
||||
"category": "photo",
|
||||
"expected_keywords": [],
|
||||
"ground_truth_ocr": "",
|
||||
"expected_structure": {"min_length": 30, "min_sentences": 1, "has_numbers": false}
|
||||
},
|
||||
{
|
||||
"id": "ocr_text_02",
|
||||
"url": "https://dummyimage.com/1200x320/ffffff/000000.png&text=Prompt+Cache+Hit+87%",
|
||||
"category": "ocr",
|
||||
"expected_keywords": [
|
||||
"prompt",
|
||||
"cache"
|
||||
],
|
||||
"ground_truth_ocr": "Prompt Cache Hit 87%",
|
||||
"expected_structure": {
|
||||
"min_length": 10,
|
||||
"min_sentences": 1,
|
||||
"has_numbers": true
|
||||
}
|
||||
"id": "screenshot_error",
|
||||
"url": "https://http.cat/404.jpg",
|
||||
"category": "screenshot",
|
||||
"expected_keywords": ["404", "error", "cat"],
|
||||
"ground_truth_ocr": "",
|
||||
"expected_structure": {"min_length": 30, "min_sentences": 1, "has_numbers": true}
|
||||
},
|
||||
{
|
||||
"id": "ocr_text_03",
|
||||
"url": "https://dummyimage.com/1200x320/ffffff/000000.png&text=Session+42+Ready",
|
||||
"category": "ocr",
|
||||
"expected_keywords": [
|
||||
"session",
|
||||
"42"
|
||||
],
|
||||
"ground_truth_ocr": "Session 42 Ready",
|
||||
"expected_structure": {
|
||||
"min_length": 10,
|
||||
"min_sentences": 1,
|
||||
"has_numbers": true
|
||||
}
|
||||
"id": "diagram_network",
|
||||
"url": "https://mermaid.ink/img/pako:eNpdkE9PwzAMxb-K5VOl7gc7sAOIIDuAw9gptnRaSJLSJttQStmXs9LCH-ymBOI1ef_42U6cUSae4IkDxbAAWtB6iuyIWyrLgXLALrPEAfFy-iCcmk-83RSjcFZ-51ac2k7AW0JqAKY9y9IcsAPzdS3jxBb5NrHUAraH_lutjbpi6oJqG7P7IPEd3-ItJsWCaO1FVYLw8qQwANsJbIt8i1AExAX0OCwjNqoa6LoPaq7oCvbHHmv5f7pVfX4K5b8mvg",
|
||||
"category": "diagram",
|
||||
"expected_keywords": ["network", "node", "connection"],
|
||||
"ground_truth_ocr": "",
|
||||
"expected_structure": {"min_length": 50, "min_sentences": 2, "has_numbers": false}
|
||||
},
|
||||
{
|
||||
"id": "ocr_text_04",
|
||||
"url": "https://dummyimage.com/1200x320/ffffff/000000.png&text=Latency+118+ms",
|
||||
"category": "ocr",
|
||||
"expected_keywords": [
|
||||
"latency",
|
||||
"118"
|
||||
],
|
||||
"ground_truth_ocr": "Latency 118 ms",
|
||||
"expected_structure": {
|
||||
"min_length": 10,
|
||||
"min_sentences": 1,
|
||||
"has_numbers": true
|
||||
}
|
||||
"id": "photo_random_7",
|
||||
"url": "https://picsum.photos/seed/vision7/400/300",
|
||||
"category": "photo",
|
||||
"expected_keywords": [],
|
||||
"ground_truth_ocr": "",
|
||||
"expected_structure": {"min_length": 30, "min_sentences": 1, "has_numbers": false}
|
||||
},
|
||||
{
|
||||
"id": "ocr_text_05",
|
||||
"url": "https://dummyimage.com/1200x320/ffffff/000000.png&text=Voice+Mode+Enabled",
|
||||
"category": "ocr",
|
||||
"expected_keywords": [
|
||||
"voice",
|
||||
"mode"
|
||||
],
|
||||
"ground_truth_ocr": "Voice Mode Enabled",
|
||||
"expected_structure": {
|
||||
"min_length": 10,
|
||||
"min_sentences": 1,
|
||||
"has_numbers": false
|
||||
}
|
||||
"id": "chart_stacked_bar",
|
||||
"url": "https://quickchart.io/chart?c={type:'bar',data:{labels:['2022','2023','2024'],datasets:[{label:'Cloud',data:[100,150,200]},{label:'On-prem',data:[200,180,160]}]},options:{scales:{x:{stacked:true},y:{stacked:true}}}}",
|
||||
"category": "chart",
|
||||
"expected_keywords": ["stacked", "bar", "chart"],
|
||||
"ground_truth_ocr": "",
|
||||
"expected_structure": {"min_length": 50, "min_sentences": 2, "has_numbers": true}
|
||||
},
|
||||
{
|
||||
"id": "document_text_01",
|
||||
"url": "https://dummyimage.com/1400x900/f8fafc/0f172a.png&text=Invoice+1001+Total+42+Due+2026-04-22",
|
||||
"category": "document",
|
||||
"expected_keywords": [
|
||||
"invoice",
|
||||
"1001",
|
||||
"total"
|
||||
],
|
||||
"ground_truth_ocr": "Invoice 1001 Total 42 Due 2026-04-22",
|
||||
"expected_structure": {
|
||||
"min_length": 20,
|
||||
"min_sentences": 1,
|
||||
"has_numbers": true
|
||||
}
|
||||
"id": "screenshot_dashboard",
|
||||
"url": "https://github.githubassets.com/images/modules/site/features-code-search.png",
|
||||
"category": "screenshot",
|
||||
"expected_keywords": ["search", "code", "feature"],
|
||||
"ground_truth_ocr": "",
|
||||
"expected_structure": {"min_length": 30, "min_sentences": 1, "has_numbers": false}
|
||||
},
|
||||
{
|
||||
"id": "document_text_02",
|
||||
"url": "https://dummyimage.com/1400x900/f8fafc/0f172a.png&text=Form+A+Name+Alice+Status+Approved",
|
||||
"category": "document",
|
||||
"expected_keywords": [
|
||||
"form",
|
||||
"a",
|
||||
"name"
|
||||
],
|
||||
"ground_truth_ocr": "Form A Name Alice Status Approved",
|
||||
"expected_structure": {
|
||||
"min_length": 20,
|
||||
"min_sentences": 1,
|
||||
"has_numbers": false
|
||||
}
|
||||
},
|
||||
{
|
||||
"id": "document_text_03",
|
||||
"url": "https://dummyimage.com/1400x900/f8fafc/0f172a.png&text=Report+Memory+Recall+Score+91+Percent",
|
||||
"category": "document",
|
||||
"expected_keywords": [
|
||||
"report",
|
||||
"memory",
|
||||
"recall"
|
||||
],
|
||||
"ground_truth_ocr": "Report Memory Recall Score 91 Percent",
|
||||
"expected_structure": {
|
||||
"min_length": 20,
|
||||
"min_sentences": 1,
|
||||
"has_numbers": true
|
||||
}
|
||||
},
|
||||
{
|
||||
"id": "document_text_04",
|
||||
"url": "https://dummyimage.com/1400x900/f8fafc/0f172a.png&text=Checklist+Crisis+Escalation+Call+988+Now",
|
||||
"category": "document",
|
||||
"expected_keywords": [
|
||||
"checklist",
|
||||
"crisis",
|
||||
"escalation"
|
||||
],
|
||||
"ground_truth_ocr": "Checklist Crisis Escalation Call 988 Now",
|
||||
"expected_structure": {
|
||||
"min_length": 20,
|
||||
"min_sentences": 1,
|
||||
"has_numbers": true
|
||||
}
|
||||
},
|
||||
{
|
||||
"id": "document_text_05",
|
||||
"url": "https://dummyimage.com/1400x900/f8fafc/0f172a.png&text=Meeting+Notes+Vision+Benchmark+Run+Pending",
|
||||
"category": "document",
|
||||
"expected_keywords": [
|
||||
"meeting",
|
||||
"notes",
|
||||
"vision"
|
||||
],
|
||||
"ground_truth_ocr": "Meeting Notes Vision Benchmark Run Pending",
|
||||
"expected_structure": {
|
||||
"min_length": 20,
|
||||
"min_sentences": 1,
|
||||
"has_numbers": false
|
||||
}
|
||||
"id": "photo_random_8",
|
||||
"url": "https://picsum.photos/seed/vision8/400/300",
|
||||
"category": "photo",
|
||||
"expected_keywords": [],
|
||||
"ground_truth_ocr": "",
|
||||
"expected_structure": {"min_length": 30, "min_sentences": 1, "has_numbers": false}
|
||||
}
|
||||
]
|
||||
]
|
||||
|
||||
@@ -22,12 +22,10 @@ import argparse
|
||||
import asyncio
|
||||
import base64
|
||||
import json
|
||||
import mimetypes
|
||||
import os
|
||||
import statistics
|
||||
import sys
|
||||
import time
|
||||
import urllib.request
|
||||
from datetime import datetime, timezone
|
||||
from pathlib import Path
|
||||
from typing import Any, Dict, List, Optional
|
||||
@@ -43,16 +41,12 @@ MODELS = {
|
||||
"model_id": "google/gemma-4-27b-it",
|
||||
"display_name": "Gemma 4 27B",
|
||||
"provider": "nous",
|
||||
"fallback_provider": "ollama",
|
||||
"fallback_model_id": "gemma4:latest",
|
||||
"description": "Google's multimodal Gemma 4 model",
|
||||
},
|
||||
"gemini3_flash": {
|
||||
"model_id": "google/gemini-3-flash-preview",
|
||||
"display_name": "Gemini 3 Flash Preview",
|
||||
"provider": "openrouter",
|
||||
"fallback_provider": "gemini",
|
||||
"fallback_model_id": "gemini-2.5-flash",
|
||||
"description": "Current default vision model",
|
||||
},
|
||||
}
|
||||
@@ -90,150 +84,91 @@ async def analyze_with_model(
|
||||
"""
|
||||
import httpx
|
||||
|
||||
def _load_image_bytes_cached() -> tuple[bytes, str]:
|
||||
nonlocal _image_bytes, _mime_type
|
||||
if _image_bytes is not None:
|
||||
return _image_bytes, _mime_type
|
||||
if image_url.startswith(("http://", "https://")):
|
||||
with urllib.request.urlopen(image_url, timeout=30) as resp:
|
||||
_image_bytes = resp.read()
|
||||
_mime_type = resp.headers.get_content_type() or mimetypes.guess_type(image_url)[0] or "image/png"
|
||||
else:
|
||||
path = Path(image_url).expanduser()
|
||||
_image_bytes = path.read_bytes()
|
||||
_mime_type = mimetypes.guess_type(str(path))[0] or "image/png"
|
||||
return _image_bytes, _mime_type
|
||||
|
||||
def _data_url() -> str:
|
||||
image_bytes, mime_type = _load_image_bytes_cached()
|
||||
return f"data:{mime_type};base64,{base64.b64encode(image_bytes).decode()}"
|
||||
|
||||
def _provider_key(provider: str) -> str:
|
||||
if provider == "openrouter":
|
||||
return os.getenv("OPENROUTER_API_KEY", "")
|
||||
if provider == "nous":
|
||||
return os.getenv("NOUS_API_KEY", "") or os.getenv("NOUS_INFERENCE_API_KEY", "")
|
||||
if provider == "gemini":
|
||||
return os.getenv("GEMINI_API_KEY", "") or os.getenv("GOOGLE_API_KEY", "")
|
||||
return os.getenv(f"{provider.upper()}_API_KEY", "")
|
||||
|
||||
provider = model_config["provider"]
|
||||
model_id = model_config["model_id"]
|
||||
candidates = [(provider, model_id)]
|
||||
if model_config.get("fallback_provider") and model_config.get("fallback_model_id"):
|
||||
candidates.append((model_config["fallback_provider"], model_config["fallback_model_id"]))
|
||||
|
||||
_image_bytes: Optional[bytes] = None
|
||||
_mime_type = "image/png"
|
||||
failures = []
|
||||
# Prepare messages
|
||||
messages = [
|
||||
{
|
||||
"role": "user",
|
||||
"content": [
|
||||
{"type": "text", "text": prompt},
|
||||
{"type": "image_url", "image_url": {"url": image_url}},
|
||||
],
|
||||
}
|
||||
]
|
||||
|
||||
for candidate_provider, candidate_model in candidates:
|
||||
api_key = _provider_key(candidate_provider)
|
||||
start = time.perf_counter()
|
||||
try:
|
||||
if candidate_provider in {"openrouter", "nous"}:
|
||||
api_url = (
|
||||
"https://openrouter.ai/api/v1/chat/completions"
|
||||
if candidate_provider == "openrouter"
|
||||
else "https://inference.nousresearch.com/v1/chat/completions"
|
||||
)
|
||||
if not api_key:
|
||||
raise RuntimeError(f"No API key for provider {candidate_provider}")
|
||||
payload = {
|
||||
"model": candidate_model,
|
||||
"messages": [{
|
||||
"role": "user",
|
||||
"content": [
|
||||
{"type": "text", "text": prompt},
|
||||
{"type": "image_url", "image_url": {"url": _data_url() if not image_url.startswith(("http://", "https://")) else image_url}},
|
||||
],
|
||||
}],
|
||||
"max_tokens": 2000,
|
||||
"temperature": 0.1,
|
||||
}
|
||||
headers = {
|
||||
"Authorization": f"Bearer {api_key}",
|
||||
"Content-Type": "application/json",
|
||||
}
|
||||
async with httpx.AsyncClient(timeout=timeout) as client:
|
||||
resp = await client.post(api_url, json=payload, headers=headers)
|
||||
resp.raise_for_status()
|
||||
data = resp.json()
|
||||
analysis = data.get("choices", [{}])[0].get("message", {}).get("content", "")
|
||||
usage = data.get("usage", {})
|
||||
tokens = {
|
||||
"prompt_tokens": usage.get("prompt_tokens", 0),
|
||||
"completion_tokens": usage.get("completion_tokens", 0),
|
||||
"total_tokens": usage.get("total_tokens", 0),
|
||||
}
|
||||
elif candidate_provider == "gemini":
|
||||
if not api_key:
|
||||
raise RuntimeError("No API key for provider gemini")
|
||||
image_bytes, mime_type = _load_image_bytes_cached()
|
||||
api_url = f"https://generativelanguage.googleapis.com/v1beta/models/{candidate_model}:generateContent?key={api_key}"
|
||||
payload = {
|
||||
"contents": [{"parts": [
|
||||
{"text": prompt},
|
||||
{"inline_data": {"mime_type": mime_type, "data": base64.b64encode(image_bytes).decode()}},
|
||||
]}],
|
||||
"generationConfig": {"temperature": 0.1, "maxOutputTokens": 2000},
|
||||
}
|
||||
async with httpx.AsyncClient(timeout=timeout) as client:
|
||||
resp = await client.post(api_url, json=payload)
|
||||
resp.raise_for_status()
|
||||
data = resp.json()
|
||||
parts = data.get("candidates", [{}])[0].get("content", {}).get("parts", [])
|
||||
analysis = "\n".join(part.get("text", "") for part in parts if isinstance(part, dict) and part.get("text"))
|
||||
usage = data.get("usageMetadata", {})
|
||||
tokens = {
|
||||
"prompt_tokens": usage.get("promptTokenCount", 0),
|
||||
"completion_tokens": usage.get("candidatesTokenCount", 0),
|
||||
"total_tokens": usage.get("totalTokenCount", 0),
|
||||
}
|
||||
elif candidate_provider == "ollama":
|
||||
image_bytes, _ = _load_image_bytes_cached()
|
||||
payload = {
|
||||
"model": candidate_model,
|
||||
"stream": False,
|
||||
"messages": [{"role": "user", "content": prompt, "images": [base64.b64encode(image_bytes).decode()]}],
|
||||
"options": {"temperature": 0.1},
|
||||
}
|
||||
async with httpx.AsyncClient(timeout=timeout) as client:
|
||||
resp = await client.post("http://localhost:11434/api/chat", json=payload)
|
||||
resp.raise_for_status()
|
||||
data = resp.json()
|
||||
analysis = data.get("message", {}).get("content", "")
|
||||
tokens = {
|
||||
"prompt_tokens": data.get("prompt_eval_count", 0),
|
||||
"completion_tokens": data.get("eval_count", 0),
|
||||
"total_tokens": (data.get("prompt_eval_count", 0) or 0) + (data.get("eval_count", 0) or 0),
|
||||
}
|
||||
else:
|
||||
raise RuntimeError(f"Unsupported provider {candidate_provider}")
|
||||
# Route to provider
|
||||
if provider == "openrouter":
|
||||
api_url = "https://openrouter.ai/api/v1/chat/completions"
|
||||
api_key = os.getenv("OPENROUTER_API_KEY", "")
|
||||
elif provider == "nous":
|
||||
api_url = "https://inference.nousresearch.com/v1/chat/completions"
|
||||
api_key = os.getenv("NOUS_API_KEY", "") or os.getenv("NOUS_INFERENCE_API_KEY", "")
|
||||
else:
|
||||
api_url = os.getenv(f"{provider.upper()}_API_URL", "")
|
||||
api_key = os.getenv(f"{provider.upper()}_API_KEY", "")
|
||||
|
||||
latency_ms = (time.perf_counter() - start) * 1000
|
||||
return {
|
||||
"analysis": analysis,
|
||||
"latency_ms": round(latency_ms, 1),
|
||||
"tokens": tokens,
|
||||
"success": True,
|
||||
"error": "",
|
||||
"provider_used": candidate_provider,
|
||||
"model_used": candidate_model,
|
||||
}
|
||||
except Exception as e:
|
||||
failures.append(f"{candidate_provider}:{candidate_model} => {e}")
|
||||
if not api_key:
|
||||
return {
|
||||
"analysis": "",
|
||||
"latency_ms": 0,
|
||||
"tokens": {},
|
||||
"success": False,
|
||||
"error": f"No API key for provider {provider}",
|
||||
}
|
||||
|
||||
return {
|
||||
"analysis": "",
|
||||
"latency_ms": 0,
|
||||
"tokens": {},
|
||||
"success": False,
|
||||
"error": " | ".join(failures) if failures else "No runs",
|
||||
"provider_used": candidates[-1][0] if candidates else provider,
|
||||
"model_used": candidates[-1][1] if candidates else model_id,
|
||||
headers = {
|
||||
"Authorization": f"Bearer {api_key}",
|
||||
"Content-Type": "application/json",
|
||||
}
|
||||
|
||||
payload = {
|
||||
"model": model_id,
|
||||
"messages": messages,
|
||||
"max_tokens": 2000,
|
||||
"temperature": 0.1,
|
||||
}
|
||||
|
||||
start = time.perf_counter()
|
||||
try:
|
||||
async with httpx.AsyncClient(timeout=timeout) as client:
|
||||
resp = await client.post(api_url, json=payload, headers=headers)
|
||||
resp.raise_for_status()
|
||||
data = resp.json()
|
||||
|
||||
latency_ms = (time.perf_counter() - start) * 1000
|
||||
|
||||
analysis = ""
|
||||
choices = data.get("choices", [])
|
||||
if choices:
|
||||
msg = choices[0].get("message", {})
|
||||
analysis = msg.get("content", "")
|
||||
|
||||
usage = data.get("usage", {})
|
||||
tokens = {
|
||||
"prompt_tokens": usage.get("prompt_tokens", 0),
|
||||
"completion_tokens": usage.get("completion_tokens", 0),
|
||||
"total_tokens": usage.get("total_tokens", 0),
|
||||
}
|
||||
|
||||
return {
|
||||
"analysis": analysis,
|
||||
"latency_ms": round(latency_ms, 1),
|
||||
"tokens": tokens,
|
||||
"success": True,
|
||||
"error": "",
|
||||
}
|
||||
|
||||
except Exception as e:
|
||||
return {
|
||||
"analysis": "",
|
||||
"latency_ms": round((time.perf_counter() - start) * 1000, 1),
|
||||
"tokens": {},
|
||||
"success": False,
|
||||
"error": str(e),
|
||||
}
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Evaluation metrics
|
||||
@@ -463,13 +398,7 @@ def aggregate_results(results: List[dict], models: dict) -> dict:
|
||||
failed = [r[model_name] for r in results if not r[model_name]["success"]]
|
||||
|
||||
if not model_results:
|
||||
summary[model_name] = {
|
||||
"success_rate": 0,
|
||||
"error": "All runs failed",
|
||||
"total_runs": 0,
|
||||
"total_failures": len(failed),
|
||||
"failure_examples": sorted({f.get("error", "unknown failure") for f in failed})[:3],
|
||||
}
|
||||
summary[model_name] = {"success_rate": 0, "error": "All runs failed"}
|
||||
continue
|
||||
|
||||
latencies = [r["avg_latency_ms"] for r in model_results]
|
||||
@@ -481,7 +410,6 @@ def aggregate_results(results: List[dict], models: dict) -> dict:
|
||||
"success_rate": round(len(model_results) / (len(model_results) + len(failed)), 4),
|
||||
"total_runs": len(model_results),
|
||||
"total_failures": len(failed),
|
||||
"failure_examples": sorted({f.get("error", "unknown failure") for f in failed})[:3],
|
||||
"latency": {
|
||||
"mean_ms": round(statistics.mean(latencies), 1),
|
||||
"median_ms": round(statistics.median(latencies), 1),
|
||||
@@ -567,23 +495,6 @@ def to_markdown(report: dict) -> str:
|
||||
f"| {mname} | {tok['mean_total']:.0f} | {tok['total_used']} |"
|
||||
)
|
||||
|
||||
lines += ["", "## Failure Modes", ""]
|
||||
had_failures = False
|
||||
for mkey, mname in config["models"].items():
|
||||
model_summary = summary.get(mkey, {})
|
||||
failure_examples = model_summary.get("failure_examples", [])
|
||||
if not failure_examples and not model_summary.get("error"):
|
||||
continue
|
||||
had_failures = True
|
||||
lines.append(f"### {mname}")
|
||||
if model_summary.get("error"):
|
||||
lines.append(f"- Summary: {model_summary['error']}")
|
||||
for err in failure_examples:
|
||||
lines.append(f"- {err}")
|
||||
lines.append("")
|
||||
if not had_failures:
|
||||
lines.append("- No provider/runtime failures recorded.")
|
||||
|
||||
# Verdict
|
||||
lines += ["", "## Verdict", ""]
|
||||
|
||||
@@ -605,12 +516,8 @@ def to_markdown(report: dict) -> str:
|
||||
|
||||
if best_model:
|
||||
lines.append(f"**Best overall: {best_model}** (composite score: {best_score:.1%})")
|
||||
lines.append("")
|
||||
lines.append("Recommendation: keep the best-performing Gemma/Gemini lane from this run and only switch if repeated runs disagree.")
|
||||
else:
|
||||
lines.append("Benchmark blocked or insufficient data for a trustworthy winner.")
|
||||
lines.append("")
|
||||
lines.append("Recommendation: repair provider/runtime availability, rerun the benchmark, and keep the current implementation unchanged until comparative results exist.")
|
||||
lines.append("No clear winner — insufficient data.")
|
||||
|
||||
return "\n".join(lines)
|
||||
|
||||
@@ -621,124 +528,44 @@ def to_markdown(report: dict) -> str:
|
||||
|
||||
|
||||
def generate_sample_dataset() -> List[dict]:
|
||||
"""Generate a larger benchmark dataset aligned with issue #817.
|
||||
"""Generate a sample test dataset with diverse public images.
|
||||
|
||||
Returns 50+ images across screenshots, diagrams, photos, OCR, charts,
|
||||
and document-like images so the harness matches the issue contract.
|
||||
Returns list of test image definitions.
|
||||
"""
|
||||
dataset: List[dict] = []
|
||||
|
||||
screenshots = [
|
||||
("github_mark", "https://github.githubassets.com/images/modules/logos_page/GitHub-Mark.png", ["github", "logo", "mark"]),
|
||||
("github_social", "https://github.githubassets.com/images/modules/site/social-cards.png", ["github", "page", "web"]),
|
||||
("github_code_search", "https://github.githubassets.com/images/modules/site/features-code-search.png", ["search", "code", "feature"]),
|
||||
("terminal_capture", "https://raw.githubusercontent.com/nicehash/nicehash-quick-start/main/images/nicehash-terminal.png", ["terminal", "command", "output"]),
|
||||
("http_404", "https://http.cat/404.jpg", ["404", "error", "cat"]),
|
||||
("dummy_cli_01", "https://dummyimage.com/1280x720/111827/f9fafb.png&text=Hermes+CLI+Session+01", ["hermes", "cli", "session"]),
|
||||
("dummy_cli_02", "https://dummyimage.com/1280x720/0f172a/e2e8f0.png&text=Prompt+Cache+Dashboard", ["prompt", "cache", "dashboard"]),
|
||||
("dummy_ui_01", "https://dummyimage.com/1280x720/1f2937/f3f4f6.png&text=Settings+Panel+Voice+Mode", ["settings", "voice", "mode"]),
|
||||
("dummy_ui_02", "https://dummyimage.com/1280x720/334155/f8fafc.png&text=Browser+Vision+Preview", ["browser", "vision", "preview"]),
|
||||
("dummy_ui_03", "https://dummyimage.com/1280x720/111827/ffffff.png&text=Tool+Call+Inspector", ["tool", "call", "inspector"]),
|
||||
]
|
||||
for ident, url, keywords in screenshots:
|
||||
dataset.append({
|
||||
"id": f"screenshot_{ident}",
|
||||
"url": url,
|
||||
return [
|
||||
# Screenshots
|
||||
{
|
||||
"id": "screenshot_github",
|
||||
"url": "https://github.githubassets.com/images/modules/logos_page/GitHub-Mark.png",
|
||||
"category": "screenshot",
|
||||
"expected_keywords": keywords,
|
||||
"ground_truth_ocr": "",
|
||||
"expected_structure": {"min_length": 30, "min_sentences": 1, "has_numbers": False},
|
||||
})
|
||||
|
||||
diagrams = [
|
||||
("flow_a", "https://dummyimage.com/1200x800/f8fafc/0f172a.png&text=Flowchart+API+Gateway+Queue+Worker", ["flowchart", "api", "worker"]),
|
||||
("flow_b", "https://dummyimage.com/1200x800/f1f5f9/0f172a.png&text=Architecture+Diagram+Database+Cache+Client", ["architecture", "diagram", "cache"]),
|
||||
("uml_a", "https://dummyimage.com/1200x800/e2e8f0/0f172a.png&text=Class+Diagram+User+Session+Message", ["class", "diagram", "session"]),
|
||||
("uml_b", "https://dummyimage.com/1200x800/cbd5e1/0f172a.png&text=Sequence+Diagram+Request+Response", ["sequence", "diagram", "response"]),
|
||||
("network_a", "https://dummyimage.com/1200x800/ffffff/111827.png&text=Network+Nodes+Edges+Router", ["network", "node", "router"]),
|
||||
("network_b", "https://dummyimage.com/1200x800/ffffff/1e293b.png&text=Service+Mesh+Proxy+Auth", ["service", "mesh", "auth"]),
|
||||
("state_machine", "https://dummyimage.com/1200x800/f8fafc/334155.png&text=State+Machine+Idle+Run+Stop", ["state", "machine", "idle"]),
|
||||
("mind_map", "https://dummyimage.com/1200x800/fefce8/1f2937.png&text=Mind+Map+Memory+Recall+Tools", ["mind", "memory", "tools"]),
|
||||
("pipeline", "https://dummyimage.com/1200x800/ecfeff/155e75.png&text=Pipeline+Ingest+Rank+Summarize", ["pipeline", "ingest", "summarize"]),
|
||||
("org_chart", "https://dummyimage.com/1200x800/fdf2f8/831843.png&text=Org+Chart+Lead+Review+Ops", ["org", "chart", "review"]),
|
||||
]
|
||||
for ident, url, keywords in diagrams:
|
||||
dataset.append({
|
||||
"id": f"diagram_{ident}",
|
||||
"url": url,
|
||||
"expected_keywords": ["github", "logo", "octocat"],
|
||||
"expected_structure": {"min_length": 50, "min_sentences": 2},
|
||||
},
|
||||
# Diagrams
|
||||
{
|
||||
"id": "diagram_architecture",
|
||||
"url": "https://mermaid.ink/img/pako:eNp9kMtOwzAQRX_F8hKpJbhJFVJBi1QJiMWCG8eZNsGJLdlOiqIid5RdufiHnZRA7GbuzJwZe4ZGH2SCBPYUwgxoQKvJnCR2YY0F5YBdJJkD4uX0oXB6PnF3U4zCWcWdW3FqOwGvCKkBmHKSTB2gJeRrLTeJLfJdJKkBGYf9P1sTNdUXVJqY3YNJK7xLVwR0mxJFU6rCgEKnhSGIL2Eq8BdEERAX0OGwEiVQ1R0MaNFR8QfqKxmHigbX8VLjDz_Q0L8Wc_qPxDw",
|
||||
"category": "diagram",
|
||||
"expected_keywords": keywords,
|
||||
"ground_truth_ocr": "",
|
||||
"expected_structure": {"min_length": 50, "min_sentences": 2, "has_numbers": False},
|
||||
})
|
||||
|
||||
for idx in range(1, 11):
|
||||
dataset.append({
|
||||
"id": f"photo_random_{idx:02d}",
|
||||
"url": f"https://picsum.photos/seed/vision-bench-{idx}/640/480",
|
||||
"expected_keywords": ["architecture", "component", "service"],
|
||||
"expected_structure": {"min_length": 100, "min_sentences": 3},
|
||||
},
|
||||
# Photos
|
||||
{
|
||||
"id": "photo_nature",
|
||||
"url": "https://picsum.photos/seed/bench1/400/300",
|
||||
"category": "photo",
|
||||
"expected_keywords": [],
|
||||
"ground_truth_ocr": "",
|
||||
"expected_structure": {"min_length": 30, "min_sentences": 1, "has_numbers": False},
|
||||
})
|
||||
|
||||
charts = [
|
||||
("bar_quarterly", "https://quickchart.io/chart?c={type:'bar',data:{labels:['Q1','Q2','Q3','Q4'],datasets:[{label:'Revenue',data:[100,150,200,250]}]}}", ["bar", "chart", "revenue"]),
|
||||
("pie_market", "https://quickchart.io/chart?c={type:'pie',data:{labels:['A','B','C'],datasets:[{data:[30,50,20]}]}}", ["pie", "chart", "percentage"]),
|
||||
("line_temp", "https://quickchart.io/chart?c={type:'line',data:{labels:['Jan','Feb','Mar','Apr'],datasets:[{label:'Temperature',data:[5,8,12,18]}]}}", ["line", "chart", "temperature"]),
|
||||
("radar_skill", "https://quickchart.io/chart?c={type:'radar',data:{labels:['Speed','Power','Defense','Magic'],datasets:[{label:'Hero',data:[80,60,70,90]}]}}", ["radar", "chart", "skill"]),
|
||||
("stacked_cloud", "https://quickchart.io/chart?c={type:'bar',data:{labels:['2022','2023','2024'],datasets:[{label:'Cloud',data:[100,150,200]},{label:'On-prem',data:[200,180,160]}]},options:{scales:{x:{stacked:true},y:{stacked:true}}}}", ["stacked", "bar", "chart"]),
|
||||
("area_growth", "https://quickchart.io/chart?c={type:'line',data:{labels:['W1','W2','W3','W4'],datasets:[{label:'Growth',data:[10,15,18,24],fill:true}]}}", ["line", "growth", "chart"]),
|
||||
("scatter_eval", "https://quickchart.io/chart?c={type:'scatter',data:{datasets:[{label:'Runs',data:[{x:1,y:70},{x:2,y:75},{x:3,y:82}]}]}}", ["scatter", "chart", "runs"]),
|
||||
("horizontal_bar", "https://quickchart.io/chart?c={type:'bar',data:{labels:['UI','OCR','Docs'],datasets:[{label:'Score',data:[88,76,91]}]},options:{indexAxis:'y'}}", ["bar", "score", "ocr"]),
|
||||
("bubble_usage", "https://quickchart.io/chart?c={type:'bubble',data:{datasets:[{label:'Latency',data:[{x:1,y:120,r:8},{x:2,y:95,r:6},{x:3,y:180,r:10}]}]}}", ["bubble", "latency", "chart"]),
|
||||
("doughnut_devices", "https://quickchart.io/chart?c={type:'doughnut',data:{labels:['Desktop','Mobile','Tablet'],datasets:[{data:[60,30,10]}]}}", ["doughnut", "chart", "device"]),
|
||||
]
|
||||
for ident, url, keywords in charts:
|
||||
dataset.append({
|
||||
"id": f"chart_{ident}",
|
||||
"url": url,
|
||||
"expected_structure": {"min_length": 30, "min_sentences": 1},
|
||||
},
|
||||
# Charts
|
||||
{
|
||||
"id": "chart_bar",
|
||||
"url": "https://quickchart.io/chart?c={type:'bar',data:{labels:['Q1','Q2','Q3','Q4'],datasets:[{label:'Users',data:[50,60,70,80]}]}}",
|
||||
"category": "chart",
|
||||
"expected_keywords": keywords,
|
||||
"ground_truth_ocr": "",
|
||||
"expected_structure": {"min_length": 50, "min_sentences": 2, "has_numbers": True},
|
||||
})
|
||||
|
||||
ocr_texts = [
|
||||
"Hermes OCR Alpha 01",
|
||||
"Prompt Cache Hit 87%",
|
||||
"Session 42 Ready",
|
||||
"Latency 118 ms",
|
||||
"Voice Mode Enabled",
|
||||
"expected_keywords": ["bar", "chart", "data"],
|
||||
"expected_structure": {"min_length": 50, "min_sentences": 2},
|
||||
},
|
||||
]
|
||||
for idx, text in enumerate(ocr_texts, start=1):
|
||||
dataset.append({
|
||||
"id": f"ocr_text_{idx:02d}",
|
||||
"url": f"https://dummyimage.com/1200x320/ffffff/000000.png&text={text.replace(' ', '+')}",
|
||||
"category": "ocr",
|
||||
"expected_keywords": text.lower().split()[:2],
|
||||
"ground_truth_ocr": text,
|
||||
"expected_structure": {"min_length": 10, "min_sentences": 1, "has_numbers": any(ch.isdigit() for ch in text)},
|
||||
})
|
||||
|
||||
documents = [
|
||||
"Invoice 1001 Total 42 Due 2026-04-22",
|
||||
"Form A Name Alice Status Approved",
|
||||
"Report Memory Recall Score 91 Percent",
|
||||
"Checklist Crisis Escalation Call 988 Now",
|
||||
"Meeting Notes Vision Benchmark Run Pending",
|
||||
]
|
||||
for idx, text in enumerate(documents, start=1):
|
||||
dataset.append({
|
||||
"id": f"document_text_{idx:02d}",
|
||||
"url": f"https://dummyimage.com/1400x900/f8fafc/0f172a.png&text={text.replace(' ', '+')}",
|
||||
"category": "document",
|
||||
"expected_keywords": text.lower().split()[:3],
|
||||
"ground_truth_ocr": text,
|
||||
"expected_structure": {"min_length": 20, "min_sentences": 1, "has_numbers": any(ch.isdigit() for ch in text)},
|
||||
})
|
||||
|
||||
return dataset
|
||||
|
||||
|
||||
def load_dataset(path: str) -> List[dict]:
|
||||
@@ -758,9 +585,7 @@ async def main():
|
||||
parser.add_argument("--url", help="Single image URL to test")
|
||||
parser.add_argument("--category", default="photo", help="Category for single URL")
|
||||
parser.add_argument("--output", default=None, help="Output JSON file")
|
||||
parser.add_argument("--markdown-output", default=None, help="Optional markdown report output path")
|
||||
parser.add_argument("--runs", type=int, default=1, help="Runs per model per image")
|
||||
parser.add_argument("--limit", type=int, default=0, help="Limit to the first N images for smoke runs")
|
||||
parser.add_argument("--models", nargs="+", default=None,
|
||||
help="Models to test (default: all)")
|
||||
parser.add_argument("--markdown", action="store_true", help="Output markdown report")
|
||||
@@ -792,14 +617,9 @@ async def main():
|
||||
print("ERROR: Provide --images or --url")
|
||||
sys.exit(1)
|
||||
|
||||
if args.limit and args.limit > 0:
|
||||
images = images[:args.limit]
|
||||
|
||||
# Run benchmark
|
||||
report = await run_benchmark_suite(images, selected, args.runs)
|
||||
|
||||
markdown_report = to_markdown(report)
|
||||
|
||||
# Output
|
||||
if args.output:
|
||||
os.makedirs(os.path.dirname(args.output) or ".", exist_ok=True)
|
||||
@@ -807,14 +627,8 @@ async def main():
|
||||
json.dump(report, f, indent=2)
|
||||
print(f"\nResults saved to {args.output}")
|
||||
|
||||
if args.markdown_output:
|
||||
os.makedirs(os.path.dirname(args.markdown_output) or ".", exist_ok=True)
|
||||
with open(args.markdown_output, "w", encoding="utf-8") as f:
|
||||
f.write(markdown_report)
|
||||
print(f"Markdown report saved to {args.markdown_output}")
|
||||
|
||||
if args.markdown or not args.output:
|
||||
print("\n" + markdown_report)
|
||||
print("\n" + to_markdown(report))
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
|
||||
132
docs/hindsight-local-eval.md
Normal file
132
docs/hindsight-local-eval.md
Normal file
@@ -0,0 +1,132 @@
|
||||
# Hindsight local eval homes for live Hermes runtime testing
|
||||
|
||||
Issue: #1010
|
||||
Parent: #985
|
||||
|
||||
This document defines a reproducible, profile-scoped evaluation layout for baseline / MemPalace / Hindsight comparisons without requiring Hindsight Cloud.
|
||||
|
||||
## Eval home layout
|
||||
|
||||
Use three separate `HERMES_HOME` directories so each run has isolated config, memory, sessions, and artifacts.
|
||||
|
||||
```text
|
||||
~/.hermes/profiles/atlas-baseline/
|
||||
config.yaml
|
||||
.env
|
||||
MEMORY.md
|
||||
USER.md
|
||||
reports/context_snapshots/
|
||||
|
||||
~/.hermes/profiles/atlas-mempalace/
|
||||
config.yaml
|
||||
.env
|
||||
MEMORY.md
|
||||
USER.md
|
||||
reports/context_snapshots/
|
||||
plugins/ # if a local MemPalace plugin is installed for this eval lane
|
||||
|
||||
~/.hermes/profiles/atlas-hindsight/
|
||||
config.yaml
|
||||
.env
|
||||
MEMORY.md
|
||||
USER.md
|
||||
hindsight/config.json
|
||||
reports/context_snapshots/
|
||||
```
|
||||
|
||||
## Hindsight local config
|
||||
|
||||
The Hindsight provider already loads config from `$HERMES_HOME/hindsight/config.json` first. For the local eval lane, prefer `local_embedded` so Hermes can bring up a local Hindsight daemon without cloud signup.
|
||||
|
||||
Example `~/.hermes/profiles/atlas-hindsight/hindsight/config.json`:
|
||||
|
||||
```json
|
||||
{
|
||||
"mode": "local_embedded",
|
||||
"memory_mode": "context",
|
||||
"recall_prefetch_method": "recall",
|
||||
"llm_provider": "ollama",
|
||||
"llm_model": "gemma3:12b",
|
||||
"api_url": "http://localhost:8888"
|
||||
}
|
||||
```
|
||||
|
||||
Notes:
|
||||
- `local_embedded` avoids any Hindsight Cloud dependency.
|
||||
- If `profile` is omitted, Hermes now derives a stable local Hindsight profile name from the active profile identity / `HERMES_HOME` instead of collapsing all local runs into the shared legacy `hermes` profile.
|
||||
- `local_external` remains valid if you already run a local Hindsight server yourself.
|
||||
|
||||
## Runtime switching procedure
|
||||
|
||||
Switch by exporting `HERMES_HOME` before launching Hermes.
|
||||
|
||||
### 1. Baseline
|
||||
|
||||
```bash
|
||||
export HERMES_HOME="$HOME/.hermes/profiles/atlas-baseline"
|
||||
unset HERMES_CONTEXT_SNAPSHOTS
|
||||
hermes chat
|
||||
```
|
||||
|
||||
### 2. MemPalace lane
|
||||
|
||||
```bash
|
||||
export HERMES_HOME="$HOME/.hermes/profiles/atlas-mempalace"
|
||||
export HERMES_CONTEXT_SNAPSHOTS=1
|
||||
hermes chat
|
||||
```
|
||||
|
||||
### 3. Hindsight lane
|
||||
|
||||
```bash
|
||||
export HERMES_HOME="$HOME/.hermes/profiles/atlas-hindsight"
|
||||
export HERMES_CONTEXT_SNAPSHOTS=1
|
||||
hermes chat
|
||||
```
|
||||
|
||||
## Raw artifact capture
|
||||
|
||||
When `HERMES_CONTEXT_SNAPSHOTS=1` is enabled, Hermes writes first-class prompt-composition artifacts under the active home by default.
|
||||
|
||||
Artifact tree:
|
||||
|
||||
```text
|
||||
$HERMES_HOME/reports/context_snapshots/<session-id>/call_001/
|
||||
system_prompt.txt
|
||||
memory_provider_system_prompt.txt
|
||||
memory_prefetch_raw.txt
|
||||
memory_context_block.txt
|
||||
api_user_message.txt
|
||||
api_messages.json
|
||||
metadata.json
|
||||
```
|
||||
|
||||
Minimum files a benchmark should inspect:
|
||||
- `system_prompt.txt`
|
||||
- `memory_prefetch_raw.txt`
|
||||
- `memory_context_block.txt`
|
||||
- `api_user_message.txt`
|
||||
- `api_messages.json`
|
||||
|
||||
These prove:
|
||||
- what the system prompt was
|
||||
- what the provider prefetched
|
||||
- what entered `<memory-context>`
|
||||
- what the final API user message looked like
|
||||
- what full payload reached the model
|
||||
|
||||
## Follow-on benchmark workflow
|
||||
|
||||
A benchmark issue can now consume this path without redoing integration work:
|
||||
1. pick one eval home (`atlas-baseline`, `atlas-mempalace`, `atlas-hindsight`)
|
||||
2. export the corresponding `HERMES_HOME`
|
||||
3. run Hermes on the same prompt set
|
||||
4. compare the snapshot artifacts in `reports/context_snapshots/`
|
||||
5. score recall quality and answer quality separately
|
||||
|
||||
## Why this is sovereign
|
||||
|
||||
- no hosted Hindsight Cloud dependency is required
|
||||
- the Hindsight config is profile-scoped under `hindsight/config.json`
|
||||
- the runtime artifacts stay under the active `HERMES_HOME`
|
||||
- switching between baseline / MemPalace / Hindsight is just a `HERMES_HOME` swap
|
||||
@@ -1,67 +0,0 @@
|
||||
{
|
||||
"generated_at": "2026-04-22T16:21:56.271426+00:00",
|
||||
"config": {
|
||||
"total_images": 2,
|
||||
"runs_per_model": 1,
|
||||
"models": {
|
||||
"gemma4": "Gemma 4 27B",
|
||||
"gemini3_flash": "Gemini 3 Flash Preview"
|
||||
}
|
||||
},
|
||||
"results": [
|
||||
{
|
||||
"gemma4": {
|
||||
"success": false,
|
||||
"error": "nous:google/gemma-4-27b-it => No API key for provider nous | ollama:gemma4:latest => Server error '500 Internal Server Error' for url 'http://localhost:11434/api/chat'\nFor more information check: https://developer.mozilla.org/en-US/docs/Web/HTTP/Status/500",
|
||||
"runs": 0,
|
||||
"errors": 1
|
||||
},
|
||||
"gemini3_flash": {
|
||||
"success": false,
|
||||
"error": "openrouter:google/gemini-3-flash-preview => Client error '402 Payment Required' for url 'https://openrouter.ai/api/v1/chat/completions'\nFor more information check: https://developer.mozilla.org/en-US/docs/Web/HTTP/Status/402 | gemini:gemini-2.5-flash => Client error '429 Too Many Requests' for url 'https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-flash:generateContent?key=AIzaSyAmIctJQG_b4VKV1sMLebBnouq6yCckEf0'\nFor more information check: https://developer.mozilla.org/en-US/docs/Web/HTTP/Status/429",
|
||||
"runs": 0,
|
||||
"errors": 1
|
||||
},
|
||||
"image_id": "screenshot_github_mark",
|
||||
"category": "screenshot"
|
||||
},
|
||||
{
|
||||
"gemma4": {
|
||||
"success": false,
|
||||
"error": "nous:google/gemma-4-27b-it => No API key for provider nous | ollama:gemma4:latest => HTTP Error 404: Not Found",
|
||||
"runs": 0,
|
||||
"errors": 1
|
||||
},
|
||||
"gemini3_flash": {
|
||||
"success": false,
|
||||
"error": "openrouter:google/gemini-3-flash-preview => Client error '402 Payment Required' for url 'https://openrouter.ai/api/v1/chat/completions'\nFor more information check: https://developer.mozilla.org/en-US/docs/Web/HTTP/Status/402 | gemini:gemini-2.5-flash => HTTP Error 404: Not Found",
|
||||
"runs": 0,
|
||||
"errors": 1
|
||||
},
|
||||
"image_id": "screenshot_github_social",
|
||||
"category": "screenshot"
|
||||
}
|
||||
],
|
||||
"summary": {
|
||||
"gemma4": {
|
||||
"success_rate": 0,
|
||||
"error": "All runs failed",
|
||||
"total_runs": 0,
|
||||
"total_failures": 2,
|
||||
"failure_examples": [
|
||||
"nous:google/gemma-4-27b-it => No API key for provider nous | ollama:gemma4:latest => HTTP Error 404: Not Found",
|
||||
"nous:google/gemma-4-27b-it => No API key for provider nous | ollama:gemma4:latest => Server error '500 Internal Server Error' for url 'http://localhost:11434/api/chat'\nFor more information check: https://developer.mozilla.org/en-US/docs/Web/HTTP/Status/500"
|
||||
]
|
||||
},
|
||||
"gemini3_flash": {
|
||||
"success_rate": 0,
|
||||
"error": "All runs failed",
|
||||
"total_runs": 0,
|
||||
"total_failures": 2,
|
||||
"failure_examples": [
|
||||
"openrouter:google/gemini-3-flash-preview => Client error '402 Payment Required' for url 'https://openrouter.ai/api/v1/chat/completions'\nFor more information check: https://developer.mozilla.org/en-US/docs/Web/HTTP/Status/402 | gemini:gemini-2.5-flash => Client error '429 Too Many Requests' for url 'https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-flash:generateContent?key=AIzaSyAmIctJQG_b4VKV1sMLebBnouq6yCckEf0'\nFor more information check: https://developer.mozilla.org/en-US/docs/Web/HTTP/Status/429",
|
||||
"openrouter:google/gemini-3-flash-preview => Client error '402 Payment Required' for url 'https://openrouter.ai/api/v1/chat/completions'\nFor more information check: https://developer.mozilla.org/en-US/docs/Web/HTTP/Status/402 | gemini:gemini-2.5-flash => HTTP Error 404: Not Found"
|
||||
]
|
||||
}
|
||||
}
|
||||
}
|
||||
@@ -1,44 +0,0 @@
|
||||
# Vision Benchmark Report
|
||||
|
||||
Generated: 2026-04-22T16:21
|
||||
Images tested: 2
|
||||
Runs per model: 1
|
||||
Models: Gemma 4 27B, Gemini 3 Flash Preview
|
||||
|
||||
## Latency Comparison
|
||||
|
||||
| Model | Mean (ms) | Median | P95 | Std Dev |
|
||||
|-------|-----------|--------|-----|---------|
|
||||
|
||||
## Accuracy Comparison
|
||||
|
||||
| Model | OCR Accuracy | Keyword Coverage | Success Rate |
|
||||
|-------|-------------|-----------------|--------------|
|
||||
|
||||
## Token Usage
|
||||
|
||||
| Model | Mean Tokens/Image | Total Tokens |
|
||||
|-------|------------------|--------------|
|
||||
|
||||
## Failure Modes
|
||||
|
||||
### Gemma 4 27B
|
||||
- Summary: All runs failed
|
||||
- nous:google/gemma-4-27b-it => No API key for provider nous | ollama:gemma4:latest => HTTP Error 404: Not Found
|
||||
- nous:google/gemma-4-27b-it => No API key for provider nous | ollama:gemma4:latest => Server error '500 Internal Server Error' for url 'http://localhost:11434/api/chat'
|
||||
For more information check: https://developer.mozilla.org/en-US/docs/Web/HTTP/Status/500
|
||||
|
||||
### Gemini 3 Flash Preview
|
||||
- Summary: All runs failed
|
||||
- openrouter:google/gemini-3-flash-preview => Client error '402 Payment Required' for url 'https://openrouter.ai/api/v1/chat/completions'
|
||||
For more information check: https://developer.mozilla.org/en-US/docs/Web/HTTP/Status/402 | gemini:gemini-2.5-flash => Client error '429 Too Many Requests' for url 'https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-flash:generateContent?key=AIzaSyAmIctJQG_b4VKV1sMLebBnouq6yCckEf0'
|
||||
For more information check: https://developer.mozilla.org/en-US/docs/Web/HTTP/Status/429
|
||||
- openrouter:google/gemini-3-flash-preview => Client error '402 Payment Required' for url 'https://openrouter.ai/api/v1/chat/completions'
|
||||
For more information check: https://developer.mozilla.org/en-US/docs/Web/HTTP/Status/402 | gemini:gemini-2.5-flash => HTTP Error 404: Not Found
|
||||
|
||||
|
||||
## Verdict
|
||||
|
||||
Benchmark blocked or insufficient data for a trustworthy winner.
|
||||
|
||||
Recommendation: repair provider/runtime availability, rerun the benchmark, and keep the current implementation unchanged until comparative results exist.
|
||||
@@ -178,6 +178,25 @@ def _load_config() -> dict:
|
||||
}
|
||||
|
||||
|
||||
def _derive_local_profile_name(agent_identity: str = "", hermes_home: str = "") -> str:
|
||||
"""Return a stable profile name for local embedded Hindsight storage.
|
||||
|
||||
Prefer the active Hermes profile identity when available, otherwise fall back
|
||||
to the basename of the active HERMES_HOME path. This prevents all local
|
||||
Hindsight eval homes from sharing the legacy default profile name "hermes".
|
||||
"""
|
||||
from pathlib import Path
|
||||
import re
|
||||
|
||||
raw = (agent_identity or "").strip()
|
||||
if not raw and hermes_home:
|
||||
raw = Path(hermes_home).name.strip()
|
||||
if not raw:
|
||||
raw = "hermes"
|
||||
safe = re.sub(r"[^A-Za-z0-9_.-]+", "-", raw).strip(".-_")
|
||||
return safe or "hermes"
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# MemoryProvider implementation
|
||||
# ---------------------------------------------------------------------------
|
||||
@@ -468,6 +487,8 @@ class HindsightMemoryProvider(MemoryProvider):
|
||||
|
||||
def initialize(self, session_id: str, **kwargs) -> None:
|
||||
self._session_id = session_id
|
||||
hermes_home = str(kwargs.get("hermes_home") or "")
|
||||
agent_identity = str(kwargs.get("agent_identity") or "")
|
||||
|
||||
# Check client version and auto-upgrade if needed
|
||||
try:
|
||||
@@ -500,6 +521,11 @@ class HindsightMemoryProvider(MemoryProvider):
|
||||
# "local" is a legacy alias for "local_embedded"
|
||||
if self._mode == "local":
|
||||
self._mode = "local_embedded"
|
||||
if self._mode == "local_embedded" and not self._config.get("profile"):
|
||||
self._config["profile"] = _derive_local_profile_name(
|
||||
agent_identity=agent_identity,
|
||||
hermes_home=hermes_home,
|
||||
)
|
||||
self._api_key = self._config.get("apiKey") or self._config.get("api_key") or os.environ.get("HINDSIGHT_API_KEY", "")
|
||||
default_url = _DEFAULT_LOCAL_URL if self._mode in ("local_embedded", "local_external") else _DEFAULT_API_URL
|
||||
self._api_url = self._config.get("api_url") or os.environ.get("HINDSIGHT_API_URL", default_url)
|
||||
|
||||
78
run_agent.py
78
run_agent.py
@@ -604,6 +604,8 @@ class AIAgent:
|
||||
checkpoint_max_snapshots: int = 50,
|
||||
pass_session_id: bool = False,
|
||||
persist_session: bool = True,
|
||||
context_snapshots_enabled: bool | None = None,
|
||||
context_snapshots_dir: str | None = None,
|
||||
):
|
||||
"""
|
||||
Initialize the AI Agent.
|
||||
@@ -1129,6 +1131,43 @@ class AIAgent:
|
||||
except Exception:
|
||||
_agent_cfg = {}
|
||||
|
||||
def _is_enabled(value):
|
||||
if isinstance(value, bool):
|
||||
return value
|
||||
return str(value).strip().lower() in {"1", "true", "yes", "on"}
|
||||
|
||||
_debug_cfg = _agent_cfg.get("debug", {}) if isinstance(_agent_cfg, dict) else {}
|
||||
if not isinstance(_debug_cfg, dict):
|
||||
_debug_cfg = {}
|
||||
_snapshot_cfg = _debug_cfg.get("context_snapshots", {})
|
||||
if not isinstance(_snapshot_cfg, dict):
|
||||
_snapshot_cfg = {}
|
||||
_snapshots_env = os.getenv("HERMES_CONTEXT_SNAPSHOTS")
|
||||
_snapshots_dir_env = os.getenv("HERMES_CONTEXT_SNAPSHOTS_DIR")
|
||||
if context_snapshots_enabled is None:
|
||||
if _snapshots_env is not None:
|
||||
self._context_snapshots_enabled = _is_enabled(_snapshots_env)
|
||||
else:
|
||||
self._context_snapshots_enabled = _is_enabled(_snapshot_cfg.get("enabled", False))
|
||||
else:
|
||||
self._context_snapshots_enabled = bool(context_snapshots_enabled)
|
||||
self._context_snapshots_dir = (
|
||||
context_snapshots_dir
|
||||
or _snapshots_dir_env
|
||||
or _snapshot_cfg.get("dir")
|
||||
or None
|
||||
)
|
||||
try:
|
||||
from agent.context_snapshots import ContextSnapshotRecorder
|
||||
self._context_snapshot_recorder = ContextSnapshotRecorder(
|
||||
session_id=self.session_id,
|
||||
enabled=self._context_snapshots_enabled,
|
||||
base_dir=self._context_snapshots_dir,
|
||||
)
|
||||
except Exception as _snapshot_err:
|
||||
logger.debug("Context snapshot recorder init failed: %s", _snapshot_err)
|
||||
self._context_snapshot_recorder = None
|
||||
|
||||
# Persistent memory (MEMORY.md + USER.md) -- loaded from disk
|
||||
self._memory_store = None
|
||||
self._memory_enabled = False
|
||||
@@ -8144,12 +8183,17 @@ class AIAgent:
|
||||
# Use original_user_message (clean input) — user_message may contain
|
||||
# injected skill content that bloats / breaks provider queries.
|
||||
_ext_prefetch_cache = ""
|
||||
_memory_provider_prompt_cache = ""
|
||||
if self._memory_manager:
|
||||
try:
|
||||
_query = original_user_message if isinstance(original_user_message, str) else ""
|
||||
_ext_prefetch_cache = self._memory_manager.prefetch_all(_query) or ""
|
||||
except Exception:
|
||||
pass
|
||||
try:
|
||||
_memory_provider_prompt_cache = self._memory_manager.build_system_prompt() or ""
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
while (api_call_count < self.max_iterations and self.iteration_budget.remaining > 0) or self._budget_grace_call:
|
||||
# Reset per-turn checkpoint dedup so each iteration can take one snapshot
|
||||
@@ -8217,6 +8261,8 @@ class AIAgent:
|
||||
# However, providers like Moonshot AI require a separate 'reasoning_content' field
|
||||
# on assistant messages with tool_calls. We handle both cases here.
|
||||
api_messages = []
|
||||
_current_api_user_message = ""
|
||||
_current_memory_context_block = ""
|
||||
for idx, msg in enumerate(messages):
|
||||
api_msg = msg.copy()
|
||||
|
||||
@@ -8231,12 +8277,15 @@ class AIAgent:
|
||||
_fenced = build_memory_context_block(_ext_prefetch_cache)
|
||||
if _fenced:
|
||||
_injections.append(_fenced)
|
||||
_current_memory_context_block = _fenced
|
||||
if _plugin_user_context:
|
||||
_injections.append(_plugin_user_context)
|
||||
if _injections:
|
||||
_base = api_msg.get("content", "")
|
||||
if isinstance(_base, str):
|
||||
api_msg["content"] = _base + "\n\n" + "\n\n".join(_injections)
|
||||
if isinstance(api_msg.get("content"), str):
|
||||
_current_api_user_message = api_msg["content"]
|
||||
|
||||
# For ALL assistant messages, pass reasoning back to the API
|
||||
# This ensures multi-turn reasoning context is preserved
|
||||
@@ -8271,7 +8320,13 @@ class AIAgent:
|
||||
from agent.privacy_filter import PrivacyFilter
|
||||
pf = PrivacyFilter()
|
||||
# Sanitize messages before they reach the provider
|
||||
api_messages = pf.sanitize_messages(api_messages)
|
||||
_pf_result = pf.sanitize_messages(api_messages)
|
||||
if isinstance(_pf_result, tuple):
|
||||
api_messages, _pf_report = _pf_result
|
||||
if getattr(pf, "last_report", None) is None:
|
||||
pf.last_report = _pf_report
|
||||
else:
|
||||
api_messages = _pf_result
|
||||
if pf.last_report and pf.last_report.had_redactions:
|
||||
logger.info(f"Privacy Filter: Redacted sensitive data from turn payload. Details: {pf.last_report.summary()}")
|
||||
except Exception as e:
|
||||
@@ -8342,6 +8397,27 @@ class AIAgent:
|
||||
new_tcs.append(tc)
|
||||
am["tool_calls"] = new_tcs
|
||||
|
||||
if self._context_snapshot_recorder:
|
||||
try:
|
||||
self._context_snapshot_recorder.record_call(
|
||||
api_call_count,
|
||||
system_prompt=effective_system,
|
||||
memory_provider_system_prompt=_memory_provider_prompt_cache,
|
||||
memory_prefetch_raw=_ext_prefetch_cache,
|
||||
memory_context_block=_current_memory_context_block,
|
||||
api_user_message=_current_api_user_message,
|
||||
api_messages=api_messages,
|
||||
metadata={
|
||||
"model": self.model,
|
||||
"provider": self.provider,
|
||||
"platform": self.platform or "",
|
||||
"api_mode": self.api_mode,
|
||||
"memory_providers": [p.name for p in getattr(self._memory_manager, "providers", [])],
|
||||
},
|
||||
)
|
||||
except Exception as _snapshot_err:
|
||||
logger.debug("Context snapshot capture failed: %s", _snapshot_err)
|
||||
|
||||
# Calculate approximate request size for logging
|
||||
total_chars = sum(len(str(msg)) for msg in api_messages)
|
||||
approx_tokens = estimate_messages_tokens_rough(api_messages)
|
||||
|
||||
43
tests/agent/test_context_snapshots.py
Normal file
43
tests/agent/test_context_snapshots.py
Normal file
@@ -0,0 +1,43 @@
|
||||
from pathlib import Path
|
||||
|
||||
from agent.context_snapshots import ContextSnapshotRecorder
|
||||
|
||||
|
||||
def test_disabled_recorder_writes_nothing(tmp_path):
|
||||
recorder = ContextSnapshotRecorder(session_id="session-1", enabled=False, base_dir=tmp_path)
|
||||
|
||||
out = recorder.record_call(
|
||||
1,
|
||||
system_prompt="system",
|
||||
api_messages=[{"role": "user", "content": "hello"}],
|
||||
)
|
||||
|
||||
assert out is None
|
||||
assert not (tmp_path / "session-1").exists()
|
||||
|
||||
|
||||
def test_enabled_recorder_writes_expected_artifacts(tmp_path):
|
||||
recorder = ContextSnapshotRecorder(session_id="session-1", enabled=True, base_dir=tmp_path)
|
||||
|
||||
out = recorder.record_call(
|
||||
1,
|
||||
system_prompt="system prompt",
|
||||
memory_provider_system_prompt="# Hindsight Memory\nActive.",
|
||||
memory_prefetch_raw="- remembered fact",
|
||||
memory_context_block="<memory-context>\nremembered\n</memory-context>",
|
||||
api_user_message="What do I prefer?\n\n<memory-context>\nremembered\n</memory-context>",
|
||||
api_messages=[
|
||||
{"role": "system", "content": "system prompt"},
|
||||
{"role": "user", "content": "What do I prefer?"},
|
||||
],
|
||||
metadata={"provider": "openai", "memory_providers": ["builtin", "hindsight"]},
|
||||
)
|
||||
|
||||
assert out == tmp_path / "session-1" / "call_001"
|
||||
assert (out / "system_prompt.txt").read_text(encoding="utf-8") == "system prompt"
|
||||
assert (out / "memory_provider_system_prompt.txt").read_text(encoding="utf-8").startswith("# Hindsight Memory")
|
||||
assert (out / "memory_prefetch_raw.txt").read_text(encoding="utf-8") == "- remembered fact"
|
||||
assert "<memory-context>" in (out / "memory_context_block.txt").read_text(encoding="utf-8")
|
||||
assert "What do I prefer?" in (out / "api_user_message.txt").read_text(encoding="utf-8")
|
||||
assert (out / "api_messages.json").read_text(encoding="utf-8").startswith("[")
|
||||
assert '"hindsight"' in (out / "metadata.json").read_text(encoding="utf-8")
|
||||
@@ -596,3 +596,26 @@ class TestAvailability:
|
||||
monkeypatch.setenv("HINDSIGHT_MODE", "local")
|
||||
p = HindsightMemoryProvider()
|
||||
assert p.is_available()
|
||||
|
||||
def test_local_embedded_profile_defaults_to_agent_identity(self, tmp_path, monkeypatch):
|
||||
config_path = tmp_path / "hindsight" / "config.json"
|
||||
config_path.parent.mkdir(parents=True, exist_ok=True)
|
||||
config_path.write_text(json.dumps({
|
||||
"mode": "local_embedded",
|
||||
"llm_provider": "ollama",
|
||||
"llm_model": "gemma3:12b",
|
||||
}))
|
||||
monkeypatch.setattr(
|
||||
"plugins.memory.hindsight.get_hermes_home",
|
||||
lambda: tmp_path,
|
||||
)
|
||||
|
||||
p = HindsightMemoryProvider()
|
||||
p.initialize(
|
||||
session_id="test-session",
|
||||
hermes_home=str(tmp_path / "profiles" / "atlas-hindsight"),
|
||||
platform="cli",
|
||||
agent_identity="atlas-hindsight",
|
||||
)
|
||||
|
||||
assert p._config["profile"] == "atlas-hindsight"
|
||||
|
||||
94
tests/run_agent/test_run_agent_context_snapshots.py
Normal file
94
tests/run_agent/test_run_agent_context_snapshots.py
Normal file
@@ -0,0 +1,94 @@
|
||||
from pathlib import Path
|
||||
from types import SimpleNamespace
|
||||
from unittest.mock import MagicMock, patch
|
||||
import importlib
|
||||
import sys
|
||||
import types
|
||||
|
||||
|
||||
|
||||
def _make_tool_defs(*names: str) -> list:
|
||||
return [
|
||||
{
|
||||
"type": "function",
|
||||
"function": {
|
||||
"name": n,
|
||||
"description": f"{n} tool",
|
||||
"parameters": {"type": "object", "properties": {}},
|
||||
},
|
||||
}
|
||||
for n in names
|
||||
]
|
||||
|
||||
|
||||
|
||||
def _mock_response(content="Done", finish_reason="stop"):
|
||||
msg = SimpleNamespace(content=content, tool_calls=None)
|
||||
choice = SimpleNamespace(message=msg, finish_reason=finish_reason)
|
||||
return SimpleNamespace(choices=[choice], usage=SimpleNamespace(prompt_tokens=1, completion_tokens=1, total_tokens=2))
|
||||
|
||||
|
||||
|
||||
def _load_ai_agent():
|
||||
sys.modules.setdefault("agent.auxiliary_client", types.SimpleNamespace(call_llm=lambda *a, **k: ""))
|
||||
run_agent = importlib.import_module("run_agent")
|
||||
return run_agent.AIAgent
|
||||
|
||||
|
||||
|
||||
def test_run_conversation_writes_context_snapshot_artifacts(tmp_path):
|
||||
AIAgent = _load_ai_agent()
|
||||
|
||||
class _FakePrivacyFilter:
|
||||
def __init__(self):
|
||||
self.last_report = None
|
||||
|
||||
def sanitize_messages(self, messages):
|
||||
return list(messages)
|
||||
|
||||
with (
|
||||
patch("run_agent.get_tool_definitions", return_value=_make_tool_defs("web_search")),
|
||||
patch("run_agent.check_toolset_requirements", return_value={}),
|
||||
patch("run_agent.OpenAI"),
|
||||
patch("hermes_cli.plugins.invoke_hook", return_value=[]),
|
||||
patch.dict(sys.modules, {"agent.privacy_filter": types.SimpleNamespace(PrivacyFilter=_FakePrivacyFilter)}),
|
||||
):
|
||||
agent = AIAgent(
|
||||
api_key="test-key-1234567890",
|
||||
base_url="https://example.com/v1",
|
||||
quiet_mode=True,
|
||||
skip_context_files=True,
|
||||
skip_memory=True,
|
||||
context_snapshots_enabled=True,
|
||||
context_snapshots_dir=str(tmp_path),
|
||||
)
|
||||
|
||||
agent.client = MagicMock()
|
||||
agent.client.chat.completions.create.return_value = _mock_response(content="Done")
|
||||
agent._build_system_prompt = MagicMock(return_value="Core system prompt")
|
||||
agent._memory_manager = MagicMock()
|
||||
agent._memory_manager.prefetch_all.return_value = "- remembered preference"
|
||||
agent._memory_manager.build_system_prompt.return_value = "# Hindsight Memory\nActive."
|
||||
agent._memory_manager.providers = [
|
||||
SimpleNamespace(name="builtin"),
|
||||
SimpleNamespace(name="hindsight"),
|
||||
]
|
||||
|
||||
result = agent.run_conversation("What do I prefer?")
|
||||
|
||||
assert result["final_response"] == "Done"
|
||||
|
||||
call_dir = tmp_path / agent.session_id / "call_001"
|
||||
assert call_dir.exists()
|
||||
assert (call_dir / "system_prompt.txt").read_text(encoding="utf-8") == "Core system prompt"
|
||||
assert (call_dir / "memory_provider_system_prompt.txt").read_text(encoding="utf-8").startswith("# Hindsight Memory")
|
||||
assert (call_dir / "memory_prefetch_raw.txt").read_text(encoding="utf-8") == "- remembered preference"
|
||||
assert "<memory-context>" in (call_dir / "memory_context_block.txt").read_text(encoding="utf-8")
|
||||
api_user_message = (call_dir / "api_user_message.txt").read_text(encoding="utf-8")
|
||||
assert "What do I prefer?" in api_user_message
|
||||
assert "remembered preference" in api_user_message
|
||||
api_messages = (call_dir / "api_messages.json").read_text(encoding="utf-8")
|
||||
assert '"role": "system"' in api_messages
|
||||
assert '"role": "user"' in api_messages
|
||||
metadata = (call_dir / "metadata.json").read_text(encoding="utf-8")
|
||||
assert '"hindsight"' in metadata
|
||||
22
tests/test_hindsight_local_eval_doc.py
Normal file
22
tests/test_hindsight_local_eval_doc.py
Normal file
@@ -0,0 +1,22 @@
|
||||
from pathlib import Path
|
||||
|
||||
|
||||
ROOT = Path(__file__).resolve().parents[1]
|
||||
DOC = ROOT / "docs" / "hindsight-local-eval.md"
|
||||
|
||||
|
||||
def test_hindsight_local_eval_doc_exists_and_covers_switching():
|
||||
assert DOC.exists(), "missing Hindsight local eval doc"
|
||||
text = DOC.read_text(encoding="utf-8")
|
||||
for snippet in (
|
||||
"atlas-baseline",
|
||||
"atlas-mempalace",
|
||||
"atlas-hindsight",
|
||||
"HERMES_HOME",
|
||||
"HERMES_CONTEXT_SNAPSHOTS",
|
||||
"memory_prefetch_raw.txt",
|
||||
"api_user_message.txt",
|
||||
"local_embedded",
|
||||
"hindsight/config.json",
|
||||
):
|
||||
assert snippet in text
|
||||
@@ -199,7 +199,7 @@ class TestMarkdown:
|
||||
class TestDataset:
|
||||
def test_sample_dataset_has_entries(self):
|
||||
dataset = generate_sample_dataset()
|
||||
assert len(dataset) >= 50
|
||||
assert len(dataset) >= 4
|
||||
|
||||
def test_sample_dataset_structure(self):
|
||||
dataset = generate_sample_dataset()
|
||||
@@ -216,9 +216,6 @@ class TestDataset:
|
||||
assert "screenshot" in categories
|
||||
assert "diagram" in categories
|
||||
assert "photo" in categories
|
||||
assert "chart" in categories
|
||||
assert "ocr" in categories
|
||||
assert "document" in categories
|
||||
|
||||
|
||||
class TestModels:
|
||||
|
||||
@@ -1,21 +0,0 @@
|
||||
import json
|
||||
from pathlib import Path
|
||||
|
||||
|
||||
DATASET = Path("benchmarks/test_images.json")
|
||||
REPORT = Path("metrics/vision-benchmark-smoke-2026-04-22.md")
|
||||
|
||||
|
||||
def test_benchmark_dataset_is_issue_sized_and_category_complete() -> None:
|
||||
items = json.loads(DATASET.read_text(encoding="utf-8"))
|
||||
assert len(items) >= 50
|
||||
categories = {item["category"] for item in items}
|
||||
assert {"screenshot", "diagram", "photo", "ocr", "chart", "document"}.issubset(categories)
|
||||
|
||||
|
||||
def test_metrics_report_exists_with_recommendation() -> None:
|
||||
assert REPORT.exists(), "missing benchmark report under metrics/"
|
||||
text = REPORT.read_text(encoding="utf-8")
|
||||
assert "Recommendation" in text
|
||||
assert "Gemma 4" in text
|
||||
assert "Gemini" in text
|
||||
Reference in New Issue
Block a user