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Author SHA1 Message Date
Alexander Whitestone
599904d945 fix: log plugin memory provider fallback failure at debug level
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Address review feedback on PR #1002: replace silent `except Exception: pass`
with `logger.debug(...)` so plugin loading failures are visible in debug logs.

Refs #990

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-04-22 10:54:10 -04:00
Alexander Whitestone
df1bfe433a fix: add register_memory_provider to PluginContext — fixes #990
PluginContext was missing register_memory_provider(), causing any
user plugin (e.g. MemPalace) that followed the documented pattern
of calling ctx.register_memory_provider(provider) in its register()
function to fail at startup with:

  'PluginContext' object has no attribute 'register_memory_provider'

Changes:
- hermes_cli/plugins.py: Add register_memory_provider() to PluginContext,
  _plugin_memory_provider field to PluginManager, and module-level
  get_plugin_memory_provider() accessor function.
- run_agent.py: After failing to find a provider in plugins/memory/,
  fall back to checking get_plugin_memory_provider() — mirrors how
  context engine plugins are resolved.
- tests: Add TestRegisterMemoryProvider with four regression tests
  covering success, accessor, duplicate rejection, and type validation.

Fixes #990

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-04-22 10:54:10 -04:00
9 changed files with 396 additions and 1122 deletions

View File

@@ -1,757 +1,194 @@
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"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}
}
]
]

View File

@@ -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__":

View File

@@ -211,6 +211,43 @@ class PluginContext:
}
logger.debug("Plugin %s registered CLI command: %s", self.manifest.name, name)
# -- memory provider registration ----------------------------------------
def register_memory_provider(self, provider) -> None:
"""Register a memory provider supplied by this plugin.
The provider must be an instance of ``agent.memory_provider.MemoryProvider``.
Only one plugin-registered memory provider is accepted; a second
attempt is rejected with a warning.
The registered provider is retrievable via
``get_plugin_memory_provider()`` and is picked up by ``run_agent.py``
when ``memory.provider`` in *config.yaml* matches the provider's
``name`` property.
"""
from agent.memory_provider import MemoryProvider
if not isinstance(provider, MemoryProvider):
logger.warning(
"Plugin '%s' tried to register a memory provider that does not "
"inherit from MemoryProvider. Ignoring.",
self.manifest.name,
)
return
if self._manager._plugin_memory_provider is not None:
logger.warning(
"Plugin '%s' tried to register a memory provider, but one is "
"already registered by another plugin. Only one plugin-supplied "
"memory provider is allowed at a time.",
self.manifest.name,
)
return
self._manager._plugin_memory_provider = provider
logger.info(
"Plugin '%s' registered memory provider: %s",
self.manifest.name, provider.name,
)
# -- context engine registration -----------------------------------------
def register_context_engine(self, engine) -> None:
@@ -323,6 +360,7 @@ class PluginManager:
self._plugin_tool_names: Set[str] = set()
self._cli_commands: Dict[str, dict] = {}
self._context_engine = None # Set by a plugin via register_context_engine()
self._plugin_memory_provider = None # Set by a plugin via register_memory_provider()
self._discovered: bool = False
self._cli_ref = None # Set by CLI after plugin discovery
# Plugin skill registry: qualified name → metadata dict.
@@ -699,6 +737,11 @@ def get_plugin_context_engine():
return get_plugin_manager()._context_engine
def get_plugin_memory_provider():
"""Return the plugin-registered memory provider, or None."""
return get_plugin_manager()._plugin_memory_provider
def get_plugin_toolsets() -> List[tuple]:
"""Return plugin toolsets as ``(key, label, description)`` tuples.

View File

@@ -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"
]
}
}
}

View File

@@ -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.

View File

@@ -1193,6 +1193,18 @@ class AIAgent:
from plugins.memory import load_memory_provider as _load_mem
self._memory_manager = _MemoryManager()
_mp = _load_mem(_mem_provider_name)
# Fall back to a user plugin that called register_memory_provider()
if _mp is None:
try:
from hermes_cli.plugins import get_plugin_memory_provider as _gpm
_candidate = _gpm()
if _candidate and _candidate.name == _mem_provider_name:
_mp = _candidate
except Exception as _gpm_err:
logger.debug(
"get_plugin_memory_provider() failed during fallback lookup: %s",
_gpm_err,
)
if _mp and _mp.is_available():
self._memory_manager.add_provider(_mp)
if self._memory_manager.providers:

View File

@@ -19,6 +19,7 @@ from hermes_cli.plugins import (
PluginManifest,
get_plugin_manager,
get_pre_tool_call_block_message,
get_plugin_memory_provider,
discover_plugins,
invoke_hook,
)
@@ -609,3 +610,105 @@ class TestPreLlmCallTargetRouting:
# in PluginContext (hermes_cli/plugins.py). The tests referenced _plugin_commands,
# commands_registered, get_plugin_command_handler, and GATEWAY_KNOWN_COMMANDS
# integration — all of which are unimplemented features.
# ── TestRegisterMemoryProvider ─────────────────────────────────────────────
class TestRegisterMemoryProvider:
"""Regression tests for PluginContext.register_memory_provider() — issue #990.
The MemPalace plugin (and any user plugin following the developer guide)
calls ``ctx.register_memory_provider(provider)`` inside ``register(ctx)``.
Before the fix, PluginContext had no such method and the plugin failed to
load with: 'PluginContext' object has no attribute 'register_memory_provider'.
"""
def _make_memory_plugin(self, plugins_dir: "Path", name: str) -> None:
"""Write a minimal user plugin that registers a stub MemoryProvider."""
from agent.memory_provider import MemoryProvider
plugin_dir = plugins_dir / name
plugin_dir.mkdir(parents=True, exist_ok=True)
(plugin_dir / "plugin.yaml").write_text(
f"name: {name}\nversion: 0.1.0\ndescription: Stub memory plugin\n"
)
# The register() body imports and calls register_memory_provider — this
# is the exact pattern documented in memory-provider-plugin.md and used
# by third-party plugins such as MemPalace.
(plugin_dir / "__init__.py").write_text(
"from agent.memory_provider import MemoryProvider\n"
"\n"
"class _StubProvider(MemoryProvider):\n"
" @property\n"
f" def name(self): return '{name}'\n"
" def is_available(self): return True\n"
" def initialize(self, session_id, **kw): pass\n"
" def get_tool_schemas(self): return []\n"
"\n"
"def register(ctx):\n"
" ctx.register_memory_provider(_StubProvider())\n"
)
def test_register_memory_provider_succeeds(self, tmp_path, monkeypatch):
"""A user plugin calling register_memory_provider() loads without error."""
plugins_dir = tmp_path / "hermes_test" / "plugins"
self._make_memory_plugin(plugins_dir, "mempalace")
monkeypatch.setenv("HERMES_HOME", str(tmp_path / "hermes_test"))
mgr = PluginManager()
mgr.discover_and_load()
assert "mempalace" in mgr._plugins
assert mgr._plugins["mempalace"].enabled, (
mgr._plugins["mempalace"].error
)
def test_plugin_memory_provider_stored(self, tmp_path, monkeypatch):
"""The provider instance is accessible via get_plugin_memory_provider()."""
import hermes_cli.plugins as plugins_mod
plugins_dir = tmp_path / "hermes_test" / "plugins"
self._make_memory_plugin(plugins_dir, "mempalace")
monkeypatch.setenv("HERMES_HOME", str(tmp_path / "hermes_test"))
mgr = PluginManager()
# Swap the singleton so get_plugin_memory_provider() sees our manager
monkeypatch.setattr(plugins_mod, "_plugin_manager", mgr)
mgr.discover_and_load()
provider = get_plugin_memory_provider()
assert provider is not None
assert provider.name == "mempalace"
def test_second_registration_rejected(self, tmp_path, monkeypatch):
"""Only one plugin-registered memory provider is accepted."""
plugins_dir = tmp_path / "hermes_test" / "plugins"
self._make_memory_plugin(plugins_dir, "first_provider")
self._make_memory_plugin(plugins_dir, "second_provider")
monkeypatch.setenv("HERMES_HOME", str(tmp_path / "hermes_test"))
mgr = PluginManager()
mgr.discover_and_load()
# The manager should hold exactly one provider
assert mgr._plugin_memory_provider is not None
assert mgr._plugin_memory_provider.name in {"first_provider", "second_provider"}
def test_non_provider_rejected(self, tmp_path, monkeypatch):
"""Passing a non-MemoryProvider object logs a warning and is ignored."""
plugins_dir = tmp_path / "hermes_test" / "plugins"
plugin_dir = plugins_dir / "bad_provider"
plugin_dir.mkdir(parents=True, exist_ok=True)
(plugin_dir / "plugin.yaml").write_text("name: bad_provider\n")
(plugin_dir / "__init__.py").write_text(
"def register(ctx):\n"
" ctx.register_memory_provider('not-a-provider')\n"
)
monkeypatch.setenv("HERMES_HOME", str(tmp_path / "hermes_test"))
mgr = PluginManager()
mgr.discover_and_load()
# Plugin still loads (warning only), but no provider is stored
assert mgr._plugin_memory_provider is None

View File

@@ -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:

View File

@@ -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