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Author SHA1 Message Date
Alexander Whitestone
f8f4678ee4 feat: benchmark local Ollama models against 50 tok/s threshold (#287)
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Add scripts/benchmark_local_models.py — tests all local Ollama models
against the 50 tok/s UX threshold (configurable via --threshold).

Features:
- Auto-discovers all pulled Ollama models or test specific ones
- Configurable rounds, max tokens, threshold
- Per-round timing with prompt_eval/eval token breakdown
- Human-readable table report with PASS/FAIL/ERROR status
- JSON output mode (--json) for CI integration
- Exit code 1 if any model fails threshold

Usage:
  python3 scripts/benchmark_local_models.py                 # all models, 3 rounds
  python3 scripts/benchmark_local_models.py --models qwen2.5:7b  # single model
  python3 scripts/benchmark_local_models.py --json          # CI output
  python3 scripts/benchmark_local_models.py --threshold 30  # custom threshold

Tested: gemma3:1b scores 141.8 tok/s (PASS).

Closes #287
2026-04-13 17:46:53 -04:00
1ec02cf061 Merge pull request 'fix(gateway): reject known-weak placeholder tokens at startup' (#371) from fix/weak-credential-guard into main
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2026-04-13 20:33:00 +00:00
Alexander Whitestone
1156875cb5 fix(gateway): reject known-weak placeholder tokens at startup
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Fixes #318

Cherry-picked concept from ferris fork (f724079).

Problem: Users who copy .env.example without changing values
get confusing auth failures at gateway startup.

Fix: _guard_weak_credentials() checks TELEGRAM_BOT_TOKEN,
DISCORD_BOT_TOKEN, SLACK_BOT_TOKEN, HASS_TOKEN against
known-weak placeholder patterns (your-token-here, fake, xxx,
etc.) and minimum length requirements. Warns at startup.

Tests: 6 tests (no tokens, placeholder, case-insensitive,
short token, valid pass-through, multiple weak). All pass.
2026-04-13 16:32:56 -04:00
f4c102400e Merge pull request 'feat(memory): enable temporal decay with access-recency boost — #241' (#367) from feat/temporal-decay-holographic-memory into main
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Merge PR #367: feat(memory): enable temporal decay with access-recency boost
2026-04-13 19:51:04 +00:00
6555ccabc1 Merge pull request 'fix(tools): validate handler return types at dispatch boundary' (#369) from fix/tool-return-type-validation into main
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2026-04-13 19:47:56 +00:00
Alexander Whitestone
8c712866c4 fix(tools): validate handler return types at dispatch boundary
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Fixes #297

Problem: Tool handlers that return dict/list/None instead of a
JSON string crash the agent loop with cryptic errors. No error
proofing at the boundary.
Fix: In handle_function_call(), after dispatch returns:
1. If result is not str → wrap in JSON with _type_warning
2. If result is str but not valid JSON → wrap in {"output": ...}
3. Log type violations for analysis
4. Valid JSON strings pass through unchanged

Tests: 4 new tests (dict, None, non-JSON string, valid JSON).
All 16 tests in test_model_tools.py pass.
2026-04-13 15:47:52 -04:00
8fb59aae64 Merge pull request 'fix(tools): memory no-match is success, not error' (#368) from fix/memory-no-match-not-error into main
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2026-04-13 19:41:08 +00:00
Alexander Whitestone
95bde9d3cb fix(tools): memory no-match is success, not error
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Fixes #313

Problem: MemoryStore.replace() and .remove() return
{"success": false, "error": "No entry matched..."} when the
search substring is not found. This is a valid outcome, not
an error. The empirical audit showed 58.4% error rate on the
memory tool, but 98.4% of those were just empty search results.

Fix: Return {"success": true, "result": "no_match", "message": ...}
instead. This drops the memory tool error rate from ~58% to ~1%.

Tests updated: test_replace_no_match and test_remove_no_match
now assert success=True with result="no_match".
All 33 memory tool tests pass.
2026-04-13 15:40:48 -04:00
7 changed files with 507 additions and 14 deletions

View File

@@ -648,6 +648,51 @@ def load_gateway_config() -> GatewayConfig:
return config
# Known-weak placeholder tokens from .env.example, tutorials, etc.
_WEAK_TOKEN_PATTERNS = {
"your-token-here", "your_token_here", "your-token", "your_token",
"change-me", "change_me", "changeme",
"xxx", "xxxx", "xxxxx", "xxxxxxxx",
"test", "testing", "fake", "placeholder",
"replace-me", "replace_me", "replace this",
"insert-token-here", "put-your-token",
"bot-token", "bot_token",
"sk-xxxxxxxx", "sk-placeholder",
"BOT_TOKEN_HERE", "YOUR_BOT_TOKEN",
}
# Minimum token lengths by platform (tokens shorter than these are invalid)
_MIN_TOKEN_LENGTHS = {
"TELEGRAM_BOT_TOKEN": 30,
"DISCORD_BOT_TOKEN": 50,
"SLACK_BOT_TOKEN": 20,
"HASS_TOKEN": 20,
}
def _guard_weak_credentials() -> list[str]:
"""Check env vars for known-weak placeholder tokens.
Returns a list of warning messages for any weak credentials found.
"""
warnings = []
for env_var, min_len in _MIN_TOKEN_LENGTHS.items():
value = os.getenv(env_var, "").strip()
if not value:
continue
if value.lower() in _WEAK_TOKEN_PATTERNS:
warnings.append(
f"{env_var} is set to a placeholder value ('{value[:20]}'). "
f"Replace it with a real token."
)
elif len(value) < min_len:
warnings.append(
f"{env_var} is suspiciously short ({len(value)} chars, "
f"expected >{min_len}). May be truncated or invalid."
)
return warnings
def _apply_env_overrides(config: GatewayConfig) -> None:
"""Apply environment variable overrides to config."""
@@ -941,3 +986,7 @@ def _apply_env_overrides(config: GatewayConfig) -> None:
config.default_reset_policy.at_hour = int(reset_hour)
except ValueError:
pass
# Guard against weak placeholder tokens from .env.example copies
for warning in _guard_weak_credentials():
logger.warning("Weak credential: %s", warning)

View File

@@ -540,6 +540,29 @@ def handle_function_call(
except Exception:
pass
# Poka-yoke: validate tool handler return type.
# Handlers MUST return a JSON string. If they return dict/list/None,
# wrap the result so the agent loop doesn't crash with cryptic errors.
if not isinstance(result, str):
logger.warning(
"Tool '%s' returned %s instead of str — wrapping in JSON",
function_name, type(result).__name__,
)
result = json.dumps(
{"output": str(result), "_type_warning": f"Tool returned {type(result).__name__}, expected str"},
ensure_ascii=False,
)
else:
# Validate it's parseable JSON
try:
json.loads(result)
except (json.JSONDecodeError, TypeError):
logger.warning(
"Tool '%s' returned non-JSON string — wrapping in JSON",
function_name,
)
result = json.dumps({"output": result}, ensure_ascii=False)
return result
except Exception as e:

View File

@@ -0,0 +1,284 @@
#!/usr/bin/env python3
"""
Benchmark local Ollama models against the 50 tok/s UX threshold.
Usage:
python3 scripts/benchmark_local_models.py [--models MODEL1,MODEL2] [--prompt PROMPT] [--rounds N]
python3 scripts/benchmark_local_models.py --all # test all pulled models
python3 scripts/benchmark_local_models.py --json # JSON output for CI
"""
import argparse
import json
import os
import sys
import time
import urllib.request
import urllib.error
from dataclasses import dataclass, asdict
from typing import Optional
OLLAMA_BASE = os.environ.get("OLLAMA_BASE_URL", "http://localhost:11434")
THRESHOLD_TOK_S = 50.0
BENCHMARK_PROMPT = (
"Explain the difference between TCP and UDP protocols. "
"Cover reliability, ordering, speed, and use cases. "
"Be thorough but concise. Write at least 300 words."
)
@dataclass
class BenchmarkResult:
model: str
size_gb: float
prompt_tokens: int
eval_tokens: int
eval_duration_s: float
tokens_per_second: float
total_duration_s: float
rounds: int
avg_tok_s: float
meets_threshold: bool
error: Optional[str] = None
def get_models() -> list[dict]:
"""List all pulled Ollama models."""
url = f"{OLLAMA_BASE}/api/tags"
try:
req = urllib.request.Request(url)
with urllib.request.urlopen(req, timeout=10) as resp:
data = json.loads(resp.read())
return data.get("models", [])
except Exception as e:
print(f"Error connecting to Ollama at {OLLAMA_BASE}: {e}", file=sys.stderr)
sys.exit(1)
def benchmark_model(model: str, prompt: str, num_predict: int = 512) -> dict:
"""Run a single benchmark generation, return timing stats."""
url = f"{OLLAMA_BASE}/api/generate"
payload = json.dumps({
"model": model,
"prompt": prompt,
"stream": False,
"options": {
"num_predict": num_predict,
"temperature": 0.1, # low temp for consistent output
},
}).encode()
req = urllib.request.Request(url, data=payload, method="POST")
req.add_header("Content-Type", "application/json")
start = time.monotonic()
try:
with urllib.request.urlopen(req, timeout=300) as resp:
data = json.loads(resp.read())
except urllib.error.HTTPError as e:
body = e.read().decode() if e.fp else str(e)
raise RuntimeError(f"HTTP {e.code}: {body[:200]}")
except Exception as e:
raise RuntimeError(str(e))
elapsed = time.monotonic() - start
prompt_tokens = data.get("prompt_eval_count", 0)
eval_tokens = data.get("eval_count", 0)
eval_duration_ns = data.get("eval_duration", 0)
total_duration_ns = data.get("total_duration", 0)
eval_duration_s = eval_duration_ns / 1e9 if eval_duration_ns else elapsed
total_duration_s = total_duration_ns / 1e9 if total_duration_ns else elapsed
tok_s = eval_tokens / eval_duration_s if eval_duration_s > 0 else 0.0
return {
"prompt_tokens": prompt_tokens,
"eval_tokens": eval_tokens,
"eval_duration_s": round(eval_duration_s, 2),
"total_duration_s": round(total_duration_s, 2),
"tokens_per_second": round(tok_s, 1),
}
def run_benchmark(
model_name: str,
model_size: float,
prompt: str,
rounds: int,
num_predict: int,
threshold: float = 50.0,
) -> BenchmarkResult:
"""Run multiple rounds and compute average."""
results = []
errors = []
for i in range(rounds):
try:
r = benchmark_model(model_name, prompt, num_predict)
results.append(r)
print(f" Round {i+1}/{rounds}: {r['tokens_per_second']} tok/s "
f"({r['eval_tokens']} tokens in {r['eval_duration_s']}s)")
except Exception as e:
errors.append(str(e))
print(f" Round {i+1}/{rounds}: ERROR - {e}")
if not results:
return BenchmarkResult(
model=model_name,
size_gb=model_size,
prompt_tokens=0, eval_tokens=0,
eval_duration_s=0, tokens_per_second=0,
total_duration_s=0, rounds=rounds,
avg_tok_s=0, meets_threshold=False,
error="; ".join(errors),
)
avg_tok_s = sum(r["tokens_per_second"] for r in results) / len(results)
avg_tok_s = round(avg_tok_s, 1)
return BenchmarkResult(
model=model_name,
size_gb=model_size,
prompt_tokens=sum(r["prompt_tokens"] for r in results) // len(results),
eval_tokens=sum(r["eval_tokens"] for r in results) // len(results),
eval_duration_s=round(sum(r["eval_duration_s"] for r in results) / len(results), 2),
tokens_per_second=avg_tok_s,
total_duration_s=round(sum(r["total_duration_s"] for r in results) / len(results), 2),
rounds=len(results),
avg_tok_s=avg_tok_s,
meets_threshold=avg_tok_s >= threshold,
)
def format_report(results: list[BenchmarkResult], threshold: float = 50.0) -> str:
"""Format a human-readable benchmark report."""
lines = []
lines.append("")
lines.append("=" * 72)
lines.append(f" LOCAL MODEL BENCHMARK — {threshold:.0f} tok/s UX Threshold")
lines.append("=" * 72)
lines.append("")
# Summary table
header = f"{'Model':<25} {'Size':>6} {'tok/s':>8} {'Threshold':>10} {'Status':>8}"
lines.append(header)
lines.append("-" * 72)
passed = 0
failed = 0
errors = 0
for r in sorted(results, key=lambda x: x.avg_tok_s, reverse=True):
size_str = f"{r.size_gb:.1f}GB"
tok_s_str = f"{r.avg_tok_s:.1f}"
if r.error:
status = "ERROR"
errors += 1
elif r.meets_threshold:
status = "PASS"
passed += 1
else:
status = "FAIL"
failed += 1
marker = ">" if r.meets_threshold else "X" if r.error else "!"
thresh_str = f">= {threshold:.0f}"
lines.append(f" {marker} {r.model:<23} {size_str:>6} {tok_s_str:>8} {thresh_str:>10} {status:>8}")
lines.append("-" * 72)
lines.append(f" Passed: {passed} | Failed: {failed} | Errors: {errors} | Total: {len(results)}")
lines.append("")
# Detail section for failures
failures = [r for r in results if not r.meets_threshold and not r.error]
if failures:
lines.append(" FAILED MODELS (below threshold):")
for r in sorted(failures, key=lambda x: x.avg_tok_s):
gap = threshold - r.avg_tok_s
lines.append(f" - {r.model}: {r.avg_tok_s:.1f} tok/s "
f"({gap:.1f} tok/s short, {r.eval_tokens} avg tokens/round)")
lines.append("")
error_list = [r for r in results if r.error]
if error_list:
lines.append(" ERRORS:")
for r in error_list:
lines.append(f" - {r.model}: {r.error}")
lines.append("")
# Hardware info
import platform
lines.append(f" Host: {platform.node()} | {platform.system()} {platform.release()}")
lines.append(f" Ollama: {OLLAMA_BASE}")
lines.append("")
return "\n".join(lines)
def main():
parser = argparse.ArgumentParser(description="Benchmark local Ollama models vs 50 tok/s threshold")
parser.add_argument("--models", help="Comma-separated model names (default: all)")
parser.add_argument("--prompt", default=BENCHMARK_PROMPT, help="Benchmark prompt")
parser.add_argument("--rounds", type=int, default=3, help="Rounds per model (default: 3)")
parser.add_argument("--tokens", type=int, default=512, help="Max tokens to generate (default: 512)")
parser.add_argument("--json", action="store_true", help="JSON output for CI")
parser.add_argument("--all", action="store_true", help="Test all pulled models")
parser.add_argument("--threshold", type=float, default=THRESHOLD_TOK_S, help="tok/s threshold")
args = parser.parse_args()
threshold = args.threshold
# Get model list
available = get_models()
if not available:
print("No models found. Pull a model first: ollama pull <model>", file=sys.stderr)
sys.exit(1)
if args.models:
names = [m.strip() for m in args.models.split(",")]
models = [m for m in available if m["name"] in names]
missing = set(names) - set(m["name"] for m in models)
if missing:
print(f"Models not found: {', '.join(missing)}", file=sys.stderr)
print(f"Available: {', '.join(m['name'] for m in available)}", file=sys.stderr)
else:
models = available
print(f"Benchmarking {len(models)} model(s) against {threshold} tok/s threshold")
print(f"Ollama: {OLLAMA_BASE} | Rounds: {args.rounds} | Max tokens: {args.tokens}")
print()
results = []
for m in models:
name = m["name"]
size_gb = m.get("size", 0) / (1024**3)
print(f" {name} ({size_gb:.1f}GB):")
result = run_benchmark(name, size_gb, args.prompt, args.rounds, args.tokens, threshold)
results.append(result)
# Output
report = format_report(results, threshold)
if args.json:
output = {
"threshold_tok_s": threshold,
"ollama_base": OLLAMA_BASE,
"rounds": args.rounds,
"results": [asdict(r) for r in results],
"passed": sum(1 for r in results if r.meets_threshold),
"failed": sum(1 for r in results if not r.meets_threshold and not r.error),
"errors": sum(1 for r in results if r.error),
}
print(json.dumps(output, indent=2))
else:
print(report)
# Exit code: 0 if all pass, 1 if any fail/error
if any(not r.meets_threshold or r.error for r in results):
sys.exit(1)
sys.exit(0)
if __name__ == "__main__":
main()

View File

@@ -0,0 +1,52 @@
"""Tests for weak credential guard in gateway/config.py."""
import os
import pytest
from gateway.config import _guard_weak_credentials, _WEAK_TOKEN_PATTERNS, _MIN_TOKEN_LENGTHS
class TestWeakCredentialGuard:
"""Tests for _guard_weak_credentials()."""
def test_no_tokens_set(self, monkeypatch):
"""When no relevant tokens are set, no warnings."""
for var in _MIN_TOKEN_LENGTHS:
monkeypatch.delenv(var, raising=False)
warnings = _guard_weak_credentials()
assert warnings == []
def test_placeholder_token_detected(self, monkeypatch):
"""Known-weak placeholder tokens are flagged."""
monkeypatch.setenv("TELEGRAM_BOT_TOKEN", "your-token-here")
warnings = _guard_weak_credentials()
assert len(warnings) == 1
assert "TELEGRAM_BOT_TOKEN" in warnings[0]
assert "placeholder" in warnings[0].lower()
def test_case_insensitive_match(self, monkeypatch):
"""Placeholder detection is case-insensitive."""
monkeypatch.setenv("DISCORD_BOT_TOKEN", "FAKE")
warnings = _guard_weak_credentials()
assert len(warnings) == 1
assert "DISCORD_BOT_TOKEN" in warnings[0]
def test_short_token_detected(self, monkeypatch):
"""Suspiciously short tokens are flagged."""
monkeypatch.setenv("TELEGRAM_BOT_TOKEN", "abc123") # 6 chars, min is 30
warnings = _guard_weak_credentials()
assert len(warnings) == 1
assert "short" in warnings[0].lower()
def test_valid_token_passes(self, monkeypatch):
"""A long, non-placeholder token produces no warnings."""
monkeypatch.setenv("TELEGRAM_BOT_TOKEN", "1234567890:ABCDEFGHIJKLMNOPQRSTUVWXYZ1234567")
warnings = _guard_weak_credentials()
assert warnings == []
def test_multiple_weak_tokens(self, monkeypatch):
"""Multiple weak tokens each produce a warning."""
monkeypatch.setenv("TELEGRAM_BOT_TOKEN", "change-me")
monkeypatch.setenv("DISCORD_BOT_TOKEN", "xx") # short
warnings = _guard_weak_credentials()
assert len(warnings) == 2

View File

@@ -137,3 +137,78 @@ class TestBackwardCompat:
def test_tool_to_toolset_map(self):
assert isinstance(TOOL_TO_TOOLSET_MAP, dict)
assert len(TOOL_TO_TOOLSET_MAP) > 0
class TestToolReturnTypeValidation:
"""Poka-yoke: tool handlers must return JSON strings."""
def test_handler_returning_dict_is_wrapped(self, monkeypatch):
"""A handler that returns a dict should be auto-wrapped to JSON string."""
from tools.registry import registry
from model_tools import handle_function_call
import json
# Register a bad handler that returns dict instead of str
registry.register(
name="__test_bad_dict",
toolset="test",
schema={"name": "__test_bad_dict", "description": "test", "parameters": {"type": "object", "properties": {}}},
handler=lambda args, **kw: {"this is": "a dict not a string"},
)
result = handle_function_call("__test_bad_dict", {})
parsed = json.loads(result)
assert "output" in parsed
assert "_type_warning" in parsed
# Cleanup
registry._tools.pop("__test_bad_dict", None)
def test_handler_returning_none_is_wrapped(self, monkeypatch):
"""A handler that returns None should be auto-wrapped."""
from tools.registry import registry
from model_tools import handle_function_call
import json
registry.register(
name="__test_bad_none",
toolset="test",
schema={"name": "__test_bad_none", "description": "test", "parameters": {"type": "object", "properties": {}}},
handler=lambda args, **kw: None,
)
result = handle_function_call("__test_bad_none", {})
parsed = json.loads(result)
assert "_type_warning" in parsed
registry._tools.pop("__test_bad_none", None)
def test_handler_returning_non_json_string_is_wrapped(self):
"""A handler returning a plain string (not JSON) should be wrapped."""
from tools.registry import registry
from model_tools import handle_function_call
import json
registry.register(
name="__test_bad_plain",
toolset="test",
schema={"name": "__test_bad_plain", "description": "test", "parameters": {"type": "object", "properties": {}}},
handler=lambda args, **kw: "just a plain string, not json",
)
result = handle_function_call("__test_bad_plain", {})
parsed = json.loads(result)
assert "output" in parsed
registry._tools.pop("__test_bad_plain", None)
def test_handler_returning_valid_json_passes_through(self):
"""A handler returning valid JSON string passes through unchanged."""
from tools.registry import registry
from model_tools import handle_function_call
import json
registry.register(
name="__test_good",
toolset="test",
schema={"name": "__test_good", "description": "test", "parameters": {"type": "object", "properties": {}}},
handler=lambda args, **kw: json.dumps({"status": "ok", "data": [1, 2, 3]}),
)
result = handle_function_call("__test_good", {})
parsed = json.loads(result)
assert parsed == {"status": "ok", "data": [1, 2, 3]}
registry._tools.pop("__test_good", None)

View File

@@ -144,7 +144,8 @@ class TestMemoryStoreReplace:
def test_replace_no_match(self, store):
store.add("memory", "fact A")
result = store.replace("memory", "nonexistent", "new")
assert result["success"] is False
assert result["success"] is True
assert result["result"] == "no_match"
def test_replace_ambiguous_match(self, store):
store.add("memory", "server A runs nginx")
@@ -177,7 +178,8 @@ class TestMemoryStoreRemove:
def test_remove_no_match(self, store):
result = store.remove("memory", "nonexistent")
assert result["success"] is False
assert result["success"] is True
assert result["result"] == "no_match"
def test_remove_empty_old_text(self, store):
result = store.remove("memory", " ")

View File

@@ -260,8 +260,12 @@ class MemoryStore:
entries = self._entries_for(target)
matches = [(i, e) for i, e in enumerate(entries) if old_text in e]
if len(matches) == 0:
return {"success": False, "error": f"No entry matched '{old_text}'."}
if not matches:
return {
"success": True,
"result": "no_match",
"message": f"No entry matched '{old_text}'. The search substring was not found in any existing entry.",
}
if len(matches) > 1:
# If all matches are identical (exact duplicates), operate on the first one
@@ -310,8 +314,12 @@ class MemoryStore:
entries = self._entries_for(target)
matches = [(i, e) for i, e in enumerate(entries) if old_text in e]
if len(matches) == 0:
return {"success": False, "error": f"No entry matched '{old_text}'."}
if not matches:
return {
"success": True,
"result": "no_match",
"message": f"No entry matched '{old_text}'. The search substring was not found in any existing entry.",
}
if len(matches) > 1:
# If all matches are identical (exact duplicates), remove the first one
@@ -449,30 +457,30 @@ def memory_tool(
Returns JSON string with results.
"""
if store is None:
return json.dumps({"success": False, "error": "Memory is not available. It may be disabled in config or this environment."}, ensure_ascii=False)
return tool_error("Memory is not available. It may be disabled in config or this environment.", success=False)
if target not in ("memory", "user"):
return json.dumps({"success": False, "error": f"Invalid target '{target}'. Use 'memory' or 'user'."}, ensure_ascii=False)
return tool_error(f"Invalid target '{target}'. Use 'memory' or 'user'.", success=False)
if action == "add":
if not content:
return json.dumps({"success": False, "error": "Content is required for 'add' action."}, ensure_ascii=False)
return tool_error("Content is required for 'add' action.", success=False)
result = store.add(target, content)
elif action == "replace":
if not old_text:
return json.dumps({"success": False, "error": "old_text is required for 'replace' action."}, ensure_ascii=False)
return tool_error("old_text is required for 'replace' action.", success=False)
if not content:
return json.dumps({"success": False, "error": "content is required for 'replace' action."}, ensure_ascii=False)
return tool_error("content is required for 'replace' action.", success=False)
result = store.replace(target, old_text, content)
elif action == "remove":
if not old_text:
return json.dumps({"success": False, "error": "old_text is required for 'remove' action."}, ensure_ascii=False)
return tool_error("old_text is required for 'remove' action.", success=False)
result = store.remove(target, old_text)
else:
return json.dumps({"success": False, "error": f"Unknown action '{action}'. Use: add, replace, remove"}, ensure_ascii=False)
return tool_error(f"Unknown action '{action}'. Use: add, replace, remove", success=False)
return json.dumps(result, ensure_ascii=False)
@@ -539,7 +547,7 @@ MEMORY_SCHEMA = {
# --- Registry ---
from tools.registry import registry
from tools.registry import registry, tool_error
registry.register(
name="memory",