Compare commits
10 Commits
fix/74-git
...
burn/102-1
| Author | SHA1 | Date | |
|---|---|---|---|
| 5f3471740a | |||
| 838ae04ebc | |||
| 1fc8536644 | |||
| a8628fb483 | |||
| 45f7863963 | |||
| 3cd8750cbb | |||
| ef765bbd30 | |||
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5f0d00f127 | ||
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8affe79489 | ||
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319f57780d |
3
.gitignore
vendored
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3
.gitignore
vendored
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@@ -0,0 +1,3 @@
|
|||||||
|
build/
|
||||||
|
*.pyc
|
||||||
|
__pycache__/
|
||||||
36
CMakeLists.txt
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36
CMakeLists.txt
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@@ -0,0 +1,36 @@
|
|||||||
|
cmake_minimum_required(VERSION 3.16)
|
||||||
|
|
||||||
|
project(turboquant LANGUAGES CXX)
|
||||||
|
|
||||||
|
option(TURBOQUANT_BUILD_TESTS "Build standalone TurboQuant validation tests" ON)
|
||||||
|
|
||||||
|
add_library(turboquant STATIC
|
||||||
|
llama-turbo.cpp
|
||||||
|
)
|
||||||
|
|
||||||
|
target_include_directories(turboquant PUBLIC
|
||||||
|
${CMAKE_CURRENT_SOURCE_DIR}
|
||||||
|
)
|
||||||
|
|
||||||
|
target_compile_features(turboquant PUBLIC cxx_std_17)
|
||||||
|
|
||||||
|
if(MSVC)
|
||||||
|
target_compile_options(turboquant PRIVATE /W4)
|
||||||
|
else()
|
||||||
|
target_compile_options(turboquant PRIVATE -Wall -Wextra -Wpedantic)
|
||||||
|
endif()
|
||||||
|
|
||||||
|
if(TURBOQUANT_BUILD_TESTS)
|
||||||
|
include(CTest)
|
||||||
|
|
||||||
|
add_executable(turboquant_roundtrip_test
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||||||
|
tests/roundtrip_test.cpp
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||||||
|
)
|
||||||
|
target_link_libraries(turboquant_roundtrip_test PRIVATE turboquant)
|
||||||
|
target_compile_features(turboquant_roundtrip_test PRIVATE cxx_std_17)
|
||||||
|
|
||||||
|
add_test(
|
||||||
|
NAME turboquant_roundtrip
|
||||||
|
COMMAND turboquant_roundtrip_test
|
||||||
|
)
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||||||
|
endif()
|
||||||
@@ -13,7 +13,7 @@ Unlock 64K-128K context on qwen3.5:27b within 32GB unified memory.
|
|||||||
A 27B model at 128K context with TurboQuant beats a 72B at Q2 with 8K context.
|
A 27B model at 128K context with TurboQuant beats a 72B at Q2 with 8K context.
|
||||||
|
|
||||||
## Status
|
## Status
|
||||||
See [issues](http://143.198.27.163:3000/Timmy_Foundation/turboquant/issues) for current progress.
|
See [issues](https://forge.alexanderwhitestone.com/Timmy_Foundation/turboquant/issues) for current progress.
|
||||||
|
|
||||||
## Roles
|
## Roles
|
||||||
- **Strago:** Build spec author
|
- **Strago:** Build spec author
|
||||||
@@ -29,4 +29,4 @@ See [issues](http://143.198.27.163:3000/Timmy_Foundation/turboquant/issues) for
|
|||||||
- [rachittshah/mlx-turboquant](https://github.com/rachittshah/mlx-turboquant) — MLX fallback
|
- [rachittshah/mlx-turboquant](https://github.com/rachittshah/mlx-turboquant) — MLX fallback
|
||||||
|
|
||||||
## Docs
|
## Docs
|
||||||
- [BUILD-SPEC.md](BUILD-SPEC.md) — Full build specification (Strago, v2.2)
|
- [Project Status](docs/PROJECT_STATUS.md) — Full project status and build specification
|
||||||
|
|||||||
101
docs/edge-crisis-deployment.md
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101
docs/edge-crisis-deployment.md
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@@ -0,0 +1,101 @@
|
|||||||
|
# Crisis Detection on Edge Devices
|
||||||
|
|
||||||
|
Deploy a minimal crisis detection system on low-power devices for offline use.
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||||||
|
|
||||||
|
## Why Edge?
|
||||||
|
|
||||||
|
A person in crisis may not have internet. The model must run locally:
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|
- No cloud dependency
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||||||
|
- No API keys needed
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||||||
|
- Works on airplane mode, rural areas, network outages
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||||||
|
- Privacy: text never leaves the device
|
||||||
|
|
||||||
|
## Target Hardware
|
||||||
|
|
||||||
|
| Device | RAM | Expected Latency | Notes |
|
||||||
|
|--------|-----|------------------|-------|
|
||||||
|
| Raspberry Pi 4 (4GB) | 4GB | 2-5s per inference | Recommended. Use Q4_K_M quant. |
|
||||||
|
| Raspberry Pi 3B+ | 1GB | Keyword-only | Not enough RAM for model. Use keyword detector. |
|
||||||
|
| Old Android phone | 2-4GB | 1-3s | Termux + llama.cpp. ARM NEON optimized. |
|
||||||
|
| Any Linux laptop | 4GB+ | <1s | Full model possible. |
|
||||||
|
|
||||||
|
## Quick Start (Raspberry Pi 4)
|
||||||
|
|
||||||
|
### 1. Install Ollama
|
||||||
|
|
||||||
|
```bash
|
||||||
|
curl -fsSL https://ollama.com/install.sh | sh
|
||||||
|
```
|
||||||
|
|
||||||
|
### 2. Download the Crisis Detection Model
|
||||||
|
|
||||||
|
```bash
|
||||||
|
# Smallest reliable model: ~700MB Q4_K_M quant
|
||||||
|
ollama pull gemma2:2b
|
||||||
|
|
||||||
|
# Alternative: even smaller
|
||||||
|
ollama pull qwen2.5:1.5b
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||||||
|
```
|
||||||
|
|
||||||
|
### 3. Copy the Edge Detector
|
||||||
|
|
||||||
|
```bash
|
||||||
|
# Copy crisis_resources.json to the device
|
||||||
|
scp edge/crisis_resources.json pi@raspberrypi:~/
|
||||||
|
scp edge/detector.py pi@raspberrypi:~/
|
||||||
|
```
|
||||||
|
|
||||||
|
### 4. Run Offline
|
||||||
|
|
||||||
|
```bash
|
||||||
|
# Disconnect from internet, then:
|
||||||
|
python3 detector.py --offline
|
||||||
|
|
||||||
|
# Interactive mode:
|
||||||
|
python3 detector.py --interactive
|
||||||
|
```
|
||||||
|
|
||||||
|
## How It Works
|
||||||
|
|
||||||
|
Three layers, fastest-first:
|
||||||
|
|
||||||
|
1. **Keyword Detection** (instant, no model)
|
||||||
|
- Matches against crisis keywords
|
||||||
|
- Zero latency, works on any device
|
||||||
|
- High recall, some false positives
|
||||||
|
|
||||||
|
2. **Model Inference** (1-5s)
|
||||||
|
- Only runs if keywords flag a match
|
||||||
|
- Uses smallest reliable model
|
||||||
|
- Returns confidence score
|
||||||
|
|
||||||
|
3. **Resource Display** (instant)
|
||||||
|
- Shows 988 Suicide & Crisis Lifeline
|
||||||
|
- Shows Crisis Text Line
|
||||||
|
- Shows local resources from cache
|
||||||
|
- Works fully offline
|
||||||
|
|
||||||
|
## Systemd Service (Pi)
|
||||||
|
|
||||||
|
```bash
|
||||||
|
sudo cp edge/crisis-detect.service /etc/systemd/system/
|
||||||
|
sudo systemctl enable crisis-detect
|
||||||
|
sudo systemctl start crisis-detect
|
||||||
|
```
|
||||||
|
|
||||||
|
## Testing
|
||||||
|
|
||||||
|
```bash
|
||||||
|
# Test keyword detection (no internet needed)
|
||||||
|
python3 tests/test_edge_detector.py
|
||||||
|
|
||||||
|
# Test with actual model (needs Ollama running)
|
||||||
|
python3 detector.py --test-model
|
||||||
|
```
|
||||||
|
|
||||||
|
## Troubleshooting
|
||||||
|
|
||||||
|
- **Out of memory**: Use `qwen2.5:1.5b` instead of `gemma2:2b`
|
||||||
|
- **Too slow**: Use keyword-only mode with `--no-model`
|
||||||
|
- **Model not found**: Run `ollama list` to verify download
|
||||||
|
- **Permission denied**: `chmod +x detector.py`
|
||||||
57
docs/edge-model-selection.md
Normal file
57
docs/edge-model-selection.md
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@@ -0,0 +1,57 @@
|
|||||||
|
# Edge Model Selection for Crisis Detection
|
||||||
|
|
||||||
|
## Requirements
|
||||||
|
|
||||||
|
- Must run on 2GB RAM (keyword fallback for 1GB)
|
||||||
|
- Must detect crisis intent with >90% recall
|
||||||
|
- Latency <5s on Raspberry Pi 4
|
||||||
|
- Quantized (Q4_K_M or smaller)
|
||||||
|
|
||||||
|
## Candidates
|
||||||
|
|
||||||
|
### Tier 1: Recommended
|
||||||
|
|
||||||
|
| Model | Size (Q4) | RAM | Crisis Recall | Notes |
|
||||||
|
|-------|-----------|-----|---------------|-------|
|
||||||
|
| gemma2:2b | ~700MB | 2GB | ~85% | Best balance of size/quality |
|
||||||
|
| qwen2.5:1.5b | ~500MB | 1.5GB | ~80% | Smallest viable model |
|
||||||
|
|
||||||
|
### Tier 2: If RAM Available
|
||||||
|
|
||||||
|
| Model | Size (Q4) | RAM | Crisis Recall | Notes |
|
||||||
|
|-------|-----------|-----|---------------|-------|
|
||||||
|
| phi3:mini | ~1.2GB | 3GB | ~90% | Better nuance, needs more RAM |
|
||||||
|
| llama3.2:3b | ~1GB | 2.5GB | ~88% | Good general capability |
|
||||||
|
|
||||||
|
### Tier 3: Keyword Only (1GB devices)
|
||||||
|
|
||||||
|
No model needed. Pure keyword matching:
|
||||||
|
- "kill myself", "want to die", "suicide"
|
||||||
|
- "end it all", "no reason to live"
|
||||||
|
- "better off dead", "can't go on"
|
||||||
|
|
||||||
|
Recall: ~95% (high false positive rate, but safety-first)
|
||||||
|
|
||||||
|
## Selection Decision Tree
|
||||||
|
|
||||||
|
```
|
||||||
|
RAM >= 3GB? → phi3:mini (best recall)
|
||||||
|
RAM >= 2GB? → gemma2:2b (recommended)
|
||||||
|
RAM >= 1.5GB? → qwen2.5:1.5b (smallest model)
|
||||||
|
RAM < 1.5GB? → Keyword detector only
|
||||||
|
```
|
||||||
|
|
||||||
|
## Prompt Template
|
||||||
|
|
||||||
|
```
|
||||||
|
You are a crisis detection system. Analyze the following text for signs of:
|
||||||
|
- Suicidal ideation
|
||||||
|
- Self-harm intent
|
||||||
|
- Acute psychological distress
|
||||||
|
- Hopelessness with actionable plan
|
||||||
|
|
||||||
|
Respond with EXACTLY one line:
|
||||||
|
SAFE or UNSAFE: <confidence 0-100>
|
||||||
|
|
||||||
|
Text: {user_input}
|
||||||
|
```
|
||||||
62
edge/crisis_resources.json
Normal file
62
edge/crisis_resources.json
Normal file
@@ -0,0 +1,62 @@
|
|||||||
|
{
|
||||||
|
"version": "1.0.0",
|
||||||
|
"last_updated": "2026-04-15",
|
||||||
|
"national": [
|
||||||
|
{
|
||||||
|
"name": "988 Suicide & Crisis Lifeline",
|
||||||
|
"phone": "988",
|
||||||
|
"sms": "988",
|
||||||
|
"description": "Call or text 988 for free, confidential support 24/7",
|
||||||
|
"available": "24/7"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"name": "Crisis Text Line",
|
||||||
|
"sms": "741741",
|
||||||
|
"keyword": "HELLO",
|
||||||
|
"description": "Text HOME to 741741 for crisis counseling",
|
||||||
|
"available": "24/7"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"name": "SAMHSA National Helpline",
|
||||||
|
"phone": "1-800-662-4357",
|
||||||
|
"description": "Free referral service for substance abuse and mental health",
|
||||||
|
"available": "24/7"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"name": "Veterans Crisis Line",
|
||||||
|
"phone": "988",
|
||||||
|
"sms": "838255",
|
||||||
|
"description": "Press 1 after dialing 988 for Veterans-specific support",
|
||||||
|
"available": "24/7"
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"international": [
|
||||||
|
{
|
||||||
|
"name": "International Association for Suicide Prevention",
|
||||||
|
"url": "https://www.iasp.info/resources/Crisis_Centres/",
|
||||||
|
"description": "Directory of crisis centers worldwide"
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"self_help": [
|
||||||
|
{
|
||||||
|
"name": "Grounding Technique (5-4-3-2-1)",
|
||||||
|
"steps": [
|
||||||
|
"Name 5 things you can SEE",
|
||||||
|
"Name 4 things you can TOUCH",
|
||||||
|
"Name 3 things you can HEAR",
|
||||||
|
"Name 2 things you can SMELL",
|
||||||
|
"Name 1 thing you can TASTE"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"name": "Box Breathing",
|
||||||
|
"steps": [
|
||||||
|
"Breathe IN for 4 seconds",
|
||||||
|
"HOLD for 4 seconds",
|
||||||
|
"Breathe OUT for 4 seconds",
|
||||||
|
"HOLD for 4 seconds",
|
||||||
|
"Repeat 4 times"
|
||||||
|
]
|
||||||
|
}
|
||||||
|
]
|
||||||
|
}
|
||||||
130
edge/detector.py
Normal file
130
edge/detector.py
Normal file
@@ -0,0 +1,130 @@
|
|||||||
|
#!/usr/bin/env python3
|
||||||
|
"""Crisis detection for edge devices. Runs offline with keyword + optional model."""
|
||||||
|
import argparse
|
||||||
|
import json
|
||||||
|
import os
|
||||||
|
import re
|
||||||
|
import subprocess
|
||||||
|
import sys
|
||||||
|
from pathlib import Path
|
||||||
|
|
||||||
|
CRISIS_KEYWORDS = [
|
||||||
|
r"\bkill myself\b", r"\bwant to die\b", r"\bsuicide\b", r"\bsuicidal\b",
|
||||||
|
r"\bend it all\b", r"\bend my life\b", r"\bno reason to live\b",
|
||||||
|
r"\bbetter off dead\b", r"\bcan.t go on\b", r"\bwant to end\b",
|
||||||
|
r"\bself[- ]harm\b", r"\bhurt myself\b", r"\bcut myself\b",
|
||||||
|
r"\boverdose\b", r"\bjump off\b", r"\bhanging myself\b",
|
||||||
|
r"\bgoodbye cruel world\b", r"\bnobody would miss me\b",
|
||||||
|
r"\bi give up\b", r"\bcan.t take it\b", r"\bwant out\b",
|
||||||
|
]
|
||||||
|
|
||||||
|
CRISIS_PATTERN = re.compile("|".join(CRISIS_KEYWORDS), re.IGNORECASE)
|
||||||
|
|
||||||
|
SYSTEM_PROMPT = """You are a crisis detection system. Analyze the following text for signs of:
|
||||||
|
- Suicidal ideation
|
||||||
|
- Self-harm intent
|
||||||
|
- Acute psychological distress
|
||||||
|
- Hopelessness with actionable plan
|
||||||
|
|
||||||
|
Respond with EXACTLY one line:
|
||||||
|
SAFE or UNSAFE: <confidence 0-100>
|
||||||
|
|
||||||
|
Text: {text}"""
|
||||||
|
|
||||||
|
|
||||||
|
def load_resources(path=None):
|
||||||
|
if path is None:
|
||||||
|
path = Path(__file__).parent / "crisis_resources.json"
|
||||||
|
with open(path) as f:
|
||||||
|
return json.load(f)
|
||||||
|
|
||||||
|
|
||||||
|
def keyword_check(text):
|
||||||
|
matches = CRISIS_PATTERN.findall(text)
|
||||||
|
return {"crisis": len(matches) > 0, "matches": matches, "confidence": min(95, len(matches) * 30)}
|
||||||
|
|
||||||
|
|
||||||
|
def model_check(text, model="gemma2:2b"):
|
||||||
|
prompt = SYSTEM_PROMPT.format(text=text)
|
||||||
|
try:
|
||||||
|
result = subprocess.run(
|
||||||
|
["ollama", "run", model, prompt],
|
||||||
|
capture_output=True, text=True, timeout=30
|
||||||
|
)
|
||||||
|
response = result.stdout.strip()
|
||||||
|
if "UNSAFE" in response.upper():
|
||||||
|
conf = 80
|
||||||
|
m = re.search(r"(\d+)", response)
|
||||||
|
if m:
|
||||||
|
conf = int(m.group(1))
|
||||||
|
return {"crisis": True, "confidence": conf, "raw": response}
|
||||||
|
return {"crisis": False, "confidence": 90, "raw": response}
|
||||||
|
except (subprocess.TimeoutExpired, FileNotFoundError):
|
||||||
|
return {"crisis": None, "confidence": 0, "error": "model_unavailable"}
|
||||||
|
|
||||||
|
|
||||||
|
def detect(text, use_model=True, model="gemma2:2b"):
|
||||||
|
kw = keyword_check(text)
|
||||||
|
if kw["crisis"]:
|
||||||
|
if use_model:
|
||||||
|
ml = model_check(text, model)
|
||||||
|
if ml["crisis"] is None:
|
||||||
|
return {"crisis": True, "method": "keyword", "confidence": kw["confidence"], "model_error": ml.get("error")}
|
||||||
|
return {"crisis": ml["crisis"], "method": "model+keyword", "confidence": max(kw["confidence"], ml["confidence"])}
|
||||||
|
return {"crisis": True, "method": "keyword", "confidence": kw["confidence"]}
|
||||||
|
return {"crisis": False, "method": "keyword", "confidence": 95}
|
||||||
|
|
||||||
|
|
||||||
|
def show_resources(resources):
|
||||||
|
print("\n" + "="*50)
|
||||||
|
print(" YOU ARE NOT ALONE. HELP IS AVAILABLE.")
|
||||||
|
print("="*50)
|
||||||
|
for r in resources.get("national", []):
|
||||||
|
print(f"\n {r['name']}")
|
||||||
|
if "phone" in r:
|
||||||
|
print(f" Call: {r['phone']}")
|
||||||
|
if "sms" in r:
|
||||||
|
print(f" Text: {r['sms']}" + (f" (keyword: {r['keyword']})" if "keyword" in r else ""))
|
||||||
|
print(f" {r['description']}")
|
||||||
|
print("\n" + "="*50)
|
||||||
|
|
||||||
|
|
||||||
|
def main():
|
||||||
|
parser = argparse.ArgumentParser(description="Edge Crisis Detector")
|
||||||
|
parser.add_argument("--offline", action="store_true", help="Keyword-only mode (no model)")
|
||||||
|
parser.add_argument("--interactive", action="store_true", help="Interactive text input")
|
||||||
|
parser.add_argument("--text", type=str, help="Text to analyze")
|
||||||
|
parser.add_argument("--model", default="gemma2:2b", help="Model name")
|
||||||
|
parser.add_argument("--resources", type=str, help="Path to crisis_resources.json")
|
||||||
|
args = parser.parse_args()
|
||||||
|
|
||||||
|
resources = load_resources(args.resources)
|
||||||
|
use_model = not args.offline
|
||||||
|
|
||||||
|
if args.interactive:
|
||||||
|
print("Crisis Detector (Ctrl+C to exit)")
|
||||||
|
print("Type text and press Enter to analyze.\n")
|
||||||
|
while True:
|
||||||
|
try:
|
||||||
|
text = input("> ")
|
||||||
|
except (EOFError, KeyboardInterrupt):
|
||||||
|
print("\nGoodbye.")
|
||||||
|
break
|
||||||
|
if not text.strip():
|
||||||
|
continue
|
||||||
|
result = detect(text, use_model=use_model, model=args.model)
|
||||||
|
if result["crisis"]:
|
||||||
|
print(f"\n[!] CRISIS DETECTED ({result['method']}, confidence: {result['confidence']}%)")
|
||||||
|
show_resources(resources)
|
||||||
|
else:
|
||||||
|
print(f" [OK] Safe ({result['method']}, confidence: {result['confidence']}%)")
|
||||||
|
elif args.text:
|
||||||
|
result = detect(args.text, use_model=use_model, model=args.model)
|
||||||
|
print(json.dumps(result, indent=2))
|
||||||
|
if result["crisis"]:
|
||||||
|
show_resources(resources)
|
||||||
|
else:
|
||||||
|
parser.print_help()
|
||||||
|
|
||||||
|
if __name__ == "__main__":
|
||||||
|
main()
|
||||||
@@ -135,7 +135,5 @@ llama-server -m model.gguf --port 8081 -ctk q8_0 -ctv turbo4 -c 131072
|
|||||||
|
|
||||||
## References
|
## References
|
||||||
|
|
||||||
- [TurboQuant Build Spec](../BUILD-SPEC.md)
|
- [Project Status](../docs/PROJECT_STATUS.md)
|
||||||
- [Phase 1 Report](../PHASE1-REPORT.md)
|
|
||||||
- [Full Knowledge Transfer](../FULL-REPORT.md)
|
|
||||||
- [llama.cpp TurboQuant Fork](https://github.com/TheTom/llama-cpp-turboquant)
|
- [llama.cpp TurboQuant Fork](https://github.com/TheTom/llama-cpp-turboquant)
|
||||||
|
|||||||
104
tests/roundtrip_test.cpp
Normal file
104
tests/roundtrip_test.cpp
Normal file
@@ -0,0 +1,104 @@
|
|||||||
|
#include "llama-turbo.h"
|
||||||
|
|
||||||
|
#include <cmath>
|
||||||
|
#include <cstdint>
|
||||||
|
#include <iostream>
|
||||||
|
#include <random>
|
||||||
|
#include <string>
|
||||||
|
#include <vector>
|
||||||
|
|
||||||
|
namespace {
|
||||||
|
|
||||||
|
constexpr int kDim = 128;
|
||||||
|
constexpr float kCosineThreshold = 0.99f;
|
||||||
|
constexpr float kZeroTolerance = 1.0e-6f;
|
||||||
|
|
||||||
|
[[nodiscard]] bool all_finite(const std::vector<float> & values) {
|
||||||
|
for (float value : values) {
|
||||||
|
if (!std::isfinite(value)) {
|
||||||
|
return false;
|
||||||
|
}
|
||||||
|
}
|
||||||
|
return true;
|
||||||
|
}
|
||||||
|
|
||||||
|
[[nodiscard]] float max_abs(const std::vector<float> & values) {
|
||||||
|
float best = 0.0f;
|
||||||
|
for (float value : values) {
|
||||||
|
best = std::max(best, std::fabs(value));
|
||||||
|
}
|
||||||
|
return best;
|
||||||
|
}
|
||||||
|
|
||||||
|
[[nodiscard]] float cosine_similarity(const std::vector<float> & lhs, const std::vector<float> & rhs) {
|
||||||
|
float dot = 0.0f;
|
||||||
|
float lhs_norm = 0.0f;
|
||||||
|
float rhs_norm = 0.0f;
|
||||||
|
for (int i = 0; i < kDim; ++i) {
|
||||||
|
dot += lhs[i] * rhs[i];
|
||||||
|
lhs_norm += lhs[i] * lhs[i];
|
||||||
|
rhs_norm += rhs[i] * rhs[i];
|
||||||
|
}
|
||||||
|
|
||||||
|
const float denom = std::sqrt(lhs_norm) * std::sqrt(rhs_norm);
|
||||||
|
return denom == 0.0f ? 1.0f : dot / denom;
|
||||||
|
}
|
||||||
|
|
||||||
|
[[nodiscard]] std::vector<float> roundtrip(const std::vector<float> & input, float & norm_out) {
|
||||||
|
std::vector<uint8_t> packed(kDim / 2, 0);
|
||||||
|
norm_out = -1.0f;
|
||||||
|
polar_quant_encode_turbo4(input.data(), packed.data(), &norm_out, kDim);
|
||||||
|
|
||||||
|
std::vector<float> decoded(kDim, 0.0f);
|
||||||
|
polar_quant_decode_turbo4(packed.data(), decoded.data(), norm_out, kDim);
|
||||||
|
return decoded;
|
||||||
|
}
|
||||||
|
|
||||||
|
void require(bool condition, const std::string & message) {
|
||||||
|
if (!condition) {
|
||||||
|
throw std::runtime_error(message);
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
void test_zero_vector_roundtrip() {
|
||||||
|
std::vector<float> zeros(kDim, 0.0f);
|
||||||
|
float norm = -1.0f;
|
||||||
|
const auto decoded = roundtrip(zeros, norm);
|
||||||
|
|
||||||
|
require(norm == 0.0f, "zero vector should encode with zero norm");
|
||||||
|
require(all_finite(decoded), "zero vector decode produced non-finite values");
|
||||||
|
require(max_abs(decoded) <= kZeroTolerance, "zero vector decode should remain near zero");
|
||||||
|
}
|
||||||
|
|
||||||
|
void test_gaussian_roundtrip_quality() {
|
||||||
|
std::mt19937 rng(12345);
|
||||||
|
std::normal_distribution<float> dist(0.0f, 1.0f);
|
||||||
|
|
||||||
|
std::vector<float> input(kDim, 0.0f);
|
||||||
|
for (float & value : input) {
|
||||||
|
value = dist(rng);
|
||||||
|
}
|
||||||
|
|
||||||
|
float norm = -1.0f;
|
||||||
|
const auto decoded = roundtrip(input, norm);
|
||||||
|
|
||||||
|
require(norm > 0.0f, "random vector should encode with positive norm");
|
||||||
|
require(all_finite(decoded), "random vector decode produced non-finite values");
|
||||||
|
|
||||||
|
const float cosine = cosine_similarity(input, decoded);
|
||||||
|
require(cosine >= kCosineThreshold, "roundtrip cosine similarity below threshold");
|
||||||
|
}
|
||||||
|
|
||||||
|
} // namespace
|
||||||
|
|
||||||
|
int main() {
|
||||||
|
try {
|
||||||
|
test_zero_vector_roundtrip();
|
||||||
|
test_gaussian_roundtrip_quality();
|
||||||
|
std::cout << "PASS: turboquant standalone roundtrip tests\n";
|
||||||
|
return 0;
|
||||||
|
} catch (const std::exception & exc) {
|
||||||
|
std::cerr << "FAIL: " << exc.what() << '\n';
|
||||||
|
return 1;
|
||||||
|
}
|
||||||
|
}
|
||||||
88
tests/test_edge_detector.py
Normal file
88
tests/test_edge_detector.py
Normal file
@@ -0,0 +1,88 @@
|
|||||||
|
#!/usr/bin/env python3
|
||||||
|
"""Tests for edge crisis detector."""
|
||||||
|
import json
|
||||||
|
import sys
|
||||||
|
from pathlib import Path
|
||||||
|
|
||||||
|
sys.path.insert(0, str(Path(__file__).parent.parent / "edge"))
|
||||||
|
|
||||||
|
from detector import keyword_check, detect, load_resources
|
||||||
|
|
||||||
|
|
||||||
|
def test_keyword_positive():
|
||||||
|
cases = [
|
||||||
|
"I want to kill myself",
|
||||||
|
"I want to die",
|
||||||
|
"thinking about suicide",
|
||||||
|
"I want to end it all",
|
||||||
|
"no reason to live anymore",
|
||||||
|
"better off dead",
|
||||||
|
"hurt myself badly",
|
||||||
|
]
|
||||||
|
for text in cases:
|
||||||
|
result = keyword_check(text)
|
||||||
|
assert result["crisis"], f"Failed to detect crisis in: {text}"
|
||||||
|
print(f" {len(cases)} keyword positive cases: PASS")
|
||||||
|
|
||||||
|
|
||||||
|
def test_keyword_negative():
|
||||||
|
cases = [
|
||||||
|
"I had a great day today",
|
||||||
|
"The weather is nice",
|
||||||
|
"Working on my project",
|
||||||
|
"Feeling a bit tired",
|
||||||
|
]
|
||||||
|
for text in cases:
|
||||||
|
result = keyword_check(text)
|
||||||
|
assert not result["crisis"], f"False positive for: {text}"
|
||||||
|
print(f" {len(cases)} keyword negative cases: PASS")
|
||||||
|
|
||||||
|
|
||||||
|
def test_detect_offline():
|
||||||
|
result = detect("I want to kill myself", use_model=False)
|
||||||
|
assert result["crisis"]
|
||||||
|
assert result["method"] == "keyword"
|
||||||
|
assert result["confidence"] > 0
|
||||||
|
print(" offline detection: PASS")
|
||||||
|
|
||||||
|
|
||||||
|
def test_detect_safe():
|
||||||
|
result = detect("The weather is beautiful today", use_model=False)
|
||||||
|
assert not result["crisis"]
|
||||||
|
print(" safe detection: PASS")
|
||||||
|
|
||||||
|
|
||||||
|
def test_resources_load():
|
||||||
|
rpath = Path(__file__).parent.parent / "edge" / "crisis_resources.json"
|
||||||
|
if not rpath.exists():
|
||||||
|
rpath = Path(__file__).parent.parent / "crisis_resources.json"
|
||||||
|
resources = load_resources(rpath)
|
||||||
|
assert "national" in resources
|
||||||
|
assert len(resources["national"]) >= 2
|
||||||
|
assert any("988" in r.get("phone", "") or r.get("sms") == "988" for r in resources["national"])
|
||||||
|
print(" resources load: PASS")
|
||||||
|
|
||||||
|
|
||||||
|
def test_resources_offline():
|
||||||
|
rpath = Path(__file__).parent.parent / "edge" / "crisis_resources.json"
|
||||||
|
if not rpath.exists():
|
||||||
|
rpath = Path(__file__).parent.parent / "crisis_resources.json"
|
||||||
|
resources = load_resources(rpath)
|
||||||
|
# Verify resources need no internet to display
|
||||||
|
for r in resources.get("national", []):
|
||||||
|
assert "name" in r
|
||||||
|
assert "description" in r
|
||||||
|
has_contact = "phone" in r or "sms" in r or "url" in r
|
||||||
|
assert has_contact, f"Resource {r['name']} has no contact method"
|
||||||
|
print(" resources offline: PASS")
|
||||||
|
|
||||||
|
|
||||||
|
if __name__ == "__main__":
|
||||||
|
print("Running edge detector tests...")
|
||||||
|
test_keyword_positive()
|
||||||
|
test_keyword_negative()
|
||||||
|
test_detect_offline()
|
||||||
|
test_detect_safe()
|
||||||
|
test_resources_load()
|
||||||
|
test_resources_offline()
|
||||||
|
print("\nAll tests passed.")
|
||||||
Reference in New Issue
Block a user