Compare commits
8 Commits
fix/74-git
...
feat/101-b
| Author | SHA1 | Date | |
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| 590c4c7820 | |||
| 629be9714f | |||
| 3123d1fa8e | |||
| 3cd8750cbb | |||
| ef765bbd30 | |||
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5f0d00f127 | ||
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8affe79489 | ||
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319f57780d |
3
.gitignore
vendored
Normal file
3
.gitignore
vendored
Normal file
@@ -0,0 +1,3 @@
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build/
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*.pyc
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__pycache__/
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36
CMakeLists.txt
Normal file
36
CMakeLists.txt
Normal file
@@ -0,0 +1,36 @@
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cmake_minimum_required(VERSION 3.16)
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project(turboquant LANGUAGES CXX)
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option(TURBOQUANT_BUILD_TESTS "Build standalone TurboQuant validation tests" ON)
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add_library(turboquant STATIC
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llama-turbo.cpp
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)
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target_include_directories(turboquant PUBLIC
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${CMAKE_CURRENT_SOURCE_DIR}
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)
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target_compile_features(turboquant PUBLIC cxx_std_17)
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if(MSVC)
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target_compile_options(turboquant PRIVATE /W4)
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else()
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target_compile_options(turboquant PRIVATE -Wall -Wextra -Wpedantic)
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endif()
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if(TURBOQUANT_BUILD_TESTS)
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include(CTest)
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add_executable(turboquant_roundtrip_test
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tests/roundtrip_test.cpp
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)
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target_link_libraries(turboquant_roundtrip_test PRIVATE turboquant)
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target_compile_features(turboquant_roundtrip_test PRIVATE cxx_std_17)
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add_test(
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NAME turboquant_roundtrip
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COMMAND turboquant_roundtrip_test
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)
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endif()
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@@ -13,7 +13,7 @@ Unlock 64K-128K context on qwen3.5:27b within 32GB unified memory.
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A 27B model at 128K context with TurboQuant beats a 72B at Q2 with 8K context.
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## Status
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See [issues](http://143.198.27.163:3000/Timmy_Foundation/turboquant/issues) for current progress.
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See [issues](https://forge.alexanderwhitestone.com/Timmy_Foundation/turboquant/issues) for current progress.
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## Roles
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- **Strago:** Build spec author
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@@ -29,4 +29,4 @@ See [issues](http://143.198.27.163:3000/Timmy_Foundation/turboquant/issues) for
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- [rachittshah/mlx-turboquant](https://github.com/rachittshah/mlx-turboquant) — MLX fallback
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## Docs
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- [BUILD-SPEC.md](BUILD-SPEC.md) — Full build specification (Strago, v2.2)
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- [Project Status](docs/PROJECT_STATUS.md) — Full project status and build specification
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50
benchmarks/bonsai-tool-calling.md
Normal file
50
benchmarks/bonsai-tool-calling.md
Normal file
@@ -0,0 +1,50 @@
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# Tool Calling Viability: Bonsai 1-Bit Models
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**Epic**: #99 (1-Bit Models + Edge)
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**Date**: TBD (run benchmarks/test_tool_calling.py to populate)
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## Hypothesis
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1-bit quantization destroys fine-grained reasoning. Tool calling (precise JSON output) may be impossible at Q1_0. But worth testing — the field is moving fast.
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## Models to Test
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| Model | Size | Quant | Source |
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|-------|------|-------|--------|
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| Bonsai-1.7B | 1.7B | Q1_0 | prism-ml/Bonsai-1.7B-gguf |
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| Bonsai-4B | 4B | Q1_0 | prism-ml/Bonsai-4B-gguf |
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| Bonsai-8B | 8B | Q1_0 | prism-ml/Bonsai-8B-gguf |
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## Test Suite
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| # | Test | Category | Description |
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|---|------|----------|-------------|
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| 1 | simple_file_read | Simple Tool Call | Read a file with an exact path |
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| 2 | terminal_command | Terminal Command | Execute a shell command |
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| 3 | web_search | Web Search | Search the web for a query |
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| 4 | multi_step_chain | Multi-Step | Chain: read -> analyze -> write |
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| 5 | nested_schema | Schema Parsing | Complex nested parameters |
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## Results
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> **Run**: `python3 benchmarks/test_tool_calling.py --model bonsai-1.7b --output benchmarks/bonsai-tool-calling.md`
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| Test | Bonsai-1.7B | Bonsai-4B | Bonsai-8B |
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|------|-------------|-----------|-----------|
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| simple_file_read | TBD | TBD | TBD |
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| terminal_command | TBD | TBD | TBD |
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| web_search | TBD | TBD | TBD |
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| multi_step_chain | TBD | TBD | TBD |
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| nested_schema | TBD | TBD | TBD |
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## Verdict
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TBD — run the test suite to populate.
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## Failure Modes (if any)
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TBD — document specific failure patterns observed.
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## Recommendations
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TBD — based on results, recommend minimum viable quantization level for tool calling.
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435
benchmarks/test_tool_calling.py
Normal file
435
benchmarks/test_tool_calling.py
Normal file
@@ -0,0 +1,435 @@
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#!/usr/bin/env python3
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"""
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Tool Calling Viability Test for 1-Bit / Edge Models (Issue #101)
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Tests whether Bonsai 1-bit models (or any small model) can produce
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valid tool calls via Ollama or llama-server API.
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Test suite (5 categories):
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1. Simple tool call: file read with exact path
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2. Terminal command execution
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3. Web search
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4. Multi-step: read file -> analyze -> write result
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5. Schema parsing: complex nested parameters
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Each test:
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- Sends a prompt requesting a tool call
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- Checks if the response contains valid JSON tool call syntax
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- Scores structural validity + semantic accuracy
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- Records latency and token count
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Usage:
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python3 benchmarks/test_tool_calling.py --model bonsai-1.7b
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python3 benchmarks/test_tool_calling.py --model qwen3.5 --backend llama-server --url http://localhost:8080
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python3 benchmarks/test_tool_calling.py --model bonsai-1.7b --output benchmarks/bonsai-tool-calling.md
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"""
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import argparse
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import json
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import os
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import re
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import sys
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import time
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from datetime import datetime, timezone
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from typing import Optional
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try:
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import requests
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except ImportError:
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print("Error: pip install requests", file=sys.stderr)
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sys.exit(1)
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# ── Tool call test definitions ────────────────────────────────────────
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TESTS = [
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{
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"id": "simple_file_read",
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"category": "Simple Tool Call",
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"description": "Read a file with an exact path",
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"prompt": (
|
||||
"You have access to a tool called read_file. "
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"Call it to read /etc/hostname. "
|
||||
"Respond ONLY with a JSON tool call in this exact format:\n"
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'{"name": "read_file", "arguments": {"path": "/etc/hostname"}}'
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||||
),
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"validate": lambda resp: _has_json_tool_call(resp, "read_file", {"path": "/etc/hostname"}),
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"scoring": "structural", # Can we parse the JSON at all?
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||||
},
|
||||
{
|
||||
"id": "terminal_command",
|
||||
"category": "Terminal Command",
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||||
"description": "Execute a shell command",
|
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"prompt": (
|
||||
"You have access to a tool called terminal. "
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||||
"Call it to run the command: echo hello world. "
|
||||
"Respond ONLY with a JSON tool call:\n"
|
||||
'{"name": "terminal", "arguments": {"command": "echo hello world"}}'
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||||
),
|
||||
"validate": lambda resp: _has_json_tool_call(resp, "terminal", {"command": "echo hello world"}),
|
||||
"scoring": "structural",
|
||||
},
|
||||
{
|
||||
"id": "web_search",
|
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"category": "Web Search",
|
||||
"description": "Search the web for a query",
|
||||
"prompt": (
|
||||
"You have access to a tool called web_search. "
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"Search for: what is quantization in machine learning. "
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||||
"Respond ONLY with a JSON tool call:\n"
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||||
'{"name": "web_search", "arguments": {"query": "what is quantization in machine learning"}}'
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||||
),
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||||
"validate": lambda resp: _has_json_tool_call(resp, "web_search", {"query": "what is quantization in machine learning"}),
|
||||
"scoring": "structural",
|
||||
},
|
||||
{
|
||||
"id": "multi_step_chain",
|
||||
"category": "Multi-Step",
|
||||
"description": "Chain: read file -> analyze -> write result",
|
||||
"prompt": (
|
||||
"You have access to these tools: read_file, write_file.\n"
|
||||
"Task: Read /tmp/input.txt, count the words, then write the count to /tmp/count.txt.\n"
|
||||
"First, call read_file on /tmp/input.txt. "
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||||
"Respond ONLY with the first tool call as JSON:\n"
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'{"name": "read_file", "arguments": {"path": "/tmp/input.txt"}}'
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||||
),
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"validate": lambda resp: _has_json_tool_call(resp, "read_file", {"path": "/tmp/input.txt"}),
|
||||
"scoring": "structural",
|
||||
},
|
||||
{
|
||||
"id": "nested_schema",
|
||||
"category": "Schema Parsing",
|
||||
"description": "Complex nested parameters",
|
||||
"prompt": (
|
||||
"You have access to a tool called deploy_service. "
|
||||
"Deploy a service with:\n"
|
||||
'- name: "api-gateway"\n'
|
||||
'- replicas: 3\n'
|
||||
'- env: {"PORT": 8080, "NODE_ENV": "production"}\n'
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||||
'- resources: {"cpu": "500m", "memory": "256Mi"}\n\n'
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||||
"Respond ONLY with a JSON tool call:\n"
|
||||
'{"name": "deploy_service", "arguments": {"name": "api-gateway", "replicas": 3, '
|
||||
'"env": {"PORT": 8080, "NODE_ENV": "production"}, '
|
||||
'"resources": {"cpu": "500m", "memory": "256Mi"}}}'
|
||||
),
|
||||
"validate": lambda resp: _has_nested_tool_call(resp),
|
||||
"scoring": "semantic", # Needs correct nested structure
|
||||
},
|
||||
]
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||||
|
||||
|
||||
# ── Validation helpers ────────────────────────────────────────────────
|
||||
|
||||
def _extract_json(text: str) -> Optional[dict]:
|
||||
"""Try to extract a JSON object from text."""
|
||||
# Try direct parse
|
||||
text = text.strip()
|
||||
try:
|
||||
obj = json.loads(text)
|
||||
if isinstance(obj, dict):
|
||||
return obj
|
||||
except json.JSONDecodeError:
|
||||
pass
|
||||
|
||||
# Try finding JSON in code blocks
|
||||
code_block = re.search(r"```(?:json)?\s*({.*?})\s*```", text, re.DOTALL)
|
||||
if code_block:
|
||||
try:
|
||||
return json.loads(code_block.group(1))
|
||||
except json.JSONDecodeError:
|
||||
pass
|
||||
|
||||
# Try finding any JSON object
|
||||
json_match = re.search(r"({[^{}]*(?:{[^{}]*}[^{}]*)*})", text)
|
||||
if json_match:
|
||||
try:
|
||||
return json.loads(json_match.group(1))
|
||||
except json.JSONDecodeError:
|
||||
pass
|
||||
|
||||
return None
|
||||
|
||||
|
||||
def _has_json_tool_call(resp: str, expected_name: str, expected_args: dict) -> dict:
|
||||
"""Check if response contains a valid tool call with expected name and args."""
|
||||
obj = _extract_json(resp)
|
||||
if obj is None:
|
||||
return {"passed": False, "reason": "no JSON found in response"}
|
||||
|
||||
# Check name
|
||||
name = obj.get("name", obj.get("function", {}).get("name", ""))
|
||||
if name != expected_name:
|
||||
return {"passed": False, "reason": f"wrong tool name: {name!r}, expected {expected_name!r}"}
|
||||
|
||||
# Check arguments exist
|
||||
args = obj.get("arguments", obj.get("function", {}).get("arguments", obj.get("args", {})))
|
||||
if not args:
|
||||
return {"passed": False, "reason": "no arguments found"}
|
||||
|
||||
# Check key arguments match
|
||||
for key, val in expected_args.items():
|
||||
if key not in args:
|
||||
return {"passed": False, "reason": f"missing argument: {key}"}
|
||||
if args[key] != val:
|
||||
return {"passed": False, "reason": f"argument mismatch: {key}={args[key]!r}, expected {val!r}"}
|
||||
|
||||
return {"passed": True, "reason": "tool call valid", "parsed": obj}
|
||||
|
||||
|
||||
def _has_nested_tool_call(resp: str) -> dict:
|
||||
"""Check if response contains a valid tool call with nested parameters."""
|
||||
obj = _extract_json(resp)
|
||||
if obj is None:
|
||||
return {"passed": False, "reason": "no JSON found in response"}
|
||||
|
||||
name = obj.get("name", obj.get("function", {}).get("name", ""))
|
||||
if name != "deploy_service":
|
||||
return {"passed": False, "reason": f"wrong tool name: {name!r}"}
|
||||
|
||||
args = obj.get("arguments", obj.get("function", {}).get("arguments", obj.get("args", {})))
|
||||
if not args:
|
||||
return {"passed": False, "reason": "no arguments found"}
|
||||
|
||||
checks = {
|
||||
"name": str,
|
||||
"replicas": int,
|
||||
"env": dict,
|
||||
"resources": dict,
|
||||
}
|
||||
|
||||
for key, expected_type in checks.items():
|
||||
if key not in args:
|
||||
return {"passed": False, "reason": f"missing nested key: {key}"}
|
||||
if not isinstance(args[key], expected_type):
|
||||
return {"passed": False, "reason": f"{key} should be {expected_type.__name__}, got {type(args[key]).__name__}"}
|
||||
|
||||
# Check env has PORT
|
||||
env = args.get("env", {})
|
||||
if "PORT" not in env:
|
||||
return {"passed": False, "reason": "env missing PORT"}
|
||||
|
||||
return {"passed": True, "reason": "nested tool call valid", "parsed": obj}
|
||||
|
||||
|
||||
# ── Backend runners ───────────────────────────────────────────────────
|
||||
|
||||
def run_ollama(prompt: str, model: str, url: str, timeout: int = 120) -> dict:
|
||||
"""Run a prompt against Ollama."""
|
||||
api_url = f"{url.rstrip('/')}/api/generate"
|
||||
start = time.time()
|
||||
try:
|
||||
resp = requests.post(api_url, json={
|
||||
"model": model,
|
||||
"prompt": prompt,
|
||||
"stream": False,
|
||||
"options": {"num_predict": 256, "temperature": 0}
|
||||
}, timeout=timeout)
|
||||
elapsed = time.time() - start
|
||||
resp.raise_for_status()
|
||||
data = resp.json()
|
||||
return {
|
||||
"response": data.get("response", ""),
|
||||
"latency_s": round(elapsed, 3),
|
||||
"tokens": data.get("eval_count", 0),
|
||||
"status": "success",
|
||||
}
|
||||
except Exception as e:
|
||||
return {"response": "", "latency_s": round(time.time() - start, 3), "tokens": 0, "status": "failed", "error": str(e)}
|
||||
|
||||
|
||||
def run_llama_server(prompt: str, model: str, url: str, timeout: int = 120) -> dict:
|
||||
"""Run a prompt against llama-server (OpenAI-compatible)."""
|
||||
api_url = f"{url.rstrip('/')}/v1/chat/completions"
|
||||
start = time.time()
|
||||
try:
|
||||
resp = requests.post(api_url, json={
|
||||
"model": model,
|
||||
"messages": [
|
||||
{"role": "system", "content": "You are a tool-calling assistant. Respond ONLY with JSON tool calls."},
|
||||
{"role": "user", "content": prompt},
|
||||
],
|
||||
"max_tokens": 256,
|
||||
"temperature": 0,
|
||||
"stream": False,
|
||||
}, timeout=timeout)
|
||||
elapsed = time.time() - start
|
||||
resp.raise_for_status()
|
||||
data = resp.json()
|
||||
content = data.get("choices", [{}])[0].get("message", {}).get("content", "")
|
||||
usage = data.get("usage", {})
|
||||
return {
|
||||
"response": content,
|
||||
"latency_s": round(elapsed, 3),
|
||||
"tokens": usage.get("completion_tokens", 0),
|
||||
"status": "success",
|
||||
}
|
||||
except Exception as e:
|
||||
return {"response": "", "latency_s": round(time.time() - start, 3), "tokens": 0, "status": "failed", "error": str(e)}
|
||||
|
||||
|
||||
# ── Main runner ───────────────────────────────────────────────────────
|
||||
|
||||
def run_tests(model: str, backend: str = "ollama", url: str = "http://localhost:11434",
|
||||
timeout: int = 120, verbose: bool = False) -> dict:
|
||||
"""Run the full tool calling test suite."""
|
||||
runner_fn = run_ollama if backend == "ollama" else run_llama_server
|
||||
|
||||
results = {
|
||||
"model": model,
|
||||
"backend": backend,
|
||||
"url": url,
|
||||
"timestamp": datetime.now(timezone.utc).isoformat(),
|
||||
"tests": [],
|
||||
"summary": {"total": 0, "passed": 0, "failed": 0, "errors": 0},
|
||||
}
|
||||
|
||||
print(f"Testing tool calling on: {model} ({backend})\n")
|
||||
|
||||
for test in TESTS:
|
||||
print(f" [{test['id']}] {test['description']}...", end=" ", flush=True)
|
||||
|
||||
run_result = runner_fn(test["prompt"], model, url, timeout)
|
||||
|
||||
if run_result["status"] == "failed":
|
||||
result = {
|
||||
"id": test["id"],
|
||||
"category": test["category"],
|
||||
"description": test["description"],
|
||||
"passed": False,
|
||||
"reason": f"backend error: {run_result.get('error', 'unknown')}",
|
||||
"response": "",
|
||||
"latency_s": run_result["latency_s"],
|
||||
"tokens": 0,
|
||||
}
|
||||
results["summary"]["errors"] += 1
|
||||
print("ERROR")
|
||||
else:
|
||||
validation = test["validate"](run_result["response"])
|
||||
result = {
|
||||
"id": test["id"],
|
||||
"category": test["category"],
|
||||
"description": test["description"],
|
||||
"passed": validation["passed"],
|
||||
"reason": validation["reason"],
|
||||
"response": run_result["response"][:500],
|
||||
"latency_s": run_result["latency_s"],
|
||||
"tokens": run_result["tokens"],
|
||||
}
|
||||
if validation["passed"]:
|
||||
results["summary"]["passed"] += 1
|
||||
print("PASS")
|
||||
else:
|
||||
results["summary"]["failed"] += 1
|
||||
print(f"FAIL ({validation['reason']})")
|
||||
|
||||
if verbose:
|
||||
print(f" Response: {run_result['response'][:200]}")
|
||||
|
||||
results["summary"]["total"] += 1
|
||||
results["tests"].append(result)
|
||||
|
||||
return results
|
||||
|
||||
|
||||
def to_markdown(results: dict) -> str:
|
||||
"""Format test results as a markdown report."""
|
||||
lines = []
|
||||
lines.append(f"# Tool Calling Viability: {results['model']}")
|
||||
lines.append("")
|
||||
lines.append(f"**Date**: {results['timestamp']}")
|
||||
lines.append(f"**Backend**: {results['backend']} ({results['url']})")
|
||||
lines.append(f"**Model**: {results['model']}")
|
||||
lines.append("")
|
||||
|
||||
s = results["summary"]
|
||||
pass_rate = s["passed"] / s["total"] * 100 if s["total"] > 0 else 0
|
||||
lines.append(f"## Summary: {s['passed']}/{s['total']} passed ({pass_rate:.0f}%)")
|
||||
lines.append("")
|
||||
lines.append(f"| Metric | Value |")
|
||||
lines.append(f"|--------|-------|")
|
||||
lines.append(f"| Total tests | {s['total']} |")
|
||||
lines.append(f"| Passed | {s['passed']} |")
|
||||
lines.append(f"| Failed | {s['failed']} |")
|
||||
lines.append(f"| Errors | {s['errors']} |")
|
||||
lines.append("")
|
||||
|
||||
lines.append("## Results by Category")
|
||||
lines.append("")
|
||||
lines.append("| Test | Category | Result | Reason | Latency | Tokens |")
|
||||
lines.append("|------|----------|--------|--------|---------|--------|")
|
||||
for t in results["tests"]:
|
||||
icon = "PASS" if t["passed"] else ("ERROR" if "error" in t["reason"].lower() else "FAIL")
|
||||
lines.append(f"| {t['id']} | {t['category']} | {icon} | {t['reason']} | {t['latency_s']}s | {t['tokens']} |")
|
||||
lines.append("")
|
||||
|
||||
lines.append("## Verdict")
|
||||
lines.append("")
|
||||
if pass_rate == 100:
|
||||
lines.append("**FULLY VIABLE** — All tool calling patterns work. Ready for production edge deployment.")
|
||||
elif pass_rate >= 60:
|
||||
lines.append("**PARTIALLY VIABLE** — Basic tool calling works, complex patterns may fail. Consider for simple agents.")
|
||||
elif pass_rate >= 20:
|
||||
lines.append("**MARGINAL** — Only simplest tool calls work. Not recommended for production.")
|
||||
else:
|
||||
lines.append("**NOT VIABLE** — Tool calling is fundamentally broken at this quantization level.")
|
||||
lines.append("")
|
||||
|
||||
lines.append("## Failure Analysis")
|
||||
lines.append("")
|
||||
failed = [t for t in results["tests"] if not t["passed"]]
|
||||
if not failed:
|
||||
lines.append("No failures.")
|
||||
else:
|
||||
for t in failed:
|
||||
lines.append(f"### {t['id']}")
|
||||
lines.append(f"- **Category**: {t['category']}")
|
||||
lines.append(f"- **Failure**: {t['reason']}")
|
||||
lines.append(f"- **Response** (first 300 chars): `{t['response'][:300]}`")
|
||||
lines.append("")
|
||||
lines.append("")
|
||||
|
||||
lines.append("## Recommendations")
|
||||
lines.append("")
|
||||
if pass_rate >= 80:
|
||||
lines.append("- Deploy for simple single-tool-call workflows")
|
||||
lines.append("- Add retry logic for multi-step chains")
|
||||
lines.append("- Consider prompt engineering to improve nested schema parsing")
|
||||
elif pass_rate >= 40:
|
||||
lines.append("- Use for keyword/rule-based tool routing only")
|
||||
lines.append("- Do NOT use for complex multi-step workflows")
|
||||
lines.append("- Consider a larger model (Q4 quantized) as fallback")
|
||||
else:
|
||||
lines.append("- 1-bit quantization is too lossy for tool calling")
|
||||
lines.append("- Use Q4_0 as minimum viable quantization for tool use")
|
||||
lines.append("- Reserve 1-bit models for text generation only")
|
||||
|
||||
return "\n".join(lines)
|
||||
|
||||
|
||||
def main():
|
||||
parser = argparse.ArgumentParser(description="Tool Calling Viability Test for Edge Models")
|
||||
parser.add_argument("--model", "-m", required=True, help="Model name")
|
||||
parser.add_argument("--backend", "-b", default="ollama", choices=["ollama", "llama-server"])
|
||||
parser.add_argument("--url", "-u", default="http://localhost:11434", help="Backend URL")
|
||||
parser.add_argument("--timeout", "-t", type=int, default=120, help="Timeout per test (seconds)")
|
||||
parser.add_argument("--output", "-o", help="Output markdown file path")
|
||||
parser.add_argument("--json", action="store_true", help="JSON output")
|
||||
parser.add_argument("--verbose", "-v", action="store_true", help="Show full responses")
|
||||
args = parser.parse_args()
|
||||
|
||||
results = run_tests(args.model, args.backend, args.url, args.timeout, args.verbose)
|
||||
|
||||
if args.json:
|
||||
print(json.dumps(results, indent=2))
|
||||
else:
|
||||
md = to_markdown(results)
|
||||
if args.output:
|
||||
with open(args.output, "w") as f:
|
||||
f.write(md)
|
||||
print(f"\nReport written to: {args.output}")
|
||||
else:
|
||||
print("\n" + md)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
@@ -135,7 +135,5 @@ llama-server -m model.gguf --port 8081 -ctk q8_0 -ctv turbo4 -c 131072
|
||||
|
||||
## References
|
||||
|
||||
- [TurboQuant Build Spec](../BUILD-SPEC.md)
|
||||
- [Phase 1 Report](../PHASE1-REPORT.md)
|
||||
- [Full Knowledge Transfer](../FULL-REPORT.md)
|
||||
- [Project Status](../docs/PROJECT_STATUS.md)
|
||||
- [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;
|
||||
}
|
||||
}
|
||||
189
tests/test_tool_calling.py
Normal file
189
tests/test_tool_calling.py
Normal file
@@ -0,0 +1,189 @@
|
||||
#!/usr/bin/env python3
|
||||
"""
|
||||
Unit tests for benchmarks/test_tool_calling.py
|
||||
|
||||
Tests the validation logic and report generation without
|
||||
requiring a live model backend.
|
||||
"""
|
||||
|
||||
import json
|
||||
import sys
|
||||
from pathlib import Path
|
||||
|
||||
import pytest
|
||||
|
||||
sys.path.insert(0, str(Path(__file__).parent.parent / "benchmarks"))
|
||||
import test_tool_calling as tc
|
||||
|
||||
|
||||
# ── JSON Extraction ───────────────────────────────────────────────────
|
||||
|
||||
class TestExtractJson:
|
||||
def test_direct_json(self):
|
||||
obj = tc._extract_json('{"name": "read_file", "arguments": {"path": "/etc/hostname"}}')
|
||||
assert obj["name"] == "read_file"
|
||||
|
||||
def test_json_in_code_block(self):
|
||||
text = 'Here is the call:\n```json\n{"name": "terminal", "arguments": {"command": "ls"}}\n```'
|
||||
obj = tc._extract_json(text)
|
||||
assert obj["name"] == "terminal"
|
||||
|
||||
def test_json_without_lang(self):
|
||||
text = '```\n{"name": "web_search", "arguments": {"query": "test"}}\n```'
|
||||
obj = tc._extract_json(text)
|
||||
assert obj["name"] == "web_search"
|
||||
|
||||
def test_no_json(self):
|
||||
obj = tc._extract_json("I can't help with that.")
|
||||
assert obj is None
|
||||
|
||||
def test_bare_json_object(self):
|
||||
text = 'Sure, here: {"name": "read_file", "arguments": {"path": "/tmp/x"}} for you.'
|
||||
obj = tc._extract_json(text)
|
||||
assert obj is not None
|
||||
assert obj["name"] == "read_file"
|
||||
|
||||
|
||||
# ── Tool Call Validation ──────────────────────────────────────────────
|
||||
|
||||
class TestToolCallValidation:
|
||||
def test_exact_match(self):
|
||||
resp = '{"name": "read_file", "arguments": {"path": "/etc/hostname"}}'
|
||||
result = tc._has_json_tool_call(resp, "read_file", {"path": "/etc/hostname"})
|
||||
assert result["passed"] is True
|
||||
|
||||
def test_wrong_tool_name(self):
|
||||
resp = '{"name": "write_file", "arguments": {"path": "/etc/hostname"}}'
|
||||
result = tc._has_json_tool_call(resp, "read_file", {"path": "/etc/hostname"})
|
||||
assert result["passed"] is False
|
||||
assert "wrong tool name" in result["reason"]
|
||||
|
||||
def test_missing_argument(self):
|
||||
resp = '{"name": "read_file", "arguments": {}}'
|
||||
result = tc._has_json_tool_call(resp, "read_file", {"path": "/etc/hostname"})
|
||||
assert result["passed"] is False
|
||||
assert "missing argument" in result["reason"]
|
||||
|
||||
def test_wrong_argument_value(self):
|
||||
resp = '{"name": "read_file", "arguments": {"path": "/etc/passwd"}}'
|
||||
result = tc._has_json_tool_call(resp, "read_file", {"path": "/etc/hostname"})
|
||||
assert result["passed"] is False
|
||||
assert "argument mismatch" in result["reason"]
|
||||
|
||||
def test_no_json_response(self):
|
||||
result = tc._has_json_tool_call("Sorry, I can't do that.", "read_file", {"path": "/etc/hostname"})
|
||||
assert result["passed"] is False
|
||||
assert "no JSON" in result["reason"]
|
||||
|
||||
def test_nested_function_format(self):
|
||||
resp = '{"function": {"name": "terminal", "arguments": {"command": "echo hello"}}}'
|
||||
result = tc._has_json_tool_call(resp, "terminal", {"command": "echo hello"})
|
||||
assert result["passed"] is True
|
||||
|
||||
|
||||
# ── Nested Schema Validation ──────────────────────────────────────────
|
||||
|
||||
class TestNestedSchemaValidation:
|
||||
def test_valid_nested(self):
|
||||
resp = json.dumps({
|
||||
"name": "deploy_service",
|
||||
"arguments": {
|
||||
"name": "api-gateway",
|
||||
"replicas": 3,
|
||||
"env": {"PORT": 8080, "NODE_ENV": "production"},
|
||||
"resources": {"cpu": "500m", "memory": "256Mi"}
|
||||
}
|
||||
})
|
||||
result = tc._has_nested_tool_call(resp)
|
||||
assert result["passed"] is True
|
||||
|
||||
def test_missing_nested_key(self):
|
||||
resp = '{"name": "deploy_service", "arguments": {"name": "api-gateway", "replicas": 3}}'
|
||||
result = tc._has_nested_tool_call(resp)
|
||||
assert result["passed"] is False
|
||||
assert "missing nested key" in result["reason"]
|
||||
|
||||
def test_wrong_type(self):
|
||||
resp = '{"name": "deploy_service", "arguments": {"name": "api-gateway", "replicas": "three", "env": {}, "resources": {}}}'
|
||||
result = tc._has_nested_tool_call(resp)
|
||||
assert result["passed"] is False
|
||||
assert "should be int" in result["reason"]
|
||||
|
||||
def test_missing_env_port(self):
|
||||
resp = json.dumps({
|
||||
"name": "deploy_service",
|
||||
"arguments": {"name": "api", "replicas": 1, "env": {"NODE_ENV": "dev"}, "resources": {}}
|
||||
})
|
||||
result = tc._has_nested_tool_call(resp)
|
||||
assert result["passed"] is False
|
||||
assert "PORT" in result["reason"]
|
||||
|
||||
|
||||
# ── Markdown Report Generation ────────────────────────────────────────
|
||||
|
||||
class TestMarkdownReport:
|
||||
def test_report_structure(self):
|
||||
results = {
|
||||
"model": "test-model",
|
||||
"backend": "ollama",
|
||||
"url": "http://localhost:11434",
|
||||
"timestamp": "2026-04-15T00:00:00Z",
|
||||
"tests": [
|
||||
{"id": "t1", "category": "Simple", "description": "Test 1",
|
||||
"passed": True, "reason": "ok", "response": "{}", "latency_s": 1.0, "tokens": 10},
|
||||
{"id": "t2", "category": "Complex", "description": "Test 2",
|
||||
"passed": False, "reason": "wrong name", "response": "oops", "latency_s": 2.0, "tokens": 20},
|
||||
],
|
||||
"summary": {"total": 2, "passed": 1, "failed": 1, "errors": 0},
|
||||
}
|
||||
md = tc.to_markdown(results)
|
||||
assert "test-model" in md
|
||||
assert "1/2 passed" in md
|
||||
assert "PASS" in md
|
||||
assert "FAIL" in md
|
||||
assert "Failure Analysis" in md
|
||||
|
||||
def test_perfect_score(self):
|
||||
results = {
|
||||
"model": "perfect", "backend": "ollama", "url": "http://x",
|
||||
"timestamp": "2026-01-01T00:00:00Z",
|
||||
"tests": [
|
||||
{"id": "t1", "category": "C", "description": "D",
|
||||
"passed": True, "reason": "ok", "response": "{}", "latency_s": 1, "tokens": 5},
|
||||
],
|
||||
"summary": {"total": 1, "passed": 1, "failed": 0, "errors": 0},
|
||||
}
|
||||
md = tc.to_markdown(results)
|
||||
assert "FULLY VIABLE" in md
|
||||
|
||||
def test_all_failed(self):
|
||||
results = {
|
||||
"model": "bad", "backend": "ollama", "url": "http://x",
|
||||
"timestamp": "2026-01-01T00:00:00Z",
|
||||
"tests": [
|
||||
{"id": "t1", "category": "C", "description": "D",
|
||||
"passed": False, "reason": "broken", "response": "nope", "latency_s": 1, "tokens": 0},
|
||||
],
|
||||
"summary": {"total": 1, "passed": 0, "failed": 1, "errors": 0},
|
||||
}
|
||||
md = tc.to_markdown(results)
|
||||
assert "NOT VIABLE" in md
|
||||
|
||||
|
||||
# ── Test Definitions ──────────────────────────────────────────────────
|
||||
|
||||
class TestTestDefinitions:
|
||||
def test_all_tests_have_validators(self):
|
||||
for test in tc.TESTS:
|
||||
assert callable(test["validate"]), f"{test['id']} missing validate"
|
||||
assert "id" in test
|
||||
assert "category" in test
|
||||
assert "prompt" in test
|
||||
|
||||
def test_five_test_categories(self):
|
||||
categories = {t["category"] for t in tc.TESTS}
|
||||
assert len(categories) >= 4, f"Expected 4+ categories, got {categories}"
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
pytest.main([__file__, "-v"])
|
||||
Reference in New Issue
Block a user