Text Generation
PEFT
Safetensors
GGUF
Transformers
English
Spanish
harbour
fivewin
fwh
lora
sft
trl
unsloth
code-generation
xbase
clipper
conversational
Instructions to use fivetech/Harbour with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use fivetech/Harbour with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("/home/fivetech/finetune/models/Qwen3.6-35B-A3B") model = PeftModel.from_pretrained(base_model, "fivetech/Harbour") - Transformers
How to use fivetech/Harbour with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="fivetech/Harbour") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("fivetech/Harbour", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use fivetech/Harbour with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf fivetech/Harbour:Q4_K_M # Run inference directly in the terminal: llama cli -hf fivetech/Harbour:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf fivetech/Harbour:Q4_K_M # Run inference directly in the terminal: llama cli -hf fivetech/Harbour:Q4_K_M
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf fivetech/Harbour:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf fivetech/Harbour:Q4_K_M
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf fivetech/Harbour:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf fivetech/Harbour:Q4_K_M
Use Docker
docker model run hf.co/fivetech/Harbour:Q4_K_M
- LM Studio
- Jan
- vLLM
How to use fivetech/Harbour with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "fivetech/Harbour" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "fivetech/Harbour", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/fivetech/Harbour:Q4_K_M
- SGLang
How to use fivetech/Harbour with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "fivetech/Harbour" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "fivetech/Harbour", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "fivetech/Harbour" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "fivetech/Harbour", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Ollama
How to use fivetech/Harbour with Ollama:
ollama run hf.co/fivetech/Harbour:Q4_K_M
- Unsloth Studio
How to use fivetech/Harbour with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for fivetech/Harbour to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for fivetech/Harbour to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for fivetech/Harbour to start chatting
- Pi
How to use fivetech/Harbour with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf fivetech/Harbour:Q4_K_M
Configure the model in Pi
# Install Pi: npm install -g @mariozechner/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "fivetech/Harbour:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- OpenClaw new
How to use fivetech/Harbour with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf fivetech/Harbour:Q4_K_M
Configure OpenClaw
# Install OpenClaw: npm install -g openclaw@latest # Register the local server and set it as the default model: openclaw onboard --non-interactive --mode local \ --auth-choice custom-api-key \ --custom-base-url http://127.0.0.1:8080/v1 \ --custom-model-id "fivetech/Harbour:Q4_K_M" \ --custom-provider-id llama-cpp \ --custom-compatibility openai \ --custom-text-input \ --accept-risk \ --skip-health
Run OpenClaw
openclaw agent --local --agent main --message "Hello from Hugging Face"
- Docker Model Runner
How to use fivetech/Harbour with Docker Model Runner:
docker model run hf.co/fivetech/Harbour:Q4_K_M
- Lemonade
How to use fivetech/Harbour with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull fivetech/Harbour:Q4_K_M
Run and chat with the model
lemonade run user.Harbour-Q4_K_M
List all available models
lemonade list
- Hermes Agent
How to use fivetech/Harbour with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf fivetech/Harbour:Q4_K_M
Configure Hermes
# Install Hermes: curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash hermes setup # Point Hermes at the local server: hermes config set model.provider custom hermes config set model.base_url http://127.0.0.1:8080/v1 hermes config set model.default fivetech/Harbour:Q4_K_M
Run Hermes
hermes
- Atomic Chat
Upload test_battery.py with huggingface_hub
Browse files- test_battery.py +516 -0
test_battery.py
ADDED
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| 1 |
+
#!/usr/bin/env python3
|
| 2 |
+
"""
|
| 3 |
+
Harbour Test Battery - Generates code, compiles with harbour, evaluates with qwen3.6:35b
|
| 4 |
+
"""
|
| 5 |
+
|
| 6 |
+
import json
|
| 7 |
+
import time
|
| 8 |
+
import subprocess
|
| 9 |
+
import requests
|
| 10 |
+
import tempfile
|
| 11 |
+
import os
|
| 12 |
+
from pathlib import Path
|
| 13 |
+
from datetime import datetime
|
| 14 |
+
|
| 15 |
+
OLLAMA_URL = "http://localhost:11434/api/generate"
|
| 16 |
+
MODEL = "qwen3.6:35b"
|
| 17 |
+
HARBOUR = "/home/fivetech/harbour/bin/linux/gcc/harbour"
|
| 18 |
+
WORK_DIR = Path("/home/fivetech/finetune/test_output")
|
| 19 |
+
WORK_DIR.mkdir(exist_ok=True)
|
| 20 |
+
|
| 21 |
+
def query_ollama(prompt, system="", timeout=300):
|
| 22 |
+
payload = {
|
| 23 |
+
"model": MODEL,
|
| 24 |
+
"prompt": prompt,
|
| 25 |
+
"stream": False,
|
| 26 |
+
"options": {"temperature": 0.2, "num_predict": 3000, "top_p": 0.9}
|
| 27 |
+
}
|
| 28 |
+
if system:
|
| 29 |
+
payload["system"] = system
|
| 30 |
+
try:
|
| 31 |
+
start = time.time()
|
| 32 |
+
r = requests.post(OLLAMA_URL, json=payload, timeout=timeout)
|
| 33 |
+
elapsed = time.time() - start
|
| 34 |
+
data = r.json()
|
| 35 |
+
return {
|
| 36 |
+
"response": data.get("response", ""),
|
| 37 |
+
"eval_count": data.get("eval_count", 0),
|
| 38 |
+
"duration": elapsed,
|
| 39 |
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"tps": data.get("eval_count", 0) / max(data.get("eval_duration", 1) / 1e9, 0.001),
|
| 40 |
+
"error": None
|
| 41 |
+
}
|
| 42 |
+
except Exception as e:
|
| 43 |
+
return {"response": "", "error": str(e), "eval_count": 0, "duration": 0, "tps": 0}
|
| 44 |
+
|
| 45 |
+
def compile_harbour(code):
|
| 46 |
+
"""Compile code with harbour, return (success, error_msg, obj_exists)"""
|
| 47 |
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prg_file = WORK_DIR / "test.prg"
|
| 48 |
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prg_file.write_text(code)
|
| 49 |
+
|
| 50 |
+
try:
|
| 51 |
+
result = subprocess.run(
|
| 52 |
+
[HARBOUR, str(prg_file), "-n", "-w"],
|
| 53 |
+
capture_output=True, text=True, timeout=30
|
| 54 |
+
)
|
| 55 |
+
obj_file = WORK_DIR / "test.obj"
|
| 56 |
+
success = result.returncode == 0
|
| 57 |
+
obj_exists = obj_file.exists()
|
| 58 |
+
error = result.stderr.strip() if result.stderr else ""
|
| 59 |
+
if not success and not error:
|
| 60 |
+
error = result.stdout.strip()
|
| 61 |
+
return success, error, obj_exists
|
| 62 |
+
except subprocess.TimeoutExpired:
|
| 63 |
+
return False, "Compilation timeout", False
|
| 64 |
+
except Exception as e:
|
| 65 |
+
return False, str(e), False
|
| 66 |
+
|
| 67 |
+
def clean_code(response):
|
| 68 |
+
"""Extract code from model response, remove markdown."""
|
| 69 |
+
lines = response.split('\n')
|
| 70 |
+
in_code = False
|
| 71 |
+
code_lines = []
|
| 72 |
+
skip_explanation = True
|
| 73 |
+
|
| 74 |
+
for line in lines:
|
| 75 |
+
stripped = line.strip()
|
| 76 |
+
|
| 77 |
+
# Skip markdown
|
| 78 |
+
if stripped.startswith('```'):
|
| 79 |
+
in_code = not in_code
|
| 80 |
+
continue
|
| 81 |
+
|
| 82 |
+
if in_code:
|
| 83 |
+
code_lines.append(line)
|
| 84 |
+
skip_explanation = False
|
| 85 |
+
elif skip_explanation:
|
| 86 |
+
# Detect start of code
|
| 87 |
+
upper = stripped.upper()
|
| 88 |
+
if any(upper.startswith(kw) for kw in [
|
| 89 |
+
'FUNCTION', 'PROCEDURE', 'LOCAL', 'STATIC', 'PUBLIC',
|
| 90 |
+
'PRIVATE', 'MEMVAR', '#DEFINE', '#INCLUDE', 'CLASS',
|
| 91 |
+
'METHOD', 'RETURN', 'SET', 'REQUEST'
|
| 92 |
+
]):
|
| 93 |
+
in_code = True
|
| 94 |
+
code_lines.append(line)
|
| 95 |
+
skip_explanation = False
|
| 96 |
+
|
| 97 |
+
if not code_lines:
|
| 98 |
+
# Fallback: take everything
|
| 99 |
+
code_lines = response.split('\n')
|
| 100 |
+
|
| 101 |
+
return '\n'.join(code_lines).strip()
|
| 102 |
+
|
| 103 |
+
# ============================================================
|
| 104 |
+
# TEST DEFINITIONS - Based on dataset patterns
|
| 105 |
+
# ============================================================
|
| 106 |
+
|
| 107 |
+
TESTS = [
|
| 108 |
+
# ---- BASIC SYNTAX ----
|
| 109 |
+
{
|
| 110 |
+
"id": "SYNTAX_01", "category": "Basic Syntax", "name": "Variable types and declarations",
|
| 111 |
+
"prompt": "Write a Harbour program that declares LOCAL variables of each type (numeric, character, logical, date, nil), prints them with ValType(), and uses proper Hungarian notation.",
|
| 112 |
+
"expected_keywords": ["LOCAL", "ValType", "FUNCTION"],
|
| 113 |
+
"min_lines": 8,
|
| 114 |
+
},
|
| 115 |
+
{
|
| 116 |
+
"id": "SYNTAX_02", "category": "Basic Syntax", "name": "Preprocessor defines",
|
| 117 |
+
"prompt": "Write Harbour preprocessor definitions for application constants: app name, version, max records, date format. Use #define and show conditional compilation with #ifdef.",
|
| 118 |
+
"expected_keywords": ["#DEFINE", "#IFDEF", "#ENDIF"],
|
| 119 |
+
"min_lines": 6,
|
| 120 |
+
},
|
| 121 |
+
{
|
| 122 |
+
"id": "SYNTAX_03", "category": "Basic Syntax", "name": "String operations",
|
| 123 |
+
"prompt": "Write a Harbour function that takes a full name string and returns initials. Use AllTrim, Upper, Left, At, SubStr, and Space functions.",
|
| 124 |
+
"expected_keywords": ["FUNCTION", "AllTrim", "Upper", "Left", "At", "SubStr"],
|
| 125 |
+
"min_lines": 6,
|
| 126 |
+
},
|
| 127 |
+
{
|
| 128 |
+
"id": "SYNTAX_04", "category": "Basic Syntax", "name": "Date functions",
|
| 129 |
+
"prompt": "Write a Harbour function that calculates the number of business days between two dates, excluding weekends. Use Date(), DOW(), and date arithmetic.",
|
| 130 |
+
"expected_keywords": ["FUNCTION", "Date", "DOW"],
|
| 131 |
+
"min_lines": 8,
|
| 132 |
+
},
|
| 133 |
+
{
|
| 134 |
+
"id": "SYNTAX_05", "category": "Basic Syntax", "name": "Type conversion",
|
| 135 |
+
"prompt": "Write Harbour code that converts between all types: Str, Val, CTOD, DTOC, ASC, Chr, Transform. Show edge cases.",
|
| 136 |
+
"expected_keywords": ["Str", "Val", "CTOD", "DTOC"],
|
| 137 |
+
"min_lines": 8,
|
| 138 |
+
},
|
| 139 |
+
|
| 140 |
+
# ---- CONTROL FLOW ----
|
| 141 |
+
{
|
| 142 |
+
"id": "CTRL_01", "category": "Control Flow", "name": "IF/ELSEIF/ENDIF",
|
| 143 |
+
"prompt": "Write a Harbour function that classifies employee salary into tax brackets using IF/ELSEIF/ELSE/ENDIF. Include 5 brackets and error handling.",
|
| 144 |
+
"expected_keywords": ["FUNCTION", "IF", "ELSEIF", "ELSE", "ENDIF"],
|
| 145 |
+
"min_lines": 10,
|
| 146 |
+
},
|
| 147 |
+
{
|
| 148 |
+
"id": "CTRL_02", "category": "Control Flow", "name": "DO CASE",
|
| 149 |
+
"prompt": "Write a Harbour function using DO CASE to convert month number (1-12) to season name. Handle invalid input with OTHERWISE.",
|
| 150 |
+
"expected_keywords": ["DO CASE", "CASE", "OTHERWISE", "ENDCASE"],
|
| 151 |
+
"min_lines": 8,
|
| 152 |
+
},
|
| 153 |
+
{
|
| 154 |
+
"id": "CTRL_03", "category": "Control Flow", "name": "FOR/NEXT loop",
|
| 155 |
+
"prompt": "Write a Harbour function using FOR/NEXT to calculate the sum of all prime numbers below 100. Include STEP and EXIT.",
|
| 156 |
+
"expected_keywords": ["FOR", "TO", "NEXT", "IF", "EXIT"],
|
| 157 |
+
"min_lines": 10,
|
| 158 |
+
},
|
| 159 |
+
{
|
| 160 |
+
"id": "CTRL_04", "category": "Control Flow", "name": "DO WHILE",
|
| 161 |
+
"prompt": "Write a Harbour function using DO WHILE to implement the Euclidean algorithm for GCD. Include LOOP and EXIT.",
|
| 162 |
+
"expected_keywords": ["DO WHILE", "ENDDO", "IF", "LOOP", "EXIT"],
|
| 163 |
+
"min_lines": 6,
|
| 164 |
+
},
|
| 165 |
+
{
|
| 166 |
+
"id": "CTRL_05", "category": "Control Flow", "name": "SCAN/ENDSCAN",
|
| 167 |
+
"prompt": "Write Harbour code using SCAN/ENDSCAN to find the longest string in an array. Include NEXT clause.",
|
| 168 |
+
"expected_keywords": ["SCAN", "ENDSCAN"],
|
| 169 |
+
"min_lines": 6,
|
| 170 |
+
},
|
| 171 |
+
{
|
| 172 |
+
"id": "CTRL_06", "category": "Control Flow", "name": "FOR EACH",
|
| 173 |
+
"prompt": "Write Harbour code using FOR EACH to count word frequencies in a string. Use a hash for storage.",
|
| 174 |
+
"expected_keywords": ["FOR EACH", "NEXT", ":="],
|
| 175 |
+
"min_lines": 8,
|
| 176 |
+
},
|
| 177 |
+
|
| 178 |
+
# ---- FUNCTIONS ----
|
| 179 |
+
{
|
| 180 |
+
"id": "FUNC_01", "category": "Functions", "name": "Parameters and return",
|
| 181 |
+
"prompt": "Write a Harbour function with default parameters, pass-by-reference using @, and return an array. Include proper Hungarian notation.",
|
| 182 |
+
"expected_keywords": ["FUNCTION", "LOCAL", "RETURN"],
|
| 183 |
+
"min_lines": 6,
|
| 184 |
+
},
|
| 185 |
+
{
|
| 186 |
+
"id": "FUNC_02", "category": "Functions", "name": "Recursion",
|
| 187 |
+
"prompt": "Write a recursive Harbour function for Fibonacci numbers with memoization using a hash. Include base case and error handling.",
|
| 188 |
+
"expected_keywords": ["FUNCTION", "IF", "RETURN"],
|
| 189 |
+
"min_lines": 8,
|
| 190 |
+
},
|
| 191 |
+
{
|
| 192 |
+
"id": "FUNC_03", "category": "Functions", "name": "Variable scope",
|
| 193 |
+
"prompt": "Write Harbour code demonstrating LOCAL, STATIC, PRIVATE, PUBLIC variables. Show scope differences with nested function calls.",
|
| 194 |
+
"expected_keywords": ["LOCAL", "STATIC", "PRIVATE", "PUBLIC"],
|
| 195 |
+
"min_lines": 8,
|
| 196 |
+
},
|
| 197 |
+
{
|
| 198 |
+
"id": "FUNC_04", "category": "Functions", "name": "Code blocks",
|
| 199 |
+
"prompt": "Write Harbour code using code blocks: AEval with {|x| x*2}, AScan, ASort with custom sort. Show evaluation with Eval().",
|
| 200 |
+
"expected_keywords": ["AEval", "AScan", "ASort", "Eval"],
|
| 201 |
+
"min_lines": 6,
|
| 202 |
+
},
|
| 203 |
+
{
|
| 204 |
+
"id": "FUNC_05", "category": "Functions", "name": "Error handling",
|
| 205 |
+
"prompt": "Write a Harbour function with BEGIN SEQUENCE/RECOVER/END SEQUENCE for file reading. Include DEFAULT and BREAK.",
|
| 206 |
+
"expected_keywords": ["BEGIN SEQUENCE", "RECOVER", "END SEQUENCE"],
|
| 207 |
+
"min_lines": 8,
|
| 208 |
+
},
|
| 209 |
+
|
| 210 |
+
# ---- ARRAYS ----
|
| 211 |
+
{
|
| 212 |
+
"id": "ARRAY_01", "category": "Arrays", "name": "Array operations",
|
| 213 |
+
"prompt": "Write Harbour functions for: create 2D array, AAdd elements, ASort with custom order, AScan by value, ASize to resize. Include error handling.",
|
| 214 |
+
"expected_keywords": ["ARRAY", "AAdd", "ASort", "AScan", "ASize"],
|
| 215 |
+
"min_lines": 8,
|
| 216 |
+
},
|
| 217 |
+
{
|
| 218 |
+
"id": "ARRAY_02", "category": "Arrays", "name": "Hash operations",
|
| 219 |
+
"prompt": "Write Harbour code using hashes: create, add keys, iterate with FOR EACH, merge two hashes, check key existence with HB_HHasKey, convert to array.",
|
| 220 |
+
"expected_keywords": [":=", "FOR EACH", "HB_HHasKey"],
|
| 221 |
+
"min_lines": 8,
|
| 222 |
+
},
|
| 223 |
+
{
|
| 224 |
+
"id": "ARRAY_03", "category": "Arrays", "name": "Sorting algorithm",
|
| 225 |
+
"prompt": "Implement QuickSort in Harbour for an array of numbers. Include partition logic and proper recursion.",
|
| 226 |
+
"expected_keywords": ["FUNCTION", "LOCAL", "IF", "RETURN"],
|
| 227 |
+
"min_lines": 12,
|
| 228 |
+
},
|
| 229 |
+
|
| 230 |
+
# ---- OOP ----
|
| 231 |
+
{
|
| 232 |
+
"id": "OOP_01", "category": "OOP", "name": "Class definition",
|
| 233 |
+
"prompt": "Write a Harbour class Person with DATA (name, age), METHOD (New constructor, GetName, SetAge), and CLASSDATA. Include validation in SetAge.",
|
| 234 |
+
"expected_keywords": ["CLASS", "DATA", "METHOD", "RETURN"],
|
| 235 |
+
"min_lines": 10,
|
| 236 |
+
},
|
| 237 |
+
{
|
| 238 |
+
"id": "OOP_02", "category": "OOP", "name": "Inheritance",
|
| 239 |
+
"prompt": "Write Harbour classes: Shape (base), Circle (derived) with area() method. Show inheritance syntax and method override.",
|
| 240 |
+
"expected_keywords": ["CLASS", "METHOD", "INHERIT"],
|
| 241 |
+
"min_lines": 10,
|
| 242 |
+
},
|
| 243 |
+
{
|
| 244 |
+
"id": "OOP_03", "category": "OOP", "name": "Operator overloading",
|
| 245 |
+
"prompt": "Write a Harbour class Vec2 for 2D vectors. Overload + and - operators. Include magnitude and normalize methods.",
|
| 246 |
+
"expected_keywords": ["CLASS", "METHOD", "OPERATOR"],
|
| 247 |
+
"min_lines": 12,
|
| 248 |
+
},
|
| 249 |
+
{
|
| 250 |
+
"id": "OOP_04", "category": "OOP", "name": "Singleton pattern",
|
| 251 |
+
"prompt": "Implement Singleton pattern in Harbour for a config manager. Ensure only one instance exists.",
|
| 252 |
+
"expected_keywords": ["CLASS", "CLASSDATA", "METHOD"],
|
| 253 |
+
"min_lines": 10,
|
| 254 |
+
},
|
| 255 |
+
|
| 256 |
+
# ---- DATABASE ----
|
| 257 |
+
{
|
| 258 |
+
"id": "DB_01", "category": "Database", "name": "Basic RDD",
|
| 259 |
+
"prompt": "Write Harbour code that creates a DBF file, opens it, appends records, and closes properly. Use DBCreate and DBUseArea.",
|
| 260 |
+
"expected_keywords": ["DBCreate", "DBUseArea", "DBAppend", "DBCLOSEALL"],
|
| 261 |
+
"min_lines": 10,
|
| 262 |
+
},
|
| 263 |
+
{
|
| 264 |
+
"id": "DB_02", "category": "Database", "name": "Indexing",
|
| 265 |
+
"prompt": "Write Harbour code creating an index on a DBF field using RDD. Include ORDSCOPE for range queries.",
|
| 266 |
+
"expected_keywords": ["ORDCREATE", "ORDSCOPE"],
|
| 267 |
+
"min_lines": 8,
|
| 268 |
+
},
|
| 269 |
+
{
|
| 270 |
+
"id": "DB_03", "category": "Database", "name": "DBEval",
|
| 271 |
+
"prompt": "Write Harbour code using DBEval to process all records: count, sum field values, and mark records meeting a condition.",
|
| 272 |
+
"expected_keywords": ["DBEval", "FOR", "WHILE"],
|
| 273 |
+
"min_lines": 8,
|
| 274 |
+
},
|
| 275 |
+
|
| 276 |
+
# ---- FILE I/O ----
|
| 277 |
+
{
|
| 278 |
+
"id": "FILE_01", "category": "File I/O", "name": "Text file read/write",
|
| 279 |
+
"prompt": "Write Harbour functions to read a text file line by line and write processed output. Use FCreate, FOpen, FRead, FWrite, FClose, FEof.",
|
| 280 |
+
"expected_keywords": ["FCreate", "FOpen", "FRead", "FWrite", "FClose", "FEof"],
|
| 281 |
+
"min_lines": 10,
|
| 282 |
+
},
|
| 283 |
+
{
|
| 284 |
+
"id": "FILE_02", "category": "File I/O", "name": "Directory listing",
|
| 285 |
+
"prompt": "Write Harbour code using Directory() to list files with a pattern, get file size and date, and process each file.",
|
| 286 |
+
"expected_keywords": ["Directory", "LEN", "FOR"],
|
| 287 |
+
"min_lines": 6,
|
| 288 |
+
},
|
| 289 |
+
|
| 290 |
+
# ---- COMPLEX ----
|
| 291 |
+
{
|
| 292 |
+
"id": "CMPX_01", "category": "Complex", "name": "CSV parser",
|
| 293 |
+
"prompt": "Write a Harbour CSV parser that reads a CSV file, handles quoted fields, and returns an array of arrays. Include error handling.",
|
| 294 |
+
"expected_keywords": ["FUNCTION", "LOCAL", "FClose", "FEof"],
|
| 295 |
+
"min_lines": 15,
|
| 296 |
+
},
|
| 297 |
+
{
|
| 298 |
+
"id": "CMPX_02", "category": "Complex", "name": "INI file reader",
|
| 299 |
+
"prompt": "Write a Harbour INI file parser. Read sections, keys, and values into a hash. Handle comments and empty lines.",
|
| 300 |
+
"expected_keywords": ["FUNCTION", "LOCAL", "HASH"],
|
| 301 |
+
"min_lines": 12,
|
| 302 |
+
},
|
| 303 |
+
{
|
| 304 |
+
"id": "CMPX_03", "category": "Complex", "name": "String template engine",
|
| 305 |
+
"prompt": "Write a Harbour template engine replacing {{variable}} placeholders with hash values. Include error handling for missing keys.",
|
| 306 |
+
"expected_keywords": ["FUNCTION", "LOCAL", "STRTRAN"],
|
| 307 |
+
"min_lines": 8,
|
| 308 |
+
},
|
| 309 |
+
{
|
| 310 |
+
"id": "CMPX_04", "category": "Complex", "name": "Logger",
|
| 311 |
+
"prompt": "Write a Harbour logging system with DEBUG/INFO/WARN/ERROR levels, timestamp, file output, and configurable level filtering.",
|
| 312 |
+
"expected_keywords": ["FUNCTION", "LOCAL", "FClose"],
|
| 313 |
+
"min_lines": 12,
|
| 314 |
+
},
|
| 315 |
+
{
|
| 316 |
+
"id": "CMPX_05", "category": "Complex", "name": "Base64 encoder",
|
| 317 |
+
"prompt": "Write a Harbour Base64 encoder/decode function. Use Asc(), Chr(), and bit operations.",
|
| 318 |
+
"expected_keywords": ["FUNCTION", "LOCAL", "Asc", "Chr"],
|
| 319 |
+
"min_lines": 10,
|
| 320 |
+
},
|
| 321 |
+
{
|
| 322 |
+
"id": "CMPX_06", "category": "Complex", "name": "JSON serializer",
|
| 323 |
+
"prompt": "Write a Harbour function that serializes a hash to JSON string. Handle strings, numbers, booleans, arrays, and nested objects.",
|
| 324 |
+
"expected_keywords": ["FUNCTION", "LOCAL", "HB_IsHash"],
|
| 325 |
+
"min_lines": 15,
|
| 326 |
+
},
|
| 327 |
+
{
|
| 328 |
+
"id": "CMPX_07", "category": "Complex", "name": "LRU Cache",
|
| 329 |
+
"prompt": "Write a Harbour LRU cache class with get/set/delete, TTL expiration, and max size. Use a hash and an array for ordering.",
|
| 330 |
+
"expected_keywords": ["CLASS", "DATA", "METHOD"],
|
| 331 |
+
"min_lines": 15,
|
| 332 |
+
},
|
| 333 |
+
{
|
| 334 |
+
"id": "CMPX_08", "category": "Complex", "name": "SQL-like query on arrays",
|
| 335 |
+
"prompt": "Write a Harbour function that filters an array of hashes like SQL WHERE clause. Support =, <>, >, <, LIKE operators.",
|
| 336 |
+
"expected_keywords": ["FUNCTION", "LOCAL", "FOR"],
|
| 337 |
+
"min_lines": 12,
|
| 338 |
+
},
|
| 339 |
+
{
|
| 340 |
+
"id": "CMPX_09", "category": "Complex", "name": "Rate limiter",
|
| 341 |
+
"prompt": "Write a Harbour rate limiter class: max N requests per M seconds. Use timestamps and a queue.",
|
| 342 |
+
"expected_keywords": ["CLASS", "METHOD", "LOCAL"],
|
| 343 |
+
"min_lines": 12,
|
| 344 |
+
},
|
| 345 |
+
{
|
| 346 |
+
"id": "CMPX_10", "category": "Complex", "name": "Config file writer",
|
| 347 |
+
"prompt": "Write a Harbour config manager that saves/loads settings to JSON file. Include defaults, validation, and typed getters.",
|
| 348 |
+
"expected_keywords": ["FUNCTION", "LOCAL", "FClose"],
|
| 349 |
+
"min_lines": 12,
|
| 350 |
+
},
|
| 351 |
+
|
| 352 |
+
# ---- BUGGY CODE TO FIX ----
|
| 353 |
+
{
|
| 354 |
+
"id": "FIX_01", "category": "Bug Fix", "name": "Null pointer",
|
| 355 |
+
"prompt": "Fix this Harbour code that crashes when array is empty:\nLOCAL a := {}\n? a[1]",
|
| 356 |
+
"expected_keywords": ["IF", "LEN", "RETURN"],
|
| 357 |
+
"min_lines": 3,
|
| 358 |
+
},
|
| 359 |
+
{
|
| 360 |
+
"id": "FIX_02", "category": "Bug Fix", "name": "Wrong loop bounds",
|
| 361 |
+
"prompt": "Fix this code that skips last element:\nLOCAL a := {10,20,30}\nFOR i := 1 TO LEN(a)-1\n ? a[i]\nNEXT",
|
| 362 |
+
"expected_keywords": ["FOR", "TO", "LEN"],
|
| 363 |
+
"min_lines": 3,
|
| 364 |
+
},
|
| 365 |
+
{
|
| 366 |
+
"id": "FIX_03", "category": "Bug Fix", "name": "String concat error",
|
| 367 |
+
"prompt": "Fix this code that fails on nil values:\nLOCAL cName := NIL\n? 'Hello ' + cName",
|
| 368 |
+
"expected_keywords": ["IF", "LOCAL", "RETURN"],
|
| 369 |
+
"min_lines": 3,
|
| 370 |
+
},
|
| 371 |
+
|
| 372 |
+
# ---- HARBOUR-SPECIFIC ----
|
| 373 |
+
{
|
| 374 |
+
"id": "HARB_01", "category": "Harbour-Specific", "name": "HB_* functions",
|
| 375 |
+
"prompt": "Write Harbour code using HB_IsString, HB_IsNumeric, HB_IsArray, HB_IsHash, HB_IsNil to validate function arguments. Include proper error messages.",
|
| 376 |
+
"expected_keywords": ["HB_IsString", "HB_IsNumeric", "IF"],
|
| 377 |
+
"min_lines": 6,
|
| 378 |
+
},
|
| 379 |
+
{
|
| 380 |
+
"id": "HARB_02", "category": "Harbour-Specific", "name": "Regex",
|
| 381 |
+
"prompt": "Write a Harbour function using HB_RegEx to validate email addresses. Use HB_RegExCompile and HB_RegExMatch.",
|
| 382 |
+
"expected_keywords": ["HB_RegEx", "FUNCTION"],
|
| 383 |
+
"min_lines": 6,
|
| 384 |
+
},
|
| 385 |
+
{
|
| 386 |
+
"id": "HARB_03", "category": "Harbour-Specific", "name": "Serialization",
|
| 387 |
+
"prompt": "Write Harbour code that serializes a hash to binary with HB_Serialize and deserializes with HB_Deserialize.",
|
| 388 |
+
"expected_keywords": ["HB_Serialize", "HB_Deserialize"],
|
| 389 |
+
"min_lines": 6,
|
| 390 |
+
},
|
| 391 |
+
{
|
| 392 |
+
"id": "HARB_04", "category": "Harbour-Specific", "name": "File path operations",
|
| 393 |
+
"prompt": "Write Harbour code using hb_DirBuild, hb_DirNameGet, hb_FileNameGet, hb_PathNormalize for cross-platform file handling.",
|
| 394 |
+
"expected_keywords": ["hb_Dir", "hb_File", "hb_Path"],
|
| 395 |
+
"min_lines": 6,
|
| 396 |
+
},
|
| 397 |
+
]
|
| 398 |
+
|
| 399 |
+
# ============================================================
|
| 400 |
+
# MAIN
|
| 401 |
+
# ============================================================
|
| 402 |
+
|
| 403 |
+
def main():
|
| 404 |
+
print("=" * 70)
|
| 405 |
+
print("HARBOUR CODE GENERATION TEST BATTERY")
|
| 406 |
+
print(f"Model: {MODEL}")
|
| 407 |
+
print(f"Tests: {len(TESTS)}")
|
| 408 |
+
print(f"Harbour: {HARBOUR}")
|
| 409 |
+
print(f"Started: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}")
|
| 410 |
+
print("=" * 70)
|
| 411 |
+
|
| 412 |
+
SYSTEM = """You are an expert Harbour programmer. Write clean, correct, COMPILABLE Harbour code.
|
| 413 |
+
Use Hungarian notation: n=numeric, c=character, l=logical, a=array, o=object, d=date.
|
| 414 |
+
Use 3-space indentation.
|
| 415 |
+
Do NOT include explanations or markdown. Only raw Harbour code.
|
| 416 |
+
End functions with RETURN and END FUNCTION."""
|
| 417 |
+
|
| 418 |
+
results = []
|
| 419 |
+
compile_pass = 0
|
| 420 |
+
compile_fail = 0
|
| 421 |
+
|
| 422 |
+
for i, test in enumerate(TESTS, 1):
|
| 423 |
+
print(f"\n[{i:2d}/{len(TESTS)}] {test['id']}: {test['name']}")
|
| 424 |
+
|
| 425 |
+
# Query model
|
| 426 |
+
result = query_ollama(test["prompt"], SYSTEM)
|
| 427 |
+
|
| 428 |
+
if result["error"]:
|
| 429 |
+
print(f" MODEL ERROR: {result['error']}")
|
| 430 |
+
results.append({"test": test, "model_error": result["error"], "compile": False, "compile_error": ""})
|
| 431 |
+
continue
|
| 432 |
+
|
| 433 |
+
# Clean response
|
| 434 |
+
code = clean_code(result["response"])
|
| 435 |
+
|
| 436 |
+
# Check for expected keywords
|
| 437 |
+
keywords_found = [kw for kw in test["expected_keywords"] if kw.upper() in code.upper()]
|
| 438 |
+
keywords_missing = [kw for kw in test["expected_keywords"] if kw.upper() not in code.upper()]
|
| 439 |
+
|
| 440 |
+
# Compile
|
| 441 |
+
success, error, obj = compile_harbour(code)
|
| 442 |
+
|
| 443 |
+
status = "PASS" if success else "FAIL"
|
| 444 |
+
if success:
|
| 445 |
+
compile_pass += 1
|
| 446 |
+
else:
|
| 447 |
+
compile_fail += 1
|
| 448 |
+
|
| 449 |
+
print(f" Compile: {status} | Keywords: {len(keywords_found)}/{len(test['expected_keywords'])} | TPS: {result['tps']:.0f}")
|
| 450 |
+
if keywords_missing:
|
| 451 |
+
print(f" Missing keywords: {', '.join(keywords_missing)}")
|
| 452 |
+
if not success and error:
|
| 453 |
+
# Show first error only
|
| 454 |
+
first_error = error.split('\n')[0][:120]
|
| 455 |
+
print(f" Error: {first_error}")
|
| 456 |
+
|
| 457 |
+
results.append({
|
| 458 |
+
"test": test,
|
| 459 |
+
"code": code[:3000],
|
| 460 |
+
"compile_success": success,
|
| 461 |
+
"compile_error": error[:500] if error else "",
|
| 462 |
+
"keywords_found": keywords_found,
|
| 463 |
+
"keywords_missing": keywords_missing,
|
| 464 |
+
"tokens": result["eval_count"],
|
| 465 |
+
"tps": result["tps"],
|
| 466 |
+
"duration": result["duration"],
|
| 467 |
+
"lines": code.count('\n') + 1,
|
| 468 |
+
})
|
| 469 |
+
|
| 470 |
+
# Summary by category
|
| 471 |
+
print("\n" + "=" * 70)
|
| 472 |
+
print("RESULTS SUMMARY")
|
| 473 |
+
print("=" * 70)
|
| 474 |
+
|
| 475 |
+
categories = {}
|
| 476 |
+
for r in results:
|
| 477 |
+
cat = r["test"]["category"]
|
| 478 |
+
if cat not in categories:
|
| 479 |
+
categories[cat] = {"pass": 0, "fail": 0, "total": 0}
|
| 480 |
+
categories[cat]["total"] += 1
|
| 481 |
+
if r.get("compile_success"):
|
| 482 |
+
categories[cat]["pass"] += 1
|
| 483 |
+
else:
|
| 484 |
+
categories[cat]["fail"] += 1
|
| 485 |
+
|
| 486 |
+
print(f"\n{'Category':<20} {'Pass':<6} {'Fail':<6} {'Rate':<8}")
|
| 487 |
+
print("-" * 45)
|
| 488 |
+
for cat, data in sorted(categories.items()):
|
| 489 |
+
rate = data["pass"] / data["total"] * 100 if data["total"] > 0 else 0
|
| 490 |
+
print(f"{cat:<20} {data['pass']:<6} {data['fail']:<6} {rate:.0f}%")
|
| 491 |
+
|
| 492 |
+
print(f"\n{'TOTAL':<20} {compile_pass:<6} {compile_fail:<6} {compile_pass/len(results)*100:.0f}%")
|
| 493 |
+
print(f"Total tests: {len(results)}")
|
| 494 |
+
|
| 495 |
+
total_tokens = sum(r.get("tokens", 0) for r in results)
|
| 496 |
+
total_time = sum(r.get("duration", 0) for r in results)
|
| 497 |
+
print(f"Total tokens: {total_tokens:,}")
|
| 498 |
+
print(f"Total time: {total_time:.1f}s")
|
| 499 |
+
|
| 500 |
+
# Save
|
| 501 |
+
output = Path("/home/fivetech/finetune/test_baseline_qwen36.json")
|
| 502 |
+
with open(output, "w") as f:
|
| 503 |
+
json.dump({
|
| 504 |
+
"model": MODEL,
|
| 505 |
+
"timestamp": datetime.now().isoformat(),
|
| 506 |
+
"compile_pass": compile_pass,
|
| 507 |
+
"compile_fail": compile_fail,
|
| 508 |
+
"compile_rate": compile_pass / len(results) * 100,
|
| 509 |
+
"categories": categories,
|
| 510 |
+
"results": results,
|
| 511 |
+
}, f, indent=2, ensure_ascii=False)
|
| 512 |
+
|
| 513 |
+
print(f"\nResults saved to: {output}")
|
| 514 |
+
|
| 515 |
+
if __name__ == "__main__":
|
| 516 |
+
main()
|