repo stringclasses 454
values | file_path stringlengths 5 201 | extension stringclasses 1
value | content stringlengths 8 509k | num_lines int64 3 16.9k | size_bytes int64 8 511k |
|---|---|---|---|---|---|
ai-agent-book | chapter1/learning-from-experience/tests/test_zero_episodes.py | .py | #!/usr/bin/env python3
"""Regression tests for zero-episode division guards.
Bug: train()/evaluate() divided victory counts by episode counts, so
num_episodes=0 (accepted by experiment.py's argparse) crashed with
ZeroDivisionError. Fixed by guarding the divisions and rejecting
episode counts < 1 in experiment.py's fro... | 44 | 1,545 |
ai-agent-book | chapter1/learning-from-experience/tests/test_basic.py | .py | #!/usr/bin/env python3
"""
Basic test to verify all components work correctly.
"""
import sys
from pathlib import Path
PROJECT_ROOT = Path(__file__).resolve().parents[1]
if str(PROJECT_ROOT) not in sys.path:
sys.path.insert(0, str(PROJECT_ROOT))
def test_game_environment():
"""Test that the game environment... | 168 | 4,862 |
ai-agent-book | chapter1/learning-from-experience/tests/test_rl_progress_small_episodes.py | .py | """Regression: progress prints must not ZeroDivisionError when episodes < 10."""
def test_progress_every_never_zero():
for num_episodes in (1, 5, 9, 10, 100):
progress_every = max(1, num_episodes // 10)
assert progress_every >= 1
# modulo must be defined
for episode in range(num_ep... | 17 | 587 |
ai-agent-book | chapter1/learning-from-experience/tests/manual/rl_learning_check.py | .py | #!/usr/bin/env python3
"""
Manual check to verify Q-learning can learn the simplified game.
"""
import sys
import argparse
from pathlib import Path
import numpy as np
PROJECT_ROOT = Path(__file__).resolve().parents[2]
if str(PROJECT_ROOT) not in sys.path:
sys.path.insert(0, str(PROJECT_ROOT))
from game_environme... | 183 | 6,260 |
ai-agent-book | chapter1/context/create_sample_pdf.py | .py | """
Create Sample PDF for Testing
Generates a financial report PDF with various currency amounts and calculations
"""
from reportlab.lib import colors
from reportlab.lib.pagesizes import letter, A4
from reportlab.platypus import SimpleDocTemplate, Table, TableStyle, Paragraph, Spacer, PageBreak
from reportlab.lib.styl... | 275 | 10,567 |
ai-agent-book | chapter1/context/main.py | .py | """
Main entry point for Context-Aware Agent
"""
import os
import sys
import argparse
import logging
from agent import ContextAwareAgent, ContextMode
from config import PROVIDERS, SUPPORTED_PROVIDERS, canonical_provider, resolve_backend
import json
from pathlib import Path
import subprocess
import time
from typing imp... | 1,229 | 51,297 |
ai-agent-book | chapter1/context/test_main_result_semantics.py | .py | from main import _completed
def test_completed_field_is_authoritative_over_legacy_success_alias():
assert _completed({"completed": False, "success": True}) is False
assert _completed({"completed": True, "success": False}) is True
def test_completed_falls_back_for_old_result_artifacts():
assert _complete... | 12 | 400 |
ai-agent-book | chapter1/context/run_experiment_1_1.py | .py | #!/usr/bin/env python3
"""Run the exact five-arm context ablation from book/chapter1.md.
Unlike the legacy demo table, this runner persists every credential-free API
request and response. That makes it possible to prove which context component
was removed on every inference instead of inferring the ablation from a CL... | 464 | 17,119 |
ai-agent-book | chapter1/context/test_experiment_1_1.py | .py | from agent import AgentTrajectory, ContextMode
from run_experiment_1_1 import (
canonical_answer_correct,
evaluate_context_contract,
summarize_arm,
)
def turn(messages, *, tools=True, reasoning="reason"):
request = {"messages": messages}
if tools:
request.update({"tools": [{"type": "functi... | 126 | 4,423 |
ai-agent-book | chapter1/context/config.py | .py | """
Configuration module for Context-Aware Agent
"""
import os
from typing import Optional
from dotenv import load_dotenv
# Load environment variables
load_dotenv()
def _reasoning_safe_temperature(model, requested=1.0):
"""Reasoning models (Kimi K3, GPT-5, ...) only accept temperature=1.
Return 1 for those;... | 219 | 7,174 |
ai-agent-book | chapter1/context/agent.py | .py | """
Context-Aware AI Agent with Tool Calls
An agent using Qwen model from SiliconFlow with document parsing, currency conversion, and calculator tools.
Designed to demonstrate the importance of context through ablation studies.
"""
import json
import logging
from typing import List, Dict, Any, Optional
from dataclasse... | 967 | 40,573 |
ai-agent-book | chapter1/context/tests/test_malformed_tool_json.py | .py | """Regression: malformed tool-argument JSON must not abort the ReAct loop."""
from types import SimpleNamespace
from unittest.mock import MagicMock
from agent import ContextAwareAgent, ContextMode
def _choice(*, content=None, tool_calls=None):
msg = SimpleNamespace(
content=content,
tool_calls=to... | 75 | 2,669 |
ai-agent-book | chapter1/context/tests/test_agent.py | .py | #!/usr/bin/env python3
"""
Test script for Context-Aware Agent
Validates installation and basic functionality
"""
import sys
from agent import ContextAwareAgent, ContextMode, ToolRegistry
import unittest
from unittest.mock import MagicMock, patch
class TestToolRegistry(unittest.TestCase):
"""Test the tool regist... | 306 | 10,842 |
ai-agent-book | chapter1/context/tests/test_code_interpreter.py | .py | #!/usr/bin/env python3
"""
Test the code_interpreter tool with the agent
"""
import os
from agent import ContextAwareAgent, ContextMode
def test_code_interpreter():
"""Test code interpreter integration"""
print("\n" + "="*60)
print("🧪 CODE INTERPRETER TEST")
print("="*60)
# Check API ke... | 126 | 3,592 |
ai-agent-book | chapter1/context/tests/conftest.py | .py | """Pytest bootstrap for the context experiment tests."""
from pathlib import Path
import sys
PROJECT_ROOT = Path(__file__).resolve().parents[1]
if str(PROJECT_ROOT) not in sys.path:
sys.path.insert(0, str(PROJECT_ROOT))
| 10 | 227 |
ai-agent-book | chapter1/context/tests/manual/quickstart.py | .py | #!/usr/bin/env python3
"""
Quick Start Script for Context-Aware Agent
Run this to test the agent with a simple example
"""
import os
import sys
from _bootstrap import add_project_root
add_project_root()
from agent import ContextAwareAgent, ContextMode
from config import Config
def main():
"""Quick start demons... | 115 | 3,910 |
ai-agent-book | chapter1/context/tests/manual/check_deepseek.py | .py | #!/usr/bin/env python3
"""
Test script for DeepSeek model integration.
Tests deepseek-v4-flash (default) with conversation and tool calling.
"""
import os
import sys
from _bootstrap import add_project_root
add_project_root()
from dotenv import load_dotenv
from agent import ContextAwareAgent, ContextMode
from config... | 227 | 6,673 |
ai-agent-book | chapter1/context/tests/manual/check_deepseek_quick.py | .py | #!/usr/bin/env python3
"""
Quick smoke test for DeepSeek provider (deepseek-v4-flash).
"""
import os
import sys
import time
from _bootstrap import add_project_root
add_project_root()
from dotenv import load_dotenv
load_dotenv()
task = "What is 10 + 5? Provide FINAL ANSWER with just the number."
print("=" * 60)
p... | 67 | 1,656 |
ai-agent-book | chapter1/context/tests/manual/check_doubao_quick.py | .py | #!/usr/bin/env python3
"""
Quick test with Doubao as default
"""
import os
import sys
import time
from _bootstrap import add_project_root
add_project_root()
# Set a very simple task to test quickly
task = "What is 10 + 5? Provide FINAL ANSWER with just the number."
print("="*60)
print("QUICK TEST - Doubao Default ... | 61 | 1,454 |
ai-agent-book | chapter1/context/tests/manual/check_provider_switching.py | .py | #!/usr/bin/env python3
"""
Test script to verify provider switching functionality
"""
import os
from _bootstrap import add_project_root
add_project_root()
from dotenv import load_dotenv
from agent import ContextAwareAgent, ContextMode
from config import Config
# Load environment variables
load_dotenv()
def test_p... | 118 | 3,939 |
ai-agent-book | chapter1/context/tests/manual/check_doubao.py | .py | #!/usr/bin/env python3
"""
Quick test for Doubao provider
"""
import os
from _bootstrap import add_project_root
add_project_root()
from agent import ContextAwareAgent, ContextMode
def test_doubao():
"""Test Doubao provider with a simple task"""
print("\n" + "="*60)
print("🧪 DOUBAO PROVIDER TEST")... | 65 | 1,985 |
ai-agent-book | chapter1/context/tests/manual/check_conversation_history.py | .py | #!/usr/bin/env python3
"""
Test script to verify conversation history persistence
"""
import os
from _bootstrap import add_project_root
add_project_root()
from dotenv import load_dotenv
from agent import ContextAwareAgent, ContextMode
import json
# Load environment variables
load_dotenv()
def test_conversation_hi... | 138 | 5,139 |
ai-agent-book | chapter1/context/tests/manual/check_kimi.py | .py | #!/usr/bin/env python3
"""
Test script for Kimi K3 model integration
Tests the Kimi K3 model (kimi-k3) with various tasks
"""
import os
import sys
from _bootstrap import add_project_root
add_project_root()
from dotenv import load_dotenv
from agent import ContextAwareAgent, ContextMode
from config import Config
# L... | 250 | 7,234 |
ai-agent-book | chapter1/context/tests/manual/demo_conversation.py | .py | #!/usr/bin/env python3
"""
Demo script showing conversation history persistence
"""
import os
from _bootstrap import add_project_root
add_project_root()
from dotenv import load_dotenv
from agent import ContextAwareAgent, ContextMode
# Load environment variables
load_dotenv()
def main():
# Get API key (use any... | 86 | 2,877 |
ai-agent-book | chapter1/context/tests/manual/check_pdf_task.py | .py | #!/usr/bin/env python3
"""
Test script to verify PDF parsing and currency conversion
"""
import os
import sys
from _bootstrap import add_project_root
add_project_root()
from agent import ContextAwareAgent, ContextMode
def test_pdf_with_currencies():
"""Test PDF parsing with currency conversion"""
prin... | 102 | 3,378 |
ai-agent-book | chapter1/context/tests/manual/check_default_provider.py | .py | #!/usr/bin/env python3
"""
Test that Doubao is the default provider
"""
import os
import sys
from _bootstrap import add_project_root
add_project_root()
# Test without any arguments - should use Doubao
print("Testing default provider...")
# Check if ARK_API_KEY is available
ark_key = os.getenv("ARK_API_KEY")
sf_key... | 46 | 1,350 |
ai-agent-book | chapter1/context/tests/manual/check_provider_config.py | .py | #!/usr/bin/env python3
"""
Test script to verify provider configuration
"""
import os
from _bootstrap import add_project_root
add_project_root()
from agent import ContextAwareAgent, ContextMode
def test_providers():
"""Test different provider configurations"""
print("\n" + "="*60)
print("🧪 PROVID... | 130 | 4,535 |
ai-agent-book | chapter1/context/tests/manual/check_kimi_quick.py | .py | #!/usr/bin/env python3
"""
Quick test script to verify Kimi K3 model integration
"""
import os
from _bootstrap import add_project_root
add_project_root()
from dotenv import load_dotenv
from agent import ContextAwareAgent, ContextMode
# Load environment variables
load_dotenv()
def main():
# Get API key
api... | 58 | 1,461 |
ai-agent-book | chapter1/context/tests/manual/_bootstrap.py | .py | """Helpers for running manual smoke scripts from tests/manual."""
from pathlib import Path
import sys
def add_project_root() -> Path:
project_root = Path(__file__).resolve().parents[2]
if str(project_root) not in sys.path:
sys.path.insert(0, str(project_root))
return project_root
| 12 | 304 |
ai-agent-book | chapter1/context/tests/manual/show_sample_tasks.py | .py | #!/usr/bin/env python3
"""
Demo script to showcase sample tasks with PDF functionality
"""
import os
import sys
from pathlib import Path
from _bootstrap import add_project_root
add_project_root()
from main import get_sample_tasks, ensure_sample_pdfs
def main():
"""Demo the sample tasks"""
print("\n" + "="*... | 87 | 2,712 |
ai-agent-book | chapter1/context/tests/manual/check_simple_task.py | .py | #!/usr/bin/env python3
"""
Test with a simpler task to diagnose the issue
"""
import os
import sys
import time
from _bootstrap import add_project_root
add_project_root()
from agent import ContextAwareAgent, ContextMode
def test_simple_task():
"""Test with a very simple task to check if the agent is working"""
... | 88 | 2,575 |
ai-agent-book | chapter1/web-search-agent/quickstart.py | .py | #!/usr/bin/env python3
"""
快速开始脚本 - 一键体验 Kimi Web Search Agent
"""
import os
import sys
from agent import WebSearchAgent
from config import Config
# 彩色输出
class Colors:
HEADER = '\033[95m'
BLUE = '\033[94m'
CYAN = '\033[96m'
GREEN = '\033[92m'
WARNING = '\033[93m'
FAIL = '\033[91m'
END = '\... | 197 | 6,176 |
ai-agent-book | chapter1/web-search-agent/main.py | .py | """
主程序 - Web Search Agent 使用示例
演示第一章的 ReAct 循环（Reasoning + Acting）：模型先思考，再调用 web_search
行动，观察搜索结果后继续思考，直到综合出最终答案。运行时会逐步打印 ReAct 轨迹。
"""
import os
import sys
import json
import argparse
import logging
from typing import Optional
from agent import WebSearchAgent, run_offline_demo
from config import Config
# 设置日志
logg... | 223 | 8,593 |
ai-agent-book | chapter1/web-search-agent/run_experiment_1_2.py | .py | #!/usr/bin/env python3
"""Run Experiment 1-2 through Kimi K3's official Formula web-search tool."""
from __future__ import annotations
import argparse
import hashlib
import json
import os
import platform
import shutil
import subprocess
import sys
import time
from datetime import datetime, timezone
from pathlib import... | 282 | 10,982 |
ai-agent-book | chapter1/web-search-agent/examples.py | .py | """
高级示例 - 展示 Web Search Agent 的各种用法
"""
import asyncio
import json
from typing import List, Dict, Any
from agent import WebSearchAgent, is_failure_answer
from config import Config
import logging
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)
class AdvancedWebSearchAgent(WebSearchAgent... | 325 | 10,130 |
ai-agent-book | chapter1/web-search-agent/config.py | .py | """
配置文件 - Kimi API 配置
"""
import os
from typing import Optional
from dotenv import load_dotenv
load_dotenv()
from dotenv import load_dotenv
# Read the nearest .env, searching upward from the working directory, so a
# single file at the repository root serves every chapter.
load_dotenv()
# Provider resolution liv... | 93 | 2,698 |
ai-agent-book | chapter1/web-search-agent/agent.py | .py | """
Kimi Web Search Agent
一个基于 Kimi API 的智能搜索 Agent，能够理解用户问题，通过搜索引擎获取信息，并总结出答案。
"""
import json
from typing import List, Dict, Any, Optional
from openai import OpenAI
from openai.types.chat.chat_completion import Choice
import logging
import os
import requests
import time
# 设置日志
logging.basicConfig(level=logging.INFO... | 599 | 26,362 |
ai-agent-book | chapter1/web-search-agent/tests/test_config.py | .py | """Unit tests for model mapping and provider selection."""
import pytest
from config import map_model_to_openrouter, resolve_llm_backend
@pytest.mark.parametrize(
("model", "expected"),
[
("openai/gpt-5.6-luna", "openai/gpt-5.6-luna"),
("gpt-5.6-luna", "openai/gpt-5.6-luna"),
("o3-min... | 79 | 2,564 |
ai-agent-book | chapter1/web-search-agent/tests/test_examples.py | .py | """Unit tests for AdvancedWebSearchAgent helpers and failure classification."""
from unittest.mock import Mock
from agent import (
MAX_ITERATIONS_MESSAGE,
NO_INFO_MESSAGE,
SEARCH_ERROR_PREFIX,
is_failure_answer,
)
from examples import AdvancedWebSearchAgent
def build_advanced(answers):
"""Advanc... | 44 | 1,494 |
ai-agent-book | chapter1/web-search-agent/tests/test_experiment_1_2.py | .py | from run_experiment_1_2 import fiber_ids, validate
def formula_tool():
return {
"type": "function",
"function": {
"name": "web_search",
"description": "Search the web",
"parameters": {
"type": "object",
"properties": {"query": {"t... | 186 | 6,008 |
ai-agent-book | chapter1/web-search-agent/tests/test_agent.py | .py | """Unit tests for ReAct formatting, tools, and the agent loop."""
from unittest.mock import Mock
from agent import WebSearchAgent, _reasoning_safe_temperature, format_trace_step
class FakeResponse:
def __init__(self, payload, status_code=200):
self._payload = payload
self.status_code = status_co... | 285 | 9,591 |
ai-agent-book | chapter1/web-search-agent/tests/test_offline_demo.py | .py | """Tests for the deterministic offline ReAct demonstration."""
from agent import run_offline_demo
def test_offline_demo_returns_a_complete_deterministic_trace():
result = run_offline_demo("캐싱이 뭐야?", verbose=False)
assert result["question"] == "캐싱이 뭐야?"
assert [step["type"] for step in result["trace"]] =... | 38 | 1,099 |
ai-agent-book | chapter1/web-search-agent/tests/test_main.py | .py | """Tests for CLI parsing, offline dispatch, and JSON output."""
import json
import main as cli
from config import Config
def test_parser_defaults_to_interactive_kimi_mode():
args = cli.build_parser().parse_args([])
assert args.query == []
assert args.provider == "kimi"
assert args.model == Config.D... | 82 | 2,332 |
ai-agent-book | chapter1/web-search-agent/tests/conftest.py | .py | """Shared pytest fixtures for the web search agent test suite."""
import json
import socket
from types import SimpleNamespace
import pytest
PROVIDER_ENV_VARS = (
"MOONSHOT_API_KEY",
"KIMI_API_KEY",
"OPENROUTER_API_KEY",
"OPENROUTER_BASE_URL",
"OPENROUTER_MODEL",
)
@pytest.fixture(autouse=True)
... | 81 | 2,166 |
ai-agent-book | chapter1/search-codegen/quickstart.py | .py | #!/usr/bin/env python3
"""
Quick Start Demo for GPT-5 Native Tools Agent
Demonstrates basic usage of web_search and code_interpreter tools
"""
import os
import sys
from agent import GPT5NativeAgent
from config import Config
def demo_web_search():
"""Demonstrate web search capability"""
print("\n" + "="*60)
... | 162 | 4,830 |
ai-agent-book | chapter1/search-codegen/main.py | .py | """
Main entry point for GPT-5 Native Tools Agent
Interactive CLI for using web_search and code_interpreter tools
"""
import sys
import json
import logging
from typing import Optional
from agent import GPT5NativeAgent, GPT5AgentChain
from config import Config
import argparse
# Set up logging
logging.basicConfig(
... | 445 | 15,959 |
ai-agent-book | chapter1/search-codegen/example_request.py | .py | #!/usr/bin/env python3
"""
Example showing the exact OpenRouter GPT-5 request format matching the Go implementation
"""
import json
import requests
import os
from typing import Dict, Any
try:
from dotenv import load_dotenv
load_dotenv()
except ImportError:
pass
def make_gpt5_openrouter_request(
api_k... | 250 | 7,659 |
ai-agent-book | chapter1/search-codegen/run_experiment_1_3.py | .py | #!/usr/bin/env python3
"""Run Experiment 1-3 on a hosted web-search + code-execution Responses API.
Acceptance policy (author-mandated, 2026-07-31): the experiment's essence is
model-directed multi-round web search + hosted code execution, clarification
before tools, and a current answer with authoritative sources. Th... | 448 | 16,885 |
ai-agent-book | chapter1/search-codegen/test_responses_agent.py | .py | from agent import GPT5NativeAgent
from config import Config
from run_experiment_1_3 import (
acceptance,
independent_asean_reference,
validate_asean,
validate_clarification,
)
DASHSCOPE_URL = "https://dashscope-intl.aliyuncs.com/compatible-mode/v1"
def test_request_uses_official_responses_tool_shapes... | 193 | 7,098 |
ai-agent-book | chapter1/search-codegen/config.py | .py | """Configuration for the exact GPT-5.6 Responses API companion."""
import os
from typing import Optional, Tuple
from dotenv import load_dotenv
load_dotenv()
def _optional_int_env(name: str) -> Optional[int]:
"""Read an optional integer without making module import configuration-fatal."""
raw_value = os.get... | 87 | 3,400 |
ai-agent-book | chapter1/search-codegen/test_config_and_usage.py | .py | import os
from pathlib import Path
import subprocess
import sys
import example_request
ROOT = Path(__file__).parent
def _import_config_with(value: str | None) -> subprocess.CompletedProcess[str]:
env = os.environ.copy()
if value is None:
env.pop("DEFAULT_MAX_TOKENS", None)
else:
env["DE... | 90 | 2,520 |
ai-agent-book | chapter1/search-codegen/agent.py | .py | """Exact GPT-5.6 Responses API agent for Experiment 1-3.
The previous companion sent Responses-style hosted tools to Chat Completions
through a proxy and then reported an empty ``tool_calls`` list. This module
uses the actual ``/v1/responses`` protocol and preserves its typed output items
(``web_search_call``, ``code... | 397 | 16,312 |
ai-agent-book | chapter1/search-codegen/tests/manual/agent_cases.py | .py | """
Live manual cases for GPT-5 Native Tools Agent.
These cases demonstrate web_search with the OpenRouter format and require
OPENROUTER_API_KEY.
"""
import json
import logging
import sys
from typing import Dict, Any, List
from datetime import datetime
from pathlib import Path
PROJECT_ROOT = Path(__file__).resolve()... | 364 | 11,743 |
ai-agent-book | book-ar/svg_lib.py | .py | """SVG diagram generation library for book illustrations.
Style: black/white/grayscale for B&W printing.
- White (#fff) backgrounds
- Light gray (#f0f0f0) box fills
- Medium gray (#d0d0d0) secondary fills
- Dark gray (#999) emphasis fills
- Black (#333) borders and text
- 2px stroke, 6px rounded corners
- Sans-serif f... | 693 | 27,564 |
ai-agent-book | book-ar/test_svg_lib.py | .py | import unittest
from svg_lib import _char_w, _text_width, _wrap_line
class ArabicTextWidthTests(unittest.TestCase):
def test_combining_marks_have_zero_width(self):
self.assertEqual(_char_w('\u064e'), 0) # Fatha
self.assertEqual(_char_w('\u0651'), 0) # Shadda
def test_harakat_do_not_force_a... | 23 | 692 |
ai-agent-book | book-zhtw/strip_titles.py | .py | #!/usr/bin/env python3
"""Strip in-figure titles from checked-in SVGs and crop top whitespace.
按學術規範：圖本身不包含標題（標題寫在正文）。本指令碼保守地處理
`images/` 中已簽入的 SVG 檔案。
判定規則（保守）：
- 第一處出現的 <text> 元素，若同時滿足：font-size>=20 且 y<60 且 text-anchor=middle，
則視為圖示題——刪除該元素，並將 viewBox 上沿和 height 各下移/縮小 CROP_PX。
- 否則該檔案不做任何修改。
用法：python3 strip_t... | 112 | 3,577 |
ai-agent-book | book-zhtw/gen_cover.py | .py | #!/usr/bin/env python3
"""Generate the book cover image with an image-generation model.
This is, fittingly, the book eating its own dog food: the cover of a book about
AI agents is produced by calling an image-generation model. Run it once; the
cover (cover.tex) automatically switches to images/cover-image.png when pr... | 85 | 4,156 |
ai-agent-book | chapter8/speech-sft-experiment/run_orpheus.py | .py | #!/usr/bin/env python3
"""Run the Orpheus half of Experiment 7-6 on one local CUDA GPU.
The campaign deliberately keeps a held-out split and emits base/adapted audio
for identical prompts and seeds. It is bounded for a workstation, but it is
not a one-batch smoke test: the default run encodes 144 real utterances and
... | 309 | 12,098 |
ai-agent-book | chapter8/speech-sft-experiment/test_experiment.py | .py | import importlib.util
from pathlib import Path
import torch
HERE = Path(__file__).parent
def load(name):
spec = importlib.util.spec_from_file_location(name, HERE / f"{name}.py")
module = importlib.util.module_from_spec(spec)
spec.loader.exec_module(module)
return module
def test_sesame_tag_catego... | 50 | 1,638 |
ai-agent-book | chapter8/speech-sft-experiment/analyze_campaign.py | .py | #!/usr/bin/env python3
"""Build the strict, hash-verified acceptance package for Experiment 7-6."""
from __future__ import annotations
import argparse
import hashlib
import itertools
import json
from pathlib import Path
import librosa
import numpy as np
import soundfile as sf
import torch
from huggingface_hub import... | 290 | 14,968 |
ai-agent-book | chapter8/speech-sft-experiment/run_sesame.py | .py | #!/usr/bin/env python3
"""Run the Sesame CSM paralinguistic-tag half of Experiment 7-6."""
from __future__ import annotations
import argparse
import hashlib
import json
import os
import random
import re
import shutil
import tempfile
import time
from pathlib import Path
import numpy as np
import soundfile as sf
impor... | 315 | 13,148 |
ai-agent-book | chapter8/continued-pretraining/continued-pretrain.py | .py | # -*- coding: utf-8 -*-
"""Continued pretraining - Korean + Unsloth.ipynb
Automatically generated by Colab.
Original file is located at
https://colab.research.google.com/drive/1tEd1FrOXWMnCU9UIvdYhs61tkxdMuKZu
To run this, press "*Runtime*" and press "*Run all*" on a **free** Tesla T4 Google Colab instance!
<div... | 646 | 30,047 |
ai-agent-book | chapter8/continued-pretraining/evaluate_model.py | .py | # -*- coding: utf-8 -*-
"""
Evaluation script for Korean Mistral continued-pretrained models
Loads saved LoRA adapters and evaluates on Korean and English tasks
"""
import os
import argparse
# 说明：unsloth / torch / transformers 等重型依赖在函数内按需导入，
# 这样 `python evaluate_model.py --help` 无需 GPU 环境即可查看参数。
# ANSI color codes ... | 286 | 10,402 |
ai-agent-book | chapter8/continued-pretraining/compare_models.py | .py | # -*- coding: utf-8 -*-
"""
Compare baseline → pretrained → finetuned Korean Mistral models (3-way comparison)
Shows progression from original model to final Korean-capable model
"""
import argparse
# 说明：unsloth / torch 等重型依赖在函数内按需导入，
# 这样 `python compare_models.py --help` 无需 GPU 环境即可查看参数。
# ANSI color codes for col... | 297 | 13,980 |
ai-agent-book | chapter8/continued-pretraining/validation/validate_evidence.py | .py | #!/usr/bin/env python3
"""Fail-closed validator for the canonical Experiment 7-5 report evidence."""
from __future__ import annotations
import argparse
import hashlib
import json
import re
from pathlib import Path
from typing import Any
HERE = Path(__file__).resolve().parent
EXPERIMENT_DIR = HERE.parent
REPO_ROOT =... | 213 | 9,947 |
ai-agent-book | chapter8/continued-pretraining/validation/test_report_audit.py | .py | from __future__ import annotations
import importlib.util
import json
from pathlib import Path
HERE = Path(__file__).resolve().parent
def load_module(name: str, path: Path):
spec = importlib.util.spec_from_file_location(name, path)
assert spec and spec.loader
module = importlib.util.module_from_spec(spe... | 55 | 1,985 |
ai-agent-book | chapter8/continued-pretraining/validation/run_report_audit.py | .py | #!/usr/bin/env python3
"""Build the canonical, checkpoint-free evidence package for Experiment 7-5.
The historical RTX 4090 run is retained as a raw terminal transcript in
``model_eval_results.md``. This tool does not pretend to rerun that GPU job.
It extracts the fifteen saved generations, submits five stage-blind c... | 781 | 30,897 |
ai-agent-book | chapter8/premature-completion-dpo/train_dpo.py | .py | """DPO 训练脚本（实验 7-17 主线，需要单卡 GPU）。
默认配置面向单卡：bf16、gradient checkpointing、LoRA r=16 alpha=32、
per_device_batch_size=1、gradient_accumulation 2、learning_rate 3e-5、
beta 0.1、4 epochs。小数据集使用较小的累积步数，确保确实有足够的更新步；可用
`--epochs`、`--gradient-accumulation` 和 `--learning-rate` 覆盖。训练产物：output/adapter/（仅 LoRA adapter），
训练回执 validation... | 174 | 6,919 |
ai-agent-book | chapter8/premature-completion-dpo/llm_client.py | .py | """OpenAI 兼容 API 客户端与证据回执工具（真实 LLM 路径专用）。
约定与 chapter8/self-modifying-agent/llm_generator.py 一致：
原始请求、原始响应、token 用量、延迟、请求/响应哈希都进入证据回执；
validation/<run>/evidence.json 保存完整证据，validation/latest.json 指向最近一次。
"""
from __future__ import annotations
import hashlib
import json
import os
import time
from pathlib import Path
... | 100 | 3,901 |
ai-agent-book | chapter8/premature-completion-dpo/test_pipeline.py | .py | """实验 7-17 的离线单元测试（pytest，不依赖 API key 与 GPU）。
覆盖：
- bad case 数据结构完整性（24 条、四类各 6 条、字段齐全）；
- 偏好对构造规则（chosen 无完成宣称且含验证动作，rejected 含完成宣称）；
- 评估分类器对宣称完成/继续验证的判别；
- boundary/retention 与训练数据的隔离（无重复 id/任务）；
- mock 评估指标与隐藏测试奖励函数。
"""
from __future__ import annotations
import json
from pathlib import Path
import pytest
from... | 201 | 7,328 |
ai-agent-book | chapter8/premature-completion-dpo/evaluate.py | .py | """评估脚本：对比 base 与 base+adapter 在边界集/保留集上的"下一步动作"行为。
指标口径：
- boundary 过早宣称率：任务未真正完成时仍宣称完成的比例（训练后应下降）；
- retention 正常收尾率：任务确实完成时正常宣称完成的比例（训练后应保持）；
- 过度矫正率 = 1 - retention 正常收尾率（模型被训得永远不敢收尾的程度）。
判定使用确定性分类器（关键词/模式），不依赖 LLM；可选 --judge 用 LLM 复核并留证据回执。
--mock 模式不加载模型，用预置样例输出演示评估逻辑，离线可跑。
"""
from __future__ import annotatio... | 352 | 15,385 |
ai-agent-book | chapter8/premature-completion-dpo/demo.py | .py | """离线端到端教学演示（实验 7-17）。
不依赖 API key、不依赖 GPU，演示完整链路：
1. 从过早结束 bad case 构造 DPO 偏好对（离线确定性路径）；
2. 展示 2 条样例偏好对；
3. 用 --mock 评估演示指标计算（base vs adapter 的预置样例输出）；
4. 打印全流程摘要与真实训练所需的后续步骤。
"""
from __future__ import annotations
import json
from build_preference_data import build_pairs, load_bad_cases
from evaluate import compu... | 64 | 2,960 |
ai-agent-book | chapter8/premature-completion-dpo/train_grpo_optional.py | .py | """可选 RL 分支：GRPO + 隐藏验收测试作为奖励（实验 7-17 可选路径，主线是 DPO）。
奖励函数 = 隐藏验收测试：对每个端到端任务，模型输出若宣称完成，则在隔离的
临时目录里还原工作区并运行该任务附带的隐藏检查脚本：
- 宣称完成且隐藏测试通过：+1
- 宣称完成但测试不过：-1
- 未宣称完成但执行了验证动作：+0.3
- 其它：0
隐藏测试定义在 data/hidden_tests.json。脚本真实可运行，但属于可选分支：
正文以 DPO 为主线，GRPO 路径需要 GPU 且训练成本更高。
"""
from __future__ import annotations
import argparse... | 131 | 4,684 |
ai-agent-book | chapter8/premature-completion-dpo/build_preference_data.py | .py | """从过早结束 bad case 构造 DPO 偏好对。
两条 chosen 生成路径：
1. 离线确定性路径（默认）：从模板 + 各 case 的 missing_verification 合成规范的
chosen 文本，不依赖 API key，保证全流程可跑通。
2. 教师模型路径（--teacher）：调用 OpenAI 兼容 API 生成 chosen，用规则过滤做
拒绝采样——chosen 必须包含验证动作（运行测试/核对验收条件）且不含完成宣称；
原始请求/响应与 token 用量保存为证据回执。
输出 DPO 格式的 output/preference_pairs.jsonl，每行含 promp... | 190 | 8,009 |
ai-agent-book | chapter8/sesame/inference.py | .py | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Sesame CSM (1B) TTS - Inference Script
This script loads a trained LoRA model and generates speech from text.
"""
import argparse
import torch
import soundfile as sf
from pathlib import Path
from datasets import load_dataset, Audio
from unsloth import FastModel
from ... | 231 | 6,813 |
ai-agent-book | chapter8/sesame/test_batch_inference.py | .py | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Regression tests for batch_inference.py JSON input handling:
- Items missing the required "text" field must raise a clear ValueError
(previously a bare KeyError: 'text' aborted the whole batch).
- An explicit JSON null "output" must fall back to the default filename... | 86 | 2,987 |
ai-agent-book | chapter8/sesame/sesame_csm_sft_unsloth.py | .py | # -*- coding: utf-8 -*-
"""Sesame_CSM_(1B)-TTS.ipynb
Automatically generated by Colab.
Original file is located at
https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Sesame_CSM_(1B)-TTS.ipynb
To run this, press "*Runtime*" and press "*Run all*" on a **free** Tesla T4 Google Colab instance!... | 415 | 17,435 |
ai-agent-book | chapter8/sesame/batch_inference.py | .py | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Sesame CSM (1B) TTS - Batch Inference Script
This script loads a trained LoRA model and generates speech from multiple texts.
"""
import argparse
import json
import torch
import soundfile as sf
from pathlib import Path
from typing import List, Dict
from tqdm import t... | 239 | 7,430 |
ai-agent-book | chapter8/curly-quote-sft/quality_audit.py | .py | """Deterministic quality gate for the scope-sensitive synthetic corpus.
This is the machine-checkable part of the manual audit: a reviewer samples
rows from each language/type stratum, while this gate rejects malformed or
ambiguous targets before they reach SFT.
"""
from __future__ import annotations
import json, re
... | 68 | 2,616 |
ai-agent-book | chapter8/curly-quote-sft/evaluate.py | .py | from __future__ import annotations
import argparse, hashlib, json, re
from pathlib import Path
import torch
from peft import PeftModel
from transformers import AutoModelForCausalLM, AutoTokenizer
ROOT = Path(__file__).resolve().parent
def rows(path): return [json.loads(x) for x in Path(path).read_text(encoding="utf-8"... | 45 | 3,636 |
ai-agent-book | chapter8/curly-quote-sft/generate_data.py | .py | from __future__ import annotations
import hashlib
import json
from pathlib import Path
ROOT = Path(__file__).resolve().parent
DATA = ROOT / "data"
VERSIONS = ["v2", "v2.1", "v3", "v4-beta", "2026.08", "release-候选"]
ACTIONS = ["先运行测试", "先备份数据", "检查权限", "重新读取文件", "核对验收条件", "查看变更记录"]
STATUSES = ["ok", "ready", "pending... | 150 | 8,626 |
ai-agent-book | chapter8/curly-quote-sft/train_sft.py | .py | from __future__ import annotations
import argparse
import hashlib
import json
from datetime import datetime, timezone
from pathlib import Path
import torch
from peft import LoraConfig, get_peft_model
from transformers import AutoModelForCausalLM, AutoTokenizer
ROOT = Path(__file__).resolve().parent
def load_rows(p... | 94 | 5,199 |
ai-agent-book | chapter8/curly-quote-sft/tests/test_curly_pipeline.py | .py | import json
from pathlib import Path
ROOT = Path(__file__).parents[1]
def test_splits_are_nonempty_and_structured():
for name in ("train", "eval", "boundary"):
rows = [json.loads(x) for x in (ROOT / "data" / f"{name}.jsonl").read_text(encoding="utf-8").splitlines() if x.strip()]
assert rows
... | 50 | 2,663 |
ai-agent-book | chapter8/cot-distillation/test_load_verified_messages_colon.py | .py | """Regression: load_verified_messages must accept fullwidth colon and case-insensitive Final Answer."""
import json
from pathlib import Path
from train_student import load_verified_messages
def test_load_verified_messages_fullwidth_colon(tmp_path: Path):
sample = {
"messages": [
{"role": "use... | 33 | 1,154 |
ai-agent-book | chapter8/cot-distillation/test_analyze_null_assistant_content.py | .py | """SFT rows with null assistant content must not TypeError in analyze_data."""
import json
import sys
import analyze_data as ad
def test_null_assistant_content_skipped(tmp_path, monkeypatch, capsys):
sft = tmp_path / "sft.jsonl"
rows = [
{
"messages": [
{"role": "user", "... | 67 | 1,846 |
ai-agent-book | chapter8/cot-distillation/test_student_pipeline.py | .py | import json
from evaluate_student import (
BEHAVIORS,
behavior_flags,
compare_binary,
completion_and_findings,
exact_two_sided_sign_p_value,
)
from train_student import load_verified_messages
def test_load_verified_messages_rejects_unverified_shape(tmp_path):
path = tmp_path / "bad.jsonl"
... | 60 | 2,153 |
ai-agent-book | chapter8/cot-distillation/train_student.py | .py | #!/usr/bin/env python3
"""Train the Experiment 7-9 student on verified teacher CoT trajectories.
This is the parameter-update stage missing from the original collection-only
companion. It deliberately has no mock training mode: a successful run writes
a real Hugging Face/PEFT checkpoint plus a provenance manifest.
""... | 342 | 14,304 |
ai-agent-book | chapter8/cot-distillation/evaluate_student.py | .py | #!/usr/bin/env python3
"""Baseline/student/teacher acceptance campaign for Experiment 7-9."""
from __future__ import annotations
import argparse
import hashlib
import json
import math
import re
from datetime import datetime, timezone
from pathlib import Path
from typing import Any
from generate_data import ANSWER_SU... | 279 | 11,221 |
ai-agent-book | chapter8/cot-distillation/test_empty_problems.py | .py | """Empty problems JSONL must not ZeroDivisionError in the pass-rate summary."""
import asyncio
import json
import os
from types import ModuleType
import sys
# generate_data imports openai; stub if missing so the test stays offline.
try:
import openai # noqa: F401
except ImportError:
_oai = ModuleType("openai... | 119 | 3,976 |
ai-agent-book | chapter8/cot-distillation/analyze_data.py | .py | """统计蒸馏得到的 SFT 数据：规模、token/字符分布、思考链特征。"""
import argparse
import json
import re
def main():
parser = argparse.ArgumentParser(description="统计 CoT 蒸馏 SFT 数据")
parser.add_argument("--sft", default="./data/sft_cot_distill_aime.jsonl")
parser.add_argument("--raw", default="./data/raw_trajectories_aime.jsonl")... | 72 | 2,742 |
ai-agent-book | chapter8/cot-distillation/generate_data.py | .py | """
CoT 蒸馏数据采集脚本（实验 7-9 配套代码）
方法（对应书中实验 7-9 的三步流程之第一步"采集轨迹"）：
1. 从 problems.jsonl 读取带标准答案的数学题（规则可验证的任务分布）；
2. 通过 OpenRouter 调用前沿教师模型（默认 Claude），开启 reasoning 获取
完整"思考 + 答案"轨迹（Claude 4 系列返回的是 summarized thinking——由另一个
模型对原始思维链做的高保真摘要，原始思维链只存在于加密的 signature 字段中）；
3. 用规则验证器核对最终答案，只把答对的轨迹写成 SFT 训练数据
（"... | 321 | 14,508 |
ai-agent-book | chapter8/cot-distillation/test_analyze_short_messages.py | .py | """SFT rows with messages shorter than 2 must not IndexError in analyze_data."""
import json
import sys
from pathlib import Path
import analyze_data as ad
def test_short_messages_skipped_without_index_error(tmp_path, monkeypatch, capsys):
sft = tmp_path / "sft.jsonl"
rows = [
{"messages": [{"role": ... | 65 | 1,884 |
ai-agent-book | chapter8/cot-distillation/sft_data_auditor.py | .py | """
SFT training-data quality auditor (chapter 7 CoT distillation).
Every chapter 7 SFT experiment (7-8, 7-9, 7-17, 7-18, 7-19) consumes JSONL
training data: one JSON object per line, each carrying a ``messages`` array of
``{"role", "content"}`` pairs. ``generate_data.py`` synthesizes that data and
``analyze_data.py``... | 666 | 26,998 |
ai-agent-book | chapter8/orpheus/test_orpheus_inference.py | .py | import importlib.util
import sys
from pathlib import Path
from types import ModuleType
from unittest.mock import MagicMock, patch
import pytest
import torch
def _optional_dependency_stubs():
torchaudio = ModuleType("torchaudio")
torchaudio.__path__ = []
transforms = ModuleType("torchaudio.transforms")
... | 86 | 2,696 |
ai-agent-book | chapter8/orpheus/inference.py | .py | #!/usr/bin/env python3
"""
Orpheus TTS Inference Script
This script provides a standalone inference interface for the Orpheus text-to-speech model.
It supports both single-speaker and multi-speaker TTS generation.
Usage:
python inference.py
Or import as a module:
from inference import OrpheusInference
tt... | 385 | 13,974 |
ai-agent-book | chapter8/orpheus/orpheus_sft_unsloth.py | .py | # -*- coding: utf-8 -*-
"""Orpheus_(3B)-TTS.ipynb
Automatically generated by Colab.
Original file is located at
https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Orpheus_(3B)-TTS.ipynb
To run this, press "*Runtime*" and press "*Run all*" on a **free** Tesla T4 Google Colab instance!
<div ... | 510 | 19,987 |
ai-agent-book | chapter8/MiniMind-pretrain/validation/run_training_report_audit.py | .py | #!/usr/bin/env python3
"""Build checkpoint-free retained training evidence for Experiment 7-3.
The book already contains the author's historical six-cell evaluation report:
original versus QK-Norm + Muon at pretrain, SFT, and DPO. This program does
not pretend to rerun the GPU training job. It extracts every saved g... | 761 | 34,784 |
ai-agent-book | chapter8/MiniMind-pretrain/validation/validate_evidence.py | .py | #!/usr/bin/env python3
"""Fail-closed validator for Experiment 7-3 retained training evidence."""
from __future__ import annotations
import argparse
import hashlib
import json
import re
from pathlib import Path
from typing import Any
HERE = Path(__file__).resolve().parent
EXPERIMENT_DIR = HERE.parent
REPO_ROOT = EX... | 314 | 14,855 |
ai-agent-book | chapter8/MiniMind-pretrain/validation/validate_vlm_evidence.py | .py | #!/usr/bin/env python3
"""Fail-closed validator for the canonical Experiment 7-4 evidence package."""
from __future__ import annotations
import argparse
import base64
import hashlib
import json
import re
from pathlib import Path
from typing import Any
import run_vlm_training_report_audit as audit
HERE = Path(__file... | 360 | 14,797 |
ai-agent-book | chapter8/MiniMind-pretrain/validation/run_vlm_training_report_audit.py | .py | #!/usr/bin/env python3
"""Build checkpoint-free retained training evidence for Experiment 7-4.
The book contains 64 historical MiniMind-V image descriptions: eight model
configurations evaluated on the same eight images. This program extracts all
of them, asks a real image-capable model to judge every anonymous candi... | 923 | 42,148 |
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