Initial commit: Original Python LLMTester project

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2025-10-03 01:11:39 -04:00
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import hashlib
import re
import textwrap
from pathlib import Path
from typing import Dict, List, Optional
from config import RESULTS_DIR, TEMPLATE_PATH, TEMP_DIR
from markdown_linter import infer_language_from_prompt, lint_response_markdown
_TEMPLATE_CACHE: Optional[str] = None
class TemplateNotFoundError(FileNotFoundError):
pass
def load_template() -> str:
"""Load the test block template from disk, caching the content."""
global _TEMPLATE_CACHE
if _TEMPLATE_CACHE is None:
if not TEMPLATE_PATH.exists():
raise TemplateNotFoundError(
f"Template file not found at '{TEMPLATE_PATH}'. Please create it before running tests."
)
_TEMPLATE_CACHE = TEMPLATE_PATH.read_text(encoding="utf-8")
return _TEMPLATE_CACHE
def has_unclosed_code_block(markdown_text: str) -> bool:
"""Check if markdown text ends inside an unclosed triple-backtick block."""
fence_count = markdown_text.count("```")
return fence_count % 2 == 1
def render_response_block(result: Dict[str, object], *, language_hint: str) -> str:
"""Render the response portion of the template based on the result payload."""
if "error" in result:
return "\n".join(["### Response:", f"**ERROR:** {result['error']}", ""])
cleaned_response = lint_response_markdown(result["response"], language_hint=language_hint)
section_lines = ["### Response:"]
if cleaned_response:
section_lines.append("")
section_lines.append(cleaned_response)
section_lines.append("")
return "\n".join(section_lines)
def render_test_block(
prompt_info: Dict[str, str],
result: Dict[str, object],
index: int,
) -> str:
"""Populate the test block template with data for a single test."""
template = load_template()
metrics = result.get("metrics", {}) if "error" not in result else {}
ttft_value = metrics.get("time_to_first_token") if metrics else None
language_hint = infer_language_from_prompt(prompt_info["prompt"])
replacements = {
"{{TEST_NUMBER}}": str(index),
"{{TEST_TITLE}}": prompt_info.get("title", f"Test {index}"),
"{{SOURCE_FILENAME}}": prompt_info.get("filename", "unknown"),
"{{PROMPT_CONTENT}}": prompt_info["prompt"].strip(),
"{{RESPONSE_BLOCK}}": render_response_block(result, language_hint=language_hint).rstrip(),
"{{METRIC_TOKENS_PER_SECOND}}": (
str(metrics.get("tokens_per_second", "N/A"))
if metrics
else "N/A"
),
"{{METRIC_TOTAL_TOKENS}}": (
str(metrics.get("total_tokens", "N/A"))
if metrics
else "N/A"
),
"{{METRIC_TTFT}}": (
f"{ttft_value}s" if isinstance(ttft_value, (int, float)) else "N/A"
),
"{{METRIC_STOP_REASON}}": (
str(metrics.get("stop_reason", "N/A"))
if metrics
else "N/A"
),
}
rendered = template
for placeholder, value in replacements.items():
rendered = rendered.replace(placeholder, value)
return rendered.rstrip() + "\n\n"
def sanitize_model_name(model_name: str) -> str:
sanitized = re.sub(r"[^A-Za-z0-9._-]+", "_", model_name.strip())
return sanitized or "unknown-model"
def initialize_report_file(model_label: str) -> Path:
"""Create the markdown report shell and return its path."""
sanitized = sanitize_model_name(model_label)
RESULTS_DIR.mkdir(parents=True, exist_ok=True)
report_path = RESULTS_DIR / f"automated_report_{sanitized}.md"
header = textwrap.dedent(
f"""
# Automated Diagnostic Report: {model_label}
---
## Performance Summary
<!--SUMMARY_START-->
* **Average Tokens/s:** TBD
* **Average Time to First Token:** TBD
* **Total Tokens Generated:** TBD
<!--SUMMARY_END-->
## Qualitative Analysis
*(Manual grading and analysis of the responses is required to determine the final letter grade.)*
---
"""
).lstrip()
report_path.write_text(header, encoding="utf-8")
return report_path
def append_test_result(
report_path: Path,
prompt_info: Dict[str, str],
result: Dict[str, object],
index: int,
) -> None:
"""Append a single test section to the markdown report."""
block_content = render_test_block(prompt_info, result, index)
slug_base = re.sub(r"[^A-Za-z0-9._-]+", "-", prompt_info.get("title", f"test-{index}")).strip("-")
if not slug_base:
slug_base = f"test-{index}"
slug_hash = hashlib.sha1(slug_base.encode("utf-8")).hexdigest()[:8]
truncated_slug = slug_base[:48]
title_slug = f"{truncated_slug}-{slug_hash}"
temp_file = TEMP_DIR / f"{index:03d}_{title_slug}.md"
try:
temp_file.write_text(block_content, encoding="utf-8")
except OSError:
pass
block_text = temp_file.read_text(encoding="utf-8") if temp_file.exists() else block_content
if has_unclosed_code_block(block_text):
block_text = block_text.rstrip() + "\n```\n"
separator = "\n\n---\n\n"
existing_tail = report_path.read_text(encoding="utf-8") if report_path.exists() else ""
needs_separator = existing_tail and not existing_tail.endswith(separator)
with report_path.open("a", encoding="utf-8") as report_file:
if existing_tail and has_unclosed_code_block(existing_tail):
report_file.write("\n```\n\n")
if needs_separator and existing_tail:
report_file.write(separator)
report_file.write(block_text)
if temp_file.exists():
try:
temp_file.unlink()
except OSError:
pass
def finalize_report_summary(report_path: Path, results: List[Dict[str, object]]) -> None:
"""Update the performance summary placeholder once all tests have run."""
valid_results = [r for r in results if "error" not in r]
if valid_results:
total_tok_s = sum(r["metrics"]["tokens_per_second"] for r in valid_results)
total_ttft = sum(r["metrics"]["time_to_first_token"] for r in valid_results)
total_tokens = sum(r["metrics"]["total_tokens"] for r in valid_results)
avg_tok_s = round(total_tok_s / len(valid_results), 2)
avg_ttft = round(total_ttft / len(valid_results), 2)
else:
avg_tok_s = avg_ttft = total_tokens = 0
summary_block = textwrap.dedent(
f"""
* **Average Tokens/s:** {avg_tok_s}
* **Average Time to First Token:** {avg_ttft}s
* **Total Tokens Generated:** {total_tokens}
"""
).strip()
content = report_path.read_text(encoding="utf-8")
updated_content = re.sub(
r"<!--SUMMARY_START-->.*?<!--SUMMARY_END-->",
f"<!--SUMMARY_START-->\n{summary_block}\n<!--SUMMARY_END-->",
content,
flags=re.DOTALL,
)
report_path.write_text(updated_content, encoding="utf-8")