feat: add OpenAI LLM evaluation step for connector regression tests (#68673)

Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
2025-12-19 10:00:34 -05:00 · 2025-11-20 17:27:25 -08:00
parent 13c3e1e34f
commit cf1379d105
7 changed files with 663 additions and 1 deletions
--- a/.github/prompts/regression-evaluation.prompt.yaml
+++ b/.github/prompts/regression-evaluation.prompt.yaml
@@ -0,0 +1,34 @@
+name: Regression Report Evaluation
+description: Evaluate Airbyte connector regression test reports and return a JSON verdict with reasoning
+model: llama3.2:3b
+modelParameters:
+  temperature: 0.3
+messages:
+  - role: system
+    content: |
+      You are an expert at evaluating connector regression test results. 
+      Your task is to analyze the test report and determine if the regression tests should PASS or FAIL.
+
+      Consider the following criteria:
+      1. All test cases should pass (no failed tests)
+      2. Record count differences between control and target versions should be minimal or explainable
+      3. Message count differences should not indicate data loss or corruption
+      4. Stream coverage should be reasonable
+      5. Any warnings or errors in test outputs should be evaluated for severity
+
+      Provide your evaluation in the following JSON format:
+      {
+          "pass": true/false,
+          "summary": "A concise 2-3 sentence summary of the evaluation",
+          "reasoning": "Detailed reasoning for your pass/fail decision, including specific issues found",
+          "severity": "critical/major/minor/none",
+          "recommendations": "Any recommendations for addressing issues"
+      }
+
+      Be strict but fair in your evaluation. Minor differences are acceptable, but data loss, 
+      corruption, or test failures should result in a FAIL.
+  - role: user
+    content: |
+      Report:
+
+      {{report_text}}
--- a/.github/workflows/run-regression-tests-command.yml
+++ b/.github/workflows/run-regression-tests-command.yml
@@ -84,7 +84,24 @@ jobs:
    name: Regression Tests
    runs-on: linux-24.04-large # Custom runner, defined in GitHub org settings
    timeout-minutes: 360 # 6 hours
+    permissions:
+      contents: read
+      pull-requests: write
+      issues: write
    steps:
+      - name: Append start with run link
+        id: pr-comment-id
+        if: github.event_name == 'workflow_dispatch' && github.event.inputs.pr != ''
+        uses: peter-evans/create-or-update-comment@v4
+        with:
+          token: ${{ github.token }}
+          issue-number: ${{ github.event.inputs.pr }}
+          comment-id: ${{ github.event.inputs.comment-id }}
+          edit-mode: append
+          body: |
+            > Starting regression tests (filter: `${{ github.event.inputs.connector_filter || '--modified' }}`)
+            > Workflow run: [${{ github.run_id }}](${{ github.server_url }}/${{ github.repository }}/actions/runs/${{ github.run_id }})
+
      - name: Install Python
        id: install_python
        uses: actions/setup-python@7f4fc3e22c37d6ff65e88745f38bd3157c663f7c # v4.9.1
@@ -183,6 +200,7 @@ jobs:
      # forks if the user installs the app into their fork. Until we document this as a clear
      # path, we will have to keep using the PAT.
      - name: Run Regression Tests [WORKFLOW DISPATCH]
+        id: run-regression-tests
        if: github.event_name == 'workflow_dispatch' # TODO: consider using the matrix strategy (https://docs.github.com/en/actions/using-jobs/using-a-matrix-for-your-jobs). See https://github.com/airbytehq/airbyte/pull/37659#discussion_r1583380234 for details.
        uses: ./.github/actions/run-airbyte-ci
        with:
@@ -199,3 +217,87 @@ jobs:
          s3_build_cache_access_key_id: ${{ secrets.SELF_RUNNER_AWS_ACCESS_KEY_ID }}
          s3_build_cache_secret_key: ${{ secrets.SELF_RUNNER_AWS_SECRET_ACCESS_KEY }}
          subcommand: connectors ${{ env.USE_LOCAL_CDK_FLAG }} ${{ inputs.connector_filter }} test --only-step connector_live_tests --connector_live_tests.test-suite=regression --connector_live_tests.connection-id=${{ github.event.inputs.connection_id }} --connector_live_tests.pr-url="https://github.com/airbytehq/airbyte/pull/${{ github.event.inputs.pr }}" ${{ env.READ_WITH_STATE_FLAG }} ${{ env.DISABLE_PROXY_FLAG }} ${{ env.STREAM_PARAMS }} ${{ env.CONNECTION_SUBSET }} ${{ env.CONTROL_VERSION }} --global-status-check-context="Regression Tests" --global-status-check-description='Running regression tests'
+
+      - name: Upload regression test report
+        if: always() && github.event_name == 'workflow_dispatch'
+        uses: actions/upload-artifact@v4
+        with:
+          name: regression-test-report
+          path: /tmp/regression_tests_artifacts/report.html
+          if-no-files-found: ignore
+
+      - name: Append regression outcome
+        if: always() && github.event_name == 'workflow_dispatch' && github.event.inputs.pr != ''
+        uses: peter-evans/create-or-update-comment@v4
+        with:
+          token: ${{ github.token }}
+          comment-id: ${{ steps.pr-comment-id.outputs.comment-id }}
+          edit-mode: append
+          body: |
+            > Regression tests: ${{ steps.run-regression-tests.outcome == 'success' && '✅ PASSED' || steps.run-regression-tests.outcome == 'failure' && '❌ FAILED' || steps.run-regression-tests.outcome == 'cancelled' && '⚠️ CANCELLED' || steps.run-regression-tests.outcome == 'skipped' && '⏭️ SKIPPED' || '❓ UNKNOWN' }}
+            > Report: ${{ hashFiles('/tmp/regression_tests_artifacts/report.html') != '' && 'artifact `regression-test-report` available in the run' || 'not generated' }}
+
+      - name: Install live-tests dependencies for LLM evaluation
+        if: always() && github.event_name == 'workflow_dispatch'
+        working-directory: airbyte-ci/connectors/live-tests
+        run: poetry install
+
+      - name: Install and Start Ollama
+        if: always() && github.event_name == 'workflow_dispatch'
+        run: |
+          curl -fsSL https://ollama.com/install.sh | sh
+          ollama serve &
+          sleep 5
+          ollama pull llama3.2:3b
+          echo "Ollama server started and model pulled"
+
+      - name: Evaluate Regression Test Report with LLM
+        if: always() && github.event_name == 'workflow_dispatch'
+        id: llm-eval
+        continue-on-error: true
+        working-directory: airbyte-ci/connectors/live-tests
+        env:
+          OPENAI_API_KEY: ollama
+          OPENAI_BASE_URL: http://127.0.0.1:11434/v1
+          EVAL_MODEL: llama3.2:3b
+        run: |
+          set -u
+          echo "ran=false" >> "$GITHUB_OUTPUT"
+          echo "result=error" >> "$GITHUB_OUTPUT"
+
+          # Find the most recent report.html file in /tmp/regression_tests_artifacts/
+          REPORT_PATH=$(find /tmp/regression_tests_artifacts -name "report.html" -type f -printf '%T@ %p\n' | sort -n | tail -1 | cut -f2- -d" ")
+
+          if [ -z "$REPORT_PATH" ]; then
+            echo "Error: No report.html found in /tmp/regression_tests_artifacts/" >&2
+            echo "## ⚠️ LLM Evaluation Skipped" >> "$GITHUB_STEP_SUMMARY"
+            echo "No regression test report found. The tests may have failed to generate a report." >> "$GITHUB_STEP_SUMMARY"
+            exit 1
+          fi
+
+          echo "Found report at: $REPORT_PATH"
+          echo "Running LLM evaluation..."
+
+          # Run the evaluation script
+          OUT_JSON="$RUNNER_TEMP/llm_eval.json"
+          poetry run python src/live_tests/regression_tests/llm_evaluation/evaluate_report.py \
+            --report-path "$REPORT_PATH" \
+            --output-json "$OUT_JSON"
+
+          # If we got here, script exit 0 and produced a judgment
+          PASS=$(jq -r '.evaluation.pass' "$OUT_JSON")
+          if [ "$PASS" = "true" ]; then RES="pass"; else RES="fail"; fi
+          echo "ran=true" >> "$GITHUB_OUTPUT"
+          echo "result=$RES" >> "$GITHUB_OUTPUT"
+
+      - name: Append LLM outcome
+        if: always() && github.event_name == 'workflow_dispatch' && github.event.inputs.pr != ''
+        env:
+          EVAL_MODEL: llama3.2:3b
+        uses: peter-evans/create-or-update-comment@v4
+        with:
+          token: ${{ github.token }}
+          comment-id: ${{ steps.pr-comment-id.outputs.comment-id }}
+          edit-mode: append
+          body: |
+            > LLM Evaluation: ${{ steps.llm-eval.outputs.ran == 'true' && (steps.llm-eval.outputs.result == 'pass' && '✅ PASS' || steps.llm-eval.outputs.result == 'fail' && '❌ FAIL' || '⚠️ ERROR') || '⚠️ Did not run' }}${{ steps.llm-eval.outputs.ran == 'true' && format(' (model: {0})', env.EVAL_MODEL) || '' }}
--- a/airbyte-ci/connectors/live-tests/poetry.lock
+++ b/airbyte-ci/connectors/live-tests/poetry.lock
@@ -355,6 +355,29 @@ test = ["coverage (>=5.5)", "equinox", "jax[cpu]", "jaxtyping", "mypy (>=0.800)"
 test-tox = ["equinox", "jax[cpu]", "jaxtyping", "mypy (>=0.800)", "numba", "numpy", "pandera", "pygments", "pyright (>=1.1.370)", "pytest (>=4.0.0)", "sphinx", "typing-extensions (>=3.10.0.0)"]
 test-tox-coverage = ["coverage (>=5.5)"]

+[[package]]
+name = "beautifulsoup4"
+version = "4.14.2"
+description = "Screen-scraping library"
+optional = false
+python-versions = ">=3.7.0"
+groups = ["main"]
+files = [
+    {file = "beautifulsoup4-4.14.2-py3-none-any.whl", hash = "sha256:5ef6fa3a8cbece8488d66985560f97ed091e22bbc4e9c2338508a9d5de6d4515"},
+    {file = "beautifulsoup4-4.14.2.tar.gz", hash = "sha256:2a98ab9f944a11acee9cc848508ec28d9228abfd522ef0fad6a02a72e0ded69e"},
+]
+
+[package.dependencies]
+soupsieve = ">1.2"
+typing-extensions = ">=4.0.0"
+
+[package.extras]
+cchardet = ["cchardet"]
+chardet = ["chardet"]
+charset-normalizer = ["charset-normalizer"]
+html5lib = ["html5lib"]
+lxml = ["lxml"]
+
 [[package]]
 name = "blessed"
 version = "1.20.0"
@@ -979,6 +1002,18 @@ wrapt = ">=1.10,<2"
 [package.extras]
 dev = ["PyTest", "PyTest-Cov", "bump2version (<1)", "sphinx (<2)", "tox"]

+[[package]]
+name = "distro"
+version = "1.9.0"
+description = "Distro - an OS platform information API"
+optional = false
+python-versions = ">=3.6"
+groups = ["main"]
+files = [
+    {file = "distro-1.9.0-py3-none-any.whl", hash = "sha256:7bffd925d65168f85027d8da9af6bddab658135b840670a223589bc0c8ef02b2"},
+    {file = "distro-1.9.0.tar.gz", hash = "sha256:2fa77c6fd8940f116ee1d6b94a2f90b13b5ea8d019b98bc8bafdcabcdd9bdbed"},
+]
+
 [[package]]
 name = "docker"
 version = "6.1.3"
@@ -1943,6 +1978,118 @@ files = [
 [package.dependencies]
 ansicon = {version = "*", markers = "platform_system == \"Windows\""}

+[[package]]
+name = "jiter"
+version = "0.11.1"
+description = "Fast iterable JSON parser."
+optional = false
+python-versions = ">=3.9"
+groups = ["main"]
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+    {file = "jiter-0.11.1.tar.gz", hash = "sha256:849dcfc76481c0ea0099391235b7ca97d7279e0fa4c86005457ac7c88e8b76dc"},
+]
+
 [[package]]
 name = "jsonschema"
 version = "3.2.0"
@@ -2492,6 +2639,34 @@ rsa = ["cryptography (>=3.0.0)"]
 signals = ["blinker (>=1.4.0)"]
 signedtoken = ["cryptography (>=3.0.0)", "pyjwt (>=2.0.0,<3)"]

+[[package]]
+name = "openai"
+version = "1.109.1"
+description = "The official Python library for the openai API"
+optional = false
+python-versions = ">=3.8"
+groups = ["main"]
+files = [
+    {file = "openai-1.109.1-py3-none-any.whl", hash = "sha256:6bcaf57086cf59159b8e27447e4e7dd019db5d29a438072fbd49c290c7e65315"},
+    {file = "openai-1.109.1.tar.gz", hash = "sha256:d173ed8dbca665892a6db099b4a2dfac624f94d20a93f46eb0b56aae940ed869"},
+]
+
+[package.dependencies]
+anyio = ">=3.5.0,<5"
+distro = ">=1.7.0,<2"
+httpx = ">=0.23.0,<1"
+jiter = ">=0.4.0,<1"
+pydantic = ">=1.9.0,<3"
+sniffio = "*"
+tqdm = ">4"
+typing-extensions = ">=4.11,<5"
+
+[package.extras]
+aiohttp = ["aiohttp", "httpx-aiohttp (>=0.1.8)"]
+datalib = ["numpy (>=1)", "pandas (>=1.2.3)", "pandas-stubs (>=1.1.0.11)"]
+realtime = ["websockets (>=13,<16)"]
+voice-helpers = ["numpy (>=2.0.2)", "sounddevice (>=0.5.1)"]
+
 [[package]]
 name = "opentelemetry-api"
 version = "1.27.0"
@@ -3864,6 +4039,18 @@ files = [
    {file = "sortedcontainers-2.4.0.tar.gz", hash = "sha256:25caa5a06cc30b6b83d11423433f65d1f9d76c4c6a0c90e3379eaa43b9bfdb88"},
 ]

+[[package]]
+name = "soupsieve"
+version = "2.8"
+description = "A modern CSS selector implementation for Beautiful Soup."
+optional = false
+python-versions = ">=3.9"
+groups = ["main"]
+files = [
+    {file = "soupsieve-2.8-py3-none-any.whl", hash = "sha256:0cc76456a30e20f5d7f2e14a98a4ae2ee4e5abdc7c5ea0aafe795f344bc7984c"},
+    {file = "soupsieve-2.8.tar.gz", hash = "sha256:e2dd4a40a628cb5f28f6d4b0db8800b8f581b65bb380b97de22ba5ca8d72572f"},
+]
+
 [[package]]
 name = "sqlalchemy"
 version = "2.0.35"
@@ -4477,4 +4664,4 @@ cffi = ["cffi (>=1.11)"]
 [metadata]
 lock-version = "2.1"
 python-versions = "^3.11,<3.12"
-content-hash = "979b7f159a1a284b77b9bec889298c50e3c269149524e647978b517463142e1f"
+content-hash = "d6f93822b88fad4aaf0ae5d60932e0e93d9e95aa79fdddc44f9f6045387d3b4c"
--- a/airbyte-ci/connectors/live-tests/pyproject.toml
+++ b/airbyte-ci/connectors/live-tests/pyproject.toml
@@ -41,6 +41,8 @@ dpath = "^2.1.6"
 genson = "^1.3.0"
 segment-analytics-python = "^2.3.2"
 python-slugify = ">=8.0.4"
+beautifulsoup4 = "^4.12.0"
+openai = "^1.0.0"


 [tool.poetry.group.dev.dependencies]
--- a/airbyte-ci/connectors/live-tests/src/live_tests/regression_tests/llm_evaluation/README.md
+++ b/airbyte-ci/connectors/live-tests/src/live_tests/regression_tests/llm_evaluation/README.md
@@ -0,0 +1,37 @@
+# LLM-Based Regression Test Evaluation
+
+Automated evaluation of connector regression test reports using LLM models.
+
+## How It Works
+
+After regression tests complete, this evaluates the HTML report and writes a pass/fail judgment to `GITHUB_STEP_SUMMARY`.
+
+## Configuration
+
+**Environment Variables:**
+- `OPENAI_API_KEY` - API key (use `ollama` for Ollama)
+- `OPENAI_BASE_URL` - Base URL for OpenAI-compatible API (e.g., `http://127.0.0.1:11434/v1` for Ollama)
+- `EVAL_MODEL` - Model name (defaults to `gpt-4o`)
+
+**Evaluation Prompt:**
+Stored in `.github/prompts/regression-evaluation.prompt.yaml` following GitHub's prompt format. Uses `{{report_text}}` placeholder for dynamic content injection.
+
+## Local Testing
+
+```bash
+# Install Ollama
+curl -fsSL https://ollama.com/install.sh | sh
+ollama serve &
+ollama pull llama3.2:3b
+
+# Set environment
+export OPENAI_API_KEY=ollama
+export OPENAI_BASE_URL=http://127.0.0.1:11434/v1
+export EVAL_MODEL=llama3.2:3b
+
+# Run evaluation
+cd airbyte-ci/connectors/live-tests
+poetry install
+poetry run python src/live_tests/regression_tests/llm_evaluation/evaluate_report.py \
+  --report-path /path/to/report.html
+```
--- a/airbyte-ci/connectors/live-tests/src/live_tests/regression_tests/llm_evaluation/init.py
+++ b/airbyte-ci/connectors/live-tests/src/live_tests/regression_tests/llm_evaluation/init.py
@@ -0,0 +1 @@
+# Copyright (c) 2024 Airbyte, Inc., all rights reserved.
--- a/airbyte-ci/connectors/live-tests/src/live_tests/regression_tests/llm_evaluation/evaluate_report.py
+++ b/airbyte-ci/connectors/live-tests/src/live_tests/regression_tests/llm_evaluation/evaluate_report.py
@@ -0,0 +1,299 @@
+#!/usr/bin/env python3
+# Copyright (c) 2024 Airbyte, Inc., all rights reserved.
+
+"""
+LLM-based evaluation of regression test reports.
+
+This script reads a regression test report (HTML format) and uses OpenAI's LLM
+to evaluate the results, make a pass/fail judgment, and generate a summary.
+The summary is written to GITHUB_STEP_SUMMARY for display in GitHub Actions.
+"""
+
+import argparse
+import json
+import os
+import sys
+from pathlib import Path
+from typing import Any
+
+import yaml
+from bs4 import BeautifulSoup
+from openai import OpenAI
+
+MAX_REPORT_CHARS = 200000
+
+# Default evaluation prompt
+EVAL_PROMPT = """You are an expert at evaluating connector regression test results. 
+Your task is to analyze the test report and determine if the regression tests should PASS or FAIL.
+
+Consider the following criteria:
+1. All test cases should pass (no failed tests)
+2. Record count differences between control and target versions should be minimal or explainable
+3. Message count differences should not indicate data loss or corruption
+4. Stream coverage should be reasonable
+5. Any warnings or errors in test outputs should be evaluated for severity
+
+Provide your evaluation in the following JSON format:
+{
+    "pass": true/false,
+    "summary": "A concise 2-3 sentence summary of the evaluation",
+    "reasoning": "Detailed reasoning for your pass/fail decision, including specific issues found",
+    "severity": "critical/major/minor/none",
+    "recommendations": "Any recommendations for addressing issues"
+}
+
+Be strict but fair in your evaluation. Minor differences are acceptable, but data loss, 
+corruption, or test failures should result in a FAIL."""
+
+
+def load_prompt_from_yaml(yaml_path: Path | None = None) -> tuple[list[dict[str, str]] | None, str | None, dict[str, Any] | None]:
+    """
+    Load prompt from GitHub-format YAML file.
+
+    Args:
+        yaml_path: Path to the .prompt.yaml file. If None, uses default location.
+
+    Returns:
+        Tuple of (messages, model, modelParameters) or (None, None, None) if file not found or invalid
+    """
+    if yaml_path is None:
+        # Default location: .github/prompts/regression-evaluation.prompt.yaml
+        github_workspace = os.environ.get("GITHUB_WORKSPACE")
+        if github_workspace:
+            yaml_path = Path(github_workspace) / ".github" / "prompts" / "regression-evaluation.prompt.yaml"
+        else:
+            script_dir = Path(__file__).parent
+            repo_root = script_dir.parent.parent.parent.parent.parent.parent
+            yaml_path = repo_root / ".github" / "prompts" / "regression-evaluation.prompt.yaml"
+
+    if not yaml_path.exists():
+        print(f"Prompt file not found at {yaml_path}, using default hardcoded prompt")
+        return None, None, None
+
+    try:
+        with open(yaml_path, "r", encoding="utf-8") as f:
+            prompt_data = yaml.safe_load(f)
+
+        messages = prompt_data.get("messages", [])
+        model = prompt_data.get("model")
+        model_params = prompt_data.get("modelParameters", {})
+
+        if not messages:
+            print(f"Warning: No messages found in {yaml_path}, using default hardcoded prompt")
+            return None, None, None
+
+        print(f"Loaded prompt from {yaml_path}")
+        return messages, model, model_params
+
+    except Exception as e:
+        print(f"Warning: Failed to load prompt from {yaml_path}: {e}")
+        print("Using default hardcoded prompt")
+        return None, None, None
+
+
+def load_report_text(html_path: Path) -> str:
+    """
+    Load and convert HTML report to clean text.
+
+    Args:
+        html_path: Path to the report.html file
+
+    Returns:
+        Clean text representation of the report
+    """
+    with open(html_path, "r", encoding="utf-8") as f:
+        html_content = f.read()
+
+    soup = BeautifulSoup(html_content, "html.parser")
+
+    for element in soup(["script", "style"]):
+        element.decompose()
+
+    report_text = soup.get_text("\n", strip=True)
+
+    report_text = "\n".join(line.strip() for line in report_text.splitlines() if line.strip())
+
+    if len(report_text) > MAX_REPORT_CHARS:
+        original_length = len(report_text)
+        report_text = report_text[:MAX_REPORT_CHARS]
+        truncation_note = f"\n\n[Report truncated from {original_length} to {MAX_REPORT_CHARS} characters for evaluation]"
+        report_text += truncation_note
+        print(f"Warning: Report truncated from {original_length} to {MAX_REPORT_CHARS} characters")
+
+    return report_text
+
+
+def evaluate_with_llm(report_text: str, prompt: str | None = None, prompt_yaml_path: Path | None = None) -> dict[str, Any]:
+    """
+    Use OpenAI LLM to evaluate the regression test report.
+
+    Supports both OpenAI API and Ollama (OpenAI-compatible).
+    Configure via environment variables:
+    - OPENAI_API_KEY: API key (use 'ollama' for Ollama)
+    - OPENAI_BASE_URL: Optional base URL (e.g., http://127.0.0.1:11434/v1 for Ollama)
+    - EVAL_MODEL: Model name (defaults to gpt-4o, use llama3.2:3b for Ollama)
+    - EVAL_PROMPT_PATH: Optional path to custom .prompt.yaml file
+
+    Args:
+        report_text: Full text of the report
+        prompt: Optional custom evaluation prompt string (legacy, overrides YAML)
+        prompt_yaml_path: Optional path to .prompt.yaml file
+
+    Returns:
+        Dictionary containing evaluation results with 'pass', 'summary', 'reasoning', 'severity', and 'recommendations' keys
+
+    Raises:
+        Exception: If LLM evaluation fails after retry
+    """
+    api_key = os.environ.get("OPENAI_API_KEY")
+    base_url = os.environ.get("OPENAI_BASE_URL")
+    model = os.environ.get("EVAL_MODEL", "gpt-4o")
+
+    if base_url:
+        client = OpenAI(api_key=api_key, base_url=base_url)
+        print(f"Using custom base URL: {base_url}")
+    else:
+        client = OpenAI(api_key=api_key)
+
+    yaml_messages, yaml_model, yaml_params = load_prompt_from_yaml(prompt_yaml_path)
+
+    if yaml_model and not os.environ.get("EVAL_MODEL"):
+        model = yaml_model
+
+    temperature = 0.3
+    if yaml_params and "temperature" in yaml_params:
+        temperature = yaml_params["temperature"]
+
+    print(f"Using model: {model}")
+
+    if prompt is not None:
+        messages = [
+            {"role": "system", "content": prompt},
+            {"role": "user", "content": f"Report:\n\n{report_text}"},
+        ]
+    elif yaml_messages:
+        messages = []
+        for msg in yaml_messages:
+            content = msg.get("content", "")
+            content = content.replace("{{report_text}}", report_text)
+            messages.append({"role": msg["role"], "content": content})
+    else:
+        # Fallback to hardcoded EVAL_PROMPT
+        messages = [
+            {"role": "system", "content": EVAL_PROMPT},
+            {"role": "user", "content": f"Report:\n\n{report_text}"},
+        ]
+
+    try:
+        response = client.chat.completions.create(
+            model=model,
+            messages=messages,
+            temperature=temperature,
+            response_format={"type": "json_object"},
+        )
+
+        evaluation = json.loads(response.choices[0].message.content)
+        return evaluation
+    except Exception as e:
+        error_msg = str(e).lower()
+        if "response_format" in error_msg or "json_object" in error_msg:
+            print(f"Warning: JSON response format not supported, retrying without it: {e}")
+            response = client.chat.completions.create(
+                model=model,
+                messages=messages,
+                temperature=temperature,
+            )
+            content = response.choices[0].message.content
+            evaluation = json.loads(content)
+            return evaluation
+        raise
+
+
+def write_github_summary(evaluation: dict[str, Any], model: str | None = None) -> None:
+    """
+    Write the evaluation summary to GITHUB_STEP_SUMMARY.
+
+    Args:
+        evaluation: LLM evaluation results
+        model: Model name used for evaluation (optional)
+    """
+    summary_file = os.environ.get("GITHUB_STEP_SUMMARY")
+    if not summary_file:
+        print("Warning: GITHUB_STEP_SUMMARY environment variable not set. Writing to stdout instead.")
+        summary_file = "/dev/stdout"
+
+    status_emoji = "✅" if evaluation["pass"] else "❌"
+
+    model_info = f"model: {model}" if model else "OpenAI-compatible API"
+
+    markdown = f"""# {status_emoji} Regression Test Evaluation: {"PASS" if evaluation['pass'] else "FAIL"}
+
+{evaluation['summary']}
+
+
+{evaluation['reasoning']}
+
+{evaluation.get('recommendations', 'No specific recommendations.')}
+
+---
+*This evaluation was generated using {model_info}*
+"""
+
+    with open(summary_file, "a", encoding="utf-8") as f:
+        f.write(markdown)
+
+    print(f"Summary written to {summary_file}")
+
+
+def main():
+    """Main entry point for the LLM evaluation script."""
+    parser = argparse.ArgumentParser(description="Evaluate regression test reports using OpenAI LLM")
+    parser.add_argument("--report-path", type=Path, required=True, help="Path to the report.html file")
+    parser.add_argument("--prompt-file", type=Path, help="Optional path to a custom evaluation prompt file")
+    parser.add_argument("--output-json", type=Path, help="Optional path to write evaluation results as JSON")
+
+    args = parser.parse_args()
+
+    if not os.environ.get("OPENAI_API_KEY"):
+        print("Error: OPENAI_API_KEY environment variable not set", file=sys.stderr)
+        sys.exit(1)
+
+    if not args.report_path.exists():
+        print(f"Error: Report file not found: {args.report_path}", file=sys.stderr)
+        sys.exit(1)
+
+    print(f"Loading report from: {args.report_path}")
+    report_text = load_report_text(args.report_path)
+    print(f"Report loaded: {len(report_text)} characters")
+
+    custom_prompt = None
+    if args.prompt_file and args.prompt_file.exists():
+        with open(args.prompt_file, "r", encoding="utf-8") as f:
+            custom_prompt = f.read()
+        print(f"Using custom prompt from: {args.prompt_file}")
+
+    prompt_yaml_path = None
+    eval_prompt_path = os.environ.get("EVAL_PROMPT_PATH")
+    if eval_prompt_path:
+        prompt_yaml_path = Path(eval_prompt_path)
+
+    print("Evaluating report with LLM...")
+    evaluation = evaluate_with_llm(report_text, custom_prompt, prompt_yaml_path)
+
+    print(f"\nEvaluation Result: {'PASS' if evaluation['pass'] else 'FAIL'}")
+    print(f"Summary: {evaluation['summary']}")
+
+    model = os.environ.get("EVAL_MODEL", "gpt-4o")
+    write_github_summary(evaluation, model)
+
+    if args.output_json:
+        output_data = {"evaluation": evaluation}
+        with open(args.output_json, "w", encoding="utf-8") as f:
+            json.dump(output_data, f, indent=2)
+        print(f"Evaluation results written to: {args.output_json}")
+
+    sys.exit(0 if evaluation["pass"] else 1)
+
+
+if __name__ == "__main__":
+    main()
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				`# Copyright (c) 2024 Airbyte, Inc., all rights reserved.`