feat(mma): Implement run_tier4_analysis in ai_client.py
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37
ai_client.py
37
ai_client.py
@@ -1764,6 +1764,43 @@ def _send_deepseek(md_content: str, user_message: str, base_dir: str,
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raise _classify_deepseek_error(e) from e
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def run_tier4_analysis(stderr: str) -> str:
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"""
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Stateless Tier 4 QA analysis of an error message.
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Uses gemini-2.5-flash-lite to summarize the error and suggest a fix.
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"""
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if not stderr or not stderr.strip():
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return ""
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try:
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_ensure_gemini_client()
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prompt = (
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f"You are a Tier 4 QA Agent specializing in error analysis.\n"
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f"Analyze the following stderr output from a PowerShell command:\n\n"
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f"```\n{stderr}\n```\n\n"
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f"Provide a concise summary of the failure and suggest a fix in approximately 20 words."
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)
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# Use flash-lite for cost-effective stateless analysis
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model_name = "gemini-2.5-flash-lite"
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# We don't use the chat session here to keep it stateless
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resp = _gemini_client.models.generate_content(
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model=model_name,
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contents=prompt,
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config=types.GenerateContentConfig(
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temperature=0.0,
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max_output_tokens=150,
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)
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)
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analysis = resp.text.strip()
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return analysis
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except Exception as e:
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# We don't want to crash the main loop if QA analysis fails
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return f"[QA ANALYSIS FAILED] {e}"
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# ------------------------------------------------------------------ unified send
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def send(
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@@ -100,3 +100,29 @@ def test_run_powershell_optional_qa_callback():
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assert "STDERR:\nerror" in output
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assert "EXIT CODE: 1" in output
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def test_end_to_end_tier4_integration():
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"""
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Verifies that shell_runner.run_powershell correctly uses ai_client.run_tier4_analysis.
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"""
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import ai_client
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script = "Invoke-Item non_existent_file"
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base_dir = "."
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stderr_content = "Invoke-Item : Cannot find path 'C:\\non_existent_file' because it does not exist."
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mock_result = MagicMock()
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mock_result.stdout = ""
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mock_result.stderr = stderr_content
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mock_result.returncode = 1
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expected_analysis = "Path does not exist. Verify the file path and ensure the file is present before invoking."
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with patch("subprocess.run", return_value=mock_result), \
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patch("shutil.which", return_value="powershell.exe"), \
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patch("ai_client.run_tier4_analysis", return_value=expected_analysis) as mock_analysis:
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output = run_powershell(script, base_dir, qa_callback=ai_client.run_tier4_analysis)
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mock_analysis.assert_called_once_with(stderr_content)
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assert f"QA ANALYSIS:\n{expected_analysis}" in output
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