cortex/__init__.py (1)

1-2: Avoid duplicating the version string in multiple places.

__version__ = "0.1.0" here and version="0.1.0" in setup.py will drift over time. Consider defining the version in a single module (e.g., cortex/_version.py) and importing it both here and in setup.py.

setup.py (1)

7-8: Make requirements parsing robust to indented comments.

Current list comprehension:

requirements = [line.strip() for line in fh if line.strip() and not line.startswith("#")]

will include lines like " # comment" as a requirement because line.startswith("#") ignores leading whitespace. Consider:

stripped = line.strip()
if stripped and not stripped.startswith("#"):
    requirements.append(stripped)

to avoid accidentally treating indented comments as dependencies.

cortex/coordinator.py (5)

12-39: Use explicit None checks in duration for clarity.

To avoid relying on truthiness of floats and to be explicit about the sentinel value, consider:

def duration(self) -> Optional[float]:
    if self.start_time is not None and self.end_time is not None:
        return self.end_time - self.start_time
    return None

This is a minor readability/robustness improvement.

---

87-97: Avoid fully silent failures in _log.

Right now any error opening/writing the log file is swallowed:

try:
    ...
except Exception:
    pass

Consider at least emitting a minimal print(..., file=sys.stderr) or narrowing the exception type so that unexpected errors don’t fail silently. This keeps installation resilient while still giving a hint when logging is misconfigured.

---

99-141: Be explicit about shell=True and broad exception handling trade-offs.

Given these commands are arbitrary shell lines, shell=True is probably required, but:

• It’s a security footgun if ever exposed to untrusted input or run under elevated privileges.
• Catching bare Exception here may hide unexpected programmer errors.

At minimum, consider documenting that InstallationCoordinator is intended for local, trusted environments and not for executing untrusted commands. If feasible, narrow the except Exception to specific failures (e.g., OSError) so unexpected errors surface during development.

---

166-197: Progress callback is invoked before status is updated, so callers never see final state.

progress_callback is called before _execute_command, while step.status is still PENDING. The CLI’s callback uses step.status to print [OK]/[FAIL], so it will only ever see [PENDING].

Consider instead:

for i, step in enumerate(self.steps):
    if self.progress_callback:
        self.progress_callback(i + 1, len(self.steps), step)  # optional “starting” hook

    success = self._execute_command(step)

    if self.progress_callback:
        self.progress_callback(i + 1, len(self.steps), step)  # “completed” hook with final status

or move the callback to after _execute_command if you only want the completed status. This will make CLI progress output reflect real step outcomes.

---

269-307: install_docker is tightly coupled to Debian/Ubuntu + systemd environments.

The hard-coded apt commands, add-apt-repository, and systemctl checks make this helper effectively Ubuntu/Debian with systemd only. That’s fine for container-based tests, but if you plan to reuse it on other distros (e.g., Arch, Fedora, non-systemd setups), it may fail in surprising ways.

Consider either documenting this assumption clearly or wiring distro detection into the higher-level CLI so alternate installers can be plugged in later.

test/run_all_tests.py (1)

11-33: Test discovery correctly scoped to test/ but won’t pick tests outside

discover_tests() starts from os.path.dirname(__file__), so only tests under the test directory are discovered, which matches how cortex/cli.py locates run_all_tests.py. If you ever want LLM/test_interpreter.py (or other top-level tests) to be run via this entry point, you’ll need to broaden start_dir (e.g., repo root) or mirror those tests under test/.

README.md (1)

93-95: Contribution and testing references are helpful—verify link targets

Pointing contributors to Issues, contribution.md, and test.md is good for onboarding and testing discipline. Just double-check that these relative links resolve correctly in the GitHub UI from this README.

LLM/test_interpreter.py (1)

97-103: Remove redundant @patch('openai.OpenAI') to satisfy Ruff and simplify the test

In test_parse_empty_input, the mock_openai argument is unused, and setUp already stubs the openai module globally. You can safely drop the patch decorator and argument—this will also resolve Ruff’s ARG002 warning.

-    @patch('openai.OpenAI')
-    def test_parse_empty_input(self, mock_openai):
+    def test_parse_empty_input(self):
         interpreter = CommandInterpreter(api_key=self.api_key, provider="openai")
 
         with self.assertRaises(ValueError):
             interpreter.parse("")

test/test_cli.py (2)

32-37: Strengthen test_get_api_key_not_found by asserting error output

You already patch sys.stderr here, but the test only checks that the API key is None, and mock_stderr is otherwise unused (Ruff ARG002).

To fully exercise _get_api_key’s error path and use the mock, consider also asserting that something was written to stderr, e.g.:

@patch.dict(os.environ, {}, clear=True)
@patch('sys.stderr')
def test_get_api_key_not_found(self, mock_stderr) -> None:
-    api_key = self.cli._get_api_key('openai')
-    self.assertIsNone(api_key)
+    api_key = self.cli._get_api_key('openai')
+    self.assertIsNone(api_key)
+    self.assertTrue(mock_stderr.write.called)

This both validates the user-visible error and clears the static-analysis warning.

---

90-196: Avoid real spinner sleeps in install-path unit tests (optional)

All install tests that reach CortexCLI.install with a valid API key will run the 10‑iteration spinner loop, each iteration sleeping for 0.1s. As the number of tests grows, this can noticeably slow the suite.

If runtime becomes an issue, consider patching _animate_spinner for these tests:

@patch.object(CortexCLI, "_animate_spinner", return_value=None)
@patch.dict(os.environ, {'OPENAI_API_KEY': 'test-key'}, clear=True)
@patch('cortex.cli.CommandInterpreter')
def test_install_dry_run(self, mock_interpreter_class, _mock_spinner) -> None:
    ...

This keeps behaviour identical from the CLI’s perspective while making tests faster and less timing‑sensitive.

cortex/test_coordinator.py (1)

36-321: Coordinator tests look comprehensive; consider making test_step_timing more robust

The coordinator test suite here is thorough and matches the coordinator’s behaviour well (init, stop/continue on error, rollback, logging, verification, summaries, and JSON export).

One minor robustness point: in test_step_timing, you assert step.end_time > step.start_time. On platforms with coarse time.time() resolution, two consecutive calls can occasionally return the same value, which would make this test intermittently fail even though the coordinator is behaving correctly.

If you want to eliminate that flakiness risk, you could either:

• Relax to >= or
• Patch time.time() to return controlled, strictly increasing values during the test.

Otherwise, this module looks solid.

LLM/interpreter.py (1)

154-185: Minor cleanup in _call_fake: avoid double JSON parsing of CORTEX_FAKE_COMMANDS

The fake provider path correctly validates that CORTEX_FAKE_COMMANDS is JSON with a top‑level "commands" key, but then discards the parsed data and calls _parse_commands(payload), which re‑parses the same JSON string.

Functionally this is fine, but you can simplify and avoid double parsing by reusing data, for example:

        payload = os.environ.get("CORTEX_FAKE_COMMANDS")
        if payload:
            try:
-                data = json.loads(payload)
+                data = json.loads(payload)
             except json.JSONDecodeError as exc:
                 raise ValueError("CORTEX_FAKE_COMMANDS must contain valid JSON") from exc
-            if not isinstance(data, dict) or "commands" not in data:
-                raise ValueError("CORTEX_FAKE_COMMANDS must define a 'commands' list")
-            return self._parse_commands(payload)
+            if not isinstance(data, dict) or "commands" not in data:
+                raise ValueError("CORTEX_FAKE_COMMANDS must define a 'commands' list")
+            commands = data["commands"]
+            if not isinstance(commands, list):
+                raise ValueError("CORTEX_FAKE_COMMANDS 'commands' must be a list")
+            return [cmd for cmd in commands if cmd and isinstance(cmd, str)]

parse() will still run _validate_commands on this list, so you keep the safety guarantees while reducing redundant work.

test/integration/docker_utils.py (1)

55-108: Mounted paths are documented as read‑only but are actually read‑write

In run_in_docker() the mounts parameter is documented as:

“Iterable of host Path instances mounted read-only to the same location within the container.”

However, the volume flag is built as:

docker_cmd.extend([
    "-v",
    f"{str(host_path.resolve())}:{container_path}",
])

Without a :ro suffix, these mounts are read‑write by default. For integration tests this may be intentional (e.g., writing artifacts back to the host), but it contradicts the docstring and slightly weakens isolation.

Consider either:

• Appending :ro to the volume spec to enforce read‑only mounts, or
• Updating the docstring to reflect that mounts are read‑write and, if needed, adding an option to request read‑only behaviour.

cortex/cli.py (5)

22-36: Provider fallback could cause confusing error messages.

Line 36 returns 'openai' as the default even when no OPENAI_API_KEY is present. This will cause a delayed error in _get_api_key rather than failing fast with a clear message that no provider is configured.

Consider one of these approaches:

Option 1: Return None and handle in caller

         return 'fake'
-    return 'openai'
+    return None  # No provider configured

Then check in the install method:

provider = self._get_provider()
if provider is None:
    self._print_error("No LLM provider configured. Set OPENAI_API_KEY, ANTHROPIC_API_KEY, or KIMI_API_KEY.")
    return 1

Option 2: Emit clear error immediately

         return 'fake'
-    return 'openai'
+    self._print_error("No LLM provider configured. Set one of: OPENAI_API_KEY, ANTHROPIC_API_KEY, or KIMI_API_KEY.")
+    sys.exit(1)

---

92-108: Consider removing redundant "install" prefix.

Line 103 prefixes the software parameter with "install " when calling the interpreter. Since the CLI command is already install and the parameter is named software, this might be redundant or confusing. Users might naturally include verbs in their input (e.g., cortex install "set up docker").

Consider passing the software parameter directly:

-            commands = interpreter.parse(f"install {software}")
+            commands = interpreter.parse(software)

Or make the prompt more explicit:

-            commands = interpreter.parse(f"install {software}")
+            commands = interpreter.parse(f"Generate shell commands to install {software}")

---

118-156: Execute mode logic is sound, but consider adding else block.

The execution flow with progress callbacks and error handling is well-structured. However, Lines 153-155 should be in an else block for clarity, as flagged by static analysis (TRY300).

Apply this diff to improve structure:

                     print(f"  Error: {result.error_message}", file=sys.stderr)
                 return 1
+            else:
+                print("\nTo execute these commands, run with --execute flag")
+                print("Example: cortex install docker --execute")
+                return 0
 
-            print("\nTo execute these commands, run with --execute flag")
-            print("Example: cortex install docker --execute")
-            return 0
-
         except ValueError as exc:

---

157-166: Exception handling is appropriate for CLI entry point.

The tiered exception handling (ValueError for input errors, RuntimeError for API failures, and Exception as fallback) is suitable for a CLI entry point where graceful error messages are important. The blind Exception catch on Line 163 prevents unexpected tracebacks from reaching end users, which is acceptable in this context.

Static analysis suggests using explicit conversion flags in f-strings (RUF010):

-            self._print_error(f"API call failed: {str(exc)}")
+            self._print_error(f"API call failed: {exc!s}")

-            self._print_error(f"Unexpected error: {str(exc)}")
+            self._print_error(f"Unexpected error: {exc!s}")

These are minor style improvements and not critical.

---

197-198: Consider making --execute and --dry-run mutually exclusive.

Both flags can currently be specified together, and dry_run takes precedence (checked first on Line 114). This could confuse users who expect both flags to trigger an error.

Make the flags mutually exclusive:

     install_parser = subparsers.add_parser('install', help='Install software using natural language')
     install_parser.add_argument('software', type=str, help='Software to install (natural language)')
-    install_parser.add_argument('--execute', action='store_true', help='Execute the generated commands')
-    install_parser.add_argument('--dry-run', action='store_true', help='Show commands without executing')
+    
+    exec_group = install_parser.add_mutually_exclusive_group()
+    exec_group.add_argument('--execute', action='store_true', help='Execute the generated commands')
+    exec_group.add_argument('--dry-run', action='store_true', help='Show commands without executing')

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Plan: Pro

LLM/interpreter.py (1)

262-271: Default model identifiers have been updated appropriately.

The defaults have been updated from the previous review:

• OpenAI: "gpt-4o" (updated from deprecated "gpt-4")
• Kimi: "kimi-k2-turbo-preview" with env override support

This addresses the concerns from the previous review about deprecated model identifiers.

test/test_coordinator.py (2)

5-5: Unused import.

The time module is imported but doesn't appear to be used in this file.

-import time

---

319-319: Prefer assertGreater over assertTrue with comparison.

As flagged by SonarCloud, assertGreater provides better failure messages and is the idiomatic choice for this comparison.

-            self.assertTrue(step.end_time > step.start_time)
+            self.assertGreater(step.end_time, step.start_time)

test/test_cli.py (1)

31-35: Consider prefixing unused mock argument.

The mock_stderr parameter is used only to suppress stderr output during the test. Prefixing with underscore signals intentional non-use.

     @patch.dict(os.environ, {}, clear=True)
     @patch('sys.stderr')
-    def test_get_api_key_not_found(self, mock_stderr):
+    def test_get_api_key_not_found(self, _mock_stderr):
         api_key = self.cli._get_api_key('openai')
         self.assertIsNone(api_key)

setup.py (1)

6-6: Minor typo in comment.

The comment has an extra # character.

-# # Try to read requirements from root, fallback to LLM directory
+# Try to read requirements from root, fallback to LLM directory

docs/ISSUE_40_KIMI_K2_IMPLEMENTATION.md (1)

190-194: Add language specifier to fenced code block.

The test output code block (lines 190-194) is missing a language specifier. Add text or plaintext for better markdown rendering.

-```
+```text
 Ran 143 tests in 10.136s
 
 OK (skipped=5)

</blockquote></details>
<details>
<summary>LLM/interpreter.py (1)</summary><blockquote>

`135-136`: **Redundant import of `requests` inside `_call_kimi`.**

The `requests` module is already imported and validated during `_initialize_client()` (line 53). This second import inside `_call_kimi` is unnecessary and the ImportError handling at line 152-153 will never trigger if initialization succeeded.


```diff
         try:
-            import requests
             response = requests.post(
                 f"{self._kimi_base_url.rstrip('/')}/v1/chat/completions",
                 headers=headers,
                 json=payload,
                 timeout=60,
             )

Note: This also means removing the ImportError catch at lines 152-153 since initialization already guarantees requests is available.

cortex/user_preferences.py (5)

201-205: Silent exception swallowing hides initialization errors.

The try-except-pass pattern silently ignores all exceptions during initial load. This can hide configuration corruption or permission issues.

Consider logging the exception or at least catching a more specific exception type:

         try:
             self.load()
-        except Exception:
-            # Ignore load errors here; callers can handle later
-            pass
+        except (IOError, ValueError) as e:
+            # Log but don't fail - callers can handle missing config
+            import logging
+            logging.debug(f"Initial config load skipped: {e}")

---

328-342: Unused key_parts parameter in _coerce_value_for_set.

The key_parts parameter is defined but never used in the method body. Either remove it or use it to provide context-aware coercion (e.g., knowing the target type based on the key path).

-    def _coerce_value_for_set(self, key_parts: List[str], value: Any) -> Any:
+    def _coerce_value_for_set(self, value: Any) -> Any:
         """Coerce string inputs into appropriate types for set()."""

Then update the call site at line 361:

-            coerced = self._coerce_value_for_set(parts, value)
+            coerced = self._coerce_value_for_set(value)

---

344-432: set() method has excessive cognitive complexity (56 vs. allowed 15).

This method handles many different preference types with nested conditionals, making it difficult to maintain and test. Consider refactoring into a dispatch pattern or strategy-based approach.

One approach is to use a handler registry:

def set(self, key: str, value: Any) -> bool:
    if self._preferences is None:
        self.load()
    
    parts = key.split(".")
    coerced = self._coerce_value_for_set(value)
    
    handlers = {
        "verbosity": self._set_verbosity,
        "confirmations": self._set_confirmations,
        "auto_update": self._set_auto_update,
        "ai": self._set_ai,
        "packages": self._set_packages,
        "conflicts": self._set_conflicts,
    }
    
    handler = handlers.get(parts[0])
    if handler:
        handler(parts, coerced, value)
    elif parts[0] in ["theme", "language", "timezone"]:
        setattr(self._preferences, parts[0], coerced)
    else:
        raise ValueError(f"Unknown preference key: {key}")
    
    self.save()
    return True

Then extract each branch into a dedicated _set_* method.

---

434-461: reset() always returns True, even on success paths.

The method signature promises a boolean return indicating success, but it always returns True or raises an exception. This is fine semantically (exceptions for errors, True for success), but SonarCloud flags it because there's no False return path.

If the intent is that errors always raise exceptions, consider changing the return type to None or documenting that exceptions are the error signaling mechanism.

---

131-166: from_dict has broad exception handling that masks errors.

Lines 141-142 and 151-152 catch bare Exception and silently default to fallback values. This can hide data corruption or invalid enum values without any indication to the caller.

Consider catching the specific ValueError that Enum() raises:

             try:
                 ai_data['creativity'] = AICreativity(ai_data['creativity'])
-            except Exception:
+            except ValueError:
                 ai_data['creativity'] = AICreativity.BALANCED

Similarly for verbosity at lines 149-152.

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docs/ISSUE_40_KIMI_K2_IMPLEMENTATION.md (1)

25-26: Kimi base URL documented inconsistently across sections

Earlier sections state the default KIMI_API_BASE_URL as https://api.moonshot.ai (and the advanced config example uses that), but the “API Request Format” section uses https://api.moonshot.cn/v1/chat/completions.

Please pick the correct default (ideally whatever CommandInterpreter actually uses by default) and make all occurrences consistent, or explicitly call out that one is the default and the other is only an example.

Also applies to: 48-49, 106-111, 129-145

LLM/test_interpreter.py (3)

49-55: Avoid clearing the entire environment in Kimi init test

@patch.dict(os.environ, {}, clear=True) guarantees a clean slate for Kimi-related env vars, but it also temporarily removes all environment variables for this test, which can cause surprising behavior if CommandInterpreter or any imported code ever depends on unrelated env settings (e.g., HOME, PATH). It’s safer to patch only the keys you care about.

Consider:

-    @patch.dict(os.environ, {}, clear=True)
+    @patch.dict(os.environ, {
+        "KIMI_API_KEY": "",
+        "KIMI_API_BASE_URL": "",
+        "KIMI_DEFAULT_MODEL": "",
+    }, clear=False)

This keeps non-Kimi env intact while still testing default Kimi behavior.

---

274-341: Integration tests are well-gated; custom-model env handling now safe

The TestKimiK2Integration class:

• Uses @unittest.skipUnless(RUN_KIMI_INTEGRATION_TESTS == "1") to keep real Kimi calls out of normal CI.
• Validates basic, complex, and validated-command flows against the live API.
• Uses @patch.dict(os.environ, {'KIMI_DEFAULT_MODEL': 'kimi-k2-0905-preview'}) so the custom-model test no longer leaks env state after failures (addressing the earlier cleanup concern).

Two minor suggestions:

1. Since these are external-network integration tests, consider moving them to a dedicated integration module/package to keep this unit-test file focused on pure unit tests.
2. The doc file currently describes the default Kimi model as kimi-k2, while these tests (and likely the code) use kimi-k2-turbo-preview as the default/custom choice; please align the documentation with the actual default behavior.

Both are non-blocking; current structure is functionally correct.

---

56-73: Kimi success test is solid; asserting request URL and payload structure is a valuable strengthening—Kimi API is stable and OpenAI-compatible

The success path correctly verifies:

• Parsed commands from _call_kimi
• That requests.post is called
• Presence and value of the Authorization header

The suggested assertion for the HTTP contract is well-founded. Kimi's API uses a documented, stable OpenAI-compatible endpoint at /v1/chat/completions with standard payload structure (model field, messages array). Adding assertions for the URL path and key JSON fields will reliably catch regressions in _call_kimi's request shape without becoming brittle:

call_args, call_kwargs = mock_post.call_args
self.assertIn("/v1/chat/completions", call_args[0])
self.assertEqual(call_kwargs["json"]["model"], interpreter.model)
self.assertIn("messages", call_kwargs["json"])

This strengthens test coverage by locking in the Kimi API contract, which is officially documented and widely implemented by third-party integrators.

docs/ISSUE_40_KIMI_K2_IMPLEMENTATION.md (4)

189-194: Add language hint to fenced code in Testing Results

The test output block uses a bare fenced code block. To satisfy markdownlint (MD040) and improve rendering, you can add a language, e.g.:

-```
+```text
 Ran 143 tests in 10.136s

 OK (skipped=5)

---

3-6: Markdownlint nits: bare URLs and minor wording

A few small polish items from static analysis:

• Replace “CLI interface improvements” with just “CLI improvements” to avoid tautology.
• Wrap bare URLs in Markdown links or <...> to satisfy MD034 (e.g., [Moonshot AI Platform](https://platform.moonshot.ai/)).

These are purely cosmetic and can be deferred.

Also applies to: 83-87, 190-196, 234-236

---

5-7: Status/Date fields may need updating when PR merges

The header states Status: ✅ Implemented and a specific “Date Completed”, but this PR is still open. To avoid confusion for future readers, consider phrasing this as “Planned/Implemented in PR #192 (pending merge)” or updating the status/date when the PR actually lands.

---

50-55: Consider updating requests version constraint and documenting versioning approach

The CVE information for requests>=2.32.4 is accurate (all three CVEs are properly fixed at that version). However, the latest requests release is 2.32.5 (August 2025), making the constraint outdated within months. To make this section age more gracefully, consider:

• Updating to requests>=2.32.5 for the latest patch, or
• Noting "(minimum secure version as of [date])" and/or linking to upstream security advisories rather than hard-coding CVE IDs inline.

This ensures the documentation remains correct without requiring constant updates as newer patch versions are released.

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test/test_coordinator.py:2

• Import of 'call' is not used.

from unittest.mock import Mock, patch, call

test/test_coordinator.py:5

• Import of 'time' is not used.

import time

docs/ISSUE_40_KIMI_K2_IMPLEMENTATION.md (1)

21-22: Default Kimi model in documentation doesn't match code.

The documentation states kimi-k2 as the default model (lines 21, 48, 138), but the code in LLM/interpreter.py uses kimi-k2-turbo-preview as the actual default (line 268). This inconsistency may confuse users.

Update the documentation to consistently use kimi-k2-turbo-preview or change the code default if kimi-k2 is the intended value.

Also applies to: 48-48, 138-138

docs/ISSUE_40_KIMI_K2_IMPLEMENTATION.md (1)

190-194: Add language specifier to fenced code block.

The test results code block is missing a language specifier which aids syntax highlighting and accessibility.

-```
+```text
 Ran 143 tests in 10.136s

 OK (skipped=5)

</blockquote></details>
<details>
<summary>cortex/user_preferences.py (3)</summary><blockquote>

`328-342`: **Remove unused `key_parts` parameter.**

The `key_parts` parameter is never used in `_coerce_value_for_set()`. Either remove it or implement the intended type coercion logic based on the key path.


```diff
-    def _coerce_value_for_set(self, key_parts: List[str], value: Any) -> Any:
+    def _coerce_value_for_set(self, value: Any) -> Any:
         """Coerce string inputs into appropriate types for set()."""

And update the call site at line 361:

-            coerced = self._coerce_value_for_set(parts, value)
+            coerced = self._coerce_value_for_set(value)

---

202-206: Silent exception swallowing may hide configuration issues.

The try-except-pass block silently ignores all load errors during initialization. This could mask configuration file corruption or permission issues that users should be aware of.

Consider logging the exception or storing the error state:

         try:
             self.load()
         except Exception:
-            # Ignore load errors here; callers can handle later
-            pass
+            # Store the error; callers can check or load() will re-raise
+            self._preferences = UserPreferences()

Alternatively, if errors truly should be ignored, at least log them at debug level for troubleshooting.

---

252-256: Chain exceptions to preserve traceback context.

When re-raising exceptions, use raise ... from e to preserve the original traceback for easier debugging.

         except yaml.YAMLError as e:
-            raise ValueError(f"Invalid YAML in config file: {str(e)}")
+            raise ValueError(f"Invalid YAML in config file: {e!s}") from e
         except Exception as e:
-            raise IOError(f"Failed to load config file: {str(e)}")
+            raise IOError(f"Failed to load config file: {e!s}") from e

The same pattern applies to other exception handlers in save() (line 286), _create_backup() (line 228), and set() (line 432).

test/integration/test_end_to_end.py (1)

107-110: Potential fragile assertion on last output line.

The assertion self.assertIn("OK", result.stdout.splitlines()[-1]) will raise an IndexError if stdout is empty. Consider adding a guard or using a more robust check.

         result = self._run("python test/run_all_tests.py", env=env)

         self.assertTrue(result.succeeded(), msg=result.stderr)
-        self.assertIn("OK", result.stdout.splitlines()[-1])
+        lines = result.stdout.splitlines()
+        self.assertTrue(lines, "Expected test output but stdout was empty")
+        self.assertIn("OK", lines[-1])

LLM/test_interpreter.py (1)

56-72: Mock response missing raise_for_status stub.

The mock response in test_call_kimi_success doesn't stub raise_for_status(). While this works because Mock() returns another mock by default, explicitly stubbing it ensures the test intent is clear and protects against future changes.

         mock_response = Mock()
         mock_response.status_code = 200
+        mock_response.raise_for_status = Mock()  # Explicitly stub to avoid accidental side effects
         mock_response.json.return_value = {
             "choices": [{"message": {"content": '{"commands": ["apt update", "apt install curl"]}'}}]
         }

LLM/interpreter.py (1)

136-137: Redundant requests import inside _call_kimi.

The requests module is already imported (and validated) during _initialize_client() for the KIMI provider (lines 52-58). The import at line 136 is redundant and adds unnecessary overhead on each API call.

         try:
-            import requests
             response = requests.post(

Since self.client is set to the requests module in _initialize_client(), you can use self.client.post(...) instead for consistency:

-            import requests
-            response = requests.post(
+            response = self.client.post(

test/integration/docker_utils.py (2)

24-50: docker_available() is robust; subprocess security lint is low risk here

The availability check via docker --version and docker info with small timeouts and shell=False is solid for a test helper. Ruff’s S603 warnings here are low risk since arguments are constant and not user-controlled; if those warnings are noisy in CI, you can either # noqa: S603 these calls or disable that rule for test modules.

---

53-106: run_in_docker helper looks good; minor f-string / lint tweak and trust boundary note

The argv-based docker invocation plus bash -lc inside the container is appropriate for an integration-test harness and avoids host-side shell injection; just ensure callers only pass trusted command strings since they execute with full shell semantics in the container. To address the RUF010 hint and avoid str() inside an f-string, you can simplify the volume mount construction:

-    for host_path, container_path in mounts or []:
-        docker_cmd.extend([
-            "-v",
-            f"{str(host_path.resolve())}:{container_path}",
-        ])
+    for host_path, container_path in mounts or []:
+        docker_cmd.extend(
+            [
+                "-v",
+                f"{host_path.resolve()!s}:{container_path}",
+            ]
+        )

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Review profile: CHILL

Plan: Pro

LLM/interpreter.py (1)

37-62: Unify KIMI client setup and HTTP call; avoid re-importing requests

For the KIMI path, _initialize_client() imports requests, assigns it to self.client, and sets _kimi_base_url, but _call_kimi() re-imports requests and doesn’t use self.client. This duplication slightly complicates testability and makes the client setup pattern inconsistent with the other providers.

You can simplify and make this more consistent by relying on self.client in _call_kimi() and dropping the second import:

     def _call_kimi(self, user_input: str) -> List[str]:
         """Call the Kimi K2 HTTP API and parse the response body."""
@@
-        try:
-            import requests
-            response = requests.post(
+        try:
+            response = self.client.post(
                 f"{self._kimi_base_url.rstrip('/')}/v1/chat/completions",
                 headers=headers,
                 json=payload,
                 timeout=60,
             )

(Optionally, you could make self.client a requests.Session() in _initialize_client() if you want connection pooling, but that’s not required for correctness.)

Also, please double-check that the endpoint path (/v1/chat/completions) and response shape (choices[0].message.content) still match the current Kimi K2 API.

Also applies to: 118-154

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Review profile: CHILL

Plan: Pro

LLM/interpreter.py (1)

169-176: Missing key existence check before accessing data["commands"].

If the JSON in CORTEX_FAKE_COMMANDS is valid but lacks the "commands" key, line 174 raises a bare KeyError instead of a descriptive ValueError.

This was flagged in a previous review. Add an explicit key check:

             try:
                 data = json.loads(payload)
             except json.JSONDecodeError as exc:
                 raise ValueError("CORTEX_FAKE_COMMANDS must contain valid JSON") from exc
+            if "commands" not in data:
+                raise ValueError("CORTEX_FAKE_COMMANDS must contain a 'commands' key")
             if not isinstance(data["commands"], list):  
                 raise ValueError("'commands' must be a list in CORTEX_FAKE_COMMANDS")  
             return data["commands"]

LLM/interpreter.py (2)

145-152: Redundant requests import; use the stored client instead.

requests is already imported and stored in self.client during _initialize_client() (line 63). The re-import here is unnecessary.

         try:
-            import requests
-            response = requests.post(
+            response = self.client.post(
                 f"{self._kimi_base_url.rstrip('/')}/v1/chat/completions",
                 headers=headers,
                 json=payload,
                 timeout=60,
             )

---

306-315: _default_model() is defined but never called.

This method duplicates the default model logic already present in __init__ (lines 34-39) but is never invoked. This creates maintenance burden and potential drift between the two locations.

Either:

1. Remove _default_model() if it was added speculatively, or
2. Refactor __init__ to use it:

         if model:
             self.model = model
         else:
-            if self.provider == APIProvider.OPENAI:
-                self.model = "gpt-4"
-            elif self.provider == APIProvider.CLAUDE:
-                self.model = "claude-sonnet-4-20250514"
-            elif self.provider == APIProvider.OLLAMA:
-                self.model = "llama3.2"  # Default Ollama model
+            self.model = self._default_model()

Note: This requires moving the method definition before __init__ or deferring the call until after full initialization.

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Review profile: CHILL

Plan: Pro

Configuration used: CodeRabbit UI

Review profile: CHILL

Plan: Pro