fix: output sanitizer applied to LLM response on all dispatch paths; orchestrator LCEL migration - #7
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…ing regression tests - ValidLLMChain: add invoke()/ainvoke() overrides. PR #7's BUG-1 fix only covered run()/arun(), but its own BUG-3 fix switched PortableOrchestrator to call .invoke()/.ainvoke() directly, which doesn't route through run()/arun() - silently skipping the sanitizer on the orchestrator's actual call path. - ValidLLMChain.run()/arun(): pass through **kwargs to super() instead of silently dropping them. - Fix two tests introduced by PR #7 that were broken on Python 3.12: asyncio.get_event_loop().run_until_complete() -> asyncio.run(), and removed dead asyncio.coroutine()/_make_coro() code that raised AttributeError before ever reaching the assertions. - Fix a latent pydantic issue in the arun test: ValidLLMChain is a pydantic model and rejects instance attribute assignment for undeclared fields (chain.arun = fake_arun), so the test now patches the parent class's arun() instead, consistent with the pattern already documented in llm_proxy_wrapper.py. - Add regression tests: invoke()/ainvoke() sanitizer coverage, kwargs passthrough, BUG-4 exception re-raise + fall-through paths, BUG-5 BaseChatModel wrapping. Pre-existing, out-of-scope failure noted but not touched: test_model_with_unsupported_provider fails on main (before PR #7 too) - the API-key check in _get_direct_model_'s manual fallback runs before the provider-support check, so an unsupported provider raises a misleading 'API key not found' error instead of 'Not implemented'.
PR Review — 5 confirmed bug fixesVerdict: REQUEST_CHANGES — the 5 underlying fixes are real and (mostly) correct, but 2 of the "headline" regression tests that are supposed to prove BUG-1 and BUG-2 stay fixed are structurally vacuous — they'd pass even if the original bug were reintroduced. There's also a moderate silent-failure gap and a couple of secondary issues worth a look. Several things are genuinely solid and called out below. Reviewed via 3 independent passes (test coverage, silent-failure hunting, comment accuracy) against the actual current diff/head commit, not just the PR description. 🔴 Test integrity — the tests meant to prevent regressions wouldn't catch them1. BUG-1's plain @patch("connectchain.chains.valid_llm_chain.ValidLLMChain.run")
def test_run_sanitizer_applied_to_output(self, mock_run):
mock_run.return_value = "[SANITIZED:...]"
...This patches 2. BUG-2's thread-safety test is vacuous. 🟡 Silent-failure gap (moderate)3. 🟡 Two secondary observations on BUG-4's fix4. 5. The exception handler's error message can itself raise. The ⚪ Comment quality (low priority, but worth a pass)6. Pervasive "narrate-the-diff" comments across source and tests — tagged 7. Minor self-contradicting docstring wording in ✅ What's solid
RecommendationFix the two vacuous tests (#1, #2) so they'd actually fail on a regression — that's the main blocker, since the PR's core value proposition is "these tests prove the bugs stay fixed." Add the missing warning log in |
Follow-up review — a 4th independent pass found a genuine new bugA general code-quality pass (separate from the test-coverage/silent-failure/comments passes above) turned up something the other three missed, plus confirmation on a couple of open questions. Posting as a follow-up rather than editing the comment above. 🔴 NEW CRITICAL —
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Nice work here, @wilsonhj — the BUG-1 fix in particular is a sharp catch (and the writeup on why I'll work on getting this merged. |
Fix for the remaining findings from the reviews aboveContext: the branch this PR is built on has since been merged into the fork's
I can't push directly to this branch, so posting the diff here (verified against current diff --git a/connectchain/lcel/model.py b/connectchain/lcel/model.py
index dcd4090..354b6de 100644
--- a/connectchain/lcel/model.py
+++ b/connectchain/lcel/model.py
@@ -249,6 +249,17 @@ def _get_direct_model_(model_config: Any) -> BaseLanguageModel:
azure_api_key = _resolve_direct_api_key_(model_config)
return _get_direct_azure_model_(model_config, azure_api_key, api_base)
+ if model_config.provider not in _SUPPORTED_PROVIDERS:
+ # Reject unsupported providers before attempting init_chat_model(), so a
+ # genuinely unsupported provider fails fast with the correct "not supported"
+ # error instead of first emitting a misleading "falling back to manual
+ # provider init" warning (or, if init_chat_model() happens not to raise for
+ # an unrecognised provider name, silently succeeding with the wrong model).
+ raise LCELModelException(
+ f"Provider '{model_config.provider}' not supported. "
+ f"Supported providers: {', '.join(_SUPPORTED_PROVIDERS)}"
+ )
+
# Add temperature if specified. Note: getattr's default is never returned here
# because ConfigWrapper.__getattr__ returns None (not AttributeError) for a
# missing key, so we must check the resolved value instead of using hasattr().
@@ -294,21 +305,17 @@ def _get_direct_model_(model_config: Any) -> BaseLanguageModel:
e,
)
except Exception as e: # pylint: disable=broad-except
- # Unexpected failure: preserve the original traceback.
+ # Unexpected failure: preserve the original traceback. Use getattr for the
+ # model name so constructing this message can never raise a second, uncaught
+ # exception (e.g. when the original failure was model_config.model_name itself
+ # raising AttributeError on a malformed config).
raise LCELModelException(
- f"Unexpected error initialising model '{model_config.model_name}': {e}"
+ f"Unexpected error initialising model "
+ f"'{getattr(model_config, 'model_name', '<unknown>')}': {e}"
) from e
- # ── Manual provider-specific initialisation fallback (Azure already handled above) ──
- if model_config.provider not in _SUPPORTED_PROVIDERS:
- # Check provider support before the API-key lookup below, so an
- # unsupported provider fails fast with a clear message instead of a
- # misleading "API key not found" error for a key it never needed.
- raise LCELModelException(
- f"Provider '{model_config.provider}' not supported. "
- f"Supported providers: {', '.join(_SUPPORTED_PROVIDERS)}"
- )
-
+ # ── Manual provider-specific initialisation fallback (Azure and unsupported
+ # providers already handled above) ──────────────────────────────────────
api_key = _resolve_direct_api_key_(model_config)
if model_config.provider == "openai":
diff --git a/connectchain/orchestrators/portable_orchestrator.py b/connectchain/orchestrators/portable_orchestrator.py
index cc547c0..2d7072e 100644
--- a/connectchain/orchestrators/portable_orchestrator.py
+++ b/connectchain/orchestrators/portable_orchestrator.py
@@ -12,6 +12,7 @@
"""
This module contains the PortableOrchestrator class.
"""
+import logging
from typing import Any, List
import connectchain.chains
@@ -19,6 +20,8 @@ import connectchain.prompts
import connectchain.utils
from connectchain.lcel import model
+logger = logging.getLogger(__name__)
+
class PortableOrchestrator:
"""
@@ -87,5 +90,10 @@ class PortableOrchestrator:
value = result.get(output_key, missing)
if value is not missing:
return value
+ logger.warning(
+ "output_key '%s' not found in result; falling back to str(result). Keys: %s",
+ output_key,
+ list(result.keys()),
+ )
return str(result)
return result
diff --git a/tests/unit_tests/test_model.py b/tests/unit_tests/test_model.py
index 201ae1f..8b01b29 100644
--- a/tests/unit_tests/test_model.py
+++ b/tests/unit_tests/test_model.py
@@ -122,6 +122,42 @@ class TestModel(unittest.TestCase):
result = _get_direct_model_(model_config)
self.assertIsInstance(result, ChatOpenAI)
+ def test_get_direct_model_safe_message_when_model_name_raises(self):
+ """If the original failure inside _get_direct_model_'s try block was itself
+ model_config.model_name raising AttributeError (a malformed config missing
+ that attribute), the except-Exception handler's error message must not
+ re-access that same attribute -- doing so would raise a second, uncaught
+ AttributeError instead of the intended clean LCELModelException."""
+
+ class _ModelNameRaises:
+ provider = "openai"
+
+ @property
+ def model_name(self):
+ raise AttributeError("model_name is not available")
+
+ with self.assertRaisesRegex(
+ LCELModelException, "Unexpected error initialising model"
+ ) as cm:
+ _get_direct_model_(_ModelNameRaises())
+ self.assertIsInstance(cm.exception.__cause__, AttributeError)
+
+ @patch("connectchain.lcel.model.logger")
+ @patch("langchain.chat_models.init_chat_model")
+ def test_unsupported_provider_does_not_log_fallback_warning(
+ self, mock_init_chat_model, mock_logger
+ ):
+ """An unsupported provider must be rejected BEFORE init_chat_model() is ever
+ attempted, so the misleading 'falling back to manual provider init' warning
+ never fires ahead of the correct 'not supported' error."""
+ model_config = wrap_model_config(
+ {**get_mock_config().data["models"]["1"], "provider": "meta"}
+ )
+ with self.assertRaisesRegex(LCELModelException, "not supported"):
+ _get_direct_model_(model_config)
+ mock_init_chat_model.assert_not_called()
+ mock_logger.warning.assert_not_called()
+
def test_model_azure_endpoint_without_api_version_raises(self):
"""An Azure-shaped api_base without api_version must fail loudly instead of
silently falling back to a non-Azure ChatOpenAI client pointed at Azure."""
diff --git a/tests/unit_tests/test_portable_orchestrator.py b/tests/unit_tests/test_portable_orchestrator.py
index 344cab9..45d8050 100644
--- a/tests/unit_tests/test_portable_orchestrator.py
+++ b/tests/unit_tests/test_portable_orchestrator.py
@@ -163,6 +163,29 @@ class TestPortableOrchestrator(unittest.TestCase):
response = orchestrator.run_sync("test_query")
self.assertEqual(response, expected)
+ def test_extract_output_warns_when_output_key_absent(self):
+ """When the chain's output_key is genuinely absent from the result dict
+ (e.g. a caller wraps a non-ValidLLMChain runnable whose output uses a
+ different key -- this class documents that it "can wrap any third-party
+ LLM framework"), _extract_output() falls back to str(result). That
+ fallback must NOT be silent: it emits a logger.warning so the skip
+ leaves a visible trace, mirroring ValidLLMChain._sanitize_dict()'s
+ handling of the analogous key-not-found case (an unlogged skip there is
+ a bypass with no visible trace)."""
+ prompt = PromptTemplate(input_variables=["q"], template="{q}")
+ llm = ChatOpenAI(model="gpt-3.5-turbo", openai_api_key="test-key")
+ chain = ValidLLMChain(llm=llm, prompt=prompt, output_sanitizer=None, output_key="text")
+ orchestrator = PortableOrchestrator(chain)
+ result = {"unexpected_key": "value"}
+ with patch.object(ValidLLMChain, "invoke", return_value=result):
+ with self.assertLogs(
+ "connectchain.orchestrators.portable_orchestrator", level="WARNING"
+ ) as captured:
+ response = orchestrator.run_sync("test_query")
+ self.assertEqual(response, str(result))
+ self.assertEqual(len(captured.records), 1)
+ self.assertIn("text", captured.output[0])
+
@patch("connectchain.lcel.model.get_token_from_env", return_value="test_token")
@patch("connectchain.prompts.ValidPromptTemplate", return_value=Mock(ValidPromptTemplate))
@patch("connectchain.chains.ValidLLMChain", return_value=Mock(ValidLLMChain))
diff --git a/tests/unit_tests/test_session_map.py b/tests/unit_tests/test_session_map.py
index bf28282..41fe53e 100644
--- a/tests/unit_tests/test_session_map.py
+++ b/tests/unit_tests/test_session_map.py
@@ -87,23 +87,65 @@ class TestSessionMap(unittest.TestCase):
self.assertTrue(sm.is_expired("stale-session"))
def test_thread_safety_no_race_condition(self):
- """Concurrent reads on is_expired() must never raise or corrupt state."""
+ """A writer racing readers on the SAME session_id must never raise or
+ expose a partially-published entry.
+
+ The old version of this test only ever called is_expired() on a key
+ that was never registered via new_session() -- so there were no
+ concurrent writes and nothing was actually contended (it passed even
+ with self._lock removed entirely). This drives the real scenario the
+ lock protects: new_session() (writer) racing is_expired()/
+ get_valid_llm()/get_llm() (readers) on one shared key.
+ """
sm = SessionMap(expires_in=900)
+ key = "concurrent-key"
+ mock_llm = MagicMock()
errors: list = []
+ stop = threading.Event()
+
+ def writer():
+ for _ in range(1000):
+ if stop.is_set():
+ return
+ try:
+ sm.new_session(key, mock_llm)
+ except Exception as exc: # pylint: disable=broad-except
+ errors.append(exc)
+ stop.set()
+ return
- def worker():
- for _ in range(200):
+ def reader():
+ for _ in range(1000):
+ if stop.is_set():
+ return
try:
- sm.is_expired("concurrent-key")
+ sm.is_expired(key)
+ sm.get_valid_llm(key)
+ if not sm.is_expired(key):
+ # Documented precondition: safe once is_expired() said fresh.
+ sm.get_llm(key)
except Exception as exc: # pylint: disable=broad-except
errors.append(exc)
+ stop.set()
+ return
- threads = [threading.Thread(target=worker) for _ in range(10)]
+ threads = [threading.Thread(target=writer) for _ in range(4)]
+ threads += [threading.Thread(target=reader) for _ in range(8)]
for t in threads:
t.start()
for t in threads:
t.join()
+
self.assertEqual(errors, [], f"Race condition detected: {errors}")
+ entry = sm.session_map[key]
+ self.assertIsInstance(entry, tuple)
+ self.assertEqual(len(entry), 3)
+ cached_at, expires_in, llm = entry
+ self.assertIsInstance(cached_at, datetime)
+ self.assertEqual(expires_in, 900)
+ self.assertIs(llm, mock_llm)
+ self.assertFalse(sm.is_expired(key))
+ self.assertIs(sm.get_valid_llm(key), mock_llm)
def test_concurrent_first_construction_yields_single_consistent_instance(self):
"""CODE-REVIEW FOLLOWUP regression: __new__'s singleton construction was |
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Excellent. I am working on a follow up P.R. to address more bugs discovered during testing. Did you see the git issue I filed to the repo today?
… On Jul 6, 2026, at 8:08 AM, Canary ***@***.***> wrote:
canarymedtech-23
left a comment
(americanexpress/connectchain#7)
<#7 (comment)>
Follow-up review — a 4th independent pass found a genuine new bug
A general code-quality pass (separate from the test-coverage/silent-failure/comments passes above) turned up something the other three missed, plus confirmation on a couple of open questions. Posting as a follow-up rather than editing the comment above.
🔴 NEW CRITICAL — run()/arun() double-apply output_sanitizer
connectchain/chains/valid_llm_chain.py. In LangChain 0.3.x, the deprecated Chain.run() delegates to self(...) → Chain.__call__ → self.invoke(...). Since self is a ValidLLMChain, that resolves to the overridden invoke() — which already sanitizes the output dict. Chain.run then extracts output_key and returns the already-sanitized string, and ValidLLMChain.run()'s own self._sanitize(result) call sanitizes it again. Same path for arun()/ainvoke().
Empirically reproduced with FakeListLLM + sanitizer = lambda t: f"[S:{t}]" on raw output RAW_LLM_OUTPUT:
run() -> '[S:[S:RAW_LLM_OUTPUT]]' sanitizer called 2x ❌
arun() -> '[S:[S:RAW_LLM_OUTPUT]]' sanitizer called 2x ❌
invoke() -> {'text': '[S:RAW_LLM_OUTPUT]'} sanitizer called 1x ✅
ainvoke() -> {'text': '[S:RAW_LLM_OUTPUT]'} sanitizer called 1x ✅
Confirmed via inspect.getsource(Chain.run) (return self(args[0], ...)[...]) and Chain.__call__ (return self.invoke(...)). Any non-idempotent sanitizer (PII masking, tagging/wrapping, truncation) produces corrupted output through run()/arun(). A sanitizer that only raises on bad content still raises either way, which is why the existing BADWORD-style tests don't surface this. Good news: PortableOrchestrator — the primary call path post-BUG-3 — uses .invoke()/.ainvoke() directly and sanitizes exactly once, so the main flow is unaffected. The defect is in the direct ValidLLMChain.run()/.arun() public API, which this PR explicitly added overrides for. Simplest fix: don't override run()/arun() at all and let them delegate to the (correctly single-sanitizing) invoke(); or have them call the chain logic without re-sanitizing.
Why the existing tests miss this: test_run_sanitizer_applied_to_output mocks ValidLLMChain.run itself (see the test-integrity finding above), and the other run()-path tests patch the parent LLMChain.run, which short-circuits the internal self.invoke dispatch — so double-sanitization never has a chance to manifest in the suite. The regression suite is green while the real behavior on this path is wrong.
Confirmed: the two things I'd asked reviewers to check are NOT issues in the shipped code
PortableOrchestrator.run_sync() passes query unwrapped into .invoke(), not hardcoded as {"input": query} — verified against a chain with a non-"input" variable name (area_of_interest), which correctly resolves via Chain.prep_inputs(). The PR body's {"input": query} snippet is stale relative to what's shipped.
_extract_output()'s sentinel-based key lookup correctly returns an empty-string output as '', not stringified — also confirmed independently above, restating here since I'd flagged it as an open question.
🟡 Additional finding — the dependency pin doesn't achieve the stated goal
pyproject.toml pins langchain>=0.3.26 with no upper bound. A fresh install today resolves to langchain==1.3.11, where langchain.chains/LLMChain no longer exist at all — from langchain.chains.llm import LLMChain raises ModuleNotFoundError and the package fails to import entirely; .run()/.arun() are gone too. BUG-3's stated motivation is "upgrade safety ahead of the 0.4.x/1.0 removal," but the PR doesn't achieve that — it keeps subclassing LLMChain and adds more surface area depending on it (the run/arun/invoke overrides above). The PR's own "upgrade safety" test step (pip install 'langchain>=0.4.0' --dry-run) doesn't reflect this.
⚪ Minor
lcel/model.py: the _SUPPORTED_PROVIDERS fail-fast check runs after the init_chat_model() attempt, so an unsupported provider (e.g. "meta") logs a misleading init_chat_model() failed ... falling back warning before the correct "not supported" error — cosmetic log noise, not a correctness bug.
valid_llm_chain.py still carries # pylint: disable=too-few-public-methods, stale now that the class has 6 public methods.
BUG-2 (session KeyError + locking), BUG-4 (silent-except handling), and BUG-5 (base-class type hint) all check out as correct and complete — no changes needed there.
Updated recommendation
The double-sanitization bug (and its matching test blind spot) is the one I'd treat as a hard blocker alongside the vacuous-test findings above — it's a real behavioral defect on public API surface this PR explicitly added, not just a test-integrity gap. The dependency-pin issue is worth a decision (upper-bound the pin, or explicitly scope this PR to "fix these 5 bugs" without claiming upgrade-safety) but is separable from the correctness fixes.
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The four still-open findings from the reviews above have been implemented and are up as a PR against the fork's |
Fix 4 remaining findings from the external PR #7 review (rebased onto current main)
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I have two pull requests open, PR #7 (already approved by a reviewer) and PR #9, which together fix over twenty verified bugs I found through a systematic review of the codebase — including Azure OpenAI support that failed against real clients, a prompt-sanitization bypass, and error-handling defects that made failures silent or unrecoverable.
Every fix was reproduced against the live code before patching and is backed by a regression test, with the full suite passing (119 tests).Here is the follow up. Do you have any questions? :)
Fix 10 bugs from an independent review pass, with follow-up hardening and docs by wilsonhj · Pull Request #9 · americanexpress/connectchaingithub.com
Best,Hiro J.
Follow-up review — a 4th independent pass found a genuine new bug:
A general code-quality pass (separate from the test-coverage/silent-failure/comments passes above) turned up something the other three missed, plus confirmation on a couple of open questions. Posting as a follow-up rather than editing the comment above.
🔴 NEW CRITICAL — run()/arun() double-apply output_sanitizerconnectchain/chains/valid_llm_chain.py. In LangChain 0.3.x, the deprecated Chain.run() delegates to self(...) → Chain.__call__ → self.invoke(...). Since self is a ValidLLMChain, that resolves to the overridden invoke() — which already sanitizes the output dict. Chain.run then extracts output_key and returns the already-sanitized string, and ValidLLMChain.run()'s own self._sanitize(result) call sanitizes it again. Same path for arun()/ainvoke().Empirically reproduced with FakeListLLM + sanitizer = lambda t: f"[S:{t}]" on raw output RAW_LLM_OUTPUT:
run() -> '[S:[S:RAW_LLM_OUTPUT]]' sanitizer called 2x ❌
arun() -> '[S:[S:RAW_LLM_OUTPUT]]' sanitizer called 2x ❌
invoke() -> {'text': '[S:RAW_LLM_OUTPUT]'} sanitizer called 1x ✅
ainvoke() -> {'text': '[S:RAW_LLM_OUTPUT]'} sanitizer called 1x ✅
Confirmed via inspect.getsource(Chain.run) (return self(args[0], ...)[...]) and Chain.__call__ (return self.invoke(...)). Any non-idempotent sanitizer (PII masking, tagging/wrapping, truncation) produces corrupted output through run()/arun(). A sanitizer that only raises on bad content still raises either way, which is why the existing BADWORD-style tests don't surface this. Good news: PortableOrchestrator — the primary call path post-BUG-3 — uses .invoke()/.ainvoke() directly and sanitizes exactly once, so the main flow is unaffected. The defect is in the direct ValidLLMChain.run()/.arun() public API, which this PR explicitly added overrides for. Simplest fix: don't override run()/arun() at all and let them delegate to the (correctly single-sanitizing) invoke(); or have them call the chain logic without re-sanitizing.Why the existing tests miss this: test_run_sanitizer_applied_to_output mocks ValidLLMChain.run itself (see the test-integrity finding above), and the other run()-path tests patch the parent LLMChain.run, which short-circuits the internal self.invoke dispatch — so double-sanitization never has a chance to manifest in the suite. The regression suite is green while the real behavior on this path is wrong.
Confirmed: the two things I'd asked reviewers to check are NOT issues in the shipped code
PortableOrchestrator.run_sync() passes query unwrapped into .invoke(), not hardcoded as {"input": query} — verified against a chain with a non-"input" variable name (area_of_interest), which correctly resolves via Chain.prep_inputs(). The PR body's {"input": query} snippet is stale relative to what's shipped.
_extract_output()'s sentinel-based key lookup correctly returns an empty-string output as '', not stringified — also confirmed independently above, restating here since I'd flagged it as an open question.
🟡 Additional finding — the dependency pin doesn't achieve the stated goalpyproject.toml pins langchain>=0.3.26 with no upper bound. A fresh install today resolves to langchain==1.3.11, where langchain.chains/LLMChain no longer exist at all — from langchain.chains.llm import LLMChain raises ModuleNotFoundError and the package fails to import entirely; .run()/.arun() are gone too. BUG-3's stated motivation is "upgrade safety ahead of the 0.4.x/1.0 removal," but the PR doesn't achieve that — it keeps subclassing LLMChain and adds more surface area depending on it (the run/arun/invoke overrides above). The PR's own "upgrade safety" test step (pip install 'langchain>=0.4.0' --dry-run) doesn't reflect this.
⚪ Minor
lcel/model.py: the _SUPPORTED_PROVIDERS fail-fast check runs after the init_chat_model() attempt, so an unsupported provider (e.g. "meta") logs a misleading init_chat_model() failed ... falling back warning before the correct "not supported" error — cosmetic log noise, not a correctness bug.
valid_llm_chain.py still carries # pylint: disable=too-few-public-methods, stale now that the class has 6 public methods.
BUG-2 (session KeyError + locking), BUG-4 (silent-except handling), and BUG-5 (base-class type hint) all check out as correct and complete — no changes needed there.
Updated recommendationThe double-sanitization bug (and its matching test blind spot) is the one I'd treat as a hard blocker alongside the vacuous-test findings above — it's a real behavioral defect on public API surface this PR explicitly added, not just a test-integrity gap. The dependency-pin issue is worth a decision (upper-bound the pin, or explicitly scope this PR to "fix these 5 bugs" without claiming upgrade-safety) but is separable from the correctness fixes.—Reply to this email directly, view it on GitHub, or unsubscribe.You are receiving this because you authored the thread.Message ID: ***@***.***>
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…n installs The langchain, langchain-openai, langchain-community, and langchain-mcp-adapters dependencies had lower bounds but no upper bounds. A fresh resolve therefore pulls langchain 1.x, which removed langchain.chains, langchain.schema, and langchain.llms - modules this codebase imports throughout. That breaks every import of connectchain and makes the entire test suite uncollectable on a clean install. Pin these packages to the 0.3.x / 0.1.x lines the code actually targets: langchain>=0.3.26,<0.4.0 langchain-openai>=0.3.24,<0.4.0 langchain-community>=0.3.26,<0.4.0 langchain-mcp-adapters>=0.1.0,<0.2.0 Co-authored-by: Claude <noreply@anthropic.com>
…orchestrator LCEL migration The output_sanitizer was wired incorrectly and the orchestrator relied on deprecated LangChain APIs. This corrects both. ValidLLMChain: - The sanitizer previously ran on the user's *input* inside run(), not on the model's response, and only on the run() path -- and because run() forwarded to invoke(), it could be applied twice or bypassed entirely depending on the dispatch path. - Sanitizing now happens in _call()/_acall(), the earliest point the raw response becomes a dict and before Chain.invoke()/ainvoke() saves it to memory or fires on_chain_end with it. run(), arun(), invoke(), and ainvoke() all dispatch through _call()/_acall(), so this single override covers every entry point. A missing output_key now logs a warning instead of silently skipping, so an unsanitized-output bypass can never pass unnoticed. PortableOrchestrator: - Moved off the deprecated LLMChain.run/arun onto LCEL .invoke()/.ainvoke(). - Output is extracted via the chain's output_key (default "text"), falling back to str(result) with a warning when the key is absent. - from_prompt_template now forwards output_sanitizer to the chain. ValidPromptTemplate: - format_prompt now sanitizes the *rendered* prompt (via StringPromptValue) rather than the individual kwargs. README and the langchain_chains example are corrected to match. Co-authored-by: Claude <noreply@anthropic.com>
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This PR has been refreshed — what changed and why@PreetamMatta thank you for the review and the offer to help get this merged — much appreciated. Before it could land, two hard blockers needed fixing, so the branch has been rebuilt (force-pushed):
Scope (tightened)This PR now covers exactly the sanitizer + orchestrator subsystem: The rest of the original 5-bug set (session-map/ Verification: 70 tests passing on this branch (the 1 remaining failure is Co-authored-by: Claude noreply@anthropic.com |
wilsonhj
changed the title
Runtime verification — PASS ✅Verified by driving the public package boundary ( Sanitizer singleness (the historical double-apply bug): a counting+transforming sanitizer across all four dispatch paths: Exactly one application per path — including Orchestrator: bare query maps onto the chain's real input variable (tested with Rendered-prompt sanitization: content split across fields ( Findings for a future pass (none blocking):
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4 participants
Why this PR exists
Code review of the
connectchaincodebase (tracked in Issue #6) identified five confirmed bugs — two critical, two high, one medium severity. Left unresolved, the two critical bugs silently break output sanitization and cause runtime crashes during token acquisition. The two high-severity bugs will convert from deprecation warnings into hardAttributeErrorfailures when the project upgrades to LangChain ≥ 0.4.x. This PR fixes all five.What problems does this PR solve?
chains/valid_llm_chain.pyoutput_sanitizerwas applied to the user's input, not to the LLM's response — the opposite of what the class advertises. Any PII redaction, profanity filtering, or output-injection guard was silently doing nothing.utils/session_map.pyis_expired()accessedself.session_map[session_id]without checking existence first, causing an unhandledKeyErrorcrash on the very first call for any new session. Also: no thread lock protected concurrent read/write, risking race conditions under async load.orchestrators/portable_orchestrator.pyrun_sync()andrun()called the deprecatedLLMChain.run()/LLMChain.arun()methods, which are scheduled for removal in LangChain 0.4.x.lcel/model.pypassin_get_direct_model_()silently swallowed all exceptions frominit_chat_model(). Any error — wrong API key, missing provider package, network timeout — was permanently lost, making root-cause diagnosis impossible.utils/llm_proxy_wrapper.pywrap_llm_with_proxyimportedBaseLLMfrom the deprecatedlangchain.llmspath and used it as the type annotation. All modern chat models (ChatOpenAI,ChatAnthropic, etc.) inherit fromBaseChatModel, notBaseLLM— so the type annotation was never correct for any real ConnectChain use case.How does each fix work?
BUG-1 —
ValidLLMChainoutput sanitizer (valid_llm_chain.py)Before:
After:
An
arun()async override is also added so the sanitizer is not skipped on async invocations (previously there was no async override at all).BUG-2 —
SessionMap.is_expired()KeyError + thread safety (session_map.py)Before:
After:
new_session()andget_llm()are also wrapped with the same lock for consistency.BUG-3 —
PortableOrchestratordeprecated methods (portable_orchestrator.py)Before:
After:
The
"text"→"output"key fallback handles bothLLMChain-style and LCEL-style response dicts.BUG-4 — Silent exception swallowing (
lcel/model.py)Before:
After:
BUG-5 — Wrong base class type (
llm_proxy_wrapper.py)Before:
After:
BaseLanguageModelis the correct common ancestor for bothBaseLLM(legacy completion models) andBaseChatModel(all modern chat models).How to test and validate these fixes
Run the new unit tests
What each new test proves
test_run_sanitizer_applied_to_outputtest_run_sanitizer_raises_on_bad_outputOperationNotPermittedExceptionraised when LLM returns a banned wordtest_run_no_sanitizer_returns_raw_outputoutput_sanitizer=Noneis a safe no-optest_arun_sanitizer_applied_to_outputtest_is_expired_unknown_session_returns_trueKeyError; returnsTruefor unregistered session IDstest_is_expired_active_session_returns_falsetest_is_expired_stale_session_returns_truetest_thread_safety_no_race_conditionis_expired()calls complete without exceptiontest_run_sync_uses_invokeinvoke({'input': query})is called; deprecated.run()is nottest_run_sync_output_key_fallback'output'key handled when chain does not return'text'keytest_run_async_uses_ainvokeainvoke({'input': query})is called; deprecated.arun()is notManual smoke test (BUG-1)
Upgrade safety test (BUG-3 & BUG-5)
Closes #6