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Connector metadata encryption/decryption on connector-instance model#12

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kirtimanmishrazipstack wants to merge 6 commits intomainfrom
connector-connector-metadata-encryption
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Connector metadata encryption/decryption on connector-instance model#12
kirtimanmishrazipstack wants to merge 6 commits intomainfrom
connector-connector-metadata-encryption

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@kirtimanmishrazipstack kirtimanmishrazipstack commented Feb 28, 2024

What

  • connector_metadata field encryption on connector_instance model

Why

  • since we access the connector_metadata at several places in the code, we will be forced to encrpyt / decrypt on model itself

How

  • use django-cryptography to encrypt/decrypt on model
  • remove encrypt/decrypt on connector_instance serializers
  • remove decryption on all workflow changes

Relevant Docs

Related Issues or PRs

Dependencies Versions / Env Variables

Notes on Testing

  • Tested test-connector / file-listing on connector
  • End to end testing on WF's

Screenshots

Screenshot from 2024-02-28 19-08-17
Screenshot from 2024-02-28 19-08-11
Screenshot from 2024-02-28 19-08-27

Checklist

I have read and understood the Contribution Guidelines.

@kirtimanmishrazipstack kirtimanmishrazipstack changed the title init changes connector-metadata encryption/decryption on connector-instance model Feb 28, 2024
@kirtimanmishrazipstack kirtimanmishrazipstack changed the title connector-metadata encryption/decryption on connector-instance model Connector metadata encryption/decryption on connector-instance model Feb 28, 2024
@kirtimanmishrazipstack kirtimanmishrazipstack marked this pull request as ready for review February 28, 2024 13:50
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@chandrasekharan-zipstack chandrasekharan-zipstack left a comment

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  1. We'll have to migrate existing data as well - refer this
  2. A similar encryption was handled in adapter_processor and connector_auth apps - please check and handle those as well (can come in as separate PRs too)

@kirtimanmishrazipstack kirtimanmishrazipstack marked this pull request as draft February 29, 2024 07:14
chandrasekharan-zipstack added a commit that referenced this pull request Apr 17, 2026
…e-up log

Address review comments on PR #1886:

- #10 (resource leak): close the generator returned by fn() before
  retrying in iter_with_retry — otherwise streaming providers leak an
  in-flight HTTP socket until GC.
- #12 (behavioral regression): when we zero out SDK/wrapper retries we
  also lose the OpenAI SDK's native Retry-After handling on 429/503.
  _get_retry_delay now checks error.response.headers["retry-after"] and
  uses that value ahead of exponential backoff. HTTP-date form is not
  parsed; those fall back to backoff.
- #8 (observability gap): move the "Giving up ... after N attempt(s)"
  log into _get_retry_delay so all four retry helpers (call_with_retry,
  acall_with_retry, iter_with_retry, decorator) share the same
  exhaustion signal. Previously only the decorator path logged it.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
muhammad-ali-e added a commit that referenced this pull request Apr 17, 2026
* [FIX] Unified retry for LLM and embedding providers

litellm's retry only works for SDK-based providers (OpenAI/Azure).
httpx-based providers (Anthropic, Vertex, Bedrock, Mistral) and ALL
embedding calls silently ignore max_retries. This adds self-managed
retry with exponential backoff at the SDK layer, disabling litellm's
own retry entirely for consistency.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

* [REFACTOR] DRY retry logic into reusable call_with_retry utilities

Move retry loops out of LLM/Embedding classes into generic
call_with_retry, acall_with_retry, and iter_with_retry functions
in retry_utils.py. Both classes now call these directly instead
of maintaining their own retry helper methods.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

* [FIX] Consolidate retry logic, expose max_retries for all adapters

- Extract _get_retry_delay() shared helper to eliminate duplicated
  retry decision logic across call_with_retry, acall_with_retry,
  iter_with_retry, and retry_with_exponential_backoff
- Add num_retries=0 to embedding._pop_retry_params() to fully
  disable litellm's internal retry for embedding calls
- Expose max_retries in UI JSON schemas for embedding adapters
  (OpenAI, Azure, VertexAI, Ollama) and Ollama LLM — previously
  the field existed in Pydantic models but wasn't shown to users,
  silently defaulting to 0 retries
- Add debug logging to LLM and Embedding retry parameter extraction
- Clarify docstrings distinguishing is_retryable_litellm_error()
  from is_retryable_error() (different exception hierarchies)
- Remove stale noqa: C901 from simplified retry_with_exponential_backoff

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

* [FIX] Set max_retries default to 3 for all embedding and Ollama LLM adapters

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

* [FIX] Address greptile review: fix shadowed ConnectionError, use MRO check

- Fix `requests.ConnectionError` shadowing Python's builtin `ConnectionError`
  in `is_retryable_litellm_error()` — rename import to `RequestsConnectionError`
  and use `builtins.ConnectionError` / `builtins.TimeoutError` explicitly
- Use `__mro__`-based class name check instead of `type(error).__name__`
  to also catch subclasses of retryable error types
- P1 (num_retries not zeroed) was already fixed in prior commit

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

* [FIX] Address CodeRabbit review: add APITimeoutError, validate max_retries

- Add APITimeoutError to _RETRYABLE_ERROR_NAMES for explicit OpenAI
  SDK timeout coverage
- Add _validate_max_retries() guard to call_with_retry, acall_with_retry,
  iter_with_retry to fail fast on negative values instead of silently
  returning None

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

* UN-3344 [FIX] Reduce cognitive complexity and remove useless except clause

Address SonarCloud findings on PR #1886:
- S3776: Flatten retry_with_exponential_backoff.wrapper by moving the
  success logging + return out of the try block and using `continue` in
  the retry path, so the except branch only handles the give-up case.
- S2737: Drop the `except Exception: raise` clause — it was a no-op that
  added complexity without changing behavior (non-matching exceptions
  propagate naturally).

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* UN-3344 [FIX] Extract retry loop to top-level helper to drop cognitive complexity

Sonar still flagged retry_with_exponential_backoff at complexity 16 after
the previous flatten. Nested def decorator / def wrapper counted against
the outer function's score. Move the retry body to a module-level
_invoke_with_retries helper so the decorator factory just delegates,
bringing the outer function well under the 15 threshold.

Behavior is unchanged — all paths (success, retry, give-up, non-retryable
propagate) are preserved and covered by the existing SDK1 tests.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* UN-3344 [FIX] Honor Retry-After, close stream gen on retry, share give-up log

Address review comments on PR #1886:

- #10 (resource leak): close the generator returned by fn() before
  retrying in iter_with_retry — otherwise streaming providers leak an
  in-flight HTTP socket until GC.
- #12 (behavioral regression): when we zero out SDK/wrapper retries we
  also lose the OpenAI SDK's native Retry-After handling on 429/503.
  _get_retry_delay now checks error.response.headers["retry-after"] and
  uses that value ahead of exponential backoff. HTTP-date form is not
  parsed; those fall back to backoff.
- #8 (observability gap): move the "Giving up ... after N attempt(s)"
  log into _get_retry_delay so all four retry helpers (call_with_retry,
  acall_with_retry, iter_with_retry, decorator) share the same
  exhaustion signal. Previously only the decorator path logged it.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* UN-3344 [REFACTOR] Share retry-kwargs helper and add TypeVar to retry wrappers

Address review comments on PR #1886:

- #9 (typing): call_with_retry / acall_with_retry / iter_with_retry
  previously returned `object`, erasing caller type info. Add PEP 695
  generics so the return type flows from the wrapped callable:
  acall_with_retry now takes Callable[[], Awaitable[T]] and
  iter_with_retry takes Callable[[], Iterable[T]] -> Generator[T, ...].
- #11 / #13 (DRY): `_pop_retry_params` in embedding.py and
  `_disable_litellm_retry` in llm.py were identical logic. Lift to
  shared `pop_litellm_retry_kwargs` helper in retry_utils.py and delete
  both methods.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

---------

Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Co-authored-by: ali <117142933+muhammad-ali-e@users.noreply.github.com>
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2 participants