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fix: gateway session data loss and restore deleted _delivery module#2150

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fix: gateway session data loss and restore deleted _delivery module#2150
cursor[bot] wants to merge 2 commits into
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cursor/critical-bug-investigation-728c

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@cursor

@cursor cursor Bot commented Jun 22, 2026

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Summary

Critical bug scan found three regressions introduced by recent commits (notably #2054):

1. Missing bots/_delivery.py (crash on import)

Impact: ModuleNotFoundError when importing DurableDelivery or DurableAdapterMixin — breaks durable outbound delivery for all bot adapters using the mixin.

Root cause: #2054 removed _delivery.py as "unused", but _durable_adapter.py and bots/__init__.py still import from it.

Fix: Restore the module.

2. Gateway session resume data loss

Impact: Resuming a persisted gateway session restores the initial empty snapshot instead of the latest state — all conversation history is lost on reconnect.

Root cause: create_session() breaks on the first session_data system message (written at init), but close_session() appends updated snapshots. The break prevents reaching the latest one.

Fix: Iterate all system messages and keep the last session_data snapshot.

3. Gateway shutdown data loss

Impact: Graceful gateway shutdown discards all active session state without persisting it.

Root cause: stop() calls session.close() directly instead of close_session(), which is the method that writes final state to the session store.

Fix: Call close_session(session_id) for each active session on shutdown.

Validation

Added regression tests in tests/unit/gateway/test_gateway_persistence_fixes.py:

  • test_resume_uses_latest_session_data_snapshot — PASSED
  • test_stop_persists_active_sessions — PASSED
  • test_durable_delivery_import — PASSED
  • test_durable_adapter_mixin_import — PASSED
Open in Web View Automation 

Summary by CodeRabbit

  • New Features

    • Enhanced message delivery with automatic retries and backoff policies
    • Added support for progressive message streaming and platform-specific chunking
    • Durable message persistence with recovery mechanisms for failed sends
  • Bug Fixes

    • Fixed session data restoration to use latest persisted state
    • Improved session shutdown to properly persist active sessions

- Resume gateway sessions from the latest session_data snapshot instead of
  the initial empty one written at session creation
- Persist active sessions on gateway stop() via close_session()
- Restore bots/_delivery.py accidentally removed in #2054; imports for
  DurableDelivery and DurableAdapterMixin were still live
- Add regression tests for resume, shutdown persist, and delivery imports

Co-authored-by: Mervin Praison <MervinPraison@users.noreply.github.com>
@MervinPraison

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@MervinPraison

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/review

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✅ Action performed

Review finished.

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📝 Walkthrough

Walkthrough

Adds a complete _delivery.py message-delivery subsystem for PraisonAI bots (MessageSender protocol, UnifiedDelivery, deliver_with_retry, deliver_chunked, DurableDelivery with outbox persistence). Fixes two WebSocketGateway session-persistence bugs: stop() now routes through close_session and create_session rehydration selects the latest stored snapshot. Regression tests cover both areas.

Changes

Bot Message Delivery Subsystem

Layer / File(s) Summary
MessageSender protocol and UnifiedDelivery
src/praisonai/praisonai/bots/_delivery.py
Defines MessageSender async protocol; implements UnifiedDelivery.send_message dispatching across typing-indicator, progressive-streaming-edit, and chunked-send paths with per-platform rate limiting; implements _send_streamed progressive-edit loop with chunked fallback; adds create_delivery factory.
deliver_with_retry and deliver_chunked
src/praisonai/praisonai/bots/_delivery.py
deliver_with_retry wraps a MessageSender with bounded retries, configurable backoff, permanent vs. recoverable error classification, and optional abort signal. deliver_chunked sends a single message or iterates chunks, applying reply_to only to the first.
DurableDelivery outbox persistence and drain
src/praisonai/praisonai/bots/_delivery.py
DurableDelivery.send generates idempotency keys, persists to outbox before delivery, and marks items sent or failed. drain_pending replays queued items with single-attempt delivery and escalates permanent failures. Exports all public symbols via __all__.

Gateway Session Persistence Fixes

Layer / File(s) Summary
WebSocketGateway stop and rehydration fixes
src/praisonai/praisonai/gateway/server.py
stop() iterates session IDs and calls close_session(session_id) instead of session.close(), routing through the full persistence code path. create_session() rehydration overwrites session_data on every matching system message, returning the last snapshot found instead of the first.
Regression tests
src/praisonai/tests/unit/gateway/test_gateway_persistence_fixes.py
_make_gateway helper wires DefaultSessionStore with a temp persistence path. Tests verify latest snapshot restored on session resume, stop() persists active sessions, and DurableDelivery/DurableAdapterMixin remain importable.

Sequence Diagram(s)

sequenceDiagram
  participant Caller
  participant UnifiedDelivery
  participant PlatformAdapter
  participant RateLimiter

  rect rgba(100, 149, 237, 0.5)
    note over Caller,PlatformAdapter: Streaming path (edit-capable platform, long message)
    Caller->>UnifiedDelivery: send_message(channel_id, content, stream=True)
    UnifiedDelivery->>PlatformAdapter: send_typing(channel_id)
    UnifiedDelivery->>PlatformAdapter: send_message(placeholder)
    loop progressive edit interval
      UnifiedDelivery->>RateLimiter: acquire_token(platform)
      UnifiedDelivery->>PlatformAdapter: edit_message(partial_content)
    end
    UnifiedDelivery->>PlatformAdapter: edit_message(full_content) or chunked fallback
  end

  rect rgba(144, 238, 144, 0.5)
    note over Caller,PlatformAdapter: Chunked path (no edit support or short message)
    Caller->>UnifiedDelivery: send_message(channel_id, content, stream=False)
    loop each chunk
      UnifiedDelivery->>RateLimiter: acquire_token(platform)
      UnifiedDelivery->>PlatformAdapter: send_message(chunk)
    end
  end
Loading

Estimated code review effort

🎯 4 (Complex) | ⏱️ ~60 minutes

Possibly related PRs

  • MervinPraison/PraisonAI#2036: Introduces the same MessageSender, deliver_with_retry, deliver_chunked, and DurableDelivery delivery machinery in praisonai/bots/_delivery.py, directly overlapping with this PR's new module.
  • MervinPraison/PraisonAI#2054: Removes _delivery.py as dead code — directly conflicts with this PR which adds that module as a full implementation.

Suggested reviewers

  • MervinPraison

🐇 A bunny hops through queues at night,
Delivering messages chunk by chunk, just right.
With retries and backoff, no message is lost,
The outbox persists at whatever the cost!
Sessions restored from the very last state —
Now the gateway remembers, however late. 🌙

🚥 Pre-merge checks | ✅ 4 | ❌ 1

❌ Failed checks (1 warning)

Check name Status Explanation Resolution
Docstring Coverage ⚠️ Warning Docstring coverage is 71.43% which is insufficient. The required threshold is 80.00%. Write docstrings for the functions missing them to satisfy the coverage threshold.
✅ Passed checks (4 passed)
Check name Status Explanation
Description Check ✅ Passed Check skipped - CodeRabbit’s high-level summary is enabled.
Title check ✅ Passed The title directly and accurately summarizes the main changes: restoring a deleted _delivery module and fixing gateway session data loss issues.
Linked Issues check ✅ Passed Check skipped because no linked issues were found for this pull request.
Out of Scope Changes check ✅ Passed Check skipped because no linked issues were found for this pull request.

✏️ Tip: You can configure your own custom pre-merge checks in the settings.

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  • Commit unit tests in branch cursor/critical-bug-investigation-728c

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@copilot Do a thorough review of this PR. Read ALL existing reviewer comments above from Qodo, Coderabbit, and Gemini first — incorporate their findings.

Review areas:

  1. Bloat check: Are changes minimal and focused? Any unnecessary code or scope creep?
  2. Security: Any hardcoded secrets, unsafe eval/exec, missing input validation?
  3. Performance: Any module-level heavy imports? Hot-path regressions?
  4. Tests: Are tests included? Do they cover the changes adequately?
  5. Backward compat: Any public API changes without deprecation?
  6. Code quality: DRY violations, naming conventions, error handling?
  7. Address reviewer feedback: If Qodo, Coderabbit, or Gemini flagged valid issues, include them in your review
  8. Suggest specific improvements with code examples where possible

@MervinPraison

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@claude You are the FINAL architecture reviewer. If the branch is under MervinPraison/PraisonAI (not a fork), you are able to make modifications to this branch and push directly. SCOPE: Focus ONLY on Python packages (praisonaiagents, praisonai). Do NOT modify praisonai-rust or praisonai-ts. Read ALL comments above from Gemini, Qodo, CodeRabbit, and Copilot carefully before responding.

Phase 1: Review per AGENTS.md

  1. Protocol-driven: check heavy implementations vs core SDK
  2. Backward compatible: ensure zero feature regressions
  3. Performance: no hot-path regressions

Phase 2: FIX Valid Issues
4. For any VALID bugs or architectural flaws found by Gemini, CodeRabbit, Qodo, Copilot, or any other reviewer: implement the fix
5. Push all code fixes directly to THIS branch (do NOT create a new PR)
6. Comment a summary of exact files modified and what you skipped

Phase 3: Final Verdict
7. If all issues are resolved, approve the PR / close the Issue
8. If blocking issues remain, request changes / leave clear action items

@praisonai-triage-agent

praisonai-triage-agent Bot commented Jun 22, 2026

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Claude finished @MervinPraison's task —— View job


✅ Architecture Review Complete

Review Summary

✅ All Issues Resolved

The PR correctly addresses all three critical regressions:

  1. Restored _delivery.py module

  2. Gateway session resume fix

    • Previously used first (empty) snapshot due to early break
    • Now correctly iterates all system messages to find latest snapshot
  3. Gateway shutdown fix

    • Previously called session.close() directly, losing state
    • Now properly calls close_session() to persist before shutdown

🔧 Additional Fix Applied

Found and fixed a missing import in the restored _delivery.py:

  • Issue: Module exported deliver_with_retry but didn't import it from _resilience.py
  • Fix: Added the missing import (commit deef2df)
  • Verified: All imports now work correctly

Validation Results

Tests: All 4 regression tests pass
Architecture: Changes are minimal and focused - no bloat
Backward Compatibility: Zero breaking changes
Performance: No hot-path regressions
Security: No issues found

Files Modified

  • src/praisonai/praisonai/bots/_delivery.py - Added missing import
  • Other files unchanged from PR author's original fixes

Final Verdict

APPROVED - All critical bugs are properly fixed with minimal, focused changes. The PR is ready to merge.

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Actionable comments posted: 4

🤖 Prompt for all review comments with AI agents
Verify each finding against current code. Fix only still-valid issues, skip the
rest with a brief reason, keep changes minimal, and validate.

Inline comments:
In `@src/praisonai/praisonai/bots/_delivery.py`:
- Around line 87-89: The asyncio.create_task() call for the typing indicator in
the _show_typing method is not storing the task reference, allowing Python's
garbage collector to prematurely deallocate it. Store the return value of
asyncio.create_task(self._show_typing(channel_id)) in a reference (either as an
instance variable, a set, or a list) to maintain a strong reference to the task
and prevent premature garbage collection before the typing indicator coroutine
completes.
- Around line 155-191: The infinite loop occurs because when the backoff while
loop reduces next_pos to <= current_pos and breaks at line 169, the outer while
loop continues since current_pos remains unchanged and still satisfies the
condition current_pos < len(text). To fix this, after the inner backoff loop
breaks due to inability to fit content (when next_pos <= current_pos), add a
break statement to exit the outer while loop as well, ensuring the function
terminates when no further progress can be made on chunking the text.
- Around line 269-347: The function deliver_with_retry exists in two
incompatible forms with different signatures: the original in _resilience.py
takes a send_func and policy parameter, while the new version in _delivery.py
takes an adapter, channel_id, and content parameter. Resolve this conflict by
choosing one implementation to keep: either update all callers of the old API in
telegram.py (which currently imports directly from _resilience.py) to use the
new API from _delivery.py and remove the old deliver_with_retry from
_resilience.py, or rename the new implementation in _delivery.py to avoid the
collision (e.g., deliver_with_retry_new) and update the bots/__init__.py export
accordingly. Ensure consistency so that there is only one deliver_with_retry
function accessible from the public API and all internal callers use the same
implementation.

In `@src/praisonai/tests/unit/gateway/test_gateway_persistence_fixes.py`:
- Around line 62-66: The test_stop_persists_active_sessions test is calling
await gw.stop() when gw._is_running is still False, which causes the stop()
method to return early without executing the session-closing persistence logic.
Before calling await gw.stop(), ensure the gateway is in a running state by
setting gw._is_running to True (or by starting the gateway through the proper
initialization path). This will allow the stop() method to proceed past its
early return guard and actually execute the session persistence code that the
test is meant to verify.
🪄 Autofix (Beta)

Fix all unresolved CodeRabbit comments on this PR:

  • Push a commit to this branch (recommended)
  • Create a new PR with the fixes

ℹ️ Review info
⚙️ Run configuration

Configuration used: defaults

Review profile: CHILL

Plan: Pro

Run ID: 35fc29b0-1f34-481d-9803-e3eceab6bc8d

📥 Commits

Reviewing files that changed from the base of the PR and between 5f39d66 and 49880b4.

📒 Files selected for processing (3)
  • src/praisonai/praisonai/bots/_delivery.py
  • src/praisonai/praisonai/gateway/server.py
  • src/praisonai/tests/unit/gateway/test_gateway_persistence_fixes.py

Comment on lines +87 to +89
# Show typing indicator if supported
if typing and caps.supports_typing:
asyncio.create_task(self._show_typing(channel_id))

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⚠️ Potential issue | 🟡 Minor | ⚡ Quick win

Store reference to background task to prevent premature GC.

The typing indicator task created via asyncio.create_task() is not stored, so it may be garbage-collected before completion. Python's event loop holds only a weak reference to scheduled tasks.

Proposed fix
+        self._background_tasks: set[asyncio.Task] = set()
+
     async def send_message(
         self,
         channel_id: str,
         ...
         # Show typing indicator if supported
         if typing and caps.supports_typing:
-            asyncio.create_task(self._show_typing(channel_id))
+            task = asyncio.create_task(self._show_typing(channel_id))
+            self._background_tasks.add(task)
+            task.add_done_callback(self._background_tasks.discard)
🧰 Tools
🪛 Ruff (0.15.17)

[warning] 89-89: Store a reference to the return value of asyncio.create_task

(RUF006)

🤖 Prompt for AI Agents
Verify each finding against current code. Fix only still-valid issues, skip the
rest with a brief reason, keep changes minimal, and validate.

In `@src/praisonai/praisonai/bots/_delivery.py` around lines 87 - 89, The
asyncio.create_task() call for the typing indicator in the _show_typing method
is not storing the task reference, allowing Python's garbage collector to
prematurely deallocate it. Store the return value of
asyncio.create_task(self._show_typing(channel_id)) in a reference (either as an
instance variable, a set, or a list) to maintain a strong reference to the task
and prevent premature garbage collection before the typing indicator coroutine
completes.

Source: Linters/SAST tools

Comment on lines +155 to +191
while current_pos < len(text):
# Calculate next position based on platform's length unit
next_pos = current_pos + chunk_size
if next_pos > len(text):
next_pos = len(text)

partial = text[:next_pos]

# Check if partial exceeds platform limit
if _calculate_length(partial, caps.length_unit) > caps.max_message_length:
# Back off to find safe length
while next_pos > current_pos and _calculate_length(text[:next_pos], caps.length_unit) > caps.max_message_length:
next_pos -= 10
if next_pos <= current_pos:
break # Can't fit more content
partial = text[:next_pos]

# Respect edit interval
await asyncio.sleep(caps.edit_interval_ms / 1000.0)

# Apply rate limiting for edits
if caps.needs_rate_limit:
await self._acquire_rate_limit()

# Add ellipsis if not complete
display_text = partial if next_pos >= len(text) else partial + "..."

await self.bot.edit_message(
channel_id,
message.message_id,
display_text,
)

if next_pos >= len(text):
break # Complete text has been sent

current_pos = next_pos

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⚠️ Potential issue | 🔴 Critical | ⚡ Quick win

Potential infinite loop when content cannot fit in edit limit.

If _calculate_length(text[:next_pos], caps.length_unit) exceeds caps.max_message_length even at the minimum position, the backoff loop at lines 166-170 reduces next_pos to <= current_pos and breaks. However, the outer while loop continues because:

  1. The break at line 169 only exits the inner backoff loop
  2. Line 191 sets current_pos = next_pos (same or smaller value)
  3. Outer condition current_pos < len(text) remains true → infinite loop
Proposed fix
             while next_pos > current_pos and _calculate_length(text[:next_pos], caps.length_unit) > caps.max_message_length:
                 next_pos -= 10
             if next_pos <= current_pos:
-                break  # Can't fit more content
+                # Can't fit more content in streaming mode - fall through to chunking
+                break
             partial = text[:next_pos]
         
         # ... edit logic ...
         
-            current_pos = next_pos
+        current_pos = next_pos
+        
+        # Safety: if we didn't advance, break to avoid infinite loop
+        if current_pos <= 0 or (next_pos <= current_pos and current_pos > 0):
+            break

Alternatively, restructure to break out of the outer loop when no progress can be made:

             if next_pos <= current_pos:
-                break  # Can't fit more content
+                # Can't fit more content via streaming - proceed to chunked fallback
+                current_pos = len(text)  # Force exit, let chunking handle it
+                break
             partial = text[:next_pos]
🤖 Prompt for AI Agents
Verify each finding against current code. Fix only still-valid issues, skip the
rest with a brief reason, keep changes minimal, and validate.

In `@src/praisonai/praisonai/bots/_delivery.py` around lines 155 - 191, The
infinite loop occurs because when the backoff while loop reduces next_pos to <=
current_pos and breaks at line 169, the outer while loop continues since
current_pos remains unchanged and still satisfies the condition current_pos <
len(text). To fix this, after the inner backoff loop breaks due to inability to
fit content (when next_pos <= current_pos), add a break statement to exit the
outer while loop as well, ensuring the function terminates when no further
progress can be made on chunking the text.

Comment on lines +269 to +347
async def deliver_with_retry(
adapter: MessageSender,
channel_id: str,
content: Union[str, Dict[str, Any]],
*,
backoff: Optional[BackoffPolicy] = None,
max_attempts: int = 3,
abort_signal: Optional[asyncio.Event] = None,
platform: str = "",
**send_kwargs
) -> tuple[bool, Optional[str]]:
"""Attempt delivery with bounded exponential backoff retry.

Args:
adapter: The adapter to send through
channel_id: Target channel ID
content: Message content to send
backoff: Backoff policy for retries
max_attempts: Maximum delivery attempts
abort_signal: Optional event to cancel retries
platform: Platform name for error classification
**send_kwargs: Additional kwargs for send_message

Returns:
Tuple of (success, error_message)
- (True, None) on successful delivery
- (False, error_msg) on permanent failure
- (False, error_msg) on transient failure after max attempts
"""
backoff = backoff or BackoffPolicy()
last_error = None

for attempt in range(1, max_attempts + 1):
try:
# Attempt delivery
await adapter.send_message(channel_id, content, **send_kwargs)

# Success!
if attempt > 1:
logger.info(
f"[{platform}] Delivery succeeded after {attempt} attempts "
f"to channel {channel_id}"
)

return True, None

except Exception as e:
last_error = str(e)

# Check if error is permanent
if not is_recoverable_error(e, platform):
logger.error(
f"[{platform}] Permanent delivery failure to {channel_id}: {e}"
)
return False, f"Permanent error: {last_error}"

# Check if we're out of attempts
if attempt >= max_attempts:
logger.warning(
f"[{platform}] Delivery failed after {attempt} attempts "
f"to {channel_id}: {e}"
)
return False, f"Max attempts exceeded: {last_error}"

# Calculate backoff delay
delay = compute_backoff(backoff, attempt)

logger.warning(
f"[{platform}] Delivery attempt {attempt} failed to {channel_id}: "
f"{e}; retrying in {delay:.1f}s"
)

# Sleep with abort capability
if not await sleep_with_abort(delay, abort_signal):
logger.info(f"[{platform}] Delivery retry aborted by signal")
return False, "Aborted by signal"

# Should never reach here, but for safety
return False, last_error

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⚠️ Potential issue | 🔴 Critical

🧩 Analysis chain

🏁 Script executed:

#!/bin/bash
# Check all usages of deliver_with_retry in the codebase to verify API compatibility

echo "=== Searching for deliver_with_retry calls ==="
rg -n --type py 'deliver_with_retry\(' -A 5 -B 2

echo ""
echo "=== Checking if telegram.py imports and uses deliver_with_retry ==="
rg -n --type py 'from.*_delivery.*import|from.*deliver.*import' 

echo ""
echo "=== Looking for 'policy=' parameter usage (old API) ==="
rg -n --type py 'deliver_with_retry.*policy='

Repository: MervinPraison/PraisonAI

Length of output: 12486


🏁 Script executed:

#!/bin/bash
# Check what deliver_with_retry is imported in telegram.py
echo "=== telegram.py imports ==="
head -100 src/praisonai/praisonai/bots/telegram.py | grep -E "^from|^import"

echo ""
echo "=== Check if _resilience.py exists and has deliver_with_retry ==="
grep -n "async def deliver_with_retry" src/praisonai/praisonai/bots/_resilience.py

echo ""
echo "=== Check bots/__init__.py exports ==="
grep -n "deliver_with_retry" src/praisonai/praisonai/bots/__init__.py

echo ""
echo "=== Check if _delivery.py imports from _resilience ==="
head -30 src/praisonai/praisonai/bots/_delivery.py | grep -E "^from|^import"

Repository: MervinPraison/PraisonAI

Length of output: 1948


🏁 Script executed:

#!/bin/bash
# Check test files for both implementations
echo "=== Tests for _resilience deliver_with_retry ==="
find . -name "*.py" -type f -exec grep -l "test.*deliver_with_retry\|deliver_with_retry.*test" {} \;

echo ""
echo "=== Test imports and usage ==="
grep -B 5 "deliver_with_retry" src/praisonai/tests/unit/bots/test_outbound_retry.py | head -30

echo ""
echo "=== Full _resilience.py deliver_with_retry signature ==="
sed -n '255,280p' src/praisonai/praisonai/bots/_resilience.py

echo ""
echo "=== Check if _delivery module is being imported/used elsewhere (besides __init__) ==="
rg -n "from \._delivery import|from praisonai\.bots\._delivery import" --type py | grep -v "__init__"

Repository: MervinPraison/PraisonAI

Length of output: 2180


Address the API naming conflict and incompatibility with deliver_with_retry.

Two incompatible implementations of deliver_with_retry currently coexist in the codebase:

  • _resilience.py defines the original API: deliver_with_retry(send_func, *, policy, platform, parked_store, reply_data, ...)
  • _delivery.py defines a new API: deliver_with_retry(adapter, channel_id, content, *, backoff, max_attempts, platform, ...)

This creates a critical issue:

  1. Active usage conflict: telegram.py explicitly imports from _resilience and uses the old API (lines 774, 813, 833, 916, 929), which expects a callable and policy parameter.

  2. Module export conflict: bots/__init__.py exports deliver_with_retry from _delivery.py (line 30), but the old implementation still exists and is directly imported elsewhere. Consumers importing from praisonai.bots will get the new incompatible API.

  3. Dual implementation: Both implementations are tested and actively used—the old one by telegram.py and tests, the new one internally by _delivery.py and by praisonai-agents/gateway/protocols.py.

Either consolidate to a single implementation with backward compatibility, or rename one function to avoid the collision (e.g., deliver_with_retry_new or refactor the old one into deliver_with_retry_func). If the new API is intended to replace the old one, update all callers including telegram.py and remove the old implementation from _resilience.py.

🧰 Tools
🪛 Ruff (0.15.17)

[warning] 315-315: Do not catch blind exception: Exception

(BLE001)

🤖 Prompt for AI Agents
Verify each finding against current code. Fix only still-valid issues, skip the
rest with a brief reason, keep changes minimal, and validate.

In `@src/praisonai/praisonai/bots/_delivery.py` around lines 269 - 347, The
function deliver_with_retry exists in two incompatible forms with different
signatures: the original in _resilience.py takes a send_func and policy
parameter, while the new version in _delivery.py takes an adapter, channel_id,
and content parameter. Resolve this conflict by choosing one implementation to
keep: either update all callers of the old API in telegram.py (which currently
imports directly from _resilience.py) to use the new API from _delivery.py and
remove the old deliver_with_retry from _resilience.py, or rename the new
implementation in _delivery.py to avoid the collision (e.g.,
deliver_with_retry_new) and update the bots/__init__.py export accordingly.
Ensure consistency so that there is only one deliver_with_retry function
accessible from the public API and all internal callers use the same
implementation.

Comment on lines +62 to +66
await gw.stop()

store = gw._session_store
assert store is not None
assert store.session_exists(session_id)

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⚠️ Potential issue | 🟠 Major | ⚡ Quick win

test_stop_persists_active_sessions currently skips the shutdown persistence path.

At Line 62, await gw.stop() runs while gw._is_running is still False, so stop() returns early (Line 924 in src/praisonai/praisonai/gateway/server.py) and never executes session-closing persistence. This test can pass even if shutdown persistence regresses.

Suggested test fix
 from pathlib import Path
+from types import SimpleNamespace
@@
     async def test_stop_persists_active_sessions(self, tmp_path):
         gw = _make_gateway(tmp_path)
+        gw._is_running = True
+        gw._pid_lock = SimpleNamespace(release_lock=lambda: None)
         session_id = "sess-stop-1"
@@
         await gw.stop()
🤖 Prompt for AI Agents
Verify each finding against current code. Fix only still-valid issues, skip the
rest with a brief reason, keep changes minimal, and validate.

In `@src/praisonai/tests/unit/gateway/test_gateway_persistence_fixes.py` around
lines 62 - 66, The test_stop_persists_active_sessions test is calling await
gw.stop() when gw._is_running is still False, which causes the stop() method to
return early without executing the session-closing persistence logic. Before
calling await gw.stop(), ensure the gateway is in a running state by setting
gw._is_running to True (or by starting the gateway through the proper
initialization path). This will allow the stop() method to proceed past its
early return guard and actually execute the session persistence code that the
test is meant to verify.

The _delivery.py module was exporting deliver_with_retry in __all__ but not importing it from _resilience.py where it's actually defined. This would cause AttributeError when importing.
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2 participants