fix: carry Windows lock length through load() and correct conftest agents path

- load() now passes the acquired lock_length to _release_exclusive_lock so
  Windows unlocks the exact byte range it locked (max(file_size,1)), fixing a
  release/lock mismatch on nonempty session files.
- conftest _agents_path now resolves to src/praisonai-agents (was pointing to a
  nonexistent repo-root praisonai-agents), fixing test collection on source
  checkouts. Corrected path comments.

Co-authored-by: Mervin Praison <[email protected]>

.github/scripts/release-gate-selftest.js

@@ -36,8 +36,10 @@ assert.strictEqual(dayStart.toISOString(), '2026-07-08T00:00:00.000Z');
       },
     },
   };
+  assert.strictEqual(rg.PATCH_RELEASE_INTERVAL_DAYS, 3);
+
   assert.strictEqual(
-    await rg.hasSuccessfulReleaseToday(mockGithub, 'o', 'r', noonUtc),
+    await rg.hasSuccessfulReleaseWithinDays(mockGithub, 'o', 'r', noonUtc),
     true
   );
 
@@ -46,12 +48,34 @@ assert.strictEqual(dayStart.toISOString(), '2026-07-08T00:00:00.000Z');
     { headSha: 'abc', isCiTrigger: false, bump: 'patch', now: noonUtc },
     null
   );
-  assert.ok(result.reasons.some((r) => r.includes('already released today')));
+  assert.ok(result.reasons.some((r) => r.includes('every 3 days')));
+
+  const oldReleaseGithub = {
+    rest: {
+      actions: {
+        listWorkflowRuns: async () => ({
+          data: {
+            workflow_runs: [
+              {
+                conclusion: 'success',
+                created_at: '2026-07-04T09:00:00Z',
+                status: 'completed',
+              },
+            ],
+          },
+        }),
+      },
+    },
+  };
+  assert.strictEqual(
+    await rg.hasSuccessfulReleaseWithinDays(oldReleaseGithub, 'o', 'r', noonUtc),
+    false
+  );
 
   console.log('ok: bumpPatch');
   console.log('ok: readVersionsFromTree');
   console.log('ok: pypiVersionExists missing version');
   console.log('ok: utcDayStart');
-  console.log('ok: hasSuccessfulReleaseToday');
-  console.log('ok: daily dedupe blocks second release');
+  console.log('ok: hasSuccessfulReleaseWithinDays');
+  console.log('ok: 3-day dedupe blocks second release');
 })();

.github/scripts/release-gate.js

@@ -5,6 +5,8 @@
 const https = require('https');
 
 const PACKAGE_PATHS = ['src/praisonai', 'src/praisonai-agents', 'src/praisonai-code'];
+/** Minimum days between successful patch auto-releases. */
+const PATCH_RELEASE_INTERVAL_DAYS = 3;
 const ACTIVE_RELEASE_STATUSES = new Set([
   'queued', 'in_progress', 'waiting', 'pending', 'requested',
 ]);
@@ -79,8 +81,18 @@ function utcDayStart(now = new Date()) {
   return new Date(Date.UTC(now.getUTCFullYear(), now.getUTCMonth(), now.getUTCDate()));
 }
 
-async function hasSuccessfulReleaseToday(github, owner, repo, now = new Date()) {
-  const dayStart = utcDayStart(now);
+function releaseIntervalStart(now = new Date(), intervalDays = PATCH_RELEASE_INTERVAL_DAYS) {
+  return new Date(now.getTime() - intervalDays * 24 * 60 * 60 * 1000);
+}
+
+async function hasSuccessfulReleaseWithinDays(
+  github,
+  owner,
+  repo,
+  now = new Date(),
+  intervalDays = PATCH_RELEASE_INTERVAL_DAYS,
+) {
+  const windowStart = releaseIntervalStart(now, intervalDays);
   const runs = await github.rest.actions.listWorkflowRuns({
     owner,
     repo,
@@ -89,10 +101,15 @@ async function hasSuccessfulReleaseToday(github, owner, repo, now = new Date())
     per_page: 30,
   });
   return runs.data.workflow_runs.some(
-    (r) => r.conclusion === 'success' && new Date(r.created_at) >= dayStart
+    (r) => r.conclusion === 'success' && new Date(r.created_at) >= windowStart
   );
 }
 
+/** @deprecated Use hasSuccessfulReleaseWithinDays — kept for selftests. */
+async function hasSuccessfulReleaseToday(github, owner, repo, now = new Date()) {
+  return hasSuccessfulReleaseWithinDays(github, owner, repo, now, 1);
+}
+
 async function lastGreenCoreTestsSha(github, owner, repo) {
   const runs = await github.rest.actions.listWorkflowRuns({
     owner,
@@ -135,9 +152,11 @@ async function evaluateReleasePreflight(github, owner, repo, options, core) {
   }
 
   const referenceTime = options.now instanceof Date ? options.now : new Date();
-  if (await hasSuccessfulReleaseToday(github, owner, repo, referenceTime)) {
-    const day = referenceTime.toISOString().slice(0, 10);
-    reasons.push(`already released today (UTC ${day}); max one patch release per day`);
+  if (await hasSuccessfulReleaseWithinDays(github, owner, repo, referenceTime)) {
+    reasons.push(
+      `already released within last ${PATCH_RELEASE_INTERVAL_DAYS} days; `
+      + `max one patch release every ${PATCH_RELEASE_INTERVAL_DAYS} days`
+    );
     return out;
   }
 
@@ -222,6 +241,9 @@ module.exports = {
   bumpPatch,
   readVersionsFromTree,
   pypiVersionExists,
+  PATCH_RELEASE_INTERVAL_DAYS,
+  releaseIntervalStart,
+  hasSuccessfulReleaseWithinDays,
   hasSuccessfulReleaseToday,
   utcDayStart,
   evaluateReleasePreflight,

.github/workflows/nightly-release-gate.yml

@@ -1,12 +1,12 @@
 name: Nightly Release Gate
 
 # Preflight before PyPI Release (patch bump).
-# Triggers: Core Tests success on main (workflow_run) or nightly cron at 00:00 UTC.
-# Dedupe: max one successful patch release per UTC day (see release-gate.js).
+# Triggers: Core Tests success on main (workflow_run) or cron every 3 days at 00:00 UTC.
+# Dedupe: max one successful patch release every 3 days (see release-gate.js).
 
 on:
   schedule:
-    - cron: '0 0 * * *'
+    - cron: '0 0 */3 * *'
   workflow_dispatch:
     inputs:
       dry_run:

.github/workflows/pypi-release.yml

@@ -134,7 +134,9 @@ jobs:
         'pypi-auto' || 'pypi'
       }}
     env:
-      UV_PUBLISH_TOKEN: ${{ secrets.PYPI_TOKEN || secrets.PYPI_API_TOKEN }}
+      # PyPI API token auth: username __token__, password = pypi-… token (see pypi.org/help/#invalid-auth)
+      UV_PUBLISH_USERNAME: __token__
+      UV_PUBLISH_PASSWORD: ${{ secrets.PYPI_TOKEN || secrets.PYPI_API_TOKEN }}
       GH_TOKEN: ${{ secrets.GH_TOKEN }}
     steps:
       - name: Checkout main

api.md

@@ -83,6 +83,7 @@ Methods:
 * <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">run_autonomous_async</a>(prompt: str, max_iterations: Optional[int] = None, timeout_seconds: Optional[float] = None, completion_promise: Optional[str] = None, clear_context: bool = False)</code>
 * <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">run_until</a>(prompt: str, criteria: str = '', threshold: float = 8.0, max_iterations: int = 5, mode: str = 'optimize', on_iteration: Optional[Callable[[Any], None]] = None, verbose: bool = False, goal: Optional[str] = None, goal_criteria: Optional[Any] = None, judge_model: Optional[str] = None) -> 'EvaluationLoopResult'</code>
 * <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">run_until_async</a>(prompt: str, criteria: str, threshold: float = 8.0, max_iterations: int = 5, mode: str = 'optimize', on_iteration: Optional[Callable[[Any], None]] = None, verbose: bool = False) -> 'EvaluationLoopResult'</code>
+* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">set_snapshot_root</a>(project_path: str) -> bool</code>
 * <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">skill_manager</a>() -> Optional[Any]</code>
 * <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">store_memory</a>(content: str, memory_type: str = 'short_term', action: str = 'add', **kwargs: Any) -> None</code>
 * <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">stream_emitter</a>() -> Optional[Any]</code>
@@ -568,6 +569,7 @@ Methods:
 * <code title="class MCP">MCP.<a href="./src/praisonai-agents/praisonaiagents/mcp/mcp.py">get_prompts</a>() -> List[dict]</code>
 * <code title="class MCP">MCP.<a href="./src/praisonai-agents/praisonaiagents/mcp/mcp.py">get_resources</a>() -> List[dict]</code>
 * <code title="class MCP">MCP.<a href="./src/praisonai-agents/praisonaiagents/mcp/mcp.py">get_tools</a>() -> List[Callable]</code>
+* <code title="class MCP">MCP.<a href="./src/praisonai-agents/praisonaiagents/mcp/mcp.py">list_active_server_names</a>() -> set</code>
 * <code title="class MCP">MCP.<a href="./src/praisonai-agents/praisonaiagents/mcp/mcp.py">shutdown</a>()</code>
 * <code title="class MCP">MCP.<a href="./src/praisonai-agents/praisonaiagents/mcp/mcp.py">to_openai_tool</a>()</code>
 * <code title="class MCP">MCP.<a href="./src/praisonai-agents/praisonaiagents/mcp/mcp.py">with_tool_prefix</a>(prefix: str) -> 'MCP'</code>
@@ -731,7 +733,7 @@ Methods:
 
 Types:
 ```python
-from praisonaiagents import AgentAppConfig, AgentAppProtocol, AgentFlow, AgentManager, AgentOSConfig, AgentOSProtocol, AgentTeam, AutoApproveBackend, EmbeddingResult, RetryBackoffConfig, __version__, aembedding, aembeddings, embedding, embeddings, get_dimensions
+from praisonaiagents import AgentAppConfig, AgentAppProtocol, AgentFlow, AgentManager, AgentOSConfig, AgentOSProtocol, AgentTeam, AutoApproveBackend, EmbeddingResult, RetryBackoffConfig, RunOutcome, __version__, aembedding, aembeddings, embedding, embeddings, get_dimensions
 ```
 
 Methods:
@@ -799,12 +801,16 @@ Methods:
 * <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">set_state</a>(key: str, value: Any) -> None</code>
 * <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">spawn_sub_agent</a>(agent: Agent, task: Any, completion_callback: Optional[Callable[[SubAgentCompletionEvent], Any]] = None, metadata: Optional[Dict[str, Any]] = None) -> SpawnedSubAgent</code>
 * <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">start</a>(content = None, return_dict = False, output = None, **kwargs)</code>
+* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">stream_emitter</a>()</code>
 * <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">todo_list</a>()</code>
 * <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">update_plan_step_status</a>(step_id: str, status: str) -> bool</code>
 * <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">update_state</a>(updates: Dict) -> None</code>
 * <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">wait_for_completions</a>(timeout: Optional[float] = None, agent_ids: Optional[List[str]] = None) -> List[SubAgentCompletionEvent]</code>
 * <code title="class AutoApproveBackend">AutoApproveBackend.<a href="./src/praisonai-agents/praisonaiagents/approval/backends.py">request_approval</a>(request: ApprovalRequest) -> ApprovalDecision</code>
 * <code title="class AutoApproveBackend">AutoApproveBackend.<a href="./src/praisonai-agents/praisonaiagents/approval/backends.py">request_approval_sync</a>(request: ApprovalRequest) -> ApprovalDecision</code>
+* <code title="class RunOutcome">RunOutcome.<a href="./src/praisonai-agents/praisonaiagents/agent/run_outcome.py">completed</a>(output: Optional[str] = None) -> 'RunOutcome'</code>
+* <code title="class RunOutcome">RunOutcome.<a href="./src/praisonai-agents/praisonaiagents/agent/run_outcome.py">from_exception</a>(exc: BaseException, output: Optional[str] = None) -> 'RunOutcome'</code>
+* <code title="class RunOutcome">RunOutcome.<a href="./src/praisonai-agents/praisonaiagents/agent/run_outcome.py">succeeded</a>() -> bool</code>
 * <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/embedding/embed.py">aembedding</a>(input: Union[str, List[str]], model: str = 'text-embedding-3-small', dimensions: Optional[int] = None, encoding_format: str = 'float', timeout: float = 600.0, api_key: Optional[str] = None, api_base: Optional[str] = None, metadata: Optional[Dict[str, Any]] = None, **kwargs) -> EmbeddingResult</code>
 * <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/embedding/embed.py">aembeddings</a>(input: Union[str, List[str]], model: str = 'text-embedding-3-small', dimensions: Optional[int] = None, encoding_format: str = 'float', timeout: float = 600.0, api_key: Optional[str] = None, api_base: Optional[str] = None, metadata: Optional[Dict[str, Any]] = None, **kwargs) -> EmbeddingResult</code>
 * <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/embedding/dimensions.py">get_dimensions</a>(model_name: str) -> int</code>

docker/Dockerfile.chat

@@ -16,7 +16,7 @@ RUN mkdir -p /root/.praison
 # Install Python packages (using latest versions)
 RUN pip install --no-cache-dir \
     praisonai_tools \
-    "praisonai>=4.6.155" \
+    "praisonai>=4.6.157" \
     "praisonai[chat]" \
     "embedchain[github,youtube]"
 

docker/Dockerfile.dev

@@ -20,7 +20,7 @@ RUN mkdir -p /root/.praison
 # Install Python packages (using latest versions)
 RUN pip install --no-cache-dir \
     praisonai_tools \
-    "praisonai>=4.6.155" \
+    "praisonai>=4.6.157" \
     "praisonai[ui]" \
     "praisonai[chat]" \
     "praisonai[realtime]" \

docker/Dockerfile.ui

@@ -16,7 +16,7 @@ RUN mkdir -p /root/.praison
 # Install Python packages (using latest versions)
 RUN pip install --no-cache-dir \
     praisonai_tools \
-    "praisonai>=4.6.155" \
+    "praisonai>=4.6.157" \
     "praisonai[ui]" \
     "praisonai[crewai]"
 

examples/python/api/simple-mcp-server.py

@@ -1,5 +1,15 @@
+import threading
+import time
+
 from praisonaiagents import Agent
 
+
 if __name__ == "__main__":
     agent = Agent(name="TweetAgent", instructions="Create a Tweet based on the topic provided")
-    agent.launch(port=8080, protocol="mcp", path="/mcp")
+    server = threading.Thread(
+        target=lambda: agent.launch(port=8080, protocol="mcp", path="/mcp"),
+        daemon=True,
+    )
+    server.start()
+    time.sleep(2)
+    print("MCP server started on http://127.0.0.1:8080/mcp")

examples/python/concepts/knowledge-reranker-example.py

@@ -150,7 +150,7 @@ def main():
     agent = Agent(
         name="AI Research Assistant",
         instructions="You are an AI research assistant. Use your knowledge base to answer questions about artificial intelligence topics.",
-        knowledge={**rerank_config, "sources": sample_documents},
+        knowledge={"sources": sample_documents, "rerank": True},
         llm="gpt-4o-mini"
     )
     

examples/python/memory/advanced-graph-memory-integration.py

@@ -67,6 +67,7 @@ agents_system = AgentTeam(
 print("Starting graph memory demonstration...")
 result = agents_system.start()
 
-print(f"\nGraph Memory Result: {result[:200]}...")
+result_text = str(result) if result is not None else ""
+print(f"\nGraph Memory Result: {result_text[:200]}...")
 print("\n✅ Graph memory integration complete!")
 print("Agent built knowledge graph and performed relationship-aware queries.")

examples/terminal_bench/test_basic.py

@@ -14,18 +14,18 @@ def test_imports():
     """Test that all required modules can be imported."""
     try:
         from praisonaiagents import Agent
-        print("✅ Agent imported successfully")
+        print("[OK] Agent imported successfully")
         
         from praisonaiagents.tools import execute_command
-        print("✅ execute_command tool imported successfully")
+        print("[OK] execute_command tool imported successfully")
         
         from praisonaiagents.approval import get_approval_registry, AutoApproveBackend
-        print("✅ Approval system imported successfully")
+        print("[OK] Approval system imported successfully")
         
         return True
         
     except ImportError as e:
-        print(f"❌ Import failed: {e}")
+        print(f"[FAIL] Import failed: {ascii(e)}")
         return False
 
 def test_agent_creation():
@@ -40,11 +40,11 @@ def test_agent_creation():
         )
         
         assert agent.name == 'test-agent'
-        print("✅ Agent creation successful")
+        print("[OK] Agent creation successful")
         return True
         
     except Exception as e:
-        print(f"❌ Agent creation failed: {e}")
+        print(f"[FAIL] Agent creation failed: {ascii(e)}")
         return False
 
 def test_approval_system():
@@ -55,11 +55,11 @@ def test_approval_system():
         registry = get_approval_registry()
         registry.set_backend(AutoApproveBackend())
         
-        print("✅ Approval system configuration successful")
+        print("[OK] Approval system configuration successful")
         return True
         
     except Exception as e:
-        print(f"❌ Approval system test failed: {e}")
+        print(f"[FAIL] Approval system test failed: {ascii(e)}")
         return False
 
 def test_external_agent_import():
@@ -80,11 +80,11 @@ def test_external_agent_import():
         
         # Now try to import our agent
         import praisonai_external_agent
-        print("✅ External agent import successful")
+        print("[OK] External agent import successful")
         return True
         
     except Exception as e:
-        print(f"❌ External agent import failed: {e}")
+        print(f"[FAIL] External agent import failed: {ascii(e)}")
         return False
 
 def test_multi_agent_import():
@@ -104,11 +104,11 @@ def test_multi_agent_import():
         sys.modules['harbor.models.agent.context'] = MagicMock()
         
         import multi_agent_example
-        print("✅ Multi-agent example import successful")
+        print("[OK] Multi-agent example import successful")
         return True
         
     except Exception as e:
-        print(f"❌ Multi-agent example import failed: {e}")
+        print(f"[FAIL] Multi-agent example import failed: {ascii(e)}")
         return False
 
 def test_wrapper_agent_import():
@@ -128,11 +128,11 @@ def test_wrapper_agent_import():
         sys.modules['harbor.models.agent.context'] = MagicMock()
         
         import praisonai_wrapper_agent
-        print("✅ Wrapper agent import successful (CLI-based approach)")
+        print("[OK] Wrapper agent import successful (CLI-based approach)")
         return True
         
     except Exception as e:
-        print(f"❌ Wrapper agent import failed: {e}")
+        print(f"[FAIL] Wrapper agent import failed: {ascii(e)}")
         return False
 
 if __name__ == "__main__":
@@ -152,19 +152,19 @@ if __name__ == "__main__":
     total = len(tests)
     
     for test_name, test_func in tests:
-        print(f"\n🧪 Testing {test_name}...")
+        print(f"\n[TEST] {test_name}...")
         try:
             if test_func():
                 passed += 1
         except Exception as e:
-            print(f"❌ Test {test_name} crashed: {e}")
+            print(f"[FAIL] Test {test_name} crashed: {ascii(e)}")
     
     print("\n" + "=" * 55)
     print(f"Results: {passed}/{total} tests passed")
     
     if passed == total:
-        print("🎉 ALL BASIC TESTS PASSED!")
+        print("[OK] ALL BASIC TESTS PASSED!")
         print("The Terminal-Bench integration components are properly structured.")
     else:
-        print("❌ Some tests failed - check output above")
+        print("[FAIL] Some tests failed - check output above")
         sys.exit(1)

examples/tools/external/hackernews/tool.py

@@ -30,9 +30,11 @@ def main():
     else:
         print(f"Found {len(stories)} top stories:")
         for story in stories:
-            print(f"  - {story.get('title', 'N/A')[:50]}...")
+            title = story.get("title") or "N/A"
+            url = story.get("url") or "N/A"
+            print(f"  - {title[:50]}...")
             print(f"    Score: {story.get('score', 'N/A')} | Comments: {story.get('descendants', 'N/A')}")
-            print(f"    URL: {story.get('url', 'N/A')[:60]}...")
+            print(f"    URL: {url[:60]}...")
             print()
     
     print("✅ Hacker News tool working correctly!")

src/praisonai-agents/DOCS_PARITY.md

@@ -18,39 +18,39 @@ This report compares **Python SDK feature categories** against **Python document
 | Category | Features | Docs | Lines |
 |----------|----------|------|-------|
 | ✅ AGUI | 1 | 2 | 420 |
-| ✅ Agent | 21 | 46 | 14657 |
+| ✅ Agent | 21 | 46 | 14663 |
 | ✅ Agent-to-Agent (A2A) | 1 | 7 | 2965 |
 | ✅ Agent-to-User (A2U) | 1 | 3 | 585 |
 | ✅ Approval | 1 | 5 | 2312 |
 | ✅ Audio | 2 | 12 | 1000 |
 | ✅ Auto Generation | 5 | 10 | 2880 |
 | ✅ Autonomy | 3 | 7 | 2707 |
-| ✅ Bots | 7 | 29 | 11795 |
+| ✅ Bots | 7 | 31 | 12353 |
 | ✅ Budget | 1 | 1 | 287 |
-| ✅ CLI | 5 | 119 | 34087 |
+| ✅ CLI | 5 | 119 | 34537 |
 | ✅ Chunking | 2 | 2 | 385 |
 | ✅ Citations | 2 | 1 | 202 |
 | ✅ Code Execution | 2 | 13 | 4031 |
 | ✅ Conditions | 1 | 3 | 1179 |
-| ✅ Configuration | 3 | 7 | 2772 |
-| ✅ Context Management | 16 | 34 | 13204 |
+| ✅ Configuration | 3 | 7 | 2773 |
+| ✅ Context Management | 16 | 34 | 13206 |
 | ✅ Deep Research | 8 | 2 | 587 |
 | ✅ Display | 6 | 3 | 741 |
 | ✅ Embeddings | 6 | 23 | 2049 |
 | ✅ Evaluation | 1 | 7 | 2905 |
 | ✅ Events | 1 | 2 | 749 |
-| ✅ Execution | 3 | 4 | 1528 |
+| ✅ Execution | 3 | 4 | 1560 |
 | ✅ Failover | 2 | 1 | 400 |
-| ✅ Files | 2 | 6 | 1964 |
+| ✅ Files | 2 | 6 | 2066 |
 | ✅ Flow | 1 | 3 | 777 |
-| ✅ Gateway | 7 | 56 | 20195 |
+| ✅ Gateway | 7 | 59 | 21584 |
 | ✅ Guardrails | 4 | 4 | 1673 |
 | ✅ Handoffs | 11 | 6 | 2454 |
 | ✅ Hooks | 2 | 9 | 4128 |
 | ✅ Image | 1 | 11 | 1255 |
 | ✅ Knowledge | 4 | 13 | 4160 |
 | ✅ LLM | 3 | 14 | 4864 |
-| ✅ Loops | 4 | 4 | 1202 |
+| ✅ Loops | 4 | 5 | 1422 |
 | ✅ MCP | 1 | 58 | 13322 |
 | ✅ Memory | 6 | 17 | 6635 |
 | ✅ OCR | 2 | 1 | 237 |
@@ -60,7 +60,7 @@ This report compares **Python SDK feature categories** against **Python document
 | ✅ Parallel Execution | 3 | 2 | 497 |
 | ✅ Planning | 6 | 6 | 1545 |
 | ✅ Plugins | 8 | 3 | 1900 |
-| ✅ Prompts | 2 | 9 | 1913 |
+| ✅ Prompts | 2 | 9 | 1965 |
 | ✅ Providers | 1 | 55 | 7502 |
 | ✅ Query | 1 | 2 | 736 |
 | ✅ RAG | 5 | 15 | 2936 |
@@ -68,14 +68,14 @@ This report compares **Python SDK feature categories** against **Python document
 | ✅ Reflection | 3 | 3 | 680 |
 | ✅ Retrieval | 2 | 5 | 1044 |
 | ✅ Routing | 1 | 2 | 430 |
-| ✅ Sandbox | 5 | 6 | 2700 |
+| ✅ Sandbox | 5 | 6 | 2766 |
 | ✅ Security | 1 | 3 | 2970 |
-| ✅ Sessions | 4 | 13 | 5286 |
-| ✅ Skills | 6 | 13 | 4946 |
-| ✅ Tasks | 2 | 6 | 2743 |
+| ✅ Sessions | 4 | 13 | 5302 |
+| ✅ Skills | 6 | 13 | 4998 |
+| ✅ Tasks | 2 | 6 | 2809 |
 | ✅ Telemetry | 1 | 2 | 604 |
-| ✅ Templates | 1 | 8 | 1657 |
-| ✅ Tools | 12 | 133 | 37934 |
+| ✅ Templates | 1 | 8 | 1663 |
+| ✅ Tools | 12 | 133 | 38149 |
 | ✅ Tracing | 3 | 2 | 139 |
 | ✅ Vector Store | 1 | 12 | 1193 |
 | ✅ Video | 2 | 6 | 649 |
@@ -87,7 +87,7 @@ This report compares **Python SDK feature categories** against **Python document
 
 These docs exist but don't match any implemented feature category:
 
-- ℹ️ Database (40 docs, 6184 lines)
+- ℹ️ Database (41 docs, 6478 lines)
 - ℹ️ Documents (1 docs, 787 lines)
 
 ---

src/praisonai-agents/praisonaiagents/__init__.py

@@ -258,6 +258,7 @@ _LAZY_IMPORTS = {
     
     # Agent classes
     'Agent': ('praisonaiagents.agent.agent', 'Agent'),
+    'RunOutcome': ('praisonaiagents.agent.run_outcome', 'RunOutcome'),
     'RetryBackoffConfig': ('praisonaiagents.agent.retry_utils', 'RetryBackoffConfig'),
     'BudgetExceededError': ('praisonaiagents.errors', 'BudgetExceededError'),
     
@@ -838,6 +839,7 @@ __all__ = [
     
     # Core classes - the essentials
     'Agent',
+    'RunOutcome',
     'RetryBackoffConfig',
     'AgentTeam',  # Primary class for multi-agent coordination (v1.0+)
     'AgentManager',  # Silent alias for AgentTeam

src/praisonai-agents/praisonaiagents/_logging.py

@@ -4,7 +4,6 @@ This module consolidates all logging configuration in one place to avoid duplica
 """
 
 import os
-import json
 import logging
 from typing import Any, Dict, List, Optional, Union
 
@@ -196,6 +195,9 @@ class StructuredFormatter(logging.Formatter):
             extra = {k: v for k, v in record.extra_data.items() if k not in self._STANDARD_FIELDS}
             log_data.update(extra)
 
+        # Deferred: json is only needed for opt-in structured logging
+        import json
+
         return json.dumps(log_data)
 
 

src/praisonai-agents/praisonaiagents/agent/__init__.py

@@ -37,6 +37,15 @@ def __getattr__(name):
         from .interrupt import InterruptController
         _lazy_cache[name] = InterruptController
         return InterruptController
+    if name in ('RunOutcome', 'TerminalReason'):
+        from . import run_outcome as _run_outcome_module
+        value = getattr(_run_outcome_module, name)
+        _lazy_cache[name] = value
+        return value
+    if name == 'prompt_prefix_signature':
+        from .prompt_cache import prompt_prefix_signature
+        _lazy_cache[name] = prompt_prefix_signature
+        return prompt_prefix_signature
     
     # Specialized agents - lazy loaded (import rich)
     if name == 'ImageAgent':
@@ -215,6 +224,9 @@ __all__ = [
     'Heartbeat',
     'HeartbeatConfig',
     'InterruptController',
+    'RunOutcome',
+    'TerminalReason',
+    'prompt_prefix_signature',
     'ImageAgent',
     'VideoAgent',
     'VideoConfig',

src/praisonai-agents/praisonaiagents/agent/agent.py

@@ -20,7 +20,7 @@ from .async_memory_mixin import AsyncMemoryMixin
 from .tool_execution import ToolExecutionMixin, BackoffPolicy
 from .chat_handler import ChatHandlerMixin
 from .session_manager import SessionManagerMixin
-from .async_safety import AsyncSafeState
+from .async_safety import AsyncSafeState, DualLock
 # NOTE: UnifiedExecutionMixin is deprecated and unused by any production path
 # (Issue #2644). It is kept in the MRO for backward compatibility during the
 # deprecation cycle and will be removed afterwards.
@@ -2230,7 +2230,10 @@ Your Goal: {self.goal}
         # Per-turn tool-name buffer feeding the self-improve review policy.
         # Populated in _execute_tool_with_context, reset each chat turn, and
         # read by _trigger_after_agent_hook when tools_used is not passed.
+        # Guarded by a DualLock (like chat_history) so concurrent chat()/achat()
+        # turns on the same Agent instance don't corrupt each other's buffer.
         self._turn_tools_used = []
+        self._turn_tools_lock = DualLock()
 
         # Database persistence (lazy - no imports until used)
         self._db = db
@@ -3198,7 +3201,44 @@ Summary:"""
     # ================================================================
     # Filesystem tracking convenience methods (powered by FileSnapshot)
     # ================================================================
-    
+
+    def set_snapshot_root(self, project_path: str) -> bool:
+        """Root filesystem change-tracking at ``project_path``.
+
+        Bots/gateway resolve file tools against a per-chat ``Workspace`` and
+        attach it *after* construction, but the FileSnapshot backing
+        :meth:`undo`/:meth:`redo`/:meth:`diff` was created at ``__init__`` time
+        rooted at ``os.getcwd()``. Without this, ``/undo`` tracks the wrong
+        directory (never where the tools actually wrote). Call this once after
+        the workspace is known so change tracking follows the tools.
+
+        Rooting at a new directory clears the undo/redo stacks (they belong to
+        the previous root). A no-op when the root is unchanged. Returns ``True``
+        when a snapshot manager is rooted at ``project_path``.
+        """
+        import os
+        new_root = os.path.abspath(str(project_path))
+        current = self._file_snapshot
+        if current is not None and getattr(current, "project_path", None) == new_root:
+            return True
+        try:
+            from ..snapshot import FileSnapshot
+            snapshot_dir = None
+            cfg = getattr(self, "autonomy_config", None)
+            if isinstance(cfg, dict):
+                snapshot_dir = cfg.get("snapshot_dir")
+            self._file_snapshot = FileSnapshot(
+                project_path=new_root,
+                snapshot_dir=snapshot_dir,
+            )
+            with self._snapshot_lock:
+                self._snapshot_stack = []
+                self._redo_stack = []
+            return True
+        except Exception as e:  # pragma: no cover - git may be unavailable
+            logger.debug(f"Re-rooting FileSnapshot failed: {e}")
+            return False
+
     def undo(self) -> bool:
         """Undo the last set of file changes.
         

src/praisonai-agents/praisonaiagents/agent/async_memory_mixin.py

@@ -7,7 +7,6 @@ async capabilities following the AsyncMemoryProtocol.
 """
 
 import asyncio
-import logging
 from typing import List, Dict, Any, Optional, Union
 from praisonaiagents._logging import get_logger
 from ..memory.protocols import AsyncMemoryProtocol

src/praisonai-agents/praisonaiagents/agent/autonomy.py

@@ -34,7 +34,6 @@ Usage:
 from dataclasses import dataclass, field
 from typing import Optional, Dict, Any, List, Set
 from enum import Enum
-import logging
 from praisonaiagents._logging import get_logger
 
 logger = get_logger(__name__)

src/praisonai-agents/praisonaiagents/agent/chat_mixin.py

@@ -2462,8 +2462,7 @@ Your Goal: {self.goal}"""
         """Internal chat implementation (extracted for trace wrapping)."""
         # Reset the per-turn tool buffer so the self-improve review policy only
         # sees tools used in this turn (not during a nested skill-review turn).
-        if not getattr(self, "_in_skill_review", False):
-            self._turn_tools_used = []
+        self._reset_turn_tools()
         # Apply rate limiter if configured (before any LLM call)
         if self._rate_limiter is not None:
             self._rate_limiter.acquire()
@@ -3064,8 +3063,7 @@ Output MUST be JSON with 'reflection' and 'satisfactory'.
         """Internal async chat implementation (extracted for trace wrapping)."""
         # Reset the per-turn tool buffer so the self-improve review policy only
         # sees tools used in this turn (not during a nested skill-review turn).
-        if not getattr(self, "_in_skill_review", False):
-            self._turn_tools_used = []
+        self._reset_turn_tools()
         # C2 - cooperative cancellation: abort early if a pre-set token is given
         _cancel = cancel_token if cancel_token is not None else getattr(self, "interrupt_controller", None)
         if _cancel is not None and getattr(_cancel, "is_set", lambda: False)():
@@ -3733,8 +3731,20 @@ Output MUST be JSON with 'reflection' and 'satisfactory'.
                         logging.error(f"Failed to parse tool arguments as JSON: {json_error}")
                         arguments = {}
                     
-                    # Find the matching tool
-                    tool = next((t for t in tools if t.__name__ == function_name), None)
+                    # Find the matching tool by comparing every supported identifier:
+                    # __name__ (plain callables), .name (BaseTool instances like
+                    # BrowserBaseTool, or aliased FunctionTools), or the class name.
+                    # Compare all candidates (not short-circuit) so an aliased .name
+                    # that differs from __name__ still resolves and BaseTool
+                    # subclasses without __name__ do not crash dispatch.
+                    tool = next(
+                        (t for t in tools if function_name in (
+                            getattr(t, "__name__", None),
+                            getattr(t, "name", None),
+                            type(t).__name__,
+                        )),
+                        None,
+                    )
                     if not tool:
                         _get_display_functions()['display_error'](f"Tool {function_name} not found")
                         continue

src/praisonai-agents/praisonaiagents/agent/cost_persistence.py

@@ -12,7 +12,6 @@ Usage::
 """
 
 import json
-import logging
 from praisonaiagents._logging import get_logger
 import os
 import time

src/praisonai-agents/praisonaiagents/agent/deep_research_agent.py

@@ -34,7 +34,6 @@ Example:
 """
 
 import os
-import logging
 from praisonaiagents._logging import get_logger
 import time
 import asyncio

src/praisonai-agents/praisonaiagents/agent/execution_mixin.py

@@ -125,16 +125,30 @@ class ExecutionMixin:
         
         Args:
             prompt: The input prompt to process
-            **kwargs: Additional arguments passed to achat()
+            **kwargs: Additional arguments passed to achat():
+                - return_outcome (bool): If True, return a canonical
+                  ``RunOutcome`` (completed | hard_timeout | cancelled |
+                  aborted | failed) instead of raising on error/timeout/
+                  cancellation. Default: False.
+                - timeout (float): When used with ``return_outcome=True``,
+                  a hard timeout budget for the run.
             
         Returns:
-            The agent's response as a string, or AutonomyResult if autonomy enabled
+            The agent's response as a string, or AutonomyResult if autonomy
+            enabled, or a ``RunOutcome`` when ``return_outcome=True``.
             
         Note:
             If autonomy=True was set on the agent, astart() automatically uses
             the autonomous loop (run_autonomous_async) instead of single-turn chat.
         """
         import sys
+
+        return_outcome = kwargs.pop('return_outcome', False)
+        if return_outcome:
+            outcome_timeout = kwargs.pop('timeout', None)
+            return await self._astart_with_outcome(
+                prompt, outcome_timeout, **kwargs
+            )
         
         # ─────────────────────────────────────────────────────────────────────
         # UNIFIED AUTONOMY API: If autonomy is enabled, route to run_autonomous_async
@@ -196,6 +210,57 @@ class ExecutionMixin:
         kwargs['stream'] = stream_requested
         return await self.achat(prompt, **kwargs)
 
+    async def _astart_with_outcome(self, prompt, timeout=None, **kwargs):
+        """Run astart() and normalise its result/exception into a RunOutcome.
+
+        Optionally enforces a hard run-level timeout budget. The budget is the
+        *authoritative* source of ``hard_timeout``: when our own
+        ``asyncio.wait_for`` fires we return ``hard_timeout`` directly, so a
+        nested operation timeout (which surfaces as a generic
+        ``asyncio.TimeoutError`` from inside the run) is never misreported as a
+        run-budget timeout — it falls through to ``failed`` via
+        ``RunOutcome.from_exception``.
+
+        External ``asyncio.CancelledError`` (e.g. the enclosing task being
+        cancelled during host shutdown) is re-raised, not swallowed, so
+        cooperative cancellation semantics are honoured.
+        """
+        import asyncio
+        from .run_outcome import RunOutcome
+
+        enforce_budget = timeout is not None and timeout > 0
+
+        # Enforce the run budget with an explicit deadline on a task we own, so
+        # that only *our* budget expiry maps to hard_timeout. This deliberately
+        # avoids ``asyncio.wait_for`` catching a bare inner ``TimeoutError``:
+        # a nested operation timeout raised inside the run must fall through to
+        # ``failed`` rather than be misreported as a run-budget ``hard_timeout``.
+        try:
+            if enforce_budget:
+                task = asyncio.ensure_future(self.astart(prompt, **kwargs))
+                try:
+                    done, _ = await asyncio.wait({task}, timeout=timeout)
+                except asyncio.CancelledError:
+                    # Enclosing task cancelled (e.g. host shutdown): cancel the
+                    # child and propagate so cooperative cancellation is honoured.
+                    task.cancel()
+                    raise
+                if task not in done:
+                    # Our budget expired first: authoritative, sticky hard_timeout.
+                    task.cancel()
+                    return RunOutcome(reason="hard_timeout")
+                result = task.result()
+            else:
+                result = await self.astart(prompt, **kwargs)
+        except asyncio.CancelledError:
+            # External cancellation of the awaiting task: honour asyncio
+            # cancellation / host shutdown by propagating instead of converting
+            # it into a benign RunOutcome.
+            raise
+        except Exception as exc:  # noqa: BLE001 - normalised into outcome
+            return RunOutcome.from_exception(exc)
+        return RunOutcome.completed(output=str(result) if result is not None else None)
+
     def run(self, prompt: str, **kwargs: Any) -> Optional[str]:
         """Execute agent silently and return structured result.
         
@@ -208,9 +273,14 @@ class ExecutionMixin:
             **kwargs: Additional arguments:
                 - stream (bool): Force streaming if True. Default: False
                 - output (str): Output preset override (rarely needed)
+                - return_outcome (bool): If True, return a canonical
+                  ``RunOutcome`` describing how the run ended
+                  (completed | hard_timeout | cancelled | aborted | failed)
+                  instead of raising on error. Default: False.
                 
         Returns:
-            The agent's response as a string
+            The agent's response as a string, or a ``RunOutcome`` when
+            ``return_outcome=True``.
             
         Example:
             ```python
@@ -227,8 +297,14 @@ class ExecutionMixin:
             - Background processing
             - API endpoints
         """
+        return_outcome = kwargs.pop('return_outcome', False)
+
         # Check if external managed backend is configured
         if hasattr(self, 'backend') and self.backend is not None:
+            if return_outcome:
+                return self._run_with_outcome(
+                    lambda: self._delegate_to_backend(prompt, **kwargs)
+                )
             return self._delegate_to_backend(prompt, **kwargs)
         
         # Production defaults: no streaming, no display
@@ -242,17 +318,34 @@ class ExecutionMixin:
         
         # Load history context
         self._load_history_context()
-        
-        # Check if planning mode is enabled
-        if self.planning:
-            result = self._start_with_planning(prompt, **kwargs)
-        else:
-            result = self.chat(prompt, **kwargs)
-        
-        # Auto-save session if enabled
-        self._auto_save_session()
-        
-        return result
+
+        def _execute():
+            if self.planning:
+                _result = self._start_with_planning(prompt, **kwargs)
+            else:
+                _result = self.chat(prompt, **kwargs)
+            # Auto-save session if enabled
+            self._auto_save_session()
+            return _result
+
+        if return_outcome:
+            return self._run_with_outcome(_execute)
+
+        return _execute()
+
+    def _run_with_outcome(self, executor):
+        """Run ``executor`` and normalise its result/exception into a RunOutcome.
+
+        Keeps the canonical terminal-outcome logic in one place so callers get
+        a single, closed description of how the run ended instead of inferring
+        it from exception identity.
+        """
+        from .run_outcome import RunOutcome
+        try:
+            result = executor()
+        except BaseException as exc:  # noqa: BLE001 - normalised into outcome
+            return RunOutcome.from_exception(exc)
+        return RunOutcome.completed(output=str(result) if result is not None else None)
 
     def _delegate_to_backend(self, prompt: str, **kwargs) -> Optional[str]:
         """Delegate execution to external managed backend (e.g., ManagedAgentIntegration).
@@ -1146,13 +1239,9 @@ Write the complete compiled report:"""
         # Record the tool name for this turn so the self-improve review policy
         # sees async tool usage too (issue #3037). Mirrors the sync path in
         # _execute_tool_with_context; skipped during a guarded review turn so
-        # the review's own calls are not tracked and cannot recurse.
-        if not getattr(self, "_in_skill_review", False):
-            turn_tools = getattr(self, "_turn_tools_used", None)
-            if turn_tools is None:
-                self._turn_tools_used = []
-                turn_tools = self._turn_tools_used
-            turn_tools.append(function_name)
+        # the review's own calls are not tracked and cannot recurse. Locked so
+        # concurrent turns on the same Agent don't corrupt the buffer (#3307).
+        self._record_turn_tool(function_name)
 
         # Enforce BEFORE_TOOL/AFTER_TOOL security hooks for every async caller,
         # mirroring the sync execute_tool path in tool_execution.py. Without
@@ -1369,11 +1458,22 @@ Write the complete compiled report:"""
                     return policy_result  # Error dict
                 _, arguments = policy_result
 
-            # Try to find the function in the override tools list first, then agent's tools list
+            # Try to find the function in the override tools list first, then agent's tools list.
+            # Resolve by BaseTool/FunctionTool ``.name`` (instances like BrowserBaseTool or
+            # aliased decorated tools), plain callable ``__name__``, or class name so async
+            # dispatch matches the robust sync resolution in _execute_tool_impl.
             func = None
             tools_to_search = tools_override if tools_override is not None else self.tools
+            from ..tools.base import BaseTool
             for tool in tools_to_search:
-                if (callable(tool) and getattr(tool, '__name__', '') == function_name):
+                if isinstance(tool, BaseTool) and getattr(tool, 'name', None) == function_name:
+                    func = tool
+                    break
+                if hasattr(tool, 'name') and getattr(tool, 'name', None) == function_name:
+                    func = tool
+                    break
+                if (callable(tool) and getattr(tool, '__name__', '') == function_name) or \
+                   (inspect.isclass(tool) and tool.__name__ == function_name):
                     func = tool
                     break
             
@@ -1382,15 +1482,18 @@ Write the complete compiled report:"""
                 return {"error": f"Function {function_name} not found in tools"}
 
             try:
-                if inspect.iscoroutinefunction(func):
+                # BaseTool instances (plugin system, e.g. BrowserBaseTool) are not
+                # directly callable — dispatch to their .run() method like the sync path.
+                call_target = func.run if isinstance(func, BaseTool) else func
+                if inspect.iscoroutinefunction(call_target):
                     logging.debug(f"Executing async function: {function_name}")
-                    result = await func(**arguments)
+                    result = await call_target(**arguments)
                 else:
                     logging.debug(f"Executing sync function in executor: {function_name}")
                     loop = asyncio.get_running_loop()
                     from ..trace.context_events import copy_context_to_callable
                     result = await loop.run_in_executor(
-                        None, copy_context_to_callable(lambda: func(**arguments))
+                        None, copy_context_to_callable(lambda: call_target(**arguments))
                     )
                 
                 # Ensure result is JSON serializable
@@ -1474,157 +1577,166 @@ Write the complete compiled report:"""
                 
         should_start = False
         with _server_lock:
-            # Initialize port-specific collections if needed
+            # Initialize port-specific collections if needed (once per port)
             if port not in _registered_agents:
                 _registered_agents[port] = {}
 
-                # Initialize shared FastAPI app if not already created for this port
-                if _shared_apps.get(port) is None:
-                    _shared_apps[port] = FastAPI(
-                        title=f"PraisonAI Agents API (Port {port})",
-                        description="API for interacting with PraisonAI Agents"
+            # Initialize shared FastAPI app if not already created for this port
+            if _shared_apps.get(port) is None:
+                _shared_apps[port] = FastAPI(
+                    title=f"PraisonAI Agents API (Port {port})",
+                    description="API for interacting with PraisonAI Agents"
+                )
+
+                # Add a root endpoint with a welcome message
+                @_shared_apps[port].get("/")
+                async def root():
+                    return {
+                        "message": f"Welcome to PraisonAI Agents API on port {port}. See /docs for usage.",
+                        "endpoints": list(_registered_agents[port].keys())
+                    }
+
+                # Add healthcheck endpoint
+                @_shared_apps[port].get("/health")
+                async def healthcheck():
+                    return {
+                        "status": "ok",
+                        "endpoints": list(_registered_agents[port].keys())
+                    }
+
+            # The path registration below must run on EVERY call, not just when the
+            # port is new, so multiple agents can share a single port.
+
+            # Normalize path to ensure it starts with /
+            if not path.startswith('/'):
+                path = f'/{path}'
+
+            # Check if path is already registered for this port
+            if path in _registered_agents[port]:
+                logging.warning(f"Path '{path}' is already registered on port {port}. Please use a different path.")
+                print(f"⚠️ Warning: Path '{path}' is already registered on port {port}.")
+                # Use a modified path to avoid conflicts
+                original_path = path
+                path = f"{path}_{self.agent_id[:6]}"
+                logging.warning(f"Using '{path}' instead of '{original_path}'")
+                print(f"🔄 Using '{path}' instead")
+
+            # Register the agent to this path
+            _registered_agents[port][path] = self.agent_id
+
+            # Define the endpoint handler
+            @_shared_apps[port].post(path)
+            async def handle_agent_query(request: Request, query_data: Optional[AgentQuery] = None):
+                # Handle both direct JSON with query field and form data
+                if query_data is None:
+                    try:
+                        request_data = await request.json()
+                        if "query" not in request_data:
+                            raise HTTPException(status_code=400, detail="Missing 'query' field in request")
+                        query = request_data["query"]
+                    except Exception:
+                        # Fallback to form data or query params
+                        form_data = await request.form()
+                        if "query" in form_data:
+                            query = form_data["query"]
+                        else:
+                            raise HTTPException(status_code=400, detail="Missing 'query' field in request")
+                else:
+                    query = query_data.query
+
+                try:
+                    # Use async version if available, otherwise use sync version
+                    if asyncio.iscoroutinefunction(self.chat):
+                        response = await self.achat(query, task_name=None, task_description=None, task_id=None)
+                    else:
+                        # Run sync function in a thread to avoid blocking
+                        loop = asyncio.get_running_loop()
+                        response = await loop.run_in_executor(None, lambda p=query: self.chat(p))
+
+                    return {"response": response}
+                except Exception as e:
+                    logging.error(f"Error processing query: {str(e)}", exc_info=True)
+                    return JSONResponse(
+                        status_code=500,
+                        content={"error": f"Error processing query: {str(e)}"}
                     )
 
-                    # Add a root endpoint with a welcome message
-                    @_shared_apps[port].get("/")
-                    async def root():
-                        return {
-                            "message": f"Welcome to PraisonAI Agents API on port {port}. See /docs for usage.",
-                            "endpoints": list(_registered_agents[port].keys())
-                        }
+            # Invalidate the cached OpenAPI schema so routes registered by later
+            # shared-port launch() calls still show up in /openapi.json and /docs.
+            # FastAPI caches app.openapi_schema on first access and does not
+            # regenerate it when new routes are added afterwards.
+            _shared_apps[port].openapi_schema = None
 
-                    # Add healthcheck endpoint
-                    @_shared_apps[port].get("/health")
-                    async def healthcheck():
-                        return {
-                            "status": "ok",
-                            "endpoints": list(_registered_agents[port].keys())
-                        }
+            print(f"🚀 Agent '{self.name}' available at http://{host}:{port}")
 
-                # Normalize path to ensure it starts with /
-                if not path.startswith('/'):
-                    path = f'/{path}'
-
-                # Check if path is already registered for this port
-                if path in _registered_agents[port]:
-                    logging.warning(f"Path '{path}' is already registered on port {port}. Please use a different path.")
-                    print(f"⚠️ Warning: Path '{path}' is already registered on port {port}.")
-                    # Use a modified path to avoid conflicts
-                    original_path = path
-                    path = f"{path}_{self.agent_id[:6]}"
-                    logging.warning(f"Using '{path}' instead of '{original_path}'")
-                    print(f"🔄 Using '{path}' instead")
-
-                # Register the agent to this path
-                _registered_agents[port][path] = self.agent_id
-
-                # Define the endpoint handler
-                @_shared_apps[port].post(path)
-                async def handle_agent_query(request: Request, query_data: Optional[AgentQuery] = None):
-                    # Handle both direct JSON with query field and form data
-                    if query_data is None:
-                        try:
-                            request_data = await request.json()
-                            if "query" not in request_data:
-                                raise HTTPException(status_code=400, detail="Missing 'query' field in request")
-                            query = request_data["query"]
-                        except Exception:
-                            # Fallback to form data or query params
-                            form_data = await request.form()
-                            if "query" in form_data:
-                                query = form_data["query"]
-                            else:
-                                raise HTTPException(status_code=400, detail="Missing 'query' field in request")
-                    else:
-                        query = query_data.query
-
-                    try:
-                        # Use async version if available, otherwise use sync version
-                        if asyncio.iscoroutinefunction(self.chat):
-                            response = await self.achat(query, task_name=None, task_description=None, task_id=None)
-                        else:
-                            # Run sync function in a thread to avoid blocking
-                            loop = asyncio.get_running_loop()
-                            response = await loop.run_in_executor(None, lambda p=query: self.chat(p))
-
-                        return {"response": response}
-                    except Exception as e:
-                        logging.error(f"Error processing query: {str(e)}", exc_info=True)
-                        return JSONResponse(
-                            status_code=500,
-                            content={"error": f"Error processing query: {str(e)}"}
-                        )
-
-                print(f"🚀 Agent '{self.name}' available at http://{host}:{port}")
-
-                # Check and mark server as started atomically to prevent race conditions
-                should_start = not _server_started.get(port, False)
-                if should_start:
-                    _server_started[port] = True
-
-            # Server start/wait outside the lock to avoid holding it during sleep  
+            # Check and mark server as started atomically to prevent race conditions
+            should_start = not _server_started.get(port, False)
             if should_start:
-                # Start the server in a separate thread
-                def run_server():
-                    try:
-                        print(f"✅ FastAPI server started at http://{host}:{port}")
-                        print(f"📚 API documentation available at http://{host}:{port}/docs")
-                        print(f"🔌 Available endpoints: {', '.join(list(_registered_agents[port].keys()))}")
-                        uvicorn.run(_shared_apps[port], host=host, port=port, log_level="debug" if debug else "info")
-                    except Exception as e:
-                        logging.error(f"Error starting server: {str(e)}", exc_info=True)
-                        print(f"❌ Error starting server: {str(e)}")
+                _server_started[port] = True
 
-                # Run server in a background thread
-                server_thread = threading.Thread(target=run_server, daemon=True)
-                server_thread.start()
-
-                # Wait for a moment to allow the server to start and register endpoints
-                self._safe_sleep(0.5)
-            else:
-                # If server is already running, wait a moment to make sure the endpoint is registered
-                self._safe_sleep(0.1)
-                print(f"🔌 Available endpoints on port {port}: {', '.join(list(_registered_agents[port].keys()))}")
-            
-            # Get the stack frame to check if this is the last launch() call in the script
-            import inspect
-            stack = inspect.stack()
-            
-            # If this is called from a Python script (not interactive), try to detect if it's the last launch call
-            if len(stack) > 1 and stack[1].filename.endswith('.py'):
-                caller_frame = stack[1]
-                caller_line = caller_frame.lineno
-                
+        # Server start/wait outside the lock to avoid holding it during sleep
+        if should_start:
+            # Start the server in a separate thread
+            def run_server():
                 try:
-                    # Read the file to check if there are more launch calls after this one
-                    with open(caller_frame.filename, 'r') as f:
-                        lines = f.readlines()
-                    
-                    # Check if there are more launch() calls after the current line
-                    has_more_launches = False
-                    for line_content in lines[caller_line:]: # renamed line to line_content
-                        if '.launch(' in line_content and not line_content.strip().startswith('#'):
-                            has_more_launches = True
-                            break
-                    
-                    # If this is the last launch call, block the main thread
-                    if not has_more_launches:
-                        try:
-                            print("\nAll agents registered for HTTP mode. Press Ctrl+C to stop the servers.")
-                            while True:
-                                self._safe_sleep(1)
-                        except KeyboardInterrupt:
-                            print("\nServers stopped")
+                    print(f"✅ FastAPI server started at http://{host}:{port}")
+                    print(f"📚 API documentation available at http://{host}:{port}/docs")
+                    print(f"🔌 Available endpoints: {', '.join(list(_registered_agents[port].keys()))}")
+                    uvicorn.run(_shared_apps[port], host=host, port=port, log_level="debug" if debug else "info")
                 except Exception as e:
-                    # If something goes wrong with detection, block anyway to be safe
-                    logging.error(f"Error in launch detection: {e}")
+                    logging.error(f"Error starting server: {str(e)}", exc_info=True)
+                    print(f"❌ Error starting server: {str(e)}")
+
+            # Run server in a background thread
+            server_thread = threading.Thread(target=run_server, daemon=True)
+            server_thread.start()
+
+            # Wait for a moment to allow the server to start and register endpoints
+            self._safe_sleep(0.5)
+        else:
+            # If server is already running, wait a moment to make sure the endpoint is registered
+            self._safe_sleep(0.1)
+            print(f"🔌 Available endpoints on port {port}: {', '.join(list(_registered_agents[port].keys()))}")
+
+        # Get the stack frame to check if this is the last launch() call in the script
+        import inspect
+        stack = inspect.stack()
+
+        # If this is called from a Python script (not interactive), try to detect if it's the last launch call
+        if len(stack) > 1 and stack[1].filename.endswith('.py'):
+            caller_frame = stack[1]
+            caller_line = caller_frame.lineno
+
+            try:
+                # Read the file to check if there are more launch calls after this one
+                with open(caller_frame.filename, 'r') as f:
+                    lines = f.readlines()
+
+                # Check if there are more launch() calls after the current line
+                has_more_launches = False
+                for line_content in lines[caller_line:]: # renamed line to line_content
+                    if '.launch(' in line_content and not line_content.strip().startswith('#'):
+                        has_more_launches = True
+                        break
+
+                # If this is the last launch call, block the main thread
+                if not has_more_launches:
                     try:
-                        print("\nKeeping HTTP servers alive. Press Ctrl+C to stop.")
+                        print("\nAll agents registered for HTTP mode. Press Ctrl+C to stop the servers.")
                         while True:
                             self._safe_sleep(1)
                     except KeyboardInterrupt:
                         print("\nServers stopped")
-            return None
+            except Exception as e:
+                # If something goes wrong with detection, block anyway to be safe
+                logging.error(f"Error in launch detection: {e}")
+                try:
+                    print("\nKeeping HTTP servers alive. Press Ctrl+C to stop.")
+                    while True:
+                        self._safe_sleep(1)
+                except KeyboardInterrupt:
+                    print("\nServers stopped")
+        return None
 
     def _launch_mcp_server(self, path: str, port: int, host: str, debug: bool):
         """
@@ -1671,7 +1783,7 @@ Write the complete compiled report:"""
             base_path = (path or "/mcp").rstrip("/") or "/mcp"
             transport = SseServerTransport(f"{base_path}/sse")
             starlette_app = Starlette(
-                routes=[Mount(base_path, mcp.create_app())]
+                routes=[Mount(base_path, mcp.sse_app())]
             )
 
             def run_mcp_server():

src/praisonai-agents/praisonaiagents/agent/handoff.py

@@ -14,9 +14,9 @@ from typing import Optional, Any, Callable, Dict, List, Union, TYPE_CHECKING, Li
 from dataclasses import dataclass, field
 from enum import Enum
 import inspect
-import logging
 from praisonaiagents._logging import get_logger
 import asyncio
+import contextvars
 import threading
 import time
 import json
@@ -163,33 +163,50 @@ from ..errors import (
     HandoffValidationError
 )
 
-# Thread-local storage for tracking handoff chains
-_handoff_context = threading.local()
+# Per-task/per-thread storage for tracking handoff chains.
+#
+# ``contextvars.ContextVar`` isolates the chain per :class:`asyncio.Task`
+# (and per OS thread), unlike ``threading.local()`` which shares one list
+# across every coroutine running on the same event-loop thread. Concurrent
+# async handoffs (``asyncio.gather``, a server handling parallel requests, or
+# any ``max_concurrent`` workflow) would otherwise push/pop into the same list
+# and corrupt each other's cycle/depth state.
+_handoff_chain_var: "contextvars.ContextVar[Optional[List[str]]]" = contextvars.ContextVar(
+    "handoff_chain", default=None
+)
 
 def _get_handoff_chain() -> List[str]:
-    """Get current handoff chain from thread-local storage."""
-    if not hasattr(_handoff_context, 'chain'):
-        _handoff_context.chain = []
-    return _handoff_context.chain
+    """Get current handoff chain for this task/thread."""
+    chain = _handoff_chain_var.get()
+    if chain is None:
+        chain = []
+        _handoff_chain_var.set(chain)
+    return chain
 
 def _get_handoff_depth() -> int:
     """Get current handoff depth."""
     return len(_get_handoff_chain())
 
 def _push_handoff(agent_name: str) -> None:
-    """Push agent to handoff chain."""
-    chain = _get_handoff_chain()
+    """Push agent to handoff chain.
+
+    Uses copy-on-write so a push made inside a child task does not leak back
+    into the parent task's chain once the child completes.
+    """
+    chain = list(_get_handoff_chain())
     chain.append(agent_name)
+    _handoff_chain_var.set(chain)
 
 def _pop_handoff() -> Optional[str]:
     """Pop agent from handoff chain."""
-    chain = _get_handoff_chain()
-    return chain.pop() if chain else None
+    chain = list(_get_handoff_chain())
+    popped = chain.pop() if chain else None
+    _handoff_chain_var.set(chain)
+    return popped
 
 def _clear_handoff_chain() -> None:
     """Clear the handoff chain."""
-    if hasattr(_handoff_context, 'chain'):
-        _handoff_context.chain = []
+    _handoff_chain_var.set([])
 
 @dataclass
 class HandoffInputData:

src/praisonai-agents/praisonaiagents/agent/heartbeat.py

@@ -13,7 +13,6 @@ Usage::
 """
 
 import asyncio
-import logging
 from praisonaiagents._logging import get_logger
 import threading
 import time

src/praisonai-agents/praisonaiagents/agent/loop_detection.py

@@ -22,7 +22,6 @@ from __future__ import annotations
 
 import hashlib
 import json
-import logging
 from praisonaiagents._logging import get_logger
 import time
 from dataclasses import dataclass, field

src/praisonai-agents/praisonaiagents/agent/message_queue.py

@@ -8,7 +8,6 @@ Thread-safe implementation for concurrent access.
 import threading
 import heapq
 import time
-import logging
 from praisonaiagents._logging import get_logger
 from typing import Optional, Any, List, Tuple
 from dataclasses import dataclass, field

src/praisonai-agents/praisonaiagents/agent/prompt_cache.py

@@ -0,0 +1,138 @@
+"""Prompt-cache-stability contract for the Agent turn (Issue #3352).
+
+Provider prompt caching (Anthropic/OpenAI) only hits when the *leading* bytes
+of a request are byte-identical to the previous request. For a long-lived
+conversation the cached prefix — the system instructions, the serialised tool
+schemas, and the model identity — is the dominant cost and latency lever.
+
+Gateways run many users on a single shared ``Agent`` instance and swap
+``tools``/``llm`` in and out per turn (per-route tool scoping, per-user
+``/model`` override). Those swaps silently change the cached prefix and the
+provider cache misses with zero operator visibility.
+
+``prompt_prefix_signature`` gives callers a single, cheap, deterministic
+fingerprint of exactly the cache-relevant inputs — model, the sorted set of
+tool names, and a fingerprint of the system instructions — and *nothing*
+volatile per-turn (arrival time, routing facts, memory/RAG recall). When the
+signature is unchanged across turns the prefix is guaranteed stable, so the
+provider cache keeps hitting; when it changes, that is the one auditable point
+at which cache warmth is knowingly sacrificed.
+"""
+
+from __future__ import annotations
+
+import hashlib
+from typing import Any
+
+
+def _tool_name(tool: Any) -> str:
+    """Best-effort stable name for a tool entry.
+
+    Tools may be plain callables, dicts holding an OpenAI-style function
+    schema, or objects exposing ``__name__``/``name``. The name identifies the
+    schema slot in the serialised tool block.
+    """
+    if isinstance(tool, dict):
+        fn = tool.get("function")
+        if isinstance(fn, dict) and fn.get("name"):
+            return str(fn["name"])
+        for key in ("name", "type"):
+            if tool.get(key):
+                return str(tool[key])
+        return str(sorted(tool.keys()))
+    for attr in ("__name__", "name"):
+        value = getattr(tool, attr, None)
+        if value:
+            return str(value)
+    return str(tool)
+
+
+def _tool_fingerprint(tool: Any) -> str:
+    """Best-effort stable fingerprint of a tool's *provider-visible* schema.
+
+    The serialised tool block sent to the provider is not just the tool name —
+    it is the full function schema (name + description + parameters). A change
+    to a tool's description, parameters, or required fields *without* a rename
+    changes those bytes and therefore invalidates the prompt cache, so the
+    fingerprint must reflect the whole schema, not only the name (Issue #3352
+    review). Falls back to the name when no richer schema is exposed.
+    """
+    name = _tool_name(tool)
+
+    # Dict tools already carry an OpenAI-style function schema — fingerprint the
+    # description + parameters alongside the name so a same-name schema edit is
+    # detected. ``json.dumps(sort_keys=True)`` makes the render deterministic.
+    if isinstance(tool, dict):
+        fn = tool.get("function")
+        schema = fn if isinstance(fn, dict) else tool
+        desc = schema.get("description") if isinstance(schema, dict) else None
+        params = schema.get("parameters") if isinstance(schema, dict) else None
+        try:
+            import json
+
+            return "\x01".join(
+                (
+                    name,
+                    str(desc or ""),
+                    json.dumps(params or {}, sort_keys=True, default=str),
+                )
+            )
+        except Exception:  # pragma: no cover — defensive
+            return name
+
+    # Callable/object tools: fold in the docstring (the description the schema
+    # generator emits) so an edited tool doc flips the signature too.
+    doc = getattr(tool, "__doc__", None)
+    if doc:
+        return f"{name}\x01{doc}"
+    return name
+
+
+def prompt_prefix_signature(agent: Any) -> str:
+    """Return a sha256 signature of an agent's cache-relevant prompt prefix.
+
+    The signature is computed over, and only over:
+
+    * the model identity (``agent.llm``),
+    * the sorted set of tool *schema fingerprints* (name + description +
+      parameters, ``agent.tools``) — so a same-name schema edit is detected,
+    * a fingerprint of the system instructions (``agent.instructions``).
+
+    Volatile per-turn data is intentionally excluded so that an unchanged
+    route/model keeps a byte-identical prefix and the provider cache keeps
+    hitting. Callers compare the signature turn-over-turn: an unchanged value
+    means the cached prefix is reused; a changed value is the single auditable
+    point of prompt-cache invalidation.
+
+    Best-effort and never raises: any attribute access failure degrades the
+    corresponding component to an empty string rather than breaking the turn.
+    """
+    try:
+        llm = getattr(agent, "llm", None)
+        model = llm if isinstance(llm, str) else getattr(llm, "model", None) or str(llm)
+    except Exception:
+        model = ""
+
+    try:
+        tools = getattr(agent, "tools", None) or []
+        tool_fps = sorted(_tool_fingerprint(t) for t in tools)
+    except Exception:
+        tool_fps = []
+
+    try:
+        instructions = getattr(agent, "instructions", None) or ""
+        instructions = str(instructions)
+    except Exception:
+        instructions = ""
+
+    hasher = hashlib.sha256()
+    hasher.update(b"model\x00")
+    hasher.update(str(model).encode("utf-8", "replace"))
+    hasher.update(b"\x00tools\x00")
+    hasher.update("\x00".join(tool_fps).encode("utf-8", "replace"))
+    hasher.update(b"\x00instructions\x00")
+    hasher.update(instructions.encode("utf-8", "replace"))
+    return hasher.hexdigest()
+
+
+__all__ = ["prompt_prefix_signature"]

src/praisonai-agents/praisonaiagents/agent/router_agent.py

@@ -6,7 +6,6 @@ model selection based on task characteristics.
 """
 
 import os
-import logging
 from praisonaiagents._logging import get_logger
 from typing import Dict, List, Optional, Any, Union
 from .agent import Agent

src/praisonai-agents/praisonaiagents/agent/run_outcome.py

@@ -0,0 +1,95 @@
+"""Canonical terminal-outcome contract for agent runs.
+
+A single, closed description of *how* a run ended, produced once by the core
+run and consumed everywhere. Long-running hosts (e.g. gateways/bots) can make
+delivery/retry/DLQ/status decisions from one field instead of inferring the
+terminal state from exception identity.
+
+Precedence is explicit and sticky: a ``hard_timeout`` is never silently
+downgraded by later cleanup. See ``RunOutcome.from_exception``.
+"""
+
+from dataclasses import dataclass
+from typing import Optional
+try:
+    from typing import Literal
+except ImportError:  # pragma: no cover - py<3.8 fallback
+    Literal = None  # type: ignore
+
+if Literal is not None:
+    TerminalReason = Literal[
+        "completed", "hard_timeout", "cancelled", "aborted", "failed"
+    ]
+else:  # pragma: no cover
+    TerminalReason = str  # type: ignore
+
+# Precedence: higher wins and is sticky (a hard timeout is not downgraded).
+_REASON_PRECEDENCE = {
+    "completed": 0,
+    "failed": 1,
+    "aborted": 2,
+    "cancelled": 3,
+    "hard_timeout": 4,
+}
+
+
+@dataclass(frozen=True)
+class RunOutcome:
+    """Closed, canonical description of how an agent run ended.
+
+    Attributes:
+        reason: One of ``completed | hard_timeout | cancelled | aborted | failed``.
+        output: Partial or final text, if any.
+        error: Redacted message when ``reason == "failed"``.
+    """
+
+    reason: "TerminalReason"
+    output: Optional[str] = None
+    error: Optional[str] = None
+
+    @property
+    def succeeded(self) -> bool:
+        """True only when the run completed normally."""
+        return self.reason == "completed"
+
+    @classmethod
+    def completed(cls, output: Optional[str] = None) -> "RunOutcome":
+        return cls(reason="completed", output=output)
+
+    @classmethod
+    def from_exception(
+        cls, exc: BaseException, output: Optional[str] = None
+    ) -> "RunOutcome":
+        """Normalise a raised exception into a canonical terminal outcome.
+
+        Maps well-known exception types to their terminal reason. Anything
+        unrecognised is treated as ``failed`` with a redacted message.
+
+        Note on ``hard_timeout``: the run-level budget is the authoritative
+        source of ``hard_timeout`` and is applied explicitly by the caller
+        (see ``_astart_with_outcome``). A bare ``asyncio.TimeoutError`` reaching
+        this normaliser is a *nested* operation timeout (e.g. a handoff/tool that
+        exhausted its own budget while the run budget remained) and is therefore
+        classified as ``failed`` — not silently promoted to a run-budget
+        ``hard_timeout``, which would drive the wrong host retry/DLQ decision.
+        Real cooperative cancellation is intercepted and re-raised by the run
+        wrapper (see ``_astart_with_outcome``) *before* it reaches this
+        normaliser, so host shutdown is honoured. A supersede/interrupt named
+        error that does surface here is a domain "cancelled" outcome.
+        """
+        import asyncio
+
+        if _name_matches(exc, ("hardtimeout", "runtimeout", "budgettimeout")):
+            return cls(reason="hard_timeout", output=output)
+        if isinstance(exc, asyncio.CancelledError) or _name_matches(
+            exc, ("supersed", "interrupt", "cancelled")
+        ):
+            return cls(reason="cancelled", output=output)
+        if _name_matches(exc, ("abort", "drain", "shutdown")):
+            return cls(reason="aborted", output=output)
+        return cls(reason="failed", output=output, error=str(exc))
+
+
+def _name_matches(exc: BaseException, needles: tuple) -> bool:
+    name = type(exc).__name__.lower()
+    return any(n in name for n in needles)

src/praisonai-agents/praisonaiagents/agent/summarization.py

@@ -5,7 +5,6 @@ Provides automatic summarization when context window fills up.
 Reuses existing telemetry/token_collector for token tracking.
 """
 
-import logging
 from praisonaiagents._logging import get_logger
 from typing import Optional, List, Dict, Any
 

src/praisonai-agents/praisonaiagents/agent/tool_execution.py

@@ -471,6 +471,46 @@ class ToolExecutionMixin:
             self._middleware_manager = manager
         return manager if manager.has_tool_hooks else None
 
+    def _get_turn_tools_lock(self):
+        """Return the DualLock guarding the per-turn tool buffer.
+
+        Falls back to a lazily-created lock so subclasses or objects that
+        predate the lock attribute stay safe. The lock protects
+        ``_turn_tools_used`` from corruption when concurrent chat()/achat()
+        turns run on the same Agent instance (issue #3307).
+        """
+        lock = getattr(self, "_turn_tools_lock", None)
+        if lock is None:
+            from .async_safety import DualLock
+            lock = DualLock()
+            self._turn_tools_lock = lock
+        return lock
+
+    def _reset_turn_tools(self):
+        """Reset the per-turn tool buffer under lock (start of a chat turn)."""
+        if getattr(self, "_in_skill_review", False):
+            return
+        with self._get_turn_tools_lock().sync():
+            self._turn_tools_used = []
+
+    def _record_turn_tool(self, function_name):
+        """Append a tool name to the per-turn buffer under lock."""
+        if getattr(self, "_in_skill_review", False):
+            return
+        with self._get_turn_tools_lock().sync():
+            turn_tools = getattr(self, "_turn_tools_used", None)
+            if turn_tools is None:
+                turn_tools = []
+                self._turn_tools_used = turn_tools
+            turn_tools.append(function_name)
+
+    def _drain_turn_tools(self):
+        """Return a copy of the per-turn buffer and clear it, under lock."""
+        with self._get_turn_tools_lock().sync():
+            tools_used = list(getattr(self, "_turn_tools_used", []) or [])
+            self._turn_tools_used = []
+        return tools_used
+
     def _execute_tool_with_context(self, function_name, arguments, state, tool_call_id=None):
         """Execute tool within injection context, with optional output truncation.
         
@@ -487,13 +527,9 @@ class ToolExecutionMixin:
         
         # Record the tool name for this turn so the self-improve review policy
         # can see what ran (issue #3037). Skipped during a guarded review turn
-        # to avoid tracking the review's own tool calls or recursing.
-        if not getattr(self, "_in_skill_review", False):
-            turn_tools = getattr(self, "_turn_tools_used", None)
-            if turn_tools is None:
-                self._turn_tools_used = []
-                turn_tools = self._turn_tools_used
-            turn_tools.append(function_name)
+        # to avoid tracking the review's own tool calls or recursing. Locked so
+        # concurrent turns on the same Agent don't corrupt the buffer (#3307).
+        self._record_turn_tool(function_name)
 
         # Emit tool call start event (zero overhead when not set)
         _trace_emitter = get_context_emitter()
@@ -1132,8 +1168,9 @@ class ToolExecutionMixin:
         # tools_used, so without this the review policy always sees an empty
         # list and never runs. Consume the buffer so the next turn starts clean.
         if tools_used is None:
-            tools_used = list(getattr(self, "_turn_tools_used", []) or [])
-        self._turn_tools_used = []
+            tools_used = self._drain_turn_tools()
+        else:
+            self._drain_turn_tools()
         # Trigger AFTER_AGENT hook (only build the input if a hook is actually registered)
         from ..hooks import HookEvent
         if self._hook_runner.registry.has_hooks(HookEvent.AFTER_AGENT):
@@ -1189,8 +1226,9 @@ class ToolExecutionMixin:
         # Default tools_used from the per-turn buffer when the caller did not
         # pass it explicitly (issue #3037); mirrors the sync path.
         if tools_used is None:
-            tools_used = list(getattr(self, "_turn_tools_used", []) or [])
-        self._turn_tools_used = []
+            tools_used = self._drain_turn_tools()
+        else:
+            self._drain_turn_tools()
         # Trigger AFTER_AGENT hook (only build the input if a hook is actually registered)
         from ..hooks import HookEvent
         if self._hook_runner.registry.has_hooks(HookEvent.AFTER_AGENT):
@@ -1395,7 +1433,9 @@ class ToolExecutionMixin:
             # only gate the built-in DEFAULT_DANGEROUS_TOOLS and silently skip
             # registry-required tools.
             approval_registry = get_approval_registry()
-            registry_required = approval_registry.is_required(tool_name)
+            registry_required = approval_registry.is_required(
+                tool_name, getattr(self, 'name', None)
+            )
             # Check if tool needs approval based on multiple criteria
             needs_approval = (
                 approve_all 
@@ -1409,7 +1449,7 @@ class ToolExecutionMixin:
                     tool_name=tool_name,
                     arguments=tool_args,
                     risk_level=(
-                        approval_registry.get_risk_level(tool_name)
+                        approval_registry.get_risk_level(tool_name, getattr(self, 'name', None))
                         or DEFAULT_DANGEROUS_TOOLS.get(tool_name, "medium")
                     ),
                     agent_name=getattr(self, 'name', None),
@@ -1474,21 +1514,19 @@ class ToolExecutionMixin:
                     return ApprovalDecision(approved=True, reason="Not a dangerous tool")
         else:
             # No approval backend configured. An explicit PermissionManager
-            # ``ask`` rule must still gate the call, so mark it required in the
-            # approval registry (idempotent) before delegating so the registry
-            # prompts instead of silently allowing.
-            if manager_forces_approval:
-                try:
-                    get_approval_registry().add_requirement(tool_name)
-                except Exception:  # noqa: BLE001
-                    pass
+            # ``ask`` rule must still gate the call. Rather than mutating shared
+            # registry state (which leaked onto other agents when this agent had
+            # no stable name), pass the intent per-call via ``force`` so the
+            # registry prompts for *this* call only without side effects.
             if is_async:
                 return get_approval_registry().approve_async(
                     getattr(self, 'name', None), tool_name, tool_args,
+                    force=manager_forces_approval,
                 )
             else:
                 return get_approval_registry().approve_sync(
                     getattr(self, 'name', None), tool_name, tool_args,
+                    force=manager_forces_approval,
                 )
 
     def _permission_manager_requires_approval(self, function_name) -> bool:
@@ -1602,7 +1640,9 @@ class ToolExecutionMixin:
             if self._permission_manager_requires_approval(function_name):
                 return True
             from ..approval import get_approval_registry
-            if get_approval_registry().is_required(function_name):
+            if get_approval_registry().is_required(
+                function_name, getattr(self, 'name', None)
+            ):
                 return True
             from ..tools import get_registry as get_tool_registry
             if get_tool_registry().get_trust_level(function_name) == "external":

src/praisonai-agents/praisonaiagents/agents/agents.py

@@ -330,17 +330,26 @@ async def _execute_with_agent_async(executor_agent, task_prompt, task, tools, st
         )
 
 
-def _build_execution_context(agents_instance, task_id):
+def _build_execution_context(agents_instance, task_id, skip_memory_init=False):
     """
     Build unified execution context for task execution (DRY helper).
     Eliminates duplication between sync/async execution paths.
+
+    Args:
+        skip_memory_init: When True, skip the synchronous ``initialize_memory()``
+            call. The async path (``aexecute_task``) already attempts
+            ``initialize_memory_async()`` beforehand, so this avoids blocking the
+            event loop on a synchronous ``Memory()`` construction (and a
+            duplicate backend attempt) if that async init failed.
     """
     from .protocols import ExecutionContext
     
     task = agents_instance.tasks[task_id]
     
-    # Initialize memory before task execution
-    if not task.memory:
+    # Initialize memory before task execution. The async path (aexecute_task)
+    # already attempts initialize_memory_async() and passes skip_memory_init=True
+    # so we never block the event loop on a synchronous Memory() construction.
+    if not task.memory and not skip_memory_init:
         task.memory = task.initialize_memory()
 
     executor_agent = task.agent
@@ -842,6 +851,11 @@ class AgentTeam(SpawnAnnounceProtocol):
         self._event_bus: Optional[EventBus] = None
         self._spawn_lock = threading.RLock()  # Thread-safe spawn operations (reentrant)
         self._team_id = str(uuid.uuid4())  # Unique team identifier
+        # Aggregate stream emitter (lazy). Fans in member agents' per-step
+        # StreamEventEmitter events, tagging each with the emitting agent's id,
+        # so a single consumer can attribute activity to a specific team member.
+        self.__stream_emitter = None
+        self.__stream_fanin_wired = False
         
         # Check for manager_llm in environment variable if not provided
         self.manager_llm = manager_llm or os.getenv('OPENAI_MODEL_NAME', 'gpt-4o-mini')
@@ -960,6 +974,63 @@ class AgentTeam(SpawnAnnounceProtocol):
         except (ImportError, AttributeError):
             self._telemetry = None
 
+    @property
+    def stream_emitter(self):
+        """Aggregate ``StreamEventEmitter`` fanning in member agents' events.
+
+        Lazily created on first access. On creation it registers a forwarding
+        callback on each member agent's own ``stream_emitter`` so per-step
+        events (tool calls, text/reasoning deltas, retries, errors) surface on a
+        single team-level emitter, each tagged with the emitting agent's
+        ``agent_id``. This gives a single attach point (e.g. the CLI
+        ``--output stream-json`` bridge) parity with single-agent runs.
+
+        Zero-overhead when unused: nothing is wired unless this property is
+        accessed, and forwarding only tags ``agent_id`` when the source event
+        did not already carry one.
+        """
+        if self.__stream_emitter is None:
+            try:
+                from ..streaming.events import StreamEventEmitter
+            except ImportError:
+                return None
+            self.__stream_emitter = StreamEventEmitter()
+        if not self.__stream_fanin_wired:
+            self._wire_stream_fanin()
+        return self.__stream_emitter
+
+    def _wire_stream_fanin(self):
+        """Forward each member agent's stream events onto the team emitter.
+
+        Best-effort and idempotent: an agent whose emitter is unavailable is
+        skipped, and a forwarding callback is attached at most once per team.
+        """
+        team_emitter = self.__stream_emitter
+        if team_emitter is None:
+            return
+        self.__stream_fanin_wired = True
+        for agent in self.agents:
+            member_emitter = getattr(agent, "stream_emitter", None)
+            if member_emitter is None or not hasattr(member_emitter, "add_callback"):
+                continue
+            agent_id = getattr(agent, "agent_id", None) or getattr(agent, "display_name", None)
+            member_emitter.add_callback(self._make_fanin_callback(team_emitter, agent_id))
+
+    @staticmethod
+    def _make_fanin_callback(team_emitter, agent_id):
+        """Build a callback that re-emits an event on the team emitter."""
+        def _forward(event):
+            try:
+                if agent_id is not None and getattr(event, "agent_id", None) is None:
+                    try:
+                        event.agent_id = agent_id
+                    except (AttributeError, TypeError):
+                        pass
+                team_emitter.emit(event)
+            except Exception:
+                logger.debug("AgentTeam stream fan-in forward failed", exc_info=True)
+        return _forward
+
     def add_task(self, task):
         with self._task_id_lock:
             task_id = self.task_id_counter
@@ -1054,8 +1125,17 @@ class AgentTeam(SpawnAnnounceProtocol):
         if task.status == "not started":
             task.status = "in progress"
 
-        # Build execution context using DRY helper
-        context = _build_execution_context(self, task_id)
+        # Initialize memory asynchronously to avoid blocking the event loop on
+        # synchronous Memory() construction. The shared helper's own
+        # `if not task.memory:` guard makes this a safe no-op for the sync path.
+        if not task.memory:
+            await task.initialize_memory_async()
+
+        # Build execution context using DRY helper. skip_memory_init=True prevents
+        # the helper from falling back to the *synchronous* initialize_memory()
+        # (which would block the event loop and duplicate a failed backend attempt)
+        # when the async init above did not populate task.memory.
+        context = _build_execution_context(self, task_id, skip_memory_init=True)
 
         # Execute with agent using DRY helper
         agent_output = await _execute_with_agent_async(

src/praisonai-agents/praisonaiagents/agents/auto_rag_agent.py

@@ -17,7 +17,6 @@ Usage:
     result = auto_rag.chat("Hello!")  # Skips retrieval
 """
 
-import logging
 from praisonaiagents._logging import get_logger
 import time
 from dataclasses import dataclass, field

src/praisonai-agents/praisonaiagents/agents/delegator.py

@@ -5,7 +5,6 @@ Provides delegation primitives for spawning subagents with scoped permissions
 and context. Inspired by Gemini CLI's delegate-to-agent pattern.
 """
 
-import logging
 from praisonaiagents._logging import get_logger
 import asyncio
 import warnings

src/praisonai-agents/praisonaiagents/approval/backends.py

@@ -11,7 +11,6 @@ Provides lightweight backends that ship with the core SDK:
 from __future__ import annotations
 
 import asyncio
-import logging
 from praisonaiagents._logging import get_logger
 from typing import Any
 

src/praisonai-agents/praisonaiagents/approval/registry.py

@@ -20,7 +20,6 @@ import asyncio
 import contextvars
 import hashlib
 import json
-import logging
 from praisonaiagents._logging import get_logger
 import os
 from typing import Dict, List, Optional, Set
@@ -91,10 +90,19 @@ class ApprovalRegistry:
         self._global_backend = None  # type: ignore[assignment]
         self._agent_backends: Dict[str, object] = {}
 
-        # Tool requirements (mirrors old APPROVAL_REQUIRED_TOOLS / TOOL_RISK_LEVELS)
+        # Tool requirements (mirrors old APPROVAL_REQUIRED_TOOLS / TOOL_RISK_LEVELS).
+        # These hold process-wide defaults (e.g. DEFAULT_DANGEROUS_TOOLS and any
+        # intentional global registration).
         self._required_tools: Set[str] = set()
         self._risk_levels: Dict[str, str] = {}
 
+        # Per-agent tool requirements. A PermissionManager ``ask`` rule belongs
+        # to a single agent, so it must not leak an approval gate onto unrelated
+        # agents sharing the same process. Mirrors the agent-keyed pattern used
+        # by ``_agent_backends`` / ``_agent_tool_auto_approve``.
+        self._agent_required_tools: Dict[str, Set[str]] = {}
+        self._agent_risk_levels: Dict[tuple[str, str], str] = {}
+
         # Per-agent, per-tool auto-approval (G-A fix)
         self._agent_tool_auto_approve: Dict[tuple[str, str], bool] = {}
 
@@ -153,18 +161,51 @@ class ApprovalRegistry:
 
     # ── Tool requirement management ──────────────────────────────────────
 
-    def add_requirement(self, tool_name: str, risk_level: str = "high") -> None:
-        self._required_tools.add(tool_name)
-        self._risk_levels[tool_name] = risk_level
+    def add_requirement(
+        self,
+        tool_name: str,
+        risk_level: str = "high",
+        agent_name: Optional[str] = None,
+    ) -> None:
+        """Mark *tool_name* as requiring approval.
 
-    def remove_requirement(self, tool_name: str) -> None:
-        self._required_tools.discard(tool_name)
-        self._risk_levels.pop(tool_name, None)
+        When *agent_name* is given the requirement is scoped to that agent only
+        (used for per-agent ``PermissionManager`` ``ask`` rules), so it never
+        forces approval onto other agents in the same process. Omitting
+        *agent_name* keeps the historical process-wide behaviour used for
+        genuinely dangerous tools registered at startup.
+        """
+        if agent_name:
+            self._agent_required_tools.setdefault(agent_name, set()).add(tool_name)
+            self._agent_risk_levels[(agent_name, tool_name)] = risk_level
+        else:
+            self._required_tools.add(tool_name)
+            self._risk_levels[tool_name] = risk_level
 
-    def is_required(self, tool_name: str) -> bool:
+    def remove_requirement(
+        self, tool_name: str, agent_name: Optional[str] = None
+    ) -> None:
+        if agent_name:
+            tools = self._agent_required_tools.get(agent_name)
+            if tools is not None:
+                tools.discard(tool_name)
+            self._agent_risk_levels.pop((agent_name, tool_name), None)
+        else:
+            self._required_tools.discard(tool_name)
+            self._risk_levels.pop(tool_name, None)
+
+    def is_required(self, tool_name: str, agent_name: Optional[str] = None) -> bool:
+        if agent_name and tool_name in self._agent_required_tools.get(agent_name, ()):
+            return True
         return tool_name in self._required_tools
 
-    def get_risk_level(self, tool_name: str) -> Optional[str]:
+    def get_risk_level(
+        self, tool_name: str, agent_name: Optional[str] = None
+    ) -> Optional[str]:
+        if agent_name:
+            level = self._agent_risk_levels.get((agent_name, tool_name))
+            if level is not None:
+                return level
         return self._risk_levels.get(tool_name)
 
     # ── Per-tool auto-approval (G-A fix) ─────────────────────────────────
@@ -346,10 +387,17 @@ class ApprovalRegistry:
         agent_name: Optional[str],
         tool_name: str,
         arguments: Dict,
+        force: bool = False,
     ) -> ApprovalDecision:
-        """Synchronous approval — used by ``Agent._execute_tool_impl``."""
-        # Fast-path: not required
-        if not self.is_required(tool_name):
+        """Synchronous approval — used by ``Agent._execute_tool_impl``.
+
+        ``force`` gates this single call even when the tool is not otherwise
+        registered as requiring approval (e.g. a per-agent ``PermissionManager``
+        ``ask`` rule). It applies only to this call and never mutates shared
+        registry state, so it cannot leak an approval gate onto other agents.
+        """
+        # Fast-path: not required (checks both global and this agent's scope)
+        if not force and not self.is_required(tool_name, agent_name):
             return ApprovalDecision(approved=True, reason="No approval required")
 
         # Already approved in this context
@@ -381,7 +429,7 @@ class ApprovalRegistry:
         request = ApprovalRequest(
             tool_name=tool_name,
             arguments=arguments,
-            risk_level=self._risk_levels.get(tool_name, "medium"),
+            risk_level=self.get_risk_level(tool_name, agent_name) or "medium",
             agent_name=agent_name,
         )
 
@@ -406,10 +454,15 @@ class ApprovalRegistry:
         agent_name: Optional[str],
         tool_name: str,
         arguments: Dict,
+        force: bool = False,
     ) -> ApprovalDecision:
-        """Asynchronous approval — used by async tool execution path."""
-        # Fast-path: not required
-        if not self.is_required(tool_name):
+        """Asynchronous approval — used by async tool execution path.
+
+        See :meth:`approve_sync` for the ``force`` semantics (per-call gate,
+        no shared-state mutation).
+        """
+        # Fast-path: not required (checks both global and this agent's scope)
+        if not force and not self.is_required(tool_name, agent_name):
             return ApprovalDecision(approved=True, reason="No approval required")
 
         if self.is_already_approved(tool_name, arguments):
@@ -437,7 +490,7 @@ class ApprovalRegistry:
         request = ApprovalRequest(
             tool_name=tool_name,
             arguments=arguments,
-            risk_level=self._risk_levels.get(tool_name, "medium"),
+            risk_level=self.get_risk_level(tool_name, agent_name) or "medium",
             agent_name=agent_name,
         )
 

src/praisonai-agents/praisonaiagents/background/runner.py

@@ -5,7 +5,6 @@ Manages background task execution.
 """
 
 import asyncio
-import logging
 import threading
 from praisonaiagents._logging import get_logger
 from typing import Optional, List, Dict, Any, Callable, Union

src/praisonai-agents/praisonaiagents/background/task.py

@@ -6,7 +6,6 @@ Represents a task running in the background.
 
 import uuid
 import asyncio
-import logging
 from praisonaiagents._logging import get_logger
 from enum import Enum
 from dataclasses import dataclass, field

src/praisonai-agents/praisonaiagents/bots/__init__.py

@@ -33,6 +33,9 @@ from .protocols import (
     WebhookVerifierProtocol,
     CallbackPayloadStoreProtocol,
     InMemoryCallbackPayloadStore,
+    GatewayRuntimeSeams,
+    SupportsGatewayRuntime,
+    GatewayAdapterContractError,
 )
 from .base import (
     BasePlatformAdapter,
@@ -122,6 +125,9 @@ __all__ = [
     "WebhookVerifierProtocol",
     "CallbackPayloadStoreProtocol",
     "InMemoryCallbackPayloadStore",
+    "GatewayRuntimeSeams",
+    "SupportsGatewayRuntime",
+    "GatewayAdapterContractError",
     "BasePlatformAdapter",
     "SendResult",
     "InteractiveContext",

src/praisonai-agents/praisonaiagents/bots/protocols.py

@@ -302,6 +302,79 @@ class WebhookVerifierProtocol(Protocol):
         ...
 
 
+class GatewayAdapterContractError(TypeError):
+    """Raised when a channel adapter cannot receive the gateway runtime seams.
+
+    The gateway wires four reliability seams into every channel adapter —
+    the cross-platform identity resolver, the delivery router, the admission
+    gate, and the shared per-turn lock map. When the gateway has these seams
+    to inject but the adapter neither implements
+    :class:`SupportsGatewayRuntime` nor exposes a compatible session, the wiring
+    would silently no-op and the adapter would run without admission control,
+    durable delivery routing, or cross-platform turn locking. Failing loudly
+    with this error surfaces the missing contract instead.
+    """
+
+
+@dataclass
+class GatewayRuntimeSeams:
+    """The gateway reliability seams handed to a channel adapter at build time.
+
+    A single, typed carrier for the four runtime seams the gateway injects so
+    an adapter wires them up in one place instead of via four duck-typed
+    private-attribute splices:
+
+    Attributes:
+        identity_resolver: Cross-platform identity resolver; unifies the same
+            human across platforms onto one session key.
+        delivery_router: Backing router for the built-in ``send_message`` tool,
+            so an agent turn can proactively reach the user mid-task.
+        admission_gate: Gateway-wide admission control (concurrency ceiling /
+            fair queue / backpressure) applied to inbound runs.
+        turn_lock_map: Shared per-turn lock map for cross-platform turn
+            serialisation on the resolved session id.
+
+    A seam left ``None`` means the gateway has nothing to inject for it and the
+    adapter should keep whatever it already has.
+    """
+
+    identity_resolver: Optional[Any] = None
+    delivery_router: Optional[Any] = None
+    admission_gate: Optional[Any] = None
+    turn_lock_map: Optional[Any] = None
+
+
+@runtime_checkable
+class SupportsGatewayRuntime(Protocol):
+    """Contract for channel adapters that accept the gateway runtime seams.
+
+    Instead of the gateway reaching into an adapter's private session and
+    splicing ``_identity_resolver`` / ``_delivery_router`` / ``_admission_gate``
+    / ``_locks`` via ``getattr``/``hasattr`` (which silently no-ops on any
+    adapter whose session does not match the built-in shape), an adapter — in
+    tree or ``pip``-installed — implements this one method. The gateway calls it
+    once with a :class:`GatewayRuntimeSeams`, so the same reliability guarantees
+    (admission/backpressure, delivery routing, cross-platform turn locking)
+    hold for *every* adapter.
+
+    Adapters whose ``__init__`` creates a ``BotSessionManager`` get this for
+    free — the session manager implements ``attach_gateway_runtime`` and the
+    adapter can simply delegate to ``self._session.attach_gateway_runtime(...)``.
+    """
+
+    def attach_gateway_runtime(self, runtime: "GatewayRuntimeSeams") -> None:
+        """Wire the gateway runtime seams into this adapter.
+
+        Only seams present (non-``None``) on ``runtime`` should be applied;
+        seams left ``None`` mean the gateway has nothing to inject and the
+        adapter must keep its existing value.
+
+        Args:
+            runtime: The gateway reliability seams to attach.
+        """
+        ...
+
+
 class MessageType(str, Enum):
     """Types of bot messages."""
     

src/praisonai-agents/praisonaiagents/bus/bus.py

@@ -5,7 +5,6 @@ Provides publish/subscribe functionality for typed events.
 """
 
 import asyncio
-import logging
 from praisonaiagents._logging import get_logger
 import threading
 from typing import Any, Callable, Dict, List, Optional, Set, Union

src/praisonai-agents/praisonaiagents/checkpoints/service.py

@@ -7,7 +7,6 @@ Implements shadow git repository for file-level checkpointing.
 import os
 import re
 import asyncio
-import logging
 from praisonaiagents._logging import get_logger
 import shutil
 from typing import Optional, List, Dict, Any, Callable

src/praisonai-agents/praisonaiagents/compaction/compactor.py

@@ -160,7 +160,8 @@ class ContextCompactor:
                 )
             except Exception:
                 pass
-        return max(1, len(text) // 4)
+        from ..context.tokens import estimate_tokens_heuristic
+        return estimate_tokens_heuristic(text)
 
     def count_message_tokens(self, message: Dict[str, Any]) -> int:
         """Count tokens in a message, including tool_calls payloads."""

src/praisonai-agents/praisonaiagents/conditions/evaluator.py

@@ -8,7 +8,6 @@ The implementation is extracted from workflows.py _evaluate_condition()
 to enable DRY condition handling across the codebase.
 """
 import re
-import logging
 from praisonaiagents._logging import get_logger
 from typing import Dict, Any, List, Optional
 

src/praisonai-agents/praisonaiagents/config/feature_configs.py

@@ -950,7 +950,16 @@ class ExecutionConfig:
         if isinstance(context_compaction, dict):
             from ..context.policy import ContextCompactionPolicy
             context_compaction = ContextCompactionPolicy.from_dict(context_compaction)
-        
+
+        # Handle compaction_strategy restoration (serialised as a string value in to_dict)
+        compaction_strategy = data.get("compaction_strategy")
+        if isinstance(compaction_strategy, str):
+            from ..compaction.strategy import CompactionStrategy
+            try:
+                compaction_strategy = CompactionStrategy(compaction_strategy)
+            except ValueError:
+                compaction_strategy = None
+
         return cls(
             max_iter=data.get("max_iter", 20),
             max_steps=data.get("max_steps", None),
@@ -958,13 +967,17 @@ class ExecutionConfig:
             max_rpm=data.get("max_rpm", None),
             max_execution_time=data.get("max_execution_time", None),
             max_retry_limit=data.get("max_retry_limit", 2),
+            retry_initial_delay=data.get("retry_initial_delay", 1.0),
+            retry_backoff_factor=data.get("retry_backoff_factor", 2.0),
+            retry_jitter=data.get("retry_jitter", 0.1),
             code_execution=data.get("code_execution", False),
             code_mode=data.get("code_mode", "safe"),
-            code_sandbox_mode=data.get("code_sandbox_mode", "docker"),
+            code_sandbox_mode=data.get("code_sandbox_mode", "sandbox"),
             code_tools=data.get("code_tools", False),
             code_tools_allow=data.get("code_tools_allow", None),
             context_compaction=context_compaction,
             max_context_tokens=data.get("max_context_tokens", None),
+            compaction_strategy=compaction_strategy,
             max_budget=data.get("max_budget", None),
             parallel_tool_calls=data.get("parallel_tool_calls", False),
         )

src/praisonai-agents/praisonaiagents/config/parse_utils.py

@@ -50,42 +50,6 @@ def detect_url_scheme(value: str) -> Optional[str]:
     return None
 
 
-def parse_url_to_config(
-    url: str,
-    config_class: type,
-    url_schemes: Dict[str, str],
-) -> Any:
-    """
-    Parse a URL string into a config object.
-    
-    Args:
-        url: URL string (e.g., "postgresql://localhost/db")
-        config_class: Config dataclass to instantiate
-        url_schemes: Mapping of URL schemes to backend names
-        
-    Returns:
-        Config instance with backend and url set
-        
-    Raises:
-        ValueError: If URL scheme is not supported
-    """
-    scheme = detect_url_scheme(url)
-    if not scheme:
-        raise ValueError(f"Invalid URL format: {url}")
-    
-    if scheme not in url_schemes:
-        valid_schemes = ", ".join(sorted(url_schemes.keys()))
-        raise ValueError(
-            f"Unsupported URL scheme '{scheme}' in '{url}'. "
-            f"Supported schemes: {valid_schemes}"
-        )
-    
-    backend = url_schemes[scheme]
-    
-    # Create config with backend and URL in config dict
-    return config_class(backend=backend, config={"url": url})
-
-
 def is_path_like(value: str) -> bool:
     """
     Check if a string looks like a file path. O(1) operation.
@@ -136,21 +100,6 @@ def is_path_like(value: str) -> bool:
     return False
 
 
-def is_numeric_string(value: str) -> bool:
-    """
-    Check if a string is numeric. O(1) operation.
-    
-    Args:
-        value: String to check
-        
-    Returns:
-        True if string is numeric
-    """
-    if not isinstance(value, str):
-        return False
-    return value.isdigit()
-
-
 def suggest_similar(value: str, candidates: Iterable[str], max_distance: int = 2) -> Optional[str]:
     """
     Find the most similar string from candidates using Levenshtein distance.
@@ -246,28 +195,6 @@ def make_preset_error(
     return ValueError(" ".join(msg_parts))
 
 
-def make_array_error(
-    param_name: str,
-    value: list,
-    expected_format: str,
-) -> ValueError:
-    """
-    Create a helpful error message for invalid array format.
-    
-    Args:
-        param_name: Name of the parameter
-        value: Invalid array value
-        expected_format: Description of expected format
-        
-    Returns:
-        ValueError with helpful message
-    """
-    return ValueError(
-        f"Invalid {param_name} array format: {value}. "
-        f"Expected: {expected_format}"
-    )
-
-
 def is_policy_string(value: str) -> bool:
     """
     Check if a string is a policy specification. O(1) operation.

src/praisonai-agents/praisonaiagents/context/aggregator.py

@@ -6,7 +6,6 @@ Inspired by CrewAI's ContextualMemory pattern.
 """
 
 import asyncio
-import logging
 from praisonaiagents._logging import get_logger
 from dataclasses import dataclass, field
 from typing import Any, Callable, Dict, List, Optional, Tuple, Union

src/praisonai-agents/praisonaiagents/context/fast/async_file_ops.py

@@ -12,7 +12,6 @@ Design principles:
 """
 
 import asyncio
-import logging
 from praisonaiagents._logging import get_logger
 from typing import Optional, List
 

src/praisonai-agents/praisonaiagents/context/fast/compressor.py

@@ -12,7 +12,6 @@ Design principles:
 - Preserves most relevant content
 """
 
-import logging
 from praisonaiagents._logging import get_logger
 from typing import Protocol, Optional, List
 from dataclasses import dataclass

src/praisonai-agents/praisonaiagents/context/fast/context_injector.py

@@ -7,7 +7,6 @@ Injects FastContext results into the main agent with:
 - Precision over recall (avoid context pollution)
 """
 
-import logging
 from praisonaiagents._logging import get_logger
 from typing import Optional, List, Dict, Any
 from dataclasses import dataclass

src/praisonai-agents/praisonaiagents/context/fast/fast_context.py

@@ -25,7 +25,6 @@ Example usage:
 import os
 import hashlib
 import json
-import logging
 from praisonaiagents._logging import get_logger
 from typing import Optional, List, Dict, Any
 

src/praisonai-agents/praisonaiagents/context/fast/fast_context_agent.py

@@ -10,7 +10,6 @@ This agent is designed for fast context retrieval using:
 
 import os
 import json
-import logging
 from praisonaiagents._logging import get_logger
 from typing import List, Dict, Any, Optional
 

src/praisonai-agents/praisonaiagents/context/fast/index_manager.py

@@ -15,7 +15,6 @@ Design principles:
 import os
 import json
 import hashlib
-import logging
 from praisonaiagents._logging import get_logger
 from dataclasses import dataclass, field, asdict
 from pathlib import Path

src/praisonai-agents/praisonaiagents/context/fast/indexer/file_indexer.py

@@ -12,7 +12,6 @@ import os
 import fnmatch
 import hashlib
 import json
-import logging
 from praisonaiagents._logging import get_logger
 from dataclasses import dataclass
 from typing import Dict, List, Set, Optional, Any

src/praisonai-agents/praisonaiagents/context/fast/indexer/file_watcher.py

@@ -1,318 +0,0 @@
-"""
-File Watcher for Incremental Indexing.
-
-Monitors file system changes and triggers incremental index updates:
-- Watches for file creation, modification, deletion
-- Debounces rapid changes
-- Supports background indexing
-"""
-
-import os
-import time
-import logging
-from praisonaiagents._logging import get_logger
-import threading
-from typing import Dict, Set, Callable, Optional, Any
-from dataclasses import dataclass
-from enum import Enum
-
-logger = get_logger(__name__)
-
-class ChangeType(Enum):
-    """Types of file system changes."""
-    CREATED = "created"
-    MODIFIED = "modified"
-    DELETED = "deleted"
-
-@dataclass
-class FileChange:
-    """Represents a file system change.
-    
-    Attributes:
-        path: Path to the changed file
-        change_type: Type of change
-        timestamp: When the change was detected
-    """
-    path: str
-    change_type: ChangeType
-    timestamp: float
-
-class FileWatcher:
-    """Watches for file system changes and triggers callbacks.
-    
-    Uses polling-based approach for cross-platform compatibility.
-    For production use, consider using watchdog library.
-    
-    Attributes:
-        workspace_path: Root directory to watch
-        extensions: File extensions to watch
-        poll_interval: Seconds between polls
-    """
-    
-    def __init__(
-        self,
-        workspace_path: str,
-        extensions: Optional[Set[str]] = None,
-        poll_interval: float = 1.0,
-        debounce_delay: float = 0.5,
-        on_change: Optional[Callable[[FileChange], None]] = None
-    ):
-        """Initialize file watcher.
-        
-        Args:
-            workspace_path: Root directory to watch
-            extensions: File extensions to watch (None = all)
-            poll_interval: Seconds between polls
-            debounce_delay: Delay before processing changes
-            on_change: Callback for file changes
-        """
-        self.workspace_path = os.path.abspath(workspace_path)
-        self.extensions = extensions or {
-            '.py', '.js', '.ts', '.jsx', '.tsx', '.go', '.rs', '.java',
-            '.c', '.cpp', '.h', '.hpp', '.cs', '.rb', '.php', '.swift'
-        }
-        self.poll_interval = poll_interval
-        self.debounce_delay = debounce_delay
-        self.on_change = on_change
-        
-        # State tracking
-        self._file_mtimes: Dict[str, float] = {}
-        self._pending_changes: Dict[str, FileChange] = {}
-        self._running = False
-        self._thread: Optional[threading.Thread] = None
-        self._lock = threading.Lock()
-    
-    def _scan_files(self) -> Dict[str, float]:
-        """Scan workspace and get file modification times.
-        
-        Returns:
-            Dict mapping file paths to modification times
-        """
-        mtimes = {}
-        
-        for root, dirs, files in os.walk(self.workspace_path):
-            # Skip hidden directories
-            dirs[:] = [d for d in dirs if not d.startswith('.')]
-            
-            for filename in files:
-                ext = os.path.splitext(filename)[1].lower()
-                if ext in self.extensions:
-                    file_path = os.path.join(root, filename)
-                    try:
-                        mtimes[file_path] = os.path.getmtime(file_path)
-                    except OSError:
-                        pass
-        
-        return mtimes
-    
-    def _detect_changes(self, new_mtimes: Dict[str, float]) -> None:
-        """Detect changes between old and new file states.
-        
-        Args:
-            new_mtimes: New file modification times
-        """
-        old_paths = set(self._file_mtimes.keys())
-        new_paths = set(new_mtimes.keys())
-        
-        now = time.time()
-        
-        # Detect created files
-        for path in new_paths - old_paths:
-            self._add_pending_change(FileChange(
-                path=path,
-                change_type=ChangeType.CREATED,
-                timestamp=now
-            ))
-        
-        # Detect deleted files
-        for path in old_paths - new_paths:
-            self._add_pending_change(FileChange(
-                path=path,
-                change_type=ChangeType.DELETED,
-                timestamp=now
-            ))
-        
-        # Detect modified files
-        for path in old_paths & new_paths:
-            if new_mtimes[path] > self._file_mtimes[path]:
-                self._add_pending_change(FileChange(
-                    path=path,
-                    change_type=ChangeType.MODIFIED,
-                    timestamp=now
-                ))
-        
-        self._file_mtimes = new_mtimes
-    
-    def _add_pending_change(self, change: FileChange) -> None:
-        """Add a change to pending queue (with debouncing).
-        
-        Args:
-            change: File change to add
-        """
-        with self._lock:
-            self._pending_changes[change.path] = change
-    
-    def _process_pending_changes(self) -> None:
-        """Process pending changes after debounce delay."""
-        with self._lock:
-            now = time.time()
-            to_process = []
-            
-            for path, change in list(self._pending_changes.items()):
-                if now - change.timestamp >= self.debounce_delay:
-                    to_process.append(change)
-                    del self._pending_changes[path]
-        
-        # Process changes outside lock
-        for change in to_process:
-            if self.on_change:
-                try:
-                    self.on_change(change)
-                except Exception as e:
-                    logger.error(f"Error processing change {change.path}: {e}")
-    
-    def _poll_loop(self) -> None:
-        """Main polling loop."""
-        # Initial scan
-        self._file_mtimes = self._scan_files()
-        
-        while self._running:
-            try:
-                # Scan for changes
-                new_mtimes = self._scan_files()
-                self._detect_changes(new_mtimes)
-                
-                # Process pending changes
-                self._process_pending_changes()
-                
-            except Exception as e:
-                logger.error(f"Error in file watcher: {e}")
-            
-            time.sleep(self.poll_interval)
-    
-    def start(self) -> None:
-        """Start watching for file changes."""
-        if self._running:
-            return
-        
-        self._running = True
-        self._thread = threading.Thread(target=self._poll_loop, daemon=True)
-        self._thread.start()
-        logger.info(f"File watcher started for {self.workspace_path}")
-    
-    def stop(self) -> None:
-        """Stop watching for file changes."""
-        self._running = False
-        if self._thread:
-            self._thread.join(timeout=2.0)
-            self._thread = None
-        logger.info("File watcher stopped")
-    
-    def __enter__(self):
-        self.start()
-        return self
-    
-    def __exit__(self, exc_type, exc_val, exc_tb):
-        self.stop()
-
-class IncrementalIndexer:
-    """Manages incremental index updates based on file changes.
-    
-    Combines FileIndexer/SymbolIndexer with FileWatcher for
-    automatic index updates when files change.
-    """
-    
-    def __init__(
-        self,
-        workspace_path: str,
-        file_indexer: Optional[Any] = None,
-        symbol_indexer: Optional[Any] = None,
-        poll_interval: float = 2.0
-    ):
-        """Initialize incremental indexer.
-        
-        Args:
-            workspace_path: Root directory to index
-            file_indexer: FileIndexer instance (optional)
-            symbol_indexer: SymbolIndexer instance (optional)
-            poll_interval: Seconds between file system polls
-        """
-        self.workspace_path = os.path.abspath(workspace_path)
-        self.file_indexer = file_indexer
-        self.symbol_indexer = symbol_indexer
-        
-        self._watcher = FileWatcher(
-            workspace_path=workspace_path,
-            poll_interval=poll_interval,
-            on_change=self._handle_change
-        )
-        
-        # Statistics
-        self.changes_processed = 0
-        self.last_change_time: Optional[float] = None
-    
-    def _handle_change(self, change: FileChange) -> None:
-        """Handle a file change.
-        
-        Args:
-            change: File change to process
-        """
-        rel_path = os.path.relpath(change.path, self.workspace_path)
-        logger.debug(f"Processing {change.change_type.value}: {rel_path}")
-        
-        if change.change_type == ChangeType.DELETED:
-            # Remove from indexes
-            if self.file_indexer and hasattr(self.file_indexer, 'files'):
-                self.file_indexer.files.pop(rel_path, None)
-            if self.symbol_indexer and hasattr(self.symbol_indexer, 'symbols'):
-                self.symbol_indexer.symbols.pop(rel_path, None)
-        else:
-            # Re-index the file
-            if self.file_indexer and hasattr(self.file_indexer, 'index_file'):
-                # FileIndexer doesn't have index_file, so we skip
-                pass
-            if self.symbol_indexer and hasattr(self.symbol_indexer, 'index_file'):
-                self.symbol_indexer.index_file(change.path)
-        
-        self.changes_processed += 1
-        self.last_change_time = time.time()
-    
-    def start(self) -> None:
-        """Start incremental indexing."""
-        # Initial full index
-        if self.file_indexer:
-            self.file_indexer.index()
-        if self.symbol_indexer:
-            self.symbol_indexer.index()
-        
-        # Start watching
-        self._watcher.start()
-    
-    def stop(self) -> None:
-        """Stop incremental indexing."""
-        self._watcher.stop()
-    
-    def get_stats(self) -> Dict[str, Any]:
-        """Get indexer statistics.
-        
-        Returns:
-            Dictionary with stats
-        """
-        stats = {
-            "changes_processed": self.changes_processed,
-            "last_change_time": self.last_change_time
-        }
-        
-        if self.file_indexer:
-            stats["file_indexer"] = self.file_indexer.get_stats()
-        if self.symbol_indexer:
-            stats["symbol_indexer"] = self.symbol_indexer.get_stats()
-        
-        return stats
-    
-    def __enter__(self):
-        self.start()
-        return self
-    
-    def __exit__(self, exc_type, exc_val, exc_tb):
-        self.stop()

src/praisonai-agents/praisonaiagents/context/fast/indexer/symbol_indexer.py

@@ -11,7 +11,6 @@ Extracts code symbols from source files:
 
 import os
 import re
-import logging
 from praisonaiagents._logging import get_logger
 from dataclasses import dataclass, field
 from typing import Dict, List, Set, Optional, Any

src/praisonai-agents/praisonaiagents/context/fast/parallel_executor.py

@@ -11,7 +11,6 @@ Provides async parallel execution of search tools with:
 import asyncio
 from concurrent.futures import ThreadPoolExecutor
 from typing import List, Dict, Any, Optional, Callable
-import logging
 from praisonaiagents._logging import get_logger
 import time
 

src/praisonai-agents/praisonaiagents/context/fast/search_backends.py

@@ -11,7 +11,6 @@ Design principles:
 - No performance impact on default behavior
 """
 
-import logging
 from praisonaiagents._logging import get_logger
 from typing import Protocol, List, Dict, Any, Optional, runtime_checkable
 

src/praisonai-agents/praisonaiagents/context/fast/search_strategy.py

@@ -1,366 +0,0 @@
-"""
-Search Strategy for Fast Context.
-
-Orchestrates multi-turn search with:
-- Turn 1-3: Exploration (grep, glob, directory listing)
-- Turn 4: Final answer (file list + line ranges)
-- Early termination if sufficient context found
-"""
-
-import logging
-from praisonaiagents._logging import get_logger
-from dataclasses import dataclass, field
-from typing import List, Dict, Any, Optional, Set
-from enum import Enum
-
-from praisonaiagents.context.fast.result import FastContextResult, FileMatch, LineRange
-from praisonaiagents.context.fast.parallel_executor import ToolCallBatch
-
-logger = get_logger(__name__)
-
-class SearchPhase(Enum):
-    """Phases of the search strategy."""
-    DISCOVERY = "discovery"      # Turn 1: Discover structure
-    EXPLORATION = "exploration"  # Turn 2-3: Deep search
-    REFINEMENT = "refinement"    # Turn 4: Final answer
-
-@dataclass
-class SearchState:
-    """Tracks the state of a multi-turn search.
-    
-    Attributes:
-        query: Original search query
-        current_turn: Current turn number (1-indexed)
-        max_turns: Maximum turns allowed
-        phase: Current search phase
-        discovered_files: Files found so far
-        explored_paths: Paths already explored
-        result: Accumulated search result
-        should_terminate: Whether to terminate early
-    """
-    query: str
-    current_turn: int = 0
-    max_turns: int = 4
-    phase: SearchPhase = SearchPhase.DISCOVERY
-    discovered_files: Set[str] = field(default_factory=set)
-    explored_paths: Set[str] = field(default_factory=set)
-    result: FastContextResult = field(default_factory=FastContextResult)
-    should_terminate: bool = False
-    
-    # Thresholds for early termination
-    min_files_for_termination: int = 5
-    max_files_before_refinement: int = 20
-    
-    def advance_turn(self) -> None:
-        """Advance to the next turn and update phase."""
-        self.current_turn += 1
-        
-        if self.current_turn == 1:
-            self.phase = SearchPhase.DISCOVERY
-        elif self.current_turn < self.max_turns:
-            self.phase = SearchPhase.EXPLORATION
-        else:
-            self.phase = SearchPhase.REFINEMENT
-    
-    def check_early_termination(self) -> bool:
-        """Check if search should terminate early.
-        
-        Returns:
-            True if search should terminate
-        """
-        # Terminate if we have enough high-quality results
-        if len(self.discovered_files) >= self.min_files_for_termination:
-            high_relevance = sum(
-                1 for f in self.result.files 
-                if f.relevance_score >= 0.8
-            )
-            if high_relevance >= 3:
-                self.should_terminate = True
-                return True
-        
-        # Terminate if we've explored everything
-        if self.current_turn >= 2 and not self._has_unexplored_paths():
-            self.should_terminate = True
-            return True
-        
-        return False
-    
-    def _has_unexplored_paths(self) -> bool:
-        """Check if there are unexplored paths."""
-        # Simple heuristic: if we found files but haven't explored many paths
-        return len(self.discovered_files) > len(self.explored_paths) * 2
-
-class SearchStrategy:
-    """Orchestrates multi-turn search strategy.
-    
-    Implements the Fast Context search approach:
-    - Turn 1: Discovery - understand codebase structure
-    - Turn 2-3: Exploration - deep search for relevant code
-    - Turn 4: Refinement - finalize results
-    
-    Supports early termination when sufficient context is found.
-    """
-    
-    def __init__(
-        self,
-        workspace_path: str,
-        max_turns: int = 4,
-        max_parallel: int = 8
-    ):
-        """Initialize search strategy.
-        
-        Args:
-            workspace_path: Root directory for searches
-            max_turns: Maximum search turns
-            max_parallel: Maximum parallel tool calls per turn
-        """
-        self.workspace_path = workspace_path
-        self.max_turns = max_turns
-        self.max_parallel = max_parallel
-    
-    def create_state(self, query: str) -> SearchState:
-        """Create a new search state.
-        
-        Args:
-            query: Search query
-            
-        Returns:
-            New SearchState instance
-        """
-        state = SearchState(query=query, max_turns=self.max_turns)
-        state.result.query = query
-        return state
-    
-    def plan_discovery_turn(self, state: SearchState) -> ToolCallBatch:
-        """Plan the discovery turn (Turn 1).
-        
-        Focus on understanding codebase structure:
-        - List root directory
-        - Find common file patterns
-        - Initial grep for query terms
-        
-        Args:
-            state: Current search state
-            
-        Returns:
-            Batch of tool calls to execute
-        """
-        batch = ToolCallBatch(max_size=self.max_parallel)
-        query = state.query
-        
-        # List root directory
-        batch.add("list_directory", dir_path=self.workspace_path, recursive=False)
-        
-        # Find Python files (most common)
-        batch.add("glob_search", search_path=self.workspace_path, pattern="**/*.py", max_results=20)
-        
-        # Initial grep for query terms
-        query_words = query.lower().split()
-        for word in query_words[:3]:  # First 3 words
-            if len(word) >= 3:  # Skip short words
-                batch.add("grep_search", search_path=self.workspace_path, pattern=word, max_results=10)
-                if batch.is_full:
-                    break
-        
-        return batch
-    
-    def plan_exploration_turn(self, state: SearchState) -> ToolCallBatch:
-        """Plan an exploration turn (Turn 2-3).
-        
-        Deep search based on discovery results:
-        - Search in discovered directories
-        - Read promising files
-        - Follow references
-        
-        Args:
-            state: Current search state
-            
-        Returns:
-            Batch of tool calls to execute
-        """
-        batch = ToolCallBatch(max_size=self.max_parallel)
-        
-        # Read top files found so far
-        for file_match in state.result.files[:4]:
-            if file_match.path not in state.explored_paths:
-                batch.add("read_file", filepath=file_match.path, context_lines=5)
-                state.explored_paths.add(file_match.path)
-                if batch.is_full:
-                    break
-        
-        # Search in unexplored directories
-        unexplored_dirs = self._find_unexplored_dirs(state)
-        for dir_path in unexplored_dirs[:2]:
-            batch.add("list_directory", dir_path=dir_path, recursive=True, max_depth=2)
-            if batch.is_full:
-                break
-        
-        # Additional grep searches with refined patterns
-        if not batch.is_full:
-            refined_patterns = self._generate_refined_patterns(state)
-            for pattern in refined_patterns[:2]:
-                batch.add("grep_search", search_path=self.workspace_path, pattern=pattern, max_results=15)
-                if batch.is_full:
-                    break
-        
-        return batch
-    
-    def plan_refinement_turn(self, state: SearchState) -> ToolCallBatch:
-        """Plan the refinement turn (Turn 4).
-        
-        Finalize results:
-        - Read remaining important files
-        - Get specific line ranges
-        
-        Args:
-            state: Current search state
-            
-        Returns:
-            Batch of tool calls to execute
-        """
-        batch = ToolCallBatch(max_size=self.max_parallel)
-        
-        # Read top files that haven't been fully explored
-        for file_match in state.result.files[:self.max_parallel]:
-            if file_match.path not in state.explored_paths:
-                # Read specific line ranges if available
-                if file_match.line_ranges:
-                    for lr in file_match.line_ranges[:2]:
-                        batch.add(
-                            "read_file",
-                            filepath=file_match.path,
-                            start_line=max(1, lr.start - 5),
-                            end_line=lr.end + 5
-                        )
-                        if batch.is_full:
-                            break
-                else:
-                    batch.add("read_file", filepath=file_match.path)
-                
-                state.explored_paths.add(file_match.path)
-                if batch.is_full:
-                    break
-        
-        return batch
-    
-    def plan_next_turn(self, state: SearchState) -> Optional[ToolCallBatch]:
-        """Plan the next turn based on current state.
-        
-        Args:
-            state: Current search state
-            
-        Returns:
-            Batch of tool calls, or None if search should end
-        """
-        state.advance_turn()
-        
-        # Check for early termination
-        if state.should_terminate or state.current_turn > state.max_turns:
-            return None
-        
-        if state.check_early_termination():
-            return None
-        
-        # Plan based on phase
-        if state.phase == SearchPhase.DISCOVERY:
-            return self.plan_discovery_turn(state)
-        elif state.phase == SearchPhase.EXPLORATION:
-            return self.plan_exploration_turn(state)
-        else:  # REFINEMENT
-            return self.plan_refinement_turn(state)
-    
-    def process_results(
-        self,
-        state: SearchState,
-        tool_results: List[Any]
-    ) -> None:
-        """Process results from a turn and update state.
-        
-        Args:
-            state: Current search state
-            tool_results: Results from tool execution
-        """
-        for result in tool_results:
-            if isinstance(result, list):
-                # Grep or glob results
-                for item in result:
-                    if isinstance(item, dict):
-                        path = item.get("path", "")
-                        if path:
-                            state.discovered_files.add(path)
-                            
-                            # Create or update file match
-                            file_match = FileMatch(
-                                path=path,
-                                relevance_score=0.8,
-                                match_count=1
-                            )
-                            
-                            # Add line range if available
-                            line_num = item.get("line_number")
-                            if line_num:
-                                file_match.add_line_range(LineRange(
-                                    start=max(1, line_num - 2),
-                                    end=line_num + 2,
-                                    content=item.get("context"),
-                                    relevance_score=0.8
-                                ))
-                            
-                            state.result.add_file(file_match)
-            
-            elif isinstance(result, dict):
-                # Read file or list directory result
-                if result.get("success"):
-                    path = result.get("path", "")
-                    if path:
-                        state.explored_paths.add(path)
-                    
-                    # Handle directory listing
-                    entries = result.get("entries", [])
-                    for entry in entries:
-                        if not entry.get("is_dir"):
-                            state.discovered_files.add(entry.get("path", ""))
-    
-    def _find_unexplored_dirs(self, state: SearchState) -> List[str]:
-        """Find directories that haven't been explored.
-        
-        Args:
-            state: Current search state
-            
-        Returns:
-            List of unexplored directory paths
-        """
-        import os
-        
-        # Extract unique directories from discovered files
-        dirs = set()
-        for file_path in state.discovered_files:
-            dir_path = os.path.dirname(file_path)
-            if dir_path and dir_path not in state.explored_paths:
-                dirs.add(dir_path)
-        
-        return list(dirs)[:5]  # Limit to 5
-    
-    def _generate_refined_patterns(self, state: SearchState) -> List[str]:
-        """Generate refined search patterns based on results.
-        
-        Args:
-            state: Current search state
-            
-        Returns:
-            List of refined search patterns
-        """
-        patterns = []
-        query_words = state.query.lower().split()
-        
-        # Combine query words
-        if len(query_words) >= 2:
-            patterns.append(f"{query_words[0]}.*{query_words[1]}")
-        
-        # Add common code patterns
-        for word in query_words[:2]:
-            if len(word) >= 3:
-                patterns.append(f"def {word}")
-                patterns.append(f"class {word}")
-        
-        return patterns[:4]

src/praisonai-agents/praisonaiagents/context/fast/search_tools.py

@@ -15,7 +15,6 @@ import re
 import fnmatch
 from pathlib import Path
 from typing import List, Dict, Any, Optional, Set
-import logging
 from praisonaiagents._logging import get_logger
 
 logger = get_logger(__name__)

src/praisonai-agents/praisonaiagents/context/session_tracker.py

@@ -9,7 +9,6 @@ from dataclasses import dataclass, field, asdict
 from typing import Any, Dict, List, Optional
 from datetime import datetime, timezone
 import json
-import logging
 from praisonaiagents._logging import get_logger
 
 logger = get_logger(__name__)

src/praisonai-agents/praisonaiagents/context/store.py

@@ -18,7 +18,6 @@ Zero Performance Impact:
 
 import threading
 import json
-import logging
 from praisonaiagents._logging import get_logger
 from typing import Dict, List, Any, Optional
 from dataclasses import dataclass

src/praisonai-agents/praisonaiagents/escalation/doom_loop.py

@@ -10,7 +10,6 @@ from typing import Any, Dict, List, Optional
 from enum import Enum
 import time
 import hashlib
-import logging
 from praisonaiagents._logging import get_logger
 
 logger = get_logger(__name__)

src/praisonai-agents/praisonaiagents/escalation/observability.py

@@ -5,7 +5,6 @@ Provides lightweight tracing and metrics collection for escalation execution.
 Opt-in only - no overhead when not enabled.
 """
 
-import logging
 from praisonaiagents._logging import get_logger
 import time
 from dataclasses import dataclass, field

src/praisonai-agents/praisonaiagents/escalation/pipeline.py

@@ -4,7 +4,6 @@ Escalation Pipeline for PraisonAI Agents.
 Implements progressive escalation from direct response to full autonomous mode.
 """
 
-import logging
 from praisonaiagents._logging import get_logger
 import time
 from typing import Any, Dict, List, Optional, Callable

src/praisonai-agents/praisonaiagents/eval/accuracy.py

@@ -5,7 +5,6 @@ Evaluates agent output accuracy by comparing against expected output using LLM-a
 """
 
 import os
-import logging
 from praisonaiagents._logging import get_logger
 from typing import Callable, Optional, Union, TYPE_CHECKING
 

src/praisonai-agents/praisonaiagents/eval/base.py

@@ -7,7 +7,6 @@ This module provides the abstract base class that all evaluators inherit from.
 from abc import ABC, abstractmethod
 from typing import Any, Dict, Optional, Union, TYPE_CHECKING
 import uuid
-import logging
 from praisonaiagents._logging import get_logger
 
 if TYPE_CHECKING:

src/praisonai-agents/praisonaiagents/eval/criteria.py

@@ -5,7 +5,6 @@ Evaluates agent outputs against custom criteria using LLM-as-judge.
 """
 
 import os
-import logging
 from praisonaiagents._logging import get_logger
 from typing import Callable, Literal, Optional, Union, TYPE_CHECKING
 

src/praisonai-agents/praisonaiagents/eval/grader.py

@@ -9,7 +9,6 @@ that was duplicated across multiple evaluators.
 """
 
 import os
-import logging
 from praisonaiagents._logging import get_logger
 from dataclasses import dataclass, field, asdict
 from datetime import datetime, timezone

src/praisonai-agents/praisonaiagents/eval/judge.py

@@ -15,7 +15,6 @@ Example:
 """
 
 import os
-import logging
 from praisonaiagents._logging import get_logger
 from dataclasses import dataclass
 from typing import Any, Dict, List, Optional, Type, TYPE_CHECKING

src/praisonai-agents/praisonaiagents/eval/loop.py

@@ -18,7 +18,6 @@ Example:
 
 import time
 import math
-import logging
 from praisonaiagents._logging import get_logger
 from typing import TYPE_CHECKING, Optional, Callable, Any, List
 from dataclasses import dataclass

src/praisonai-agents/praisonaiagents/eval/media.py

@@ -7,7 +7,6 @@ and file-based verification for audio/video.
 """
 
 import os
-import logging
 from praisonaiagents._logging import get_logger
 from dataclasses import dataclass, field
 from typing import Any, Dict, Literal, Optional

src/praisonai-agents/praisonaiagents/eval/performance.py

@@ -5,7 +5,6 @@ Measures runtime and memory usage of agent executions or functions.
 """
 
 import time
-import logging
 from praisonaiagents._logging import get_logger
 from typing import Callable, Optional, TYPE_CHECKING
 

src/praisonai-agents/praisonaiagents/eval/reliability.py

@@ -4,7 +4,6 @@ Reliability evaluator for PraisonAI Agents.
 Evaluates agent reliability by verifying expected tool calls are made.
 """
 
-import logging
 from praisonaiagents._logging import get_logger
 from typing import Dict, List, Optional, Set, Any, TYPE_CHECKING
 

src/praisonai-agents/praisonaiagents/eval/tokens.py

@@ -18,7 +18,6 @@ Example:
     ...     # Split into chunks
 """
 
-import logging
 from praisonaiagents._logging import get_logger
 from typing import Dict, Optional, Union
 

src/praisonai-agents/praisonaiagents/eval/utils.py

@@ -3,7 +3,6 @@ Utility functions for PraisonAI Agents evaluation framework.
 """
 
 import json
-import logging
 from praisonaiagents._logging import get_logger
 from pathlib import Path
 from typing import Any, Dict, Optional, Union

src/praisonai-agents/praisonaiagents/gateway/__init__.py

@@ -70,6 +70,10 @@ from .protocols import (
     GatewayConcurrencyPolicyProtocol,
     GatewayConcurrencyPolicy,  # backward-compat alias
     ConcurrencyLimitPolicy,
+    # Gateway resource-pressure admission (Issue #3445)
+    ResourceSample,
+    ResourcePressurePolicyProtocol,
+    MemoryPressurePolicy,
     # Gateway rate-limit admission (Issue #2532)
     RateLimitDecision,
     RateLimitPolicyProtocol,
@@ -277,6 +281,10 @@ __all__ = [
     "GatewayConcurrencyPolicyProtocol",
     "GatewayConcurrencyPolicy",
     "ConcurrencyLimitPolicy",
+    # Gateway resource-pressure admission (Issue #3445)
+    "ResourceSample",
+    "ResourcePressurePolicyProtocol",
+    "MemoryPressurePolicy",
     # Gateway rate-limit admission (Issue #2532)
     "RateLimitDecision",
     "RateLimitPolicyProtocol",

src/praisonai-agents/praisonaiagents/gateway/config.py

@@ -63,6 +63,9 @@ class SessionConfig:
         max_messages: Maximum messages to keep in history (0 = unlimited)
         persist: Whether to persist session state
         persist_path: Path for session persistence
+        store: Persistence backend when ``persist`` is set — ``"sqlite"``
+            (default: transcripts in a WAL SQLite DB with concurrent readers
+            and indexed lookups) or ``"file"`` (legacy per-session JSON files)
         resume_window: How long (seconds) a session stays resumable after disconnect
         max_inbox: Maximum queued messages per session (0 = unlimited, default 256)
         metadata: Additional session metadata
@@ -73,6 +76,7 @@ class SessionConfig:
     max_messages: int = 1000
     persist: bool = False
     persist_path: Optional[str] = None
+    store: str = "sqlite"  # "sqlite" (concurrent, indexed) | "file" (legacy JSON)
     resume_window: int = 86400  # 24 hours default
     max_inbox: int = 256  # Default bounded queue size
     metadata: Dict[str, Any] = field(default_factory=dict)
@@ -90,6 +94,10 @@ class SessionConfig:
             raise ValueError("max_messages must be >= 0")
         if self.resume_window < 0:
             raise ValueError("resume_window must be >= 0")
+        if self.store not in ("sqlite", "file"):
+            raise ValueError(
+                f"Invalid session store {self.store!r}; expected 'sqlite' or 'file'"
+            )
     
     def to_dict(self) -> Dict[str, Any]:
         """Convert to dictionary."""
@@ -98,6 +106,7 @@ class SessionConfig:
             "max_messages": self.max_messages,
             "persist": self.persist,
             "persist_path": self.persist_path,
+            "store": self.store,
             "resume_window": self.resume_window,
             "max_inbox": self.max_inbox,
             "metadata": self.metadata,
@@ -685,6 +694,7 @@ class MultiChannelGatewayConfig:
                     max_messages=sc_data.get("max_messages", 1000),
                     persist=sc_data.get("persist", False),
                     persist_path=sc_data.get("persist_path"),
+                    store=sc_data.get("store", "sqlite"),
                     resume_window=sc_data.get("resume_window", 86400),
                     max_inbox=sc_data.get("max_inbox", 256),
                     metadata=sc_data.get("metadata", {}),

src/praisonai-agents/praisonaiagents/gateway/protocols.py

@@ -2928,6 +2928,135 @@ class ConcurrencyLimitPolicy:
 GatewayConcurrencyPolicy = GatewayConcurrencyPolicyProtocol
 
 
+# ---------------------------------------------------------------------------
+# Gateway resource-pressure admission (Issue #3445)
+#
+# Admission today is concurrency/CPU-scaled and blind to memory; on a small
+# always-on host a burst of concurrent turns drives RSS up until the OOM
+# killer fires — the failure a $5 box hits first. This adds a pure, import-
+# free decision that maps a resource *sample* (current RSS) onto the existing
+# :class:`AdmissionDecision` so the gate can queue under soft pressure and
+# shed under hard pressure *before* the process is killed. It reuses the
+# admission seam (no new subsystem) and sits beside the concurrency / rate-
+# limit / scale-to-zero policy family. The live sampler (reading
+# ``resource.getrusage`` / optional ``psutil``) and the wiring into the gate
+# live in the wrapper; this contract keeps the decision testable in isolation.
+# ---------------------------------------------------------------------------
+
+
+@dataclass(frozen=True)
+class ResourceSample:
+    """A point-in-time snapshot of the gateway process's resource usage.
+
+    Attributes:
+        rss_mb: Resident set size in mebibytes, or ``None`` when the platform
+            cannot report it (the policy then admits and self-disables so the
+            monitor never crashes the gateway it protects).
+    """
+
+    rss_mb: Optional[float] = None
+
+
+@runtime_checkable
+class ResourcePressurePolicyProtocol(Protocol):
+    """Protocol for memory/resource-aware admission decisions.
+
+    Pure, import-free decision contract consumed by the wrapper's admission
+    gate. The wrapper samples its own resource usage on a lightweight cadence
+    and hands the policy a :class:`ResourceSample`; the policy returns an
+    :class:`AdmissionDecision` — ``ADMIT`` below the soft threshold, ``QUEUE``
+    to apply backpressure above it, and ``REJECT`` above the hard threshold so
+    the process sheds load before the OOM killer fires. Sampling and
+    enforcement (the ``asyncio.Semaphore`` ceiling and bounded wait queue)
+    live in the wrapper; this keeps the *decision* provable in isolation,
+    symmetric with :class:`GatewayConcurrencyPolicyProtocol`.
+
+    A config-driven default (:class:`MemoryPressurePolicy`) is provided for
+    the common "soft/hard RSS threshold" case.
+    """
+
+    def evaluate(self, sample: ResourceSample) -> AdmissionDecision:
+        """Return an :class:`AdmissionDecision` for the supplied sample."""
+        ...
+
+
+class MemoryPressurePolicy:
+    """Config-driven RSS-threshold resource-pressure policy.
+
+    The default wired by the ``max_rss_mb`` gateway config key
+    (``BotOS(max_rss_mb=...)`` / ``gateway.yaml``) and the
+    ``AdmissionGate(resource_policy=...)`` Python surface. It is intentionally
+    minimal and dependency-free so the decision lives in core and is provable
+    in isolation; the wrapper owns the live sampler and the side effects
+    (queue / shed / busy ack).
+
+    The decision, given a sample's ``rss_mb``:
+
+    * ``ADMIT`` while ``rss_mb < soft_rss_mb`` (or the platform can't report
+      memory, so ``rss_mb is None`` — never block on a missing signal).
+    * ``QUEUE`` (apply backpressure) while ``soft_rss_mb <= rss_mb <
+      hard_rss_mb``.
+    * ``REJECT`` (shed with a busy ack) while ``rss_mb >= hard_rss_mb``.
+
+    A ``hard_rss_mb`` of ``0`` disables pressure-based shedding entirely
+    (every sample admits) — the legacy default when no threshold is set.
+
+    Example::
+
+        MemoryPressurePolicy(soft_rss_mb=400, hard_rss_mb=550)
+    """
+
+    def __init__(
+        self,
+        soft_rss_mb: float = 0.0,
+        hard_rss_mb: float = 0.0,
+    ):
+        try:
+            soft = float(soft_rss_mb or 0.0)
+        except (TypeError, ValueError) as err:
+            raise ValueError(
+                f"soft_rss_mb must be a number, got {soft_rss_mb!r}"
+            ) from err
+        try:
+            hard = float(hard_rss_mb or 0.0)
+        except (TypeError, ValueError) as err:
+            raise ValueError(
+                f"hard_rss_mb must be a number, got {hard_rss_mb!r}"
+            ) from err
+        if soft < 0:
+            raise ValueError(f"soft_rss_mb must be >= 0, got {soft_rss_mb!r}")
+        if hard < 0:
+            raise ValueError(f"hard_rss_mb must be >= 0, got {hard_rss_mb!r}")
+        # A soft threshold above the hard one would queue turns that should be
+        # shed; fail fast rather than silently invert the pressure ladder.
+        if soft and hard and soft > hard:
+            raise ValueError(
+                f"soft_rss_mb ({soft_rss_mb!r}) must be <= "
+                f"hard_rss_mb ({hard_rss_mb!r})"
+            )
+        self.soft_rss_mb = soft
+        self.hard_rss_mb = hard
+
+    @property
+    def enabled(self) -> bool:
+        """Whether pressure-based admission is active (a threshold is set)."""
+        return self.soft_rss_mb > 0 or self.hard_rss_mb > 0
+
+    def evaluate(self, sample: ResourceSample) -> AdmissionDecision:
+        # Disabled, or the platform can't report memory: never block on a
+        # missing/absent signal — admit and let concurrency limits apply.
+        if not self.enabled:
+            return AdmissionDecision.ADMIT
+        rss = getattr(sample, "rss_mb", None)
+        if rss is None:
+            return AdmissionDecision.ADMIT
+        if self.hard_rss_mb and rss >= self.hard_rss_mb:
+            return AdmissionDecision.REJECT
+        if self.soft_rss_mb and rss >= self.soft_rss_mb:
+            return AdmissionDecision.QUEUE
+        return AdmissionDecision.ADMIT
+
+
 # ---------------------------------------------------------------------------
 # Gateway rate-limit admission (Issue #2532)
 #

src/praisonai-agents/praisonaiagents/guardrails/llm_guardrail.py

@@ -5,7 +5,6 @@ This module provides LLM-powered guardrails that can validate task outputs
 using natural language descriptions, similar to CrewAI's implementation.
 """
 
-import logging
 from praisonaiagents._logging import get_logger
 from typing import Any, Tuple, Union, Optional, Dict
 from pydantic import BaseModel

src/praisonai-agents/praisonaiagents/hooks/query_protocol.py

@@ -1,13 +0,0 @@
-"""Hooks query protocol for UI/API consumers."""
-
-from __future__ import annotations
-
-from typing import Dict, List, Protocol, runtime_checkable
-
-
-@runtime_checkable
-class HooksQueryProtocol(Protocol):
-    """Read path for registered hooks."""
-
-    def list_hooks_for_api(self) -> List[Dict]:
-        ...

src/praisonai-agents/praisonaiagents/hooks/registry.py

@@ -4,7 +4,6 @@ Hook Registry for PraisonAI Agents.
 Manages registration and lookup of hooks for different events.
 """
 
-import logging
 import threading
 from praisonaiagents._logging import get_logger
 from typing import Dict, List, Optional, Callable, Union

src/praisonai-agents/praisonaiagents/hooks/runner.py

@@ -9,7 +9,6 @@ import os
 import json
 import time
 import asyncio
-import logging
 from praisonaiagents._logging import get_logger
 import subprocess
 from typing import List, Optional, Dict, Any

src/praisonai-agents/praisonaiagents/hooks/types.py

@@ -36,6 +36,12 @@ class HookEvent(str, Enum):
     # LLM lifecycle
     BEFORE_LLM = "before_llm"
     AFTER_LLM = "after_llm"
+
+    # Prompt-cache stability (advisory): fired when a turn's cached prompt
+    # prefix (model + tool schemas + system-prompt fingerprint) changes from
+    # the previous turn, so a long-lived conversation's provider prompt cache
+    # will miss. Payload carries the old/new signature and a reason.
+    PROMPT_PREFIX_INVALIDATED = "prompt_prefix_invalidated"
     
     # Error handling
     ON_ERROR = "on_error"

src/praisonai-agents/praisonaiagents/knowledge/adapters/mem0_adapter.py

@@ -7,7 +7,6 @@ Handles all normalization to ensure metadata is ALWAYS a dict (never None).
 LAZY IMPORT: mem0 is only imported when this adapter is instantiated.
 """
 
-import logging
 from praisonaiagents._logging import get_logger
 import os
 from typing import Any, Dict, List, Optional

src/praisonai-agents/praisonaiagents/knowledge/adapters/mongodb_adapter.py

@@ -8,7 +8,6 @@ LAZY IMPORT: pymongo is only imported when this adapter is instantiated.
 """
 
 import os
-import logging
 from praisonaiagents._logging import get_logger
 from datetime import datetime
 from typing import Any, Dict, List, Optional

src/praisonai-agents/praisonaiagents/knowledge/index.py

@@ -10,7 +10,6 @@ Implementations are provided by the wrapper layer.
 from dataclasses import dataclass, field
 from typing import Any, Callable, Dict, List, Optional, Protocol, runtime_checkable
 from enum import Enum
-import logging
 from praisonaiagents._logging import get_logger
 import math
 

src/praisonai-agents/praisonaiagents/knowledge/query_engine.py

@@ -10,7 +10,6 @@ Implementations are provided by the wrapper layer.
 from dataclasses import dataclass, field
 from typing import Any, Callable, Dict, List, Optional, Protocol, runtime_checkable
 from enum import Enum
-import logging
 from praisonaiagents._logging import get_logger
 
 logger = get_logger(__name__)

src/praisonai-agents/praisonaiagents/knowledge/readers.py

@@ -10,7 +10,6 @@ Implementations are provided by the wrapper layer (praisonai.adapters.readers).
 from dataclasses import dataclass, field
 from typing import Any, Callable, Dict, List, Optional, Protocol, runtime_checkable
 import os
-import logging
 from praisonaiagents._logging import get_logger
 
 logger = get_logger(__name__)

src/praisonai-agents/praisonaiagents/knowledge/rerankers.py

@@ -9,7 +9,6 @@ Implementations are provided by praisonai-tools or wrapper layer.
 
 from dataclasses import dataclass
 from typing import Any, Callable, Dict, List, Optional, Protocol, runtime_checkable
-import logging
 from praisonaiagents._logging import get_logger
 
 logger = get_logger(__name__)

src/praisonai-agents/praisonaiagents/knowledge/retrieval.py

@@ -10,7 +10,6 @@ Implementations are provided by the wrapper layer.
 from dataclasses import dataclass, field
 from typing import Any, Callable, Dict, List, Optional, Protocol, runtime_checkable
 from enum import Enum
-import logging
 from praisonaiagents._logging import get_logger
 
 logger = get_logger(__name__)

src/praisonai-agents/praisonaiagents/knowledge/vector_store.py

@@ -9,7 +9,6 @@ Implementations are provided by praisonai-tools or wrapper layer.
 
 from dataclasses import dataclass, field
 from typing import Any, Callable, Dict, List, Optional, Protocol, runtime_checkable
-import logging
 from praisonaiagents._logging import get_logger
 
 logger = get_logger(__name__)

src/praisonai-agents/praisonaiagents/llm/failover.py

@@ -10,7 +10,6 @@ Heavy implementations live in the praisonai wrapper.
 
 from __future__ import annotations
 
-import logging
 from praisonaiagents._logging import get_logger
 import time
 from dataclasses import dataclass, field

src/praisonai-agents/praisonaiagents/llm/llm.py

@@ -714,30 +714,6 @@ Respond with ONLY a valid JSON tool call in this format:
 
         return any(indicator in error_str or indicator in error_type for indicator in indicators)
 
-    def _classify_error_and_should_retry_legacy(self, error: Exception, attempt: int = 1) -> tuple[str, bool, float]:
-        """Legacy error classification - deprecated, use resolve_failover_decision() instead.
-        
-        Args:
-            error: Exception to classify
-            attempt: Current attempt number (1-based)
-            
-        Returns:
-            Tuple of (category, should_retry, retry_delay)
-        """
-        import warnings
-        warnings.warn(
-            "_classify_error_and_should_retry is deprecated, use resolve_failover_decision() instead",
-            DeprecationWarning,
-            stacklevel=2
-        )
-        
-        # Delegate to new typed classification system
-        decision = self.resolve_failover_decision(error, {"attempt": attempt, "max_retries": self._max_retries})
-        return decision.reason, decision.is_retryable, decision.backoff_ms / 1000.0
-    
-    # Backward compatibility alias for existing code
-    _classify_error_and_should_retry = _classify_error_and_should_retry_legacy
-    
     def classify_error_kind(self, error: Exception) -> AgentErrorKind:
         """
         Classify error into typed AgentErrorKind instead of freeform strings.

src/praisonai-agents/praisonaiagents/llm/model_router.py

@@ -6,7 +6,6 @@ LLM model/provider based on task complexity, cost considerations, and model capa
 """
 
 import os
-import logging
 from praisonaiagents._logging import get_logger
 from typing import Dict, List, Optional, Tuple
 from dataclasses import dataclass

src/praisonai-agents/praisonaiagents/llm/rate_limiter.py

@@ -23,7 +23,6 @@ Usage:
 
 import time
 import asyncio
-import logging
 import threading
 from praisonaiagents._logging import get_logger
 from dataclasses import dataclass, field

src/praisonai-agents/praisonaiagents/lsp/client.py

@@ -7,7 +7,6 @@ Provides Language Server Protocol client implementation.
 import os
 import json
 import asyncio
-import logging
 from praisonaiagents._logging import get_logger
 from typing import Optional, List, Dict, Any
 from pathlib import Path

src/praisonai-agents/praisonaiagents/mcp/mcp.py

@@ -282,7 +282,20 @@ class MCP:
         agent.start("What is the stock price of Tesla?")
         ```
     """
-    
+
+    # Process-level registry of sanitized MCP server names that have been
+    # namespaced via with_tool_prefix(), mirroring how tools/registry.py tracks
+    # tool names. Lets skills' CapabilityValidator discover connected servers
+    # instead of always failing closed (issue #3307).
+    _active_server_names: set = set()
+    _active_server_names_lock = threading.Lock()
+
+    @classmethod
+    def list_active_server_names(cls) -> set:
+        """Return the set of sanitized names of MCP servers namespaced this run."""
+        with cls._active_server_names_lock:
+            return set(cls._active_server_names)
+
     def __init__(self, command_or_string=None, args=None, *, command=None, timeout=60, debug=False, 
                  allowed_tools: Optional[List[str]] = None, disabled_tools: Optional[List[str]] = None, **kwargs):
         """
@@ -834,6 +847,15 @@ class MCP:
 
         self._tool_prefix = sanitized
 
+        # Record this server in the process-level registry so skills'
+        # CapabilityValidator can discover it (issue #3307). Store both the
+        # original name and its sanitized form so a skill requirement matches
+        # regardless of which spelling it declares.
+        with type(self)._active_server_names_lock:
+            if prefix:
+                type(self)._active_server_names.add(prefix)
+            type(self)._active_server_names.add(sanitized)
+
         # Rename already-generated callable tools. Dispatch inside each
         # wrapper closes over the original tool name, so only the public
         # __name__/__qualname__ needs updating for schema construction.