Release v4.6.38

* fix: resolve architectural gaps in src/praisonai/praisonai (fixes #1657)

- Fix framework adapter dispatch kwargs mismatch by adding required keyword-only arguments to AutoGenAdapter, AutoGenV4Adapter, and AG2Adapter run() methods
- Fix InteractiveRuntime lifecycle management by keeping runtime alive during agent execution instead of stopping it prematurely
- Consolidate tools.py loading paths by making ToolResolver the single source of truth and replacing duplicate loading logic in agents_generator.py
- Remove unused load_tools_from_tools_py() method
- Update ToolResolver to use _safe_loader for consistent security model

Co-authored-by: MervinPraison <[email protected]>

* fix: define tools_path in ToolResolver local loader logging

Agent-Logs-Url: https://github.com/MervinPraison/PraisonAI/sessions/bee41da9-2153-41cd-9834-439aa753a848

Co-authored-by: MervinPraison <[email protected]>

* fix: resolve critical NameError and event loop leak

- Fix NameError in ToolResolver._load_local_tools() for undefined tools_path variable
- Fix event loop leak in AgentsGenerator when InteractiveRuntime startup fails
- Change autogen_v4/ag2 adapters to raise NotImplementedError instead of returning strings

🤖 Generated with Claude Code

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

---------

Co-authored-by: praisonai-triage-agent[bot] <272766704+praisonai-triage-agent[bot]@users.noreply.github.com>
Co-authored-by: MervinPraison <[email protected]>
Co-authored-by: copilot-swe-agent[bot] <[email protected]>
Co-authored-by: MervinPraison <[email protected]>

.env.example

@@ -0,0 +1,43 @@
+# PraisonAI Environment Variables
+# Copy this file to .env and update with your actual values
+
+# === Required ===
+OPENAI_API_KEY=sk-...          # OpenAI key for LLM calls. Get yours at https://platform.openai.com
+
+# === Required for Claw web-search tool ===
+TAVILY_API_KEY=tvly-...        # Get yours at https://app.tavily.com (free tier available)
+
+# === Optional: Claw dashboard security ===
+PRAISONAI_ALLOW_LOCAL_TOOLS=0  # Set to 1 to enable local shell tools (security risk)
+
+# === Optional: Alternative LLM Providers ===
+ANTHROPIC_API_KEY=sk-ant-...   # Anthropic Claude models
+GOOGLE_API_KEY=...             # Google Gemini models  
+GROQ_API_KEY=gsk_...           # Groq (fast inference)
+COHERE_API_KEY=...             # Cohere models
+AZURE_OPENAI_API_KEY=...       # Azure OpenAI
+AZURE_OPENAI_ENDPOINT=...      # Azure OpenAI endpoint
+
+# === Optional: Memory backends ===
+MEM0_API_KEY=...               # Mem0 memory service
+REDIS_URL=redis://localhost:6379  # Redis for state management
+
+# === Optional: Observability ===
+LANGFUSE_SECRET_KEY=sk-lf-...  # Langfuse tracing
+LANGFUSE_PUBLIC_KEY=pk-lf-...  # Langfuse public key
+
+# === Optional: Bot platforms ===
+TELEGRAM_BOT_TOKEN=...         # Telegram bot token
+DISCORD_BOT_TOKEN=...          # Discord bot token  
+SLACK_BOT_TOKEN=xoxb-...       # Slack bot token
+SLACK_APP_TOKEN=xapp-...       # Slack app token
+WHATSAPP_ACCESS_TOKEN=...      # WhatsApp bot access token
+WHATSAPP_PHONE_NUMBER_ID=...   # WhatsApp phone number ID
+
+# === Optional: Database ===
+DATABASE_URL=sqlite:///~/.praison/database.sqlite  # Database connection string
+
+# === Optional: Development ===
+LOGLEVEL=INFO                  # Logging level (DEBUG, INFO, WARNING, ERROR)
+CHAINLIT_AUTH_SECRET=...       # Chainlit authentication secret
+DEBUG=false                    # Enable debug mode

README.md

@@ -294,8 +294,35 @@ def search(query: str) -> str:
 
 @tool
 def calculate(expression: str) -> float:
-    """Evaluate a math expression."""
-    return eval(expression)
+    """Safely evaluate a numeric arithmetic expression."""
+    import ast
+    import operator
+    
+    # Define allowed operations
+    _OPS = {
+        ast.Add: operator.add,
+        ast.Sub: operator.sub,
+        ast.Mult: operator.mul,
+        ast.Div: operator.truediv,
+        ast.Pow: operator.pow,
+        ast.USub: operator.neg,
+        ast.UAdd: operator.pos,
+    }
+    
+    def _safe_eval(node):
+        if isinstance(node, ast.Constant) and isinstance(node.value, (int, float)):
+            return node.value
+        elif isinstance(node, ast.BinOp) and type(node.op) in _OPS:
+            return _OPS[type(node.op)](_safe_eval(node.left), _safe_eval(node.right))
+        elif isinstance(node, ast.UnaryOp) and type(node.op) in _OPS:
+            return _OPS[type(node.op)](_safe_eval(node.operand))
+        else:
+            raise ValueError("Unsupported expression")
+    
+    try:
+        return _safe_eval(ast.parse(expression, mode="eval").body)
+    except (ValueError, SyntaxError, TypeError, ZeroDivisionError, OverflowError):
+        raise ValueError("Invalid arithmetic expression")
 
 agent = Agent(
     instructions="You are a helpful assistant",
@@ -304,6 +331,7 @@ agent = Agent(
 agent.start("Search for AI news and calculate 15*4")
 ```
 
+> ⚠️ **Security Note:** Never use `eval()`, `exec()`, or `subprocess` in tool functions that process LLM-generated or user-supplied input. Always validate and sanitize inputs to prevent code injection attacks.
 > 📖 [Full tools docs](https://docs.praison.ai/docs/tools/tools) — BaseTool, tool packages, 100+ built-in tools
 
 ### 5. Persistence (Databases)
@@ -330,6 +358,15 @@ pip install "praisonai[claw]"
 praisonai claw
 ```
 
+#### Required Environment Variables
+
+Copy `.env.example` to `.env` and configure the following variables:
+
+| Variable | Required | Description |
+|----------|----------|-------------|
+| `OPENAI_API_KEY` | Yes | OpenAI API key for all LLM calls |
+| `TAVILY_API_KEY` | Yes (Claw) | Tavily key for the built-in web-search tool. Get one free at https://app.tavily.com |
+
 Open **http://localhost:8082** — the dashboard comes with 13 built-in pages: Chat, Agents, Memory, Knowledge, Channels, Guardrails, Cron, and more. Add messaging channels directly from the UI.
 
 > 📖 [Full Claw docs](https://docs.praison.ai/docs/concepts/claw) — platform tokens, CLI options, Docker, and YAML agent mode

api.md

@@ -787,6 +787,9 @@ Methods:
 * <code title="cli">praisonai bot email <a href="./src/praisonai/praisonai/cli/commands/bot.py">--help</a></code>
 * <code title="cli">praisonai bot install-daemon <a href="./src/praisonai/praisonai/cli/commands/bot.py">--help</a></code>
 * <code title="cli">praisonai bot linear <a href="./src/praisonai/praisonai/cli/commands/bot.py">--help</a></code>
+* <code title="cli">praisonai bot list <a href="./src/praisonai/praisonai/cli/commands/bot.py">--help</a></code>
+* <code title="cli">praisonai bot purge <a href="./src/praisonai/praisonai/cli/commands/bot.py">--help</a></code>
+* <code title="cli">praisonai bot replay <a href="./src/praisonai/praisonai/cli/commands/bot.py">--help</a></code>
 * <code title="cli">praisonai bot slack <a href="./src/praisonai/praisonai/cli/commands/bot.py">--help</a></code>
 * <code title="cli">praisonai bot start <a href="./src/praisonai/praisonai/cli/commands/bot.py">--help</a></code>
 * <code title="cli">praisonai bot telegram <a href="./src/praisonai/praisonai/cli/commands/bot.py">--help</a></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>=4.6.37" \
+    "praisonai>=4.6.38" \
     "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>=4.6.37" \
+    "praisonai>=4.6.38" \
     "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>=4.6.37" \
+    "praisonai>=4.6.38" \
     "praisonai[ui]" \
     "praisonai[crewai]"
 

examples/scientific_writing/agents.yaml

@@ -0,0 +1,40 @@
+# Scientific paper workflow — YAML equivalent of multi_agent_paper.py
+# Run with:
+#   praisonai agents run --file examples/scientific_writing/agents.yaml
+framework: praisonai
+topic: "Climate change effects on coral reef biodiversity"
+
+roles:
+  literature_reviewer:
+    role: "Literature Reviewer"
+    goal: "Survey recent academic work on {topic} and produce an APA review."
+    backstory: "Expert in academic literature surveying and citation hygiene."
+    llm: "gpt-4o-mini"
+    tasks:
+      review_literature:
+        description: "Produce a concise literature review with 5-8 APA citations."
+        expected_output: "APA-formatted literature review."
+
+  methodology_designer:
+    role: "Methodology Designer"
+    goal: "Design a reproducible research methodology for {topic}."
+    backstory: "Specialises in rigorous experimental design."
+    llm: "gpt-4o-mini"
+    tasks:
+      design_methodology:
+        description: "Write a reproducible methods section in LaTeX."
+        expected_output: "LaTeX methods section."
+
+  scientific_writer:
+    role: "Scientific Writer"
+    goal: "Assemble the final LaTeX paper on {topic}."
+    backstory: >-
+      Specialised in LaTeX-formatted academic papers, fine-tuned on
+      scientific literature (CAJAL-4B checkpoint).
+    llm: "huggingface/Agnuxo/CAJAL-4B-P2PCLAW"
+    tasks:
+      write_paper:
+        description: >-
+          Combine the literature review and methodology into a full
+          scientific paper on {topic}. Use LaTeX formatting.
+        expected_output: "Complete LaTeX paper."

examples/scientific_writing/multi_agent_paper.py

@@ -0,0 +1,73 @@
+"""Multi-agent scientific paper workflow (Researcher -> Methodologist -> Writer).
+
+Demonstrates the agent-centric pattern from AGENTS.md: compose specialised
+Agents with ``AgentTeam`` + sequential ``Task``s instead of creating custom
+Agent subclasses.  The writer uses the CAJAL-4B HuggingFace model; the
+reviewer and methodologist use general-purpose LLMs.
+
+Usage:
+    python examples/scientific_writing/multi_agent_paper.py
+"""
+from praisonaiagents import Agent, AgentTeam, Task
+
+from scientific_writer import (  # noqa: E402 — example imports a sibling file
+    build_scientific_writer,
+    format_citation,
+    format_latex_section,
+)
+
+
+literature_reviewer = Agent(
+    name="Literature Reviewer",
+    instructions=(
+        "You are an expert at surveying academic literature. "
+        "Produce a concise literature review with 5-8 key citations in APA."
+    ),
+    tools=[format_citation],
+)
+
+methodology_designer = Agent(
+    name="Methodology Designer",
+    instructions=(
+        "You design rigorous research methodologies. "
+        "Output a clear, reproducible methods section."
+    ),
+    tools=[format_latex_section],
+)
+
+scientific_writer = build_scientific_writer()
+
+
+def run(topic: str) -> str:
+    """Run the 3-agent workflow for a given research ``topic``."""
+    t1 = Task(
+        name="review_literature",
+        description=f"Review literature on: {topic}",
+        agent=literature_reviewer,
+        expected_output="APA literature review.",
+    )
+    t2 = Task(
+        name="design_methodology",
+        description=f"Design research methodology for: {topic}",
+        agent=methodology_designer,
+        expected_output="LaTeX methods section.",
+    )
+    t3 = Task(
+        name="write_paper",
+        description=(
+            f"Combine the literature review and methodology into a full "
+            f"scientific paper on: {topic}. Use LaTeX formatting."
+        ),
+        agent=scientific_writer,
+        expected_output="Complete LaTeX paper.",
+    )
+    team = AgentTeam(
+        agents=[literature_reviewer, methodology_designer, scientific_writer],
+        tasks=[t1, t2, t3],
+    )
+    return team.start()
+
+
+if __name__ == "__main__":
+    result = run("Transformer architectures for protein folding prediction")
+    print(result)

examples/scientific_writing/scientific_writer.py

@@ -0,0 +1,85 @@
+"""Scientific Paper Writer — single-agent example using the CAJAL model.
+
+CAJAL (``Agnuxo/CAJAL-4B-P2PCLAW``) is a 4B-parameter HuggingFace model
+specialised for LaTeX-formatted academic writing.  This example shows how
+to use it with a regular ``Agent`` and ``@tool`` functions — no new Agent
+subclass is needed.  Run 3 ways: Python (this file), CLI, or YAML.
+
+Requirements:
+    pip install "praisonaiagents[llm]"          # for litellm / HuggingFace
+    export HUGGINGFACE_API_KEY=...              # or run a local inference server
+
+Usage:
+    python examples/scientific_writing/scientific_writer.py
+"""
+from praisonaiagents import Agent, tool
+
+
+@tool
+def format_latex_section(title: str, content: str) -> str:
+    """Wrap prose content in a LaTeX ``\\section{}`` block.
+
+    Args:
+        title: Section heading (e.g. ``"Introduction"``).
+        content: The body text.
+
+    Returns:
+        LaTeX-formatted section string.
+    """
+    return f"\\section{{{title}}}\n{content}\n"
+
+
+@tool
+def format_citation(authors: str, year: int, title: str, venue: str) -> str:
+    """Render a single APA-style citation line.
+
+    Args:
+        authors: ``"Smith, J. & Jones, A."``
+        year: Publication year.
+        title: Paper title.
+        venue: Journal / conference name.
+
+    Returns:
+        One APA-formatted citation string.
+    """
+    return f"{authors} ({year}). {title}. *{venue}*."
+
+
+SCIENTIFIC_INSTRUCTIONS = """You are a specialised scientific paper writer.
+
+Produce high-quality academic content with:
+- Clear structure (Abstract, Introduction, Methodology, Results, Discussion,
+  Conclusion, References)
+- Rigorous methodology and precise language
+- Proper APA citations and LaTeX formatting
+- Honest limitations and future work sections
+
+Use ``format_latex_section`` to wrap each section in LaTeX, and
+``format_citation`` to build the References list.
+"""
+
+
+def build_scientific_writer(
+    model: str = "huggingface/Agnuxo/CAJAL-4B-P2PCLAW",
+) -> Agent:
+    """Construct a scientific-writing Agent.
+
+    Override ``model`` for any HuggingFace / local / API model — the default
+    targets the CAJAL-4B checkpoint for LaTeX-style academic output.
+    """
+    return Agent(
+        name="Scientific Writer",
+        instructions=SCIENTIFIC_INSTRUCTIONS,
+        llm=model,
+        tools=[format_latex_section, format_citation],
+    )
+
+
+if __name__ == "__main__":
+    agent = build_scientific_writer()
+    paper = agent.start(
+        "Write a short scientific paper (Abstract + Introduction + Conclusion) "
+        "on 'Climate change effects on coral reef biodiversity'. "
+        "Use LaTeX formatting and include at least 3 APA citations."
+    )
+    print(paper)

scripts/smoke_n4_real.py

@@ -0,0 +1,118 @@
+#!/usr/bin/env python3
+"""N4 — Real agentic smoke test for inbound DLQ.
+
+Scenario:
+  1. Real Agent (anthropic/claude-haiku-4-5 or gemini/2.5-flash).
+  2. First chat attempt fails (we patch agent.chat to raise once).
+  3. BotSessionManager enqueues to DLQ.
+  4. Operator replays the DLQ — second attempt hits the **real** LLM
+     and produces a real reply.
+  5. Assert DLQ is empty and the reply contains the expected fact.
+
+Run::
+
+    cd /Users/praison/worktrees/n4-dlq
+    PYTHONPATH=src/praisonai-agents:src/praisonai python scripts/smoke_n4_real.py
+"""
+
+from __future__ import annotations
+
+import asyncio
+import os
+import sys
+import tempfile
+from pathlib import Path
+
+
+def _pick_model() -> str:
+    if os.getenv("ANTHROPIC_API_KEY"):
+        return "anthropic/claude-haiku-4-5"
+    if os.getenv("GOOGLE_API_KEY"):
+        return "gemini/gemini-2.5-flash"
+    raise RuntimeError(
+        "No supported API key found. Set ANTHROPIC_API_KEY or GOOGLE_API_KEY to run smoke tests."
+    )
+
+
+async def main() -> int:
+    from praisonaiagents import Agent
+    from praisonai.bots import BotSessionManager, InboundDLQ
+
+    model = _pick_model()
+    print(f"Model: {model}")
+
+    agent = Agent(
+        name="N4Tester",
+        instructions="You are a helpful assistant. Reply with one short sentence.",
+        llm=model,
+    )
+
+    with tempfile.TemporaryDirectory() as tmp:
+        dlq_path = Path(tmp) / "dlq.sqlite"
+        dlq = InboundDLQ(path=dlq_path)
+        mgr = BotSessionManager(platform="telegram", dlq=dlq)
+
+        # 1) Force first chat to fail by monkey-patching agent.chat.
+        original_chat = agent.chat
+
+        def failing_chat_first_time(prompt, *a, **kw):
+            agent.chat = original_chat  # next call goes to real LLM
+            raise RuntimeError("simulated LLM 503")
+
+        agent.chat = failing_chat_first_time
+
+        prompt = "What is 2 plus 2? Answer with a single digit."
+        print(f"\n[1] Sending failing message: {prompt!r}")
+        try:
+            await mgr.chat(
+                agent, "tg-1", prompt,
+                chat_id="100", user_name="OpsTester",
+            )
+            print("UNEXPECTED: first call did not raise.")
+            return 1
+        except RuntimeError as e:
+            print(f"   Caught expected error: {e}")
+
+        # 2) DLQ must hold one entry.
+        if dlq.size() != 1:
+            print(f"FAIL: expected DLQ size 1, got {dlq.size()}")
+            return 1
+        print(f"   DLQ size after fail: {dlq.size()}  ✅")
+
+        # 3) Replay through the (now-restored) real LLM.
+        print("\n[2] Replaying DLQ via real LLM …")
+        seen_replies = []
+
+        async def replayer(entry):
+            try:
+                reply = await mgr.chat(
+                    agent, entry.user_id, entry.prompt,
+                    chat_id=entry.chat_id,
+                    user_name=entry.user_name,
+                )
+                seen_replies.append(reply)
+                return True
+            except Exception as e:
+                print(f"   replay failed: {e}")
+                return False
+
+        succeeded, failed = await dlq.replay(replayer)
+        print(f"   succeeded={succeeded}, failed={failed}, "
+              f"remaining={dlq.size()}")
+
+        if succeeded != 1 or failed != 0 or dlq.size() != 0:
+            print("FAIL: replay outcome wrong.")
+            return 1
+
+        reply = seen_replies[0]
+        print(f"\n[Real LLM reply] {reply}\n")
+
+        if reply and "4" in reply:
+            print("PASS: DLQ → replay → real LLM produced expected '4'.")
+            return 0
+        print("FAIL: reply did not contain expected answer.")
+        return 1
+
+
+if __name__ == "__main__":
+    sys.exit(asyncio.run(main()))

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

@@ -126,7 +126,24 @@ class _AgentServerRegistry:
         
         thread = threading.Thread(target=run_server, daemon=True)
         thread.start()
-        ready_event.wait(timeout=5.0)  # Deterministic wait instead of sleep(0.5)
+        
+        # Check for configurable timeout via environment variable
+        try:
+            timeout = float(os.environ.get("PRAISONAI_SERVER_READY_TIMEOUT", "5.0"))
+        except ValueError:
+            logger.warning("Invalid PRAISONAI_SERVER_READY_TIMEOUT value. Using default 5.0s.")
+            timeout = 5.0
+        became_ready = ready_event.wait(timeout=timeout)
+        
+        if not became_ready:
+            logger.warning(
+                "Agent server on port %s did not become ready within %.1fs. "
+                "Proceeding, but some features may not work correctly. "
+                "Check server logs for startup errors.",
+                port,
+                timeout,
+            )
+        
         return True
 
 

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

@@ -7,7 +7,7 @@ Inspired by Agno's SessionContextStore pattern.
 
 from dataclasses import dataclass, field, asdict
 from typing import Any, Dict, List, Optional
-from datetime import datetime
+from datetime import datetime, timezone
 import json
 import logging
 from praisonaiagents._logging import get_logger
@@ -97,8 +97,8 @@ class SessionContextTracker:
         
         self._state = SessionState(
             session_id=self.session_id,
-            created_at=datetime.utcnow().isoformat() + "Z",
-            updated_at=datetime.utcnow().isoformat() + "Z",
+            created_at=datetime.now(timezone.utc).isoformat(),
+            updated_at=datetime.now(timezone.utc).isoformat(),
         )
     
     def _generate_session_id(self) -> str:
@@ -163,7 +163,7 @@ class SessionContextTracker:
     
     def _mark_updated(self) -> None:
         """Update the updated_at timestamp."""
-        self._state.updated_at = datetime.utcnow().isoformat() + "Z"
+        self._state.updated_at = datetime.now(timezone.utc).isoformat()
         self._state.turn_count += 1
     
     def to_context_string(self) -> str:
@@ -257,7 +257,7 @@ Current messages take precedence if there's any conflict with this summary.
         self._state = SessionState(
             session_id=self.session_id,
             created_at=self._state.created_at,
-            updated_at=datetime.utcnow().isoformat() + "Z",
+            updated_at=datetime.now(timezone.utc).isoformat(),
         )
     
     def to_dict(self) -> Dict[str, Any]:

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

@@ -12,7 +12,7 @@ import os
 import logging
 from praisonaiagents._logging import get_logger
 from dataclasses import dataclass, field, asdict
-from datetime import datetime
+from datetime import datetime, timezone
 from typing import Any, Dict, List, Optional
 
 logger = get_logger(__name__)
@@ -39,7 +39,7 @@ class GradeResult:
     input_text: str = ""
     output: str = ""
     expected_output: Optional[str] = None
-    timestamp: str = field(default_factory=lambda: datetime.utcnow().isoformat())
+    timestamp: str = field(default_factory=lambda: datetime.now(timezone.utc).isoformat())
     
     def to_dict(self) -> Dict[str, Any]:
         """Convert to dictionary."""
@@ -55,7 +55,7 @@ class GradeResult:
             input_text=data.get("input_text", ""),
             output=data.get("output", ""),
             expected_output=data.get("expected_output"),
-            timestamp=data.get("timestamp", datetime.utcnow().isoformat()),
+            timestamp=data.get("timestamp", datetime.now(timezone.utc).isoformat()),
         )
 
 class BaseLLMGrader:

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

@@ -7,7 +7,7 @@ import threading
 from typing import Any, Dict, List, Optional, Union, Literal
 import logging
 from praisonaiagents._logging import get_logger
-from datetime import datetime
+from datetime import datetime, timezone
 
 # Decomposed memory functionality - imported as mixins for backward compatibility
 from .storage import StorageMixin
@@ -692,7 +692,7 @@ class Memory(StorageMixin, SearchMixin, MemoryCoreMixin):
                         "_id": ident,
                         "content": text,
                         "metadata": metadata,
-                        "created_at": datetime.utcnow(),
+                        "created_at": datetime.now(timezone.utc),
                         "memory_type": "short_term"
                     }
                     self.mongo_short_term.insert_one(doc)
@@ -918,7 +918,7 @@ class Memory(StorageMixin, SearchMixin, MemoryCoreMixin):
                     "_id": ident,
                     "content": text,
                     "metadata": metadata,
-                    "created_at": datetime.utcnow(),
+                    "created_at": datetime.now(timezone.utc),
                     "memory_type": "long_term"
                 }
                 
@@ -1441,14 +1441,14 @@ class Memory(StorageMixin, SearchMixin, MemoryCoreMixin):
             self.mem0_client.add(text, user_id=user_id, metadata=meta)
         elif self.use_mongodb and hasattr(self, "mongo_users"):
             try:
-                from datetime import datetime
+                from datetime import datetime, timezone
                 ident = str(time.time_ns())
                 doc = {
                     "_id": ident,
                     "user_id": user_id,
                     "content": text,
                     "metadata": meta,
-                    "created_at": datetime.utcnow()
+                    "created_at": datetime.now(timezone.utc)
                 }
                 self.mongo_users.insert_one(doc)
                 self._log_verbose(f"Successfully stored user memory for {user_id}")

src/praisonai-agents/pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
 
 [project]
 name = "praisonaiagents"
-version = "1.6.37"
+version = "1.6.38"
 description = "Praison AI agents for completing complex tasks with Self Reflection Agents"
 readme = "README.md"
 requires-python = ">=3.10"

src/praisonai-agents/tests/unit/agents/test_server_registry_timeout.py

@@ -0,0 +1,128 @@
+"""Test for agent server readiness timeout warning functionality."""
+
+import time
+import threading
+import logging
+import pytest
+from unittest.mock import patch, MagicMock
+from praisonaiagents.agents.agents import _AgentServerRegistry
+
+
+def test_server_readiness_timeout_emits_warning(caplog):
+    """A server that does not start in time must produce a WARNING log entry."""
+    registry = _AgentServerRegistry()
+    
+    # Create a mock FastAPI app that won't signal readiness
+    mock_app = MagicMock()
+    
+    # Register the app but don't set the ready event
+    with patch.dict(registry._apps, {8000: mock_app}):
+        with patch.dict(registry._ready_events, {8000: threading.Event()}):
+            with patch.dict(registry._started, {8000: False}):
+                with patch("threading.Thread.start"):  # Prevent real server spawning
+                    with caplog.at_level(logging.WARNING):
+                        # Use a very short timeout to ensure the test doesn't hang
+                        with patch.dict("os.environ", {"PRAISONAI_SERVER_READY_TIMEOUT": "0.1"}):
+                            result = registry.start_server_if_needed(8000, host="127.0.0.1")
+                    
+                    # The method should still return True but log a warning
+                    assert result is True
+                    assert "8000" in caplog.text
+                    assert "did not become ready" in caplog.text.lower()
+
+
+def test_server_readiness_timeout_configurable_via_env():
+    """The timeout should be configurable via PRAISONAI_SERVER_READY_TIMEOUT."""
+    registry = _AgentServerRegistry()
+    
+    # Create a mock FastAPI app
+    mock_app = MagicMock()
+    
+    # Register the app but don't set the ready event
+    with patch.dict(registry._apps, {8001: mock_app}):
+        with patch.dict(registry._ready_events, {8001: threading.Event()}):
+            with patch.dict(registry._started, {8001: False}):
+                with patch("threading.Thread.start"):  # Prevent real server spawning
+                    # Test with custom timeout
+                    with patch.dict("os.environ", {"PRAISONAI_SERVER_READY_TIMEOUT": "0.05"}):
+                        start_time = time.time()
+                        result = registry.start_server_if_needed(8001, host="127.0.0.1")
+                        duration = time.time() - start_time
+                    
+                    # Should respect the custom timeout and complete quickly
+                    assert result is True
+                    assert duration < 1.0  # Should be much less than default 5s
+
+
+def test_server_readiness_success_no_warning(caplog):
+    """A server that starts in time should not produce any warning."""
+    registry = _AgentServerRegistry()
+    
+    # Create a mock FastAPI app
+    mock_app = MagicMock()
+    ready_event = threading.Event()
+    
+    # Register the app and signal readiness immediately
+    with patch.dict(registry._apps, {8002: mock_app}):
+        with patch.dict(registry._ready_events, {8002: ready_event}):
+            with patch.dict(registry._started, {8002: False}):
+                with patch("threading.Thread.start"):  # Prevent real server spawning
+                    # Set the event immediately to simulate quick startup
+                    ready_event.set()
+                    
+                    with caplog.at_level(logging.WARNING):
+                        result = registry.start_server_if_needed(8002, host="127.0.0.1")
+                    
+                    # Should succeed without warnings
+                    assert result is True
+                    assert "did not become ready" not in caplog.text.lower()
+
+
+def test_default_timeout_value(monkeypatch):
+    """Test that the default timeout is 5.0 seconds when env var is not set."""
+    registry = _AgentServerRegistry()
+    
+    # Create a mock FastAPI app
+    mock_app = MagicMock()
+    ready_event = threading.Event()
+    
+    # Register the app but don't set the ready event
+    with patch.dict(registry._apps, {8003: mock_app}):
+        with patch.dict(registry._ready_events, {8003: ready_event}):
+            with patch.dict(registry._started, {8003: False}):
+                with patch("threading.Thread.start"):  # Prevent real server spawning
+                    # Remove only the specific env var so other env vars (PATH etc.) remain intact
+                    monkeypatch.delenv("PRAISONAI_SERVER_READY_TIMEOUT", raising=False)
+                    with patch("threading.Event.wait") as mock_wait:
+                        mock_wait.return_value = False
+                        result = registry.start_server_if_needed(8003, host="127.0.0.1")
+                    
+                    # Should have called wait with default timeout of 5.0
+                    mock_wait.assert_called_once_with(timeout=5.0)
+                    assert result is True
+
+
+def test_invalid_timeout_env_var_fallback(caplog):
+    """Test that invalid PRAISONAI_SERVER_READY_TIMEOUT falls back to default with warning."""
+    registry = _AgentServerRegistry()
+    
+    # Create a mock FastAPI app
+    mock_app = MagicMock()
+    ready_event = threading.Event()
+    
+    # Register the app but don't set the ready event
+    with patch.dict(registry._apps, {8004: mock_app}):
+        with patch.dict(registry._ready_events, {8004: ready_event}):
+            with patch.dict(registry._started, {8004: False}):
+                with patch("threading.Thread.start"):  # Prevent real server spawning
+                    # Test with invalid timeout value
+                    with patch.dict("os.environ", {"PRAISONAI_SERVER_READY_TIMEOUT": "invalid"}):
+                        with caplog.at_level(logging.WARNING):
+                            with patch("threading.Event.wait") as mock_wait:
+                                mock_wait.return_value = False
+                                result = registry.start_server_if_needed(8004, host="127.0.0.1")
+                    
+                    # Should have fallen back to 5.0 and logged warning
+                    mock_wait.assert_called_once_with(timeout=5.0)
+                    assert result is True
+                    assert "Invalid PRAISONAI_SERVER_READY_TIMEOUT" in caplog.text

src/praisonai-agents/uv.lock

@@ -21,16 +21,16 @@ wheels = [
 
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 [[package]]
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-version = "3.11.11"
+version = "3.13.4"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
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 ]
 
 [[package]]

src/praisonai-rust/FEATURE_PARITY_TRACKER.json

@@ -1,6 +1,6 @@
 {
   "version": "1.5.87",
-  "lastUpdated": "2026-05-08",
+  "lastUpdated": "2026-05-13",
   "generatedBy": "praisonai._dev.parity.generator",
   "sourceOfTruth": "Python SDK (praisonaiagents)",
   "status": "PARITY_ACHIEVED",

src/praisonai-ts/FEATURE_PARITY_TRACKER.json

@@ -1,6 +1,6 @@
 {
   "version": "1.5.87",
-  "lastUpdated": "2026-05-08",
+  "lastUpdated": "2026-05-13",
   "generatedBy": "praisonai._dev.parity.generator",
   "sourceOfTruth": "Python SDK (praisonaiagents)",
   "summary": {

src/praisonai-ts/PARITY.md

@@ -1,6 +1,6 @@
 # Feature Parity Tracker
 
-> **Version:** 1.5.87 | **Last Updated:** 2026-05-08
+> **Version:** 1.5.87 | **Last Updated:** 2026-05-13
 > **Source of Truth:** Python SDK (praisonaiagents)
 
 ## Summary

src/praisonai/README.md

@@ -294,8 +294,35 @@ def search(query: str) -> str:
 
 @tool
 def calculate(expression: str) -> float:
-    """Evaluate a math expression."""
-    return eval(expression)
+    """Safely evaluate a numeric arithmetic expression."""
+    import ast
+    import operator
+    
+    # Define allowed operations
+    _OPS = {
+        ast.Add: operator.add,
+        ast.Sub: operator.sub,
+        ast.Mult: operator.mul,
+        ast.Div: operator.truediv,
+        ast.Pow: operator.pow,
+        ast.USub: operator.neg,
+        ast.UAdd: operator.pos,
+    }
+    
+    def _safe_eval(node):
+        if isinstance(node, ast.Constant) and isinstance(node.value, (int, float)):
+            return node.value
+        elif isinstance(node, ast.BinOp) and type(node.op) in _OPS:
+            return _OPS[type(node.op)](_safe_eval(node.left), _safe_eval(node.right))
+        elif isinstance(node, ast.UnaryOp) and type(node.op) in _OPS:
+            return _OPS[type(node.op)](_safe_eval(node.operand))
+        else:
+            raise ValueError("Unsupported expression")
+    
+    try:
+        return _safe_eval(ast.parse(expression, mode="eval").body)
+    except (ValueError, SyntaxError, TypeError, ZeroDivisionError, OverflowError):
+        raise ValueError("Invalid arithmetic expression")
 
 agent = Agent(
     instructions="You are a helpful assistant",
@@ -304,6 +331,7 @@ agent = Agent(
 agent.start("Search for AI news and calculate 15*4")
 ```
 
+> ⚠️ **Security Note:** Never use `eval()`, `exec()`, or `subprocess` in tool functions that process LLM-generated or user-supplied input. Always validate and sanitize inputs to prevent code injection attacks.
 > 📖 [Full tools docs](https://docs.praison.ai/docs/tools/tools) — BaseTool, tool packages, 100+ built-in tools
 
 ### 5. Persistence (Databases)
@@ -330,6 +358,15 @@ pip install "praisonai[claw]"
 praisonai claw
 ```
 
+#### Required Environment Variables
+
+Copy `.env.example` to `.env` and configure the following variables:
+
+| Variable | Required | Description |
+|----------|----------|-------------|
+| `OPENAI_API_KEY` | Yes | OpenAI API key for all LLM calls |
+| `TAVILY_API_KEY` | Yes (Claw) | Tavily key for the built-in web-search tool. Get one free at https://app.tavily.com |
+
 Open **http://localhost:8082** — the dashboard comes with 13 built-in pages: Chat, Agents, Memory, Knowledge, Channels, Guardrails, Cron, and more. Add messaging channels directly from the UI.
 
 > 📖 [Full Claw docs](https://docs.praison.ai/docs/concepts/claw) — platform tokens, CLI options, Docker, and YAML agent mode

src/praisonai/praisonai.rb

@@ -3,8 +3,8 @@ class Praisonai < Formula
   
     desc "AI tools for various AI applications"
     homepage "https://github.com/MervinPraison/PraisonAI"
-    url "https://github.com/MervinPraison/PraisonAI/archive/refs/tags/v4.6.37.tar.gz"
-    sha256 `curl -sL https://github.com/MervinPraison/PraisonAI/archive/refs/tags/v4.6.37.tar.gz | shasum -a 256`.split.first
+    url "https://github.com/MervinPraison/PraisonAI/archive/refs/tags/v4.6.38.tar.gz"
+    sha256 `curl -sL https://github.com/MervinPraison/PraisonAI/archive/refs/tags/v4.6.38.tar.gz | shasum -a 256`.split.first
     license "MIT"
   
     depends_on "[email protected]"

src/praisonai/praisonai/_registry.py

@@ -0,0 +1,164 @@
+"""Generic plugin registry implementation for PraisonAI.
+
+This module provides a unified registry pattern to replace the divergent singleton
+implementations across the codebase. It supports both built-in and entry-point
+based plugin discovery with thread-safe registration and dependency injection.
+"""
+
+from __future__ import annotations
+
+import threading
+from importlib.metadata import entry_points
+from typing import Callable, Dict, Generic, Optional, Type, TypeVar
+import logging
+
+T = TypeVar("T")
+logger = logging.getLogger(__name__)
+
+
+class PluginRegistry(Generic[T]):
+    """Generic plugin registry: builtins + entry points + runtime register().
+    
+    This replaces the singleton pattern with dependency injection while maintaining
+    the same functionality. Supports:
+    - Built-in plugins with lazy loading
+    - Entry points discovery
+    - Runtime registration
+    - Thread-safe operations
+    """
+
+    def __init__(
+        self, 
+        *,
+        entry_point_group: str,
+        builtins: Optional[Dict[str, Callable[[], Type[T]]]] = None
+    ) -> None:
+        """Initialize the registry.
+        
+        Args:
+            entry_point_group: Entry points group name for plugin discovery
+            builtins: Dict of name -> loader function for built-in plugins
+        """
+        self._entry_point_group = entry_point_group
+        self._items: Dict[str, Type[T]] = {}
+        self._lock = threading.Lock()
+        
+        # Load built-in plugins with error handling
+        if builtins:
+            for name, loader in builtins.items():
+                try:
+                    self._items[name] = loader()
+                except ImportError:
+                    # Built-in plugin dependencies not available, skip
+                    pass
+                except Exception:
+                    # Log other errors but don't crash initialization
+                    logger.warning("Failed to load built-in plugin %r", name, exc_info=True)
+        
+        self._load_entry_points()
+
+    def _load_entry_points(self) -> None:
+        """Load plugins from entry points."""
+        try:
+            for ep in entry_points(group=self._entry_point_group):
+                try:
+                    plugin_class = ep.load()
+                    with self._lock:
+                        self._items[ep.name] = plugin_class
+                except Exception:
+                    # Do not break plugin dispatch because one plugin is broken
+                    logger.warning(
+                        "Failed to load plugin %r from entry point",
+                        ep.name,
+                        exc_info=True,
+                    )
+        except Exception:
+            # entry_points() might not be available in older Python versions
+            logger.debug("Entry points not available for group %s", self._entry_point_group)
+
+    def register(self, name: str, cls: Type[T]) -> None:
+        """Register a plugin at runtime.
+        
+        Args:
+            name: Plugin name
+            cls: Plugin class
+        """
+        with self._lock:
+            self._items[name.lower()] = cls
+
+    def unregister(self, name: str) -> bool:
+        """Unregister a plugin.
+        
+        Args:
+            name: Plugin name
+            
+        Returns:
+            True if plugin was found and removed, False otherwise
+        """
+        with self._lock:
+            return self._items.pop(name.lower(), None) is not None
+
+    def resolve(self, name: str) -> Type[T]:
+        """Resolve a plugin name to its class.
+        
+        Args:
+            name: Plugin name
+            
+        Returns:
+            Plugin class
+            
+        Raises:
+            ValueError: If plugin is not found
+        """
+        with self._lock:
+            cls = self._items.get(name.lower())
+            # Capture available plugins snapshot while holding lock
+            # to avoid race condition between check and error message
+            available_snapshot = sorted(self._items.keys()) if cls is None else None
+        
+        if cls is None:
+            raise ValueError(
+                f"Unknown {self._entry_point_group} plugin: {name!r}. "
+                f"Available: {available_snapshot}"
+            )
+        return cls
+
+    def create(self, name: str, *args, **kwargs) -> T:
+        """Create an instance of the specified plugin.
+        
+        Args:
+            name: Plugin name
+            *args, **kwargs: Arguments to pass to plugin constructor
+            
+        Returns:
+            Plugin instance
+            
+        Raises:
+            ValueError: If plugin is not found
+        """
+        cls = self.resolve(name)
+        return cls(*args, **kwargs)
+
+    def list_names(self) -> list[str]:
+        """List all registered plugin names.
+        
+        Returns:
+            Sorted list of plugin names
+        """
+        with self._lock:
+            return sorted(self._items.keys())
+
+    def is_available(self, name: str) -> bool:
+        """Check if a plugin is available.
+        
+        Args:
+            name: Plugin name
+            
+        Returns:
+            True if plugin exists and can be created
+        """
+        try:
+            self.resolve(name)
+            return True
+        except ValueError:
+            return False

src/praisonai/praisonai/agents_generator.py

@@ -19,7 +19,7 @@ import difflib
 
 # Import new architecture components
 from .framework_adapters.base import FrameworkAdapter
-from .framework_adapters.registry import FrameworkAdapterRegistry
+from .framework_adapters.registry import FrameworkAdapterRegistry, get_default_registry
 from .tool_registry import ToolRegistry
 
 # Import availability flags
@@ -43,10 +43,12 @@ except ImportError:
 # Check for additional framework availability
 AG2_AVAILABLE = False
 PRAISONAI_AVAILABLE = False
+AGENTOPS_AVAILABLE = False
 try:
     import importlib.util
     AG2_AVAILABLE = importlib.util.find_spec("ag2") is not None
     PRAISONAI_AVAILABLE = importlib.util.find_spec("praisonaiagents") is not None
+    AGENTOPS_AVAILABLE = importlib.util.find_spec("agentops") is not None
 except ImportError:
     pass
 
@@ -179,7 +181,7 @@ def _resolve_yaml_cli_backend(cli_backend_config, logger):
 
 
 class AgentsGenerator:
-    def __init__(self, agent_file, framework, config_list, log_level=None, agent_callback=None, task_callback=None, agent_yaml=None, tools=None, cli_config=None):
+    def __init__(self, agent_file, framework, config_list, log_level=None, agent_callback=None, task_callback=None, agent_yaml=None, tools=None, cli_config=None, adapter_registry=None):
         """
         Initialize the AgentsGenerator object.
 
@@ -193,6 +195,7 @@ class AgentsGenerator:
             agent_yaml (str, optional): The content of the YAML file. Defaults to None.
             tools (dict, optional): A dictionary containing the tools to be used for the agents. Defaults to None.
             cli_config (dict, optional): CLI configuration to override YAML settings. Defaults to None.
+            adapter_registry (FrameworkAdapterRegistry, optional): Registry for framework adapters. Defaults to process default.
 
         Attributes:
             agent_file (str): The path to the agent file.
@@ -233,6 +236,10 @@ class AgentsGenerator:
         self.tool_registry = ToolRegistry()
         self.tool_registry.register_builtin_autogen_adapters()
         
+        # DI-friendly: tests/multi-tenant runtimes pass their own registry;
+        # CLI users get the process default.
+        self._adapter_registry = adapter_registry or get_default_registry()
+        
         # Get framework adapter (availability already validated at CLI entry)
         self.framework_adapter = self._get_framework_adapter(framework)
 
@@ -249,8 +256,7 @@ class AgentsGenerator:
         Raises:
             ValueError: If framework is not supported
         """
-        adapter_registry = FrameworkAdapterRegistry.get_instance()
-        return adapter_registry.create(framework)
+        return self._adapter_registry.create(framework)
 
     def _merge_cli_config(self, config, cli_config):
         """
@@ -375,20 +381,19 @@ class AgentsGenerator:
 
     def load_tools_from_module(self, module_path):
         """
-        Loads tools from a specified module path.
+        Load function tools from a user-supplied module (gated by PRAISONAI_ALLOW_LOCAL_TOOLS).
 
         Parameters:
             module_path (str): The path to the module containing the tools.
 
         Returns:
             dict: A dictionary containing the names of the tools as keys and the corresponding functions or objects as values.
-
-        Raises:
-            FileNotFoundError: If the specified module path does not exist.
+                  Returns an empty dict if the module cannot be loaded (path missing, loading blocked by PRAISONAI_ALLOW_LOCAL_TOOLS, or any other load error).
         """
-        spec = importlib.util.spec_from_file_location("tools_module", module_path)
-        module = importlib.util.module_from_spec(spec)
-        spec.loader.exec_module(module)
+        from ._safe_loader import load_user_module
+        module = load_user_module(module_path, name="tools_module")
+        if module is None:
+            return {}
         return {name: obj for name, obj in inspect.getmembers(module, self.is_function_or_decorated)}
     
     def _extract_tool_classes(self, module):
@@ -411,21 +416,13 @@ class AgentsGenerator:
     
     def load_tools_from_module_class(self, module_path):
         """
-        Loads tools from a specified module path containing classes that inherit from BaseTool 
-        or are part of langchain_community.tools package.
+        Load BaseTool / langchain tool classes from a user-supplied module (gated by PRAISONAI_ALLOW_LOCAL_TOOLS).
         """
-        spec = importlib.util.spec_from_file_location("tools_module", module_path)
-        module = importlib.util.module_from_spec(spec)
-        try:
-            spec.loader.exec_module(module)
-            return {name: obj() for name, obj in inspect.getmembers(module, 
-                lambda x: inspect.isclass(x) and (
-                    x.__module__.startswith('langchain_community.tools') or 
-                    (PRAISONAI_TOOLS_AVAILABLE and BaseTool and issubclass(x, BaseTool))
-                ) and x is not BaseTool)}
-        except ImportError as e:
-            self.logger.warning(f"Error loading tools from {module_path}: {e}")
+        from ._safe_loader import load_user_module
+        module = load_user_module(module_path, name="tools_module")
+        if module is None:
             return {}
+        return self._extract_tool_classes(module)
 
     def load_tools_from_package(self, package_path):
         """
@@ -451,36 +448,6 @@ class AgentsGenerator:
                     tools_dict[name] = obj
         return tools_dict
 
-    def load_tools_from_tools_py(self):
-        """
-        Imports and returns all contents from tools.py file.
-        Uses the tool registry instead of global namespace pollution.
-
-        Returns:
-            list: A list of callable functions with proper formatting
-        """
-        tools_list = []
-        try:
-            # Try to import tools.py from current directory using safe loading
-            from ._safe_loader import load_user_module
-            module = load_user_module("tools.py", name="tools")
-            if module is None:
-                self.logger.debug("tools.py not found or local tools loading disabled")
-                return tools_list
-
-            # Register functions in the tool registry instead of globals()
-            registered_tools = self.tool_registry.register_from_module(module)
-            tools_list = [self.tool_registry.get_function(name) for name in registered_tools]
-
-            self.logger.debug(f"Loaded {len(tools_list)} tool functions from tools.py")
-            self.logger.debug(f"Registered tools: {registered_tools}")
-            
-        except FileNotFoundError:
-            self.logger.debug("tools.py not found in current directory")
-        except Exception as e:
-            self.logger.warning(f"Error loading tools from tools.py: {e}")
-            
-        return tools_list
 
     def generate_crew_and_kickoff(self):
         """
@@ -590,12 +557,10 @@ class AgentsGenerator:
         tools_py_path = os.path.join(root_directory, 'tools.py')
         tools_dir_path = Path(root_directory) / 'tools'
         
+        # Use consolidated ToolResolver for tools.py loading
+        tools_dict.update(self.tool_resolver.get_local_tool_classes())
         if os.path.isfile(tools_py_path):
-            from ._safe_loader import load_user_module
-            module = load_user_module(tools_py_path, name="tools_module")
-            if module is not None:
-                tools_dict.update(self._extract_tool_classes(module))
-                self.logger.debug("tools.py exists in the root directory. Loading tools.py and skipping tools folder.")
+            self.logger.debug("tools.py exists in the root directory. Loading tools.py and skipping tools folder.")
         elif tools_dir_path.is_dir():
             from ._safe_loader import load_user_module
             for py_file in tools_dir_path.glob("*.py"):
@@ -784,7 +749,11 @@ class AgentsGenerator:
         result = "### Output ###\n" + response[-1].summary if hasattr(response[-1], 'summary') else ""
         
         if AGENTOPS_AVAILABLE:
-            agentops.end_session("Success")
+            import agentops
+            try:
+                agentops.end_session("Success")
+            except Exception as e:  # noqa: BLE001 -- agentops errors must not crash the caller
+                self.logger.warning(f"agentops.end_session failed: {e}")
             
         return result
 
@@ -1171,7 +1140,11 @@ class AgentsGenerator:
         result = f"### Task Output ###\n{response}"
         
         if AGENTOPS_AVAILABLE:
-            agentops.end_session("Success")
+            import agentops
+            try:
+                agentops.end_session("Success")
+            except Exception as e:  # noqa: BLE001 -- agentops errors must not crash the caller
+                self.logger.warning(f"agentops.end_session failed: {e}")
             
         return result
 
@@ -1190,8 +1163,8 @@ class AgentsGenerator:
 
         # Use existing tool resolver instance
         
-        # Load tools from local tools.py (backward compat)
-        tools_list = self.load_tools_from_tools_py()
+        # Load tools from local tools.py (backward compat) - use consolidated ToolResolver
+        tools_list = self.tool_resolver.get_local_callables()
         self.logger.debug(f"Loaded tools from tools.py: {tools_list}")
 
         # Initialize InteractiveRuntime for ACP/LSP if enabled globally
@@ -1219,25 +1192,24 @@ class AgentsGenerator:
                 
                 # Create a scoped event loop instead of modifying process globals
                 interactive_loop = asyncio.new_event_loop()
-                try:
-                    interactive_loop.run_until_complete(interactive_runtime.start())
-                    
-                    centric_tools = create_agent_centric_tools(interactive_runtime)
-                    self.logger.info(f"Loaded {len(centric_tools)} InteractiveRuntime tools")
-                    tools_list.extend(centric_tools)
-                    
-                finally:
-                    try:
-                        interactive_loop.run_until_complete(interactive_runtime.stop())
-                    except Exception as stop_error:
-                        self.logger.warning(f"Error stopping InteractiveRuntime: {stop_error}")
-                    finally:
-                        interactive_loop.close()
+                
+                # Start the runtime but keep it alive for agent execution
+                interactive_loop.run_until_complete(interactive_runtime.start())
+                
+                centric_tools = create_agent_centric_tools(interactive_runtime)
+                self.logger.info(f"Loaded {len(centric_tools)} InteractiveRuntime tools")
+                tools_list.extend(centric_tools)
                 
             except ImportError as e:
                 self.logger.warning(f"Failed to load InteractiveRuntime components: {e}")
+                interactive_runtime = None
+                interactive_loop = None
             except Exception as e:
                 self.logger.error(f"Error starting InteractiveRuntime: {e}")
+                if 'interactive_loop' in locals() and interactive_loop is not None:
+                    interactive_loop.close()
+                interactive_runtime = None
+                interactive_loop = None
 
         # Create agents from config
         for role, details in config['roles'].items():
@@ -1477,8 +1449,14 @@ class AgentsGenerator:
                     interactive_loop.run_until_complete(interactive_runtime.stop())
                 except Exception as e:
                     self.logger.error(f"Error stopping InteractiveRuntime: {e}")
+                finally:
+                    interactive_loop.close()
         
         if AGENTOPS_AVAILABLE:
-            agentops.end_session("Success")
+            import agentops
+            try:
+                agentops.end_session("Success")
+            except Exception as e:  # noqa: BLE001 -- agentops errors must not crash the caller
+                self.logger.warning(f"agentops.end_session failed: {e}")
             
         return result

src/praisonai/praisonai/async_agent_scheduler.py

@@ -250,10 +250,21 @@ class AsyncAgentScheduler:
             self.is_running = False
         
         logger.info("Async agent scheduler stopped")
-        logger.info(f"Execution stats - Total: {self._execution_count}, Success: {self._success_count}, Failed: {self._failure_count}")
+        
+        # Log final stats with consistent snapshot
+        if self._stats_lock is not None:
+            async with self._stats_lock:
+                total = self._execution_count
+                ok = self._success_count
+                fail = self._failure_count
+        else:
+            total = self._execution_count
+            ok = self._success_count
+            fail = self._failure_count
+        logger.info(f"Execution stats - Total: {total}, Success: {ok}, Failed: {fail}")
         return True
     
-    def get_stats(self) -> Dict[str, Any]:
+    async def get_stats(self) -> Dict[str, Any]:
         """
         Get current execution statistics (synchronous, best-effort).
         
@@ -264,12 +275,26 @@ class AsyncAgentScheduler:
         Returns:
             Dictionary with execution stats
         """
+        # Primitives are created lazily in _ensure_async_primitives(); if not yet
+        # initialized there are no concurrent writers, so a direct read is safe.
+        if self._stats_lock is not None:
+            async with self._stats_lock:
+                total = self._execution_count
+                ok = self._success_count
+                fail = self._failure_count
+                running = self.is_running
+        else:
+            total = self._execution_count
+            ok = self._success_count
+            fail = self._failure_count
+            running = self.is_running
+            
         return {
-            "is_running": self.is_running,
-            "total_executions": self._execution_count,
-            "successful_executions": self._success_count,
-            "failed_executions": self._failure_count,
-            "success_rate": (self._success_count / self._execution_count * 100) if self._execution_count > 0 else 0
+            "is_running": running,
+            "total_executions": total,
+            "successful_executions": ok,
+            "failed_executions": fail,
+            "success_rate": (ok / total * 100) if total > 0 else 0
         }
     
     async def get_stats_async(self) -> Dict[str, Any]:
@@ -327,11 +352,8 @@ class AsyncAgentScheduler:
     
     async def _execute_with_retry(self, max_retries: int):
         """Execute agent with retry logic."""
-        # Ensure async primitives are available
-        if self._stats_lock is None:
-            self._ensure_async_primitives()
-        
-        # Atomically increment execution count
+        self._ensure_async_primitives()  # guarantees _stats_lock is bound to current loop
+
         async with self._stats_lock:
             self._execution_count += 1
         
@@ -344,7 +366,6 @@ class AsyncAgentScheduler:
                 logger.info(f"Async agent execution successful on attempt {attempt + 1}")
                 logger.info(f"Result: {result}")
                 
-                # Atomically increment success count
                 async with self._stats_lock:
                     self._success_count += 1
                 safe_call(self.on_success, result)
@@ -359,7 +380,6 @@ class AsyncAgentScheduler:
                     logger.info(f"Waiting {wait_time}s before async retry...")
                     await asyncio.sleep(wait_time)
         
-        # Atomically increment failure count
         async with self._stats_lock:
             self._failure_count += 1
         logger.error(f"Async agent execution failed after {max_retries} attempts")

src/praisonai/praisonai/auto.py

@@ -628,7 +628,8 @@ class AutoGenerator(BaseAutoGenerator):
     
     def __init__(self, topic="Movie Story writing about AI", agent_file="test.yaml", 
                  framework="crewai", config_list: Optional[List[Dict]] = None,
-                 pattern: str = "sequential", single_agent: bool = False):
+                 pattern: str = "sequential", single_agent: bool = False, 
+                 adapter_registry=None):
         """
         Initialize the AutoGenerator class with the specified topic, agent file, and framework.
         
@@ -646,15 +647,15 @@ class AutoGenerator(BaseAutoGenerator):
         super().__init__(config_list=config_list)
         
         # Validate framework availability using adapter registry
-        from .framework_adapters.registry import FrameworkAdapterRegistry
+        from .framework_adapters.registry import get_default_registry
         
-        registry = FrameworkAdapterRegistry.get_instance()
+        self._adapter_registry = adapter_registry or get_default_registry()
         try:
-            adapter = registry.create(framework)
+            adapter = self._adapter_registry.create(framework)
         except ValueError as e:
             raise ImportError(
                 f"Unknown framework '{framework}'. Available frameworks: "
-                f"{', '.join(registry.list_registered())}"
+                f"{', '.join(self._adapter_registry.list_registered())}"
             ) from e
 
         # Use safe fallbacks for new adapter attributes

src/praisonai/praisonai/bots/__init__.py

@@ -17,6 +17,8 @@ if TYPE_CHECKING:
     from .agentmail import AgentMailBot
     from .bot import Bot
     from .botos import BotOS
+    from ._session import BotSessionManager
+    from ._dlq import InboundDLQ, DLQEntry
     from ._slack_approval import SlackApproval
     from ._telegram_approval import TelegramApproval
     from ._discord_approval import DiscordApproval
@@ -74,11 +76,20 @@ def __getattr__(name: str):
     if name == "BotSessionManager":
         from ._session import BotSessionManager
         return BotSessionManager
+    # N4 — inbound dead-letter queue
+    if name == "InboundDLQ":
+        from ._dlq import InboundDLQ
+        return InboundDLQ
+    if name == "DLQEntry":
+        from ._dlq import DLQEntry
+        return DLQEntry
     raise AttributeError(f"module {__name__!r} has no attribute {name!r}")
 
 __all__ = [
     "TelegramBot", "DiscordBot", "SlackBot", "WhatsAppBot", "LinearBot", "EmailBot", "AgentMailBot",
     "Bot", "BotOS",
+    "BotSessionManager",
+    "InboundDLQ", "DLQEntry",
     "SlackApproval", "TelegramApproval", "DiscordApproval",
     "WebhookApproval", "HTTPApproval",
     # W1

src/praisonai/praisonai/bots/_dlq.py

@@ -0,0 +1,299 @@
+"""
+Inbound Dead-Letter Queue (N4) for PraisonAI bot adapters.
+
+When ``BotSessionManager.chat()`` raises (LLM 5xx, transient timeout,
+provider rate-limit, etc.) the user message is normally lost. This
+module persists those failed inbound messages so an operator can
+inspect, retry, or purge them later.
+
+Design constraints (per PraisonAI principles):
+  - Wrapper-only — heavy code stays out of the core SDK.
+  - Lazy: ``sqlite3`` is stdlib so no extra dependency.
+  - Default OFF — ``BotSessionManager`` works exactly as before unless
+    a ``dlq=InboundDLQ(...)`` is passed.
+  - Bounded: TTL + ``max_size`` prevent unbounded disk growth.
+  - Thread-safe: a per-instance ``threading.Lock`` guards SQLite writes
+    (sqlite3 connections are not thread-safe by default).
+  - Reuses ``_resilience.BackoffPolicy`` for retry timing on replay.
+
+Storage schema::
+
+    entries(id INTEGER PRIMARY KEY AUTOINCREMENT,
+            ts REAL,
+            platform TEXT, user_id TEXT, prompt TEXT,
+            chat_id TEXT, thread_id TEXT, user_name TEXT,
+            error TEXT,
+            attempts INTEGER DEFAULT 0)
+
+Public API:
+  - ``InboundDLQ(path, *, max_size=10_000, ttl_seconds=7*86400)``
+  - ``enqueue(platform, user_id, prompt, error, ...)``
+  - ``size()`` / ``list(limit=100)`` / ``purge()``
+  - ``evict_expired()``
+  - ``replay(handler)`` — async, drops entries handler returns ``True`` for.
+"""
+
+from __future__ import annotations
+
+import logging
+import sqlite3
+import threading
+import time
+from dataclasses import dataclass
+from pathlib import Path
+from typing import Awaitable, Callable, List, Optional, Union
+
+logger = logging.getLogger(__name__)
+
+
+# 7 days default — long enough for ops to notice and act, short enough
+# not to blow up disk on chronic LLM failures.
+_DEFAULT_TTL_SECONDS = 7 * 86400
+_DEFAULT_MAX_SIZE = 10_000
+
+
+@dataclass(frozen=True)
+class DLQEntry:
+    """A single failed inbound message awaiting replay."""
+
+    id: int
+    ts: float
+    platform: str
+    user_id: str
+    prompt: str
+    chat_id: str
+    thread_id: str
+    user_name: str
+    error: str
+    attempts: int
+
+
+# Replay handler signature: takes an entry, returns True on success
+# (entry will be deleted) or False to keep it for later retry.
+ReplayHandler = Callable[[DLQEntry], Awaitable[bool]]
+
+
+class InboundDLQ:
+    """SQLite-backed dead-letter queue for failed inbound bot messages.
+
+    Args:
+        path: SQLite file path. Created if missing; parent dirs created.
+        max_size: Maximum entries kept; oldest evicted when exceeded.
+        ttl_seconds: Entries older than this are evicted on the next
+            ``enqueue()`` or ``evict_expired()`` call.
+
+    Example::
+
+        from praisonai.bots import InboundDLQ, BotSessionManager
+
+        dlq = InboundDLQ(path="~/.praisonai/dlq.sqlite")
+        mgr = BotSessionManager(platform="telegram", dlq=dlq)
+
+        # Later, an admin replays:
+        async def my_handler(entry):
+            try:
+                await mgr.chat(agent, entry.user_id, entry.prompt)
+                return True
+            except Exception:
+                return False
+        await dlq.replay(my_handler)
+    """
+
+    def __init__(
+        self,
+        path: Union[str, Path],
+        *,
+        max_size: int = _DEFAULT_MAX_SIZE,
+        ttl_seconds: int = _DEFAULT_TTL_SECONDS,
+    ) -> None:
+        self.path = Path(path).expanduser()
+        self.max_size = int(max_size)
+        self.ttl_seconds = int(ttl_seconds)
+        self._lock = threading.Lock()
+        self.path.parent.mkdir(parents=True, exist_ok=True)
+        self._init_schema()
+
+    # ── Schema ──────────────────────────────────────────────────────
+    def _connect(self) -> sqlite3.Connection:
+        conn = sqlite3.connect(str(self.path))
+        conn.execute("PRAGMA journal_mode=WAL")
+        conn.execute("PRAGMA synchronous=NORMAL")
+        return conn
+
+    def _init_schema(self) -> None:
+        with self._lock, self._connect() as conn:
+            conn.execute(
+                """
+                CREATE TABLE IF NOT EXISTS entries (
+                    id INTEGER PRIMARY KEY AUTOINCREMENT,
+                    ts REAL NOT NULL,
+                    platform TEXT NOT NULL,
+                    user_id TEXT NOT NULL,
+                    prompt TEXT NOT NULL,
+                    chat_id TEXT DEFAULT '',
+                    thread_id TEXT DEFAULT '',
+                    user_name TEXT DEFAULT '',
+                    error TEXT DEFAULT '',
+                    attempts INTEGER DEFAULT 0
+                )
+                """
+            )
+            conn.execute("CREATE INDEX IF NOT EXISTS idx_ts ON entries(ts)")
+
+    # ── Mutations ───────────────────────────────────────────────────
+    def enqueue(
+        self,
+        *,
+        platform: str,
+        user_id: str,
+        prompt: str,
+        error: str,
+        chat_id: str = "",
+        thread_id: str = "",
+        user_name: str = "",
+    ) -> int:
+        """Persist a failed inbound message. Returns its row id.
+
+        Runs ``evict_expired`` and ``_evict_overflow`` as side-effects so
+        TTL and ``max_size`` invariants are kept tight without a
+        background sweeper.
+        """
+        with self._lock, self._connect() as conn:
+            try:
+                conn.execute("BEGIN IMMEDIATE")
+                self._evict_expired_locked(conn)
+                cur = conn.execute(
+                    """
+                    INSERT INTO entries(ts, platform, user_id, prompt,
+                                        chat_id, thread_id, user_name, error)
+                    VALUES (?, ?, ?, ?, ?, ?, ?, ?)
+                    """,
+                    (
+                        time.time(), platform, user_id, prompt,
+                        chat_id, thread_id, user_name, error,
+                    ),
+                )
+                self._evict_overflow_locked(conn)
+                conn.commit()
+                return int(cur.lastrowid)
+            except Exception:
+                conn.rollback()
+                raise
+
+    def purge(self) -> int:
+        """Delete all entries. Returns count removed."""
+        with self._lock, self._connect() as conn:
+            n = conn.execute("SELECT COUNT(*) FROM entries").fetchone()[0]
+            conn.execute("DELETE FROM entries")
+            return int(n)
+
+    def evict_expired(self) -> int:
+        """Drop entries older than ``ttl_seconds``. Returns count removed."""
+        with self._lock, self._connect() as conn:
+            return self._evict_expired_locked(conn)
+
+    def _evict_expired_locked(self, conn: sqlite3.Connection) -> int:
+        cutoff = time.time() - self.ttl_seconds
+        cur = conn.execute("DELETE FROM entries WHERE ts <= ?", (cutoff,))
+        return int(cur.rowcount or 0)
+
+    def _evict_overflow_locked(self, conn: sqlite3.Connection) -> int:
+        n = conn.execute("SELECT COUNT(*) FROM entries").fetchone()[0]
+        if n <= self.max_size:
+            return 0
+        excess = n - self.max_size
+        cur = conn.execute(
+            "DELETE FROM entries WHERE id IN "
+            "(SELECT id FROM entries ORDER BY ts ASC LIMIT ?)",
+            (excess,),
+        )
+        return int(cur.rowcount or 0)
+
+    # ── Queries ─────────────────────────────────────────────────────
+    def size(self) -> int:
+        with self._lock, self._connect() as conn:
+            return int(conn.execute("SELECT COUNT(*) FROM entries").fetchone()[0])
+
+    def list(self, limit: int = 100) -> List[DLQEntry]:
+        """Return up to ``limit`` entries, newest first."""
+        with self._lock, self._connect() as conn:
+            rows = conn.execute(
+                """
+                SELECT id, ts, platform, user_id, prompt,
+                       chat_id, thread_id, user_name, error, attempts
+                FROM entries
+                ORDER BY ts DESC
+                LIMIT ?
+                """,
+                (int(limit),),
+            ).fetchall()
+        return [DLQEntry(*r) for r in rows]
+
+    def _list_oldest_first(self, limit: int = 100) -> List[DLQEntry]:
+        """Return up to ``limit`` entries, oldest first for replay."""
+        with self._lock, self._connect() as conn:
+            rows = conn.execute(
+                """
+                SELECT id, ts, platform, user_id, prompt,
+                       chat_id, thread_id, user_name, error, attempts
+                FROM entries
+                ORDER BY ts ASC
+                LIMIT ?
+                """,
+                (int(limit),),
+            ).fetchall()
+        return [DLQEntry(*r) for r in rows]
+
+    # ── Replay ──────────────────────────────────────────────────────
+    async def replay(
+        self,
+        handler: ReplayHandler,
+        *,
+        limit: Optional[int] = None,
+    ) -> tuple[int, int]:
+        """Re-deliver entries via ``handler``.
+
+        ``handler(entry)`` must return ``True`` on success (entry is
+        deleted) or ``False`` to keep the entry for later. Exceptions
+        from the handler are caught and treated as ``False`` (entry is
+        kept and ``attempts`` incremented).
+
+        Returns ``(succeeded, failed)`` counts.
+        """
+        # Fetch entries oldest-first for correct replay order
+        entries = self._list_oldest_first(limit=limit if limit is not None else self.max_size)
+        succeeded = failed = 0
+        for entry in entries:
+            try:
+                ok = await handler(entry)
+            except Exception as e:  # pragma: no cover — defensive
+                logger.warning("DLQ replay handler raised: %s", e)
+                ok = False
+            if ok:
+                self._delete(entry.id)
+                succeeded += 1
+            else:
+                self._increment_attempts(entry.id)
+                failed += 1
+        return succeeded, failed
+
+    def _delete(self, entry_id: int) -> None:
+        with self._lock, self._connect() as conn:
+            conn.execute("DELETE FROM entries WHERE id = ?", (entry_id,))
+
+    def _increment_attempts(self, entry_id: int) -> None:
+        with self._lock, self._connect() as conn:
+            conn.execute(
+                "UPDATE entries SET attempts = attempts + 1 WHERE id = ?",
+                (entry_id,),
+            )
+
+    def __repr__(self) -> str:
+        return (
+            f"InboundDLQ(path={str(self.path)!r}, "
+            f"size={self.size()}, "
+            f"max_size={self.max_size}, ttl={self.ttl_seconds}s)"
+        )
+
+
+__all__ = ["InboundDLQ", "DLQEntry", "ReplayHandler"]

src/praisonai/praisonai/bots/_registry.py

@@ -7,34 +7,111 @@ Extensible: third-party platforms can register via ``register_platform()``.
 
 from __future__ import annotations
 
-from typing import Any, Dict, List, Type
+import threading
+from typing import Any, Dict, List, Type, Optional
 
-# Lazy references: (module_path, class_name)
-_BUILTIN_PLATFORMS: Dict[str, tuple] = {
-    "telegram": ("praisonai.bots.telegram", "TelegramBot"),
-    "discord": ("praisonai.bots.discord", "DiscordBot"),
-    "slack": ("praisonai.bots.slack", "SlackBot"),
-    "whatsapp": ("praisonai.bots.whatsapp", "WhatsAppBot"),
-    "linear": ("praisonai.bots.linear", "LinearBot"),
-    "email": ("praisonai.bots.email", "EmailBot"),
-    "agentmail": ("praisonai.bots.agentmail", "AgentMailBot"),
+from .._registry import PluginRegistry
+
+
+def _telegram_loader():
+    import importlib
+    mod = importlib.import_module("praisonai.bots.telegram")
+    return getattr(mod, "TelegramBot")
+
+def _discord_loader():
+    import importlib
+    mod = importlib.import_module("praisonai.bots.discord")
+    return getattr(mod, "DiscordBot")
+
+def _slack_loader():
+    import importlib
+    mod = importlib.import_module("praisonai.bots.slack")
+    return getattr(mod, "SlackBot")
+
+def _whatsapp_loader():
+    import importlib
+    mod = importlib.import_module("praisonai.bots.whatsapp")
+    return getattr(mod, "WhatsAppBot")
+
+def _linear_loader():
+    import importlib
+    mod = importlib.import_module("praisonai.bots.linear")
+    return getattr(mod, "LinearBot")
+
+def _email_loader():
+    import importlib
+    mod = importlib.import_module("praisonai.bots.email")
+    return getattr(mod, "EmailBot")
+
+def _agentmail_loader():
+    import importlib
+    mod = importlib.import_module("praisonai.bots.agentmail")
+    return getattr(mod, "AgentMailBot")
+
+# Built-in bot platforms with lazy loading
+_BUILTIN_PLATFORMS = {
+    "telegram": _telegram_loader,
+    "discord": _discord_loader,
+    "slack": _slack_loader,
+    "whatsapp": _whatsapp_loader,
+    "linear": _linear_loader,
+    "email": _email_loader,
+    "agentmail": _agentmail_loader,
 }
 
-# Custom platforms registered at runtime
-_custom_platforms: Dict[str, Any] = {}
+
+class BotPlatformRegistry(PluginRegistry):
+    """Registry for bot platform adapters."""
+    
+    def __init__(self):
+        super().__init__(
+            entry_point_group="praisonai.bots",
+            builtins=_BUILTIN_PLATFORMS
+        )
+
+
+# Default registry (lazy, module-private)
+_default_registry: Optional[BotPlatformRegistry] = None
+_default_lock = threading.Lock()
+
+
+def get_default_bot_registry() -> BotPlatformRegistry:
+    """Return the process-default bot registry. Prefer DI; use this only at the edge.""" 
+    global _default_registry
+    if _default_registry is None:
+        with _default_lock:
+            if _default_registry is None:
+                _default_registry = BotPlatformRegistry()
+    return _default_registry
+
+
+# Backward compatibility API - lazy loading to preserve original behavior
+_bot_registry = None
+
+def _get_lazy_registry():
+    """Get registry lazily to avoid eager loading at module import."""
+    global _bot_registry
+    if _bot_registry is None:
+        _bot_registry = get_default_bot_registry()
+    return _bot_registry
 
 
 def get_platform_registry() -> Dict[str, Any]:
     """Return the combined registry of all known platforms.
-
-    Keys are platform names, values are either:
-    - A class (custom platforms, already resolved)
-    - A (module, classname) tuple (builtins, lazy-resolved on use)
+    
+    Backward compatibility function that returns original format:
+    {name: class_or_tuple} to preserve external caller contracts.
     """
-    combined: Dict[str, Any] = {}
-    combined.update(_BUILTIN_PLATFORMS)
-    combined.update(_custom_platforms)
-    return combined
+    registry = _get_lazy_registry()
+    result = {}
+    for name in registry.list_names():
+        try:
+            # Return the resolved class to maintain original API contract
+            result[name] = registry.resolve(name)
+        except ValueError:
+            # Skip broken registrations
+            pass
+    return result
 
 
 def register_platform(name: str, adapter_class: Type) -> None:
@@ -44,12 +121,12 @@ def register_platform(name: str, adapter_class: Type) -> None:
         name: Platform identifier (lowercase).
         adapter_class: The bot adapter class.
     """
-    _custom_platforms[name.lower()] = adapter_class
+    _get_lazy_registry().register(name.lower(), adapter_class)
 
 
 def list_platforms() -> List[str]:
     """List all registered platform names."""
-    return sorted(set(list(_BUILTIN_PLATFORMS.keys()) + list(_custom_platforms.keys())))
+    return _get_lazy_registry().list_names()
 
 
 def resolve_adapter(name: str) -> Type:
@@ -64,24 +141,4 @@ def resolve_adapter(name: str) -> Type:
     Raises:
         ValueError: If the platform is not registered.
     """
-    key = name.lower()
-
-    # Custom platforms are already classes
-    if key in _custom_platforms:
-        cls = _custom_platforms[key]
-        if isinstance(cls, type):
-            return cls
-
-    # Builtins are lazy (module, classname) tuples
-    if key in _BUILTIN_PLATFORMS:
-        ref = _BUILTIN_PLATFORMS[key]
-        if isinstance(ref, tuple):
-            module_path, class_name = ref
-            import importlib
-            mod = importlib.import_module(module_path)
-            return getattr(mod, class_name)
-
-    raise ValueError(
-        f"Unknown platform: {name!r}. "
-        f"Available: {', '.join(list_platforms())}"
-    )
+    return _get_lazy_registry().resolve(name.lower())

src/praisonai/praisonai/bots/_session.py

@@ -62,6 +62,7 @@ class BotSessionManager:
         max_history: int = 100,
         store: Optional[Any] = None,
         platform: str = "",
+        dlq: Optional[Any] = None,
         identity_resolver: Optional[Any] = None,
     ) -> None:
         self._histories: Dict[str, List[Dict[str, Any]]] = {}
@@ -71,6 +72,10 @@ class BotSessionManager:
         self._store = store
         self._platform = platform
         self._last_active: Dict[str, float] = {}
+        # N4: optional inbound DLQ — when set, failed agent.chat() calls
+        # are persisted for later replay. Default ``None`` preserves
+        # legacy behaviour (exception bubbles up untouched).
+        self._dlq = dlq
         # W1: optional cross-platform identity resolver. When set, the
         # session key is the resolver-returned unified user id, so the
         # same human pinging from multiple platforms shares one history.
@@ -172,6 +177,13 @@ class BotSessionManager:
 
         Uses both a per-user lock (serialise same user) and a per-agent
         lock (prevent concurrent history swaps on a shared Agent).
+
+        N4 — Inbound DLQ: if a ``dlq`` was passed to ``__init__`` and
+        ``agent.chat()`` raises, the failing message is persisted to
+        the dead-letter queue **before** the exception is re-raised.
+        This makes the error visible to the caller (so the bot adapter
+        can log / show the user a friendly message) while preserving
+        the message for later replay.
         """
         self._last_active[self._storage_key(user_id)] = time.monotonic()
         user_lock = self._get_lock(user_id)
@@ -209,9 +221,6 @@ class BotSessionManager:
                 # W1 robustness: hold ``agent_lock`` across the FULL LLM call
                 # (not only the history swap) so concurrent users on a shared
                 # Agent instance never observe each other's chat_history.
-                # Throughput on a shared agent is then bounded by the LLM's
-                # serial latency — this is correct: a single Agent's
-                # ``chat_history`` is mutable and cannot be safely interleaved.
                 async with agent_lock:
                     saved_history = agent.chat_history
                     agent.chat_history = user_history
@@ -226,6 +235,28 @@ class BotSessionManager:
                         )
                         # Capture updated history before restoring caller's.
                         updated_history = agent.chat_history
+                    except Exception as exc:
+                        # N4: persist the failed inbound message before bubbling.
+                        if self._dlq is not None:
+                            try:
+                                await loop.run_in_executor(
+                                    None,
+                                    lambda: self._dlq.enqueue(
+                                        platform=self._platform,
+                                        user_id=user_id,
+                                        prompt=prompt,
+                                        error=f"{type(exc).__name__}: {exc}",
+                                        chat_id=chat_id,
+                                        thread_id=thread_id,
+                                        user_name=user_name,
+                                    )
+                                )
+                            except Exception as dlq_exc:  # pragma: no cover — defensive
+                                logger.error(
+                                    "Failed to enqueue inbound DLQ entry: %s", dlq_exc
+                                )
+                        agent.chat_history = saved_history
+                        raise
                     finally:
                         agent.chat_history = saved_history
 

src/praisonai/praisonai/cli/commands/bot.py

@@ -556,6 +556,123 @@ def bot_install_daemon(
         raise typer.Exit(1)
 
 
+# ── N4: Inbound DLQ subcommand group ─────────────────────────────────
+dlq_app = typer.Typer(
+    help="Inspect / replay / purge the inbound dead-letter queue.",
+    no_args_is_help=True,
+)
+app.add_typer(dlq_app, name="dlq")
+
+
+def _resolve_dlq_path(path: Optional[str]) -> str:
+    import os
+    if path:
+        return os.path.expanduser(path)
+    return os.path.expanduser(
+        os.environ.get("PRAISONAI_DLQ_PATH", "~/.praisonai/dlq.sqlite")
+    )
+
+
+@dlq_app.command("list")
+def dlq_list(
+    path: Optional[str] = typer.Option(
+        None, "--path", "-p", help="Path to DLQ sqlite file."
+    ),
+    limit: int = typer.Option(20, "--limit", "-n", help="Max entries to show."),
+):
+    """List entries in the inbound DLQ (newest first)."""
+    from praisonai.bots import InboundDLQ
+
+    dlq = InboundDLQ(path=_resolve_dlq_path(path))
+    entries = dlq.list(limit=limit)
+    if not entries:
+        typer.echo(f"DLQ empty (path={dlq.path})")
+        raise typer.Exit(0)
+
+    typer.echo(f"DLQ {dlq.path} — {dlq.size()} entries (showing {len(entries)}):")
+    for e in entries:
+        prompt_preview = (e.prompt[:60] + "…") if len(e.prompt) > 60 else e.prompt
+        typer.echo(
+            f"  [{e.id:>5}] {e.platform:<10} user={e.user_id:<16} "
+            f"attempts={e.attempts}  err={e.error[:50]}  prompt={prompt_preview!r}"
+        )
+
+
+@dlq_app.command("purge")
+def dlq_purge(
+    path: Optional[str] = typer.Option(None, "--path", "-p"),
+    yes: bool = typer.Option(False, "--yes", "-y", help="Skip confirmation."),
+):
+    """Delete all entries from the DLQ."""
+    from praisonai.bots import InboundDLQ
+
+    dlq = InboundDLQ(path=_resolve_dlq_path(path))
+    n = dlq.size()
+    if n == 0:
+        typer.echo("DLQ already empty.")
+        raise typer.Exit(0)
+
+    if not yes:
+        confirm = typer.confirm(f"Delete all {n} entries from {dlq.path}?")
+        if not confirm:
+            raise typer.Exit(0)
+
+    removed = dlq.purge()
+    typer.echo(f"Purged {removed} entries.")
+
+
+@dlq_app.command("replay")
+def dlq_replay(
+    config: str = typer.Option(
+        ..., "--config", "-c",
+        help="Path to bot YAML config (provides agent + platform).",
+    ),
+    path: Optional[str] = typer.Option(None, "--path", "-p"),
+    limit: int = typer.Option(50, "--limit", "-n"),
+):
+    """Replay DLQ entries through the configured agent.
+
+    Loads the bot YAML, instantiates the agent, and re-runs each entry
+    through ``BotSessionManager.chat()``. Successful entries are removed;
+    failed entries are kept for the next attempt.
+    """
+    import asyncio
+    from praisonai.bots import InboundDLQ, BotSessionManager
+    from praisonai.cli.features.bots_cli import _load_bot_config, _build_agent
+
+    cfg = _load_bot_config(config)
+    agent = _build_agent(cfg)
+    platform = cfg.get("platform", "")
+
+    dlq = InboundDLQ(path=_resolve_dlq_path(path))
+    if dlq.size() == 0:
+        typer.echo("DLQ empty — nothing to replay.")
+        raise typer.Exit(0)
+
+    mgr = BotSessionManager(platform=platform)
+
+    async def replayer(entry):
+        try:
+            await mgr.chat(
+                agent, entry.user_id, entry.prompt,
+                chat_id=entry.chat_id,
+                thread_id=entry.thread_id,
+                user_name=entry.user_name,
+            )
+            return True
+        except Exception as e:
+            typer.echo(f"  entry {entry.id} failed: {e}")
+            return False
+
+    succeeded, failed = asyncio.run(dlq.replay(replayer, limit=limit))
+    typer.echo(f"Replay done: succeeded={succeeded}, failed={failed}, "
+               f"remaining={dlq.size()}")
+    
+    # Return non-zero exit code if any failures occurred and entries remain
+    if failed > 0 and dlq.size() > 0:
+        raise typer.Exit(1)
+
+
 @app.callback(invoke_without_command=True)
 def bot_callback(ctx: typer.Context):
     """Show bot help if no subcommand provided."""

src/praisonai/praisonai/cli/execution/profiler.py

@@ -16,7 +16,7 @@ import pstats
 import time
 import platform
 from dataclasses import dataclass, field
-from datetime import datetime
+from datetime import datetime, timezone
 from typing import Any, Dict, List, Optional, Tuple
 
 from .request import ExecutionRequest
@@ -409,7 +409,7 @@ class ProfileReport:
     def __post_init__(self):
         """Set timestamp if not provided."""
         if not self.timestamp:
-            self.timestamp = datetime.utcnow().isoformat() + "Z"
+            self.timestamp = datetime.now(timezone.utc).isoformat()
     
     def to_dict(self) -> Dict[str, Any]:
         """Convert to dictionary for JSON serialization."""

src/praisonai/praisonai/cli/features/profiler/core.py

@@ -15,7 +15,7 @@ import subprocess
 import sys
 import time
 from dataclasses import dataclass, field
-from datetime import datetime
+from datetime import datetime, timezone
 from pathlib import Path
 from typing import Any, Dict, List, Optional, Tuple
 
@@ -113,7 +113,7 @@ class ProfilerResult:
     callees: Dict[str, List[str]] = field(default_factory=dict)
     import_times: List[Tuple[str, float]] = field(default_factory=list)
     metadata: Dict[str, Any] = field(default_factory=dict)
-    timestamp: str = field(default_factory=lambda: datetime.utcnow().isoformat() + "Z")
+    timestamp: str = field(default_factory=lambda: datetime.now(timezone.utc).isoformat())
     
     def to_dict(self) -> Dict[str, Any]:
         return {
@@ -304,7 +304,7 @@ class QueryProfiler:
             "platform": platform.platform(),
             "praisonai_version": praisonai_version,
             "model": model or "default",
-            "timestamp": datetime.utcnow().isoformat() + "Z",
+            "timestamp": datetime.now(timezone.utc).isoformat(),
         }
     
     def _extract_function_stats(self) -> List[FunctionStats]:

src/praisonai/praisonai/cli/features/profiler/suite.py

@@ -11,7 +11,7 @@ import subprocess
 import sys
 import time
 from dataclasses import dataclass, field
-from datetime import datetime
+from datetime import datetime, timezone
 from pathlib import Path
 from typing import Any, Dict, List, Optional
 
@@ -85,7 +85,7 @@ class SuiteResult:
     startup_cold_ms: float = 0.0
     startup_warm_ms: float = 0.0
     import_analysis: List[Dict[str, Any]] = field(default_factory=list)
-    timestamp: str = field(default_factory=lambda: datetime.utcnow().isoformat() + "Z")
+    timestamp: str = field(default_factory=lambda: datetime.now(timezone.utc).isoformat())
     metadata: Dict[str, Any] = field(default_factory=dict)
     
     def to_dict(self) -> Dict[str, Any]:
@@ -182,7 +182,7 @@ class ProfileSuiteRunner:
             "python_version": platform.python_version(),
             "platform": platform.platform(),
             "praisonai_version": praisonai_version,
-            "timestamp": datetime.utcnow().isoformat() + "Z",
+            "timestamp": datetime.now(timezone.utc).isoformat(),
         }
     
     def _measure_startup(self) -> tuple:

src/praisonai/praisonai/cli/main.py

@@ -4065,6 +4065,31 @@ Do NOT add any explanations or formatting."""
         
         return results[-1].get("output", "") if results else ""
 
+    def _execute_agent_with_budget_handling(self, agent, method_name, *args, **kwargs):
+        """Run ``agent.<method_name>(*args, **kwargs)`` with a graceful
+        BudgetExceededError handler.
+
+        Wrapper-only fix (no core SDK changes). Users configure budgets via
+        ``execution=ExecutionConfig(max_budget=...)`` on the Agent — per
+        AGENTS.md §5.3 there is NO top-level ``max_budget=`` parameter on
+        Agent.__init__ (avoids parameter bloat).
+
+        When the budget is hit this prints a single-line actionable error
+        message and exits with code 1 instead of leaking a raw traceback.
+        Any other exception is re-raised unchanged.
+        """
+        from praisonaiagents.errors import BudgetExceededError
+        try:
+            return getattr(agent, method_name)(*args, **kwargs)
+        except BudgetExceededError as e:
+            from rich import print as rich_print
+            rich_print(
+                f"[red]Budget limit exceeded: {e!s}. "
+                "Hint: set budget via "
+                "execution=ExecutionConfig(max_budget=1.00) on your Agent.[/red]"
+            )
+            sys.exit(1)
+
     def _extract_cli_config_for_yaml(self):
         """
         Extract CLI configuration that should be passed to YAML processing.
@@ -4611,9 +4636,9 @@ Do NOT add any explanations or formatting."""
                     from rich.panel import Panel
                     
                     with Live(Panel(Spinner("dots", text="Generating..."), border_style="cyan"), refresh_per_second=10, transient=True):
-                        result = auto_rag.chat(prompt)
+                        result = self._execute_agent_with_budget_handling(auto_rag, 'chat', prompt)
                 else:
-                    result = auto_rag.chat(prompt)
+                    result = self._execute_agent_with_budget_handling(auto_rag, 'chat', prompt)
             else:
                 # Resolve display mode from CLI flags
                 display_mode = self._resolve_display_mode()
@@ -4621,16 +4646,16 @@ Do NOT add any explanations or formatting."""
                 if display_mode == 'silent':
                     # -qq: No output at all, exit code only
                     if hasattr(agent, 'start'):
-                        result = agent.start(prompt)
+                        result = self._execute_agent_with_budget_handling(agent, 'start', prompt)
                     else:
-                        result = agent.chat(prompt)
+                        result = self._execute_agent_with_budget_handling(agent, 'chat', prompt)
                 
                 elif display_mode == 'quiet':
                     # -q: Result only, no spinners or status
                     if hasattr(agent, 'start'):
-                        result = agent.start(prompt)
+                        result = self._execute_agent_with_budget_handling(agent, 'start', prompt)
                     else:
-                        result = agent.chat(prompt)
+                        result = self._execute_agent_with_budget_handling(agent, 'chat', prompt)
                     if result is not None:
                         output = getattr(result, 'output', None) or (str(result) if result else None)
                         if output:
@@ -4642,15 +4667,15 @@ Do NOT add any explanations or formatting."""
                         from praisonaiagents.output.status import enable_status_output, disable_status_output
                         enable_status_output(show_timestamps=True, show_metrics=True)
                         if hasattr(agent, 'start'):
-                            result = agent.start(prompt)
+                            result = self._execute_agent_with_budget_handling(agent, 'start', prompt)
                         else:
-                            result = agent.chat(prompt)
+                            result = self._execute_agent_with_budget_handling(agent, 'chat', prompt)
                         disable_status_output()
                     except ImportError:
                         if hasattr(agent, 'start'):
-                            result = agent.start(prompt)
+                            result = self._execute_agent_with_budget_handling(agent, 'start', prompt)
                         else:
-                            result = agent.chat(prompt)
+                            result = self._execute_agent_with_budget_handling(agent, 'chat', prompt)
                 
                 elif display_mode == 'debug':
                     # -vv: SDK TraceOutput with markdown rendering
@@ -4658,15 +4683,15 @@ Do NOT add any explanations or formatting."""
                         from praisonaiagents.output.trace import enable_trace_output, disable_trace_output
                         enable_trace_output(use_markdown=True)
                         if hasattr(agent, 'start'):
-                            result = agent.start(prompt)
+                            result = self._execute_agent_with_budget_handling(agent, 'start', prompt)
                         else:
-                            result = agent.chat(prompt)
+                            result = self._execute_agent_with_budget_handling(agent, 'chat', prompt)
                         disable_trace_output()
                     except ImportError:
                         if hasattr(agent, 'start'):
-                            result = agent.start(prompt)
+                            result = self._execute_agent_with_budget_handling(agent, 'start', prompt)
                         else:
-                            result = agent.chat(prompt)
+                            result = self._execute_agent_with_budget_handling(agent, 'chat', prompt)
                 
                 elif display_mode == 'jsonl':
                     # --output jsonl: JSONL structured output for CI/CD
@@ -4688,9 +4713,9 @@ Do NOT add any explanations or formatting."""
                     
                     start_time = time.time()
                     if hasattr(agent, 'start'):
-                        result = agent.start(prompt)
+                        result = self._execute_agent_with_budget_handling(agent, 'start', prompt)
                     else:
-                        result = agent.chat(prompt)
+                        result = self._execute_agent_with_budget_handling(agent, 'chat', prompt)
                     
                     # Emit final result
                     reason = getattr(result, 'completion_reason', None) if hasattr(result, 'completion_reason') else 'complete'
@@ -4709,9 +4734,9 @@ Do NOT add any explanations or formatting."""
                     import json as json_mod
                     start_time = time.time()
                     if hasattr(agent, 'start'):
-                        result = agent.start(prompt)
+                        result = self._execute_agent_with_budget_handling(agent, 'start', prompt)
                     else:
-                        result = agent.chat(prompt)
+                        result = self._execute_agent_with_budget_handling(agent, 'chat', prompt)
                     
                     output = result.output if hasattr(result, 'output') else str(result)
                     envelope = {
@@ -4732,15 +4757,15 @@ Do NOT add any explanations or formatting."""
                         flow = track_workflow()
                         flow.start()
                         if hasattr(agent, 'start'):
-                            result = agent.start(prompt)
+                            result = self._execute_agent_with_budget_handling(agent, 'start', prompt)
                         else:
-                            result = agent.chat(prompt)
+                            result = self._execute_agent_with_budget_handling(agent, 'chat', prompt)
                         flow.stop()
                     except ImportError:
                         if hasattr(agent, 'start'):
-                            result = agent.start(prompt)
+                            result = self._execute_agent_with_budget_handling(agent, 'start', prompt)
                         else:
-                            result = agent.chat(prompt)
+                            result = self._execute_agent_with_budget_handling(agent, 'chat', prompt)
                 
                 elif display_mode == 'editor':
                     # --output editor: User-friendly step-by-step format
@@ -4750,9 +4775,9 @@ Do NOT add any explanations or formatting."""
                     
                     # Run agent
                     if hasattr(agent, 'start'):
-                        result = agent.start(prompt)
+                        result = self._execute_agent_with_budget_handling(agent, 'start', prompt)
                     else:
-                        result = agent.chat(prompt)
+                        result = self._execute_agent_with_budget_handling(agent, 'chat', prompt)
                     
                     # SDK callbacks (interaction, llm_content) handle display —
                     # no explicit editor.output() needed here.
@@ -4774,15 +4799,15 @@ Do NOT add any explanations or formatting."""
                         from praisonaiagents.output.status import enable_status_output, disable_status_output
                         enable_status_output(show_timestamps=False, show_metrics=False)
                         if hasattr(agent, 'start'):
-                            result = agent.start(prompt)
+                            result = self._execute_agent_with_budget_handling(agent, 'start', prompt)
                         else:
-                            result = agent.chat(prompt)
+                            result = self._execute_agent_with_budget_handling(agent, 'chat', prompt)
                         disable_status_output()
                     except ImportError:
                         if hasattr(agent, 'start'):
-                            result = agent.start(prompt)
+                            result = self._execute_agent_with_budget_handling(agent, 'start', prompt)
                         else:
-                            result = agent.chat(prompt)
+                            result = self._execute_agent_with_budget_handling(agent, 'chat', prompt)
             
             # ===== POST-PROCESSING WITH NEW FEATURES =====
             

src/praisonai/praisonai/cli/state/identifiers.py

@@ -9,7 +9,7 @@ import os
 import secrets
 import threading
 from dataclasses import dataclass, field
-from datetime import datetime
+from datetime import datetime, timezone
 from typing import Dict, Optional
 
 
@@ -20,7 +20,7 @@ def generate_run_id() -> str:
     Format: run_YYYYMMDD_HHMMSS_<random>
     Example: run_20241231_143022_a1b2c3
     """
-    timestamp = datetime.utcnow().strftime("%Y%m%d_%H%M%S")
+    timestamp = datetime.now(timezone.utc).strftime("%Y%m%d_%H%M%S")
     random_suffix = secrets.token_hex(3)  # 6 characters
     return f"run_{timestamp}_{random_suffix}"
 
@@ -68,7 +68,7 @@ class RunContext:
     """
     run_id: str = field(default_factory=generate_run_id)
     trace_id: str = field(default_factory=generate_trace_id)
-    start_time: datetime = field(default_factory=datetime.utcnow)
+    start_time: datetime = field(default_factory=lambda: datetime.now(timezone.utc))
     
     # Agent tracking
     agents: Dict[str, str] = field(default_factory=dict)  # name -> agent_id

src/praisonai/praisonai/cli/state/sessions.py

@@ -7,7 +7,7 @@ Provides persistence and resume functionality for sessions.
 import json
 import shutil
 from dataclasses import dataclass, field
-from datetime import datetime
+from datetime import datetime, timezone
 from pathlib import Path
 from typing import Any, Dict, List, Optional, TYPE_CHECKING
 
@@ -129,7 +129,7 @@ class SessionManager:
         session_dir = self._get_session_dir(session_id)
         session_dir.mkdir(parents=True, exist_ok=True)
         
-        now = datetime.utcnow()
+        now = datetime.now(timezone.utc)
         metadata = SessionMetadata(
             session_id=session_id,
             run_id=context.run_id,
@@ -206,7 +206,7 @@ class SessionManager:
         metadata = self._load_metadata(session_id)
         if metadata:
             metadata.event_count += 1
-            metadata.updated_at = datetime.utcnow()
+            metadata.updated_at = datetime.now(timezone.utc)
             self._save_metadata(metadata)
     
     def get(self, session_id: str) -> Optional[SessionMetadata]:
@@ -365,7 +365,7 @@ class SessionManager:
         metadata = self._load_metadata(session_id)
         if metadata:
             metadata.status = status
-            metadata.updated_at = datetime.utcnow()
+            metadata.updated_at = datetime.now(timezone.utc)
             self._save_metadata(metadata)
 
 

src/praisonai/praisonai/deploy.py

@@ -57,7 +57,7 @@ class CloudDeployer:
             file.write("FROM python:3.11-slim\n")
             file.write("WORKDIR /app\n")
             file.write("COPY . .\n")
-            file.write("RUN pip install flask praisonai==4.6.37 gunicorn markdown\n")
+            file.write("RUN pip install flask praisonai==4.6.38 gunicorn markdown\n")
             file.write("EXPOSE 8080\n")
             file.write('CMD ["gunicorn", "-b", "0.0.0.0:8080", "api:app"]\n')
             

src/praisonai/praisonai/framework_adapters/autogen_adapter.py

@@ -5,7 +5,7 @@ Provides lazy-loaded integration with AutoGen v0.2, AutoGen v0.4, and AG2 framew
 """
 
 import logging
-from typing import Dict, List, Any
+from typing import Dict, List, Any, Optional, Callable
 from .base import BaseFrameworkAdapter
 
 logger = logging.getLogger(__name__)
@@ -26,7 +26,17 @@ class AutoGenAdapter(BaseFrameworkAdapter):
         except ImportError:
             return False
     
-    def run(self, config: Dict[str, Any], llm_config: List[Dict], topic: str) -> str:
+    def run(
+        self,
+        config: Dict[str, Any],
+        llm_config: List[Dict],
+        topic: str,
+        *,
+        tools_dict: Optional[Dict[str, Any]] = None,
+        agent_callback: Optional[Callable] = None,
+        task_callback: Optional[Callable] = None,
+        cli_config: Optional[Dict[str, Any]] = None,
+    ) -> str:
         """
         Run AutoGen v0.2 with given configuration.
         
@@ -34,6 +44,10 @@ class AutoGenAdapter(BaseFrameworkAdapter):
             config: AutoGen configuration with agents
             llm_config: LLM configuration list
             topic: Topic for the tasks
+            tools_dict: Available tools dictionary
+            agent_callback: Callback for agent events
+            task_callback: Callback for task events
+            cli_config: CLI configuration
             
         Returns:
             Execution result as string
@@ -110,7 +124,17 @@ class AutoGenV4Adapter(BaseFrameworkAdapter):
         except ImportError:
             return False
     
-    def run(self, config: Dict[str, Any], llm_config: List[Dict], topic: str) -> str:
+    def run(
+        self,
+        config: Dict[str, Any],
+        llm_config: List[Dict],
+        topic: str,
+        *,
+        tools_dict: Optional[Dict[str, Any]] = None,
+        agent_callback: Optional[Callable] = None,
+        task_callback: Optional[Callable] = None,
+        cli_config: Optional[Dict[str, Any]] = None,
+    ) -> str:
         """
         Run AutoGen v0.4 with given configuration.
         
@@ -118,6 +142,10 @@ class AutoGenV4Adapter(BaseFrameworkAdapter):
             config: AutoGen v0.4 configuration with agents
             llm_config: LLM configuration list
             topic: Topic for the tasks
+            tools_dict: Available tools dictionary
+            agent_callback: Callback for agent events
+            task_callback: Callback for task events
+            cli_config: CLI configuration
             
         Returns:
             Execution result as string
@@ -128,7 +156,7 @@ class AutoGenV4Adapter(BaseFrameworkAdapter):
         # For now, return a proper error message instead of delegating
         # TODO: Implement full AutoGen v0.4 adapter logic
         logger.warning("AutoGen v0.4 adapter is not yet fully implemented")
-        return "### AutoGen v0.4 Output ###\nAutoGen v0.4 adapter is not yet fully implemented. Please use 'autogen' framework for AutoGen v0.2 support."
+        raise NotImplementedError("AutoGen v0.4 adapter is not yet fully implemented. Please use 'autogen' framework for AutoGen v0.2 support.")
 
 
 class AG2Adapter(BaseFrameworkAdapter):
@@ -148,7 +176,17 @@ class AG2Adapter(BaseFrameworkAdapter):
         except Exception:
             return False
     
-    def run(self, config: Dict[str, Any], llm_config: List[Dict], topic: str) -> str:
+    def run(
+        self,
+        config: Dict[str, Any],
+        llm_config: List[Dict],
+        topic: str,
+        *,
+        tools_dict: Optional[Dict[str, Any]] = None,
+        agent_callback: Optional[Callable] = None,
+        task_callback: Optional[Callable] = None,
+        cli_config: Optional[Dict[str, Any]] = None,
+    ) -> str:
         """
         Run AG2 with given configuration.
         
@@ -156,6 +194,10 @@ class AG2Adapter(BaseFrameworkAdapter):
             config: AG2 configuration with agents
             llm_config: LLM configuration list  
             topic: Topic for the tasks
+            tools_dict: Available tools dictionary
+            agent_callback: Callback for agent events
+            task_callback: Callback for task events
+            cli_config: CLI configuration
             
         Returns:
             Execution result as string
@@ -166,4 +208,4 @@ class AG2Adapter(BaseFrameworkAdapter):
         # For now, return a proper error message instead of delegating
         # TODO: Implement full AG2 adapter logic
         logger.warning("AG2 adapter is not yet fully implemented")
-        return "### AG2 Output ###\nAG2 adapter is not yet fully implemented. Please use 'autogen' framework for AutoGen/AG2 support."
+        raise NotImplementedError("AG2 adapter is not yet fully implemented. Please use 'autogen' framework for AutoGen/AG2 support.")

src/praisonai/praisonai/framework_adapters/registry.py

@@ -3,148 +3,68 @@ Framework Adapter Registry for PraisonAI.
 
 Provides a registry pattern for managing framework adapters with entry points support,
 enabling dynamic registration and discovery of framework adapters.
-Mirrors the design of integrations/registry.py for consistency.
+Uses dependency injection instead of singleton pattern.
 """
 
 from __future__ import annotations
 
 import threading
-from importlib.metadata import entry_points
 from typing import Dict, Type, Optional
 import logging
 
 from .base import FrameworkAdapter
+from .._registry import PluginRegistry
 
 logger = logging.getLogger(__name__)
 
 
-class FrameworkAdapterRegistry:
+def _crewai_loader():
+    from .crewai_adapter import CrewAIAdapter
+    return CrewAIAdapter
+
+def _autogen_loader():
+    from .autogen_adapter import AutoGenAdapter
+    return AutoGenAdapter
+
+def _autogen_v4_loader():
+    from .autogen_adapter import AutoGenV4Adapter
+    return AutoGenV4Adapter
+
+def _ag2_loader():
+    from .autogen_adapter import AG2Adapter
+    return AG2Adapter
+
+def _praisonai_loader():
+    from .praisonai_adapter import PraisonAIAdapter
+    return PraisonAIAdapter
+
+# Built-in framework adapters with lazy loading
+_BUILTIN_ADAPTERS = {
+    "crewai": _crewai_loader,
+    "autogen": _autogen_loader,
+    "autogen_v4": _autogen_v4_loader,
+    "ag2": _ag2_loader,
+    "praisonai": _praisonai_loader,
+}
+
+class FrameworkAdapterRegistry(PluginRegistry[FrameworkAdapter]):
     """
     Registry for framework adapters.
     
     Provides centralized management of framework adapters with support
     for dynamic registration, entry points discovery, and availability checking.
     
-    Uses singleton pattern to ensure consistent state across the application.
+    Uses dependency injection pattern instead of singleton.
     """
-    
-    _instance: Optional["FrameworkAdapterRegistry"] = None
-    _instance_lock = threading.Lock()
 
     def __init__(self) -> None:
         """Initialize the registry with built-in adapters."""
-        self._adapters: Dict[str, Type[FrameworkAdapter]] = {}
-        self._lock = threading.Lock()
-        self._register_builtin()
-        self._register_entry_points()
-
-    @classmethod
-    def get_instance(cls) -> "FrameworkAdapterRegistry":
-        """
-        Get the singleton registry instance.
-        
-        Returns:
-            FrameworkAdapterRegistry: The singleton registry
-        """
-        if cls._instance is None:
-            with cls._instance_lock:
-                if cls._instance is None:
-                    cls._instance = cls()
-        return cls._instance
-
-    def _register_builtin(self) -> None:
-        """Register built-in framework adapters with lazy imports."""
-        # Lazy, optional imports - mirrors integrations/registry.py pattern
-        try:
-            from .crewai_adapter import CrewAIAdapter
-            self._adapters["crewai"] = CrewAIAdapter
-        except ImportError:
-            pass
-        
-        try:
-            from .autogen_adapter import AutoGenAdapter, AutoGenV4Adapter, AG2Adapter
-            self._adapters["autogen"] = AutoGenAdapter
-            self._adapters["autogen_v4"] = AutoGenV4Adapter
-            self._adapters["ag2"] = AG2Adapter
-        except ImportError:
-            pass
-        
-        try:
-            from .praisonai_adapter import PraisonAIAdapter
-            self._adapters["praisonai"] = PraisonAIAdapter
-        except ImportError:
-            pass
-
-    def _register_entry_points(self) -> None:
-        """Register framework adapters from entry points."""
-        try:
-            for ep in entry_points(group="praisonai.framework_adapters"):
-                try:
-                    adapter_class = ep.load()
-                    self._adapters[ep.name] = adapter_class
-                except Exception:
-                    # Do not break framework dispatch because one plugin is broken.
-                    # Surface via structured logging instead of swallowing silently.
-                    logger.warning(
-                        "Failed to load framework adapter %r from entry point",
-                        ep.name,
-                        exc_info=True,
-                    )
-        except Exception:
-            # entry_points() might not be available in older Python versions
-            # or in certain packaging environments
-            logger.debug("Entry points not available for framework adapters")
-
-    def register(self, name: str, adapter_class: Type[FrameworkAdapter]) -> None:
-        """
-        Register a new framework adapter.
-        
-        Args:
-            name: Unique name for the adapter
-            adapter_class: The adapter class (must implement FrameworkAdapter protocol)
-        """
-        # Note: We don't enforce strict type checking here since FrameworkAdapter is a Protocol
-        # and isinstance() doesn't work with Protocols. The runtime will catch typing issues.
-        with self._lock:
-            self._adapters[name] = adapter_class
-
-    def unregister(self, name: str) -> bool:
-        """
-        Unregister a framework adapter.
-        
-        Args:
-            name: Name of the adapter to unregister
-            
-        Returns:
-            bool: True if the adapter was found and removed, False otherwise
-        """
-        with self._lock:
-            return self._adapters.pop(name, None) is not None
-
-    def create(self, name: str) -> FrameworkAdapter:
-        """
-        Create an instance of the specified framework adapter.
-        
-        Args:
-            name: Name of the adapter to create
-            
-        Returns:
-            FrameworkAdapter: Instance of the adapter
-            
-        Raises:
-            ValueError: If the adapter is not found
-        """
-        with self._lock:
-            adapter_class = self._adapters.get(name)
-        
-        if adapter_class is None:
-            raise ValueError(
-                f"Unsupported framework: {name}. "
-                f"Registered: {sorted(self._adapters)}"
-            )
-        
-        return adapter_class()
+        super().__init__(
+            entry_point_group="praisonai.framework_adapters",
+            builtins=_BUILTIN_ADAPTERS
+        )
 
+    # Backward compatibility aliases - delegate to parent methods
     def list_registered(self) -> list[str]:
         """
         List all registered framework adapter names.
@@ -152,8 +72,7 @@ class FrameworkAdapterRegistry:
         Returns:
             list[str]: Sorted list of registered adapter names
         """
-        with self._lock:
-            return sorted(self._adapters)
+        return self.list_names()
 
     def is_available(self, name: str) -> bool:
         """
@@ -174,4 +93,19 @@ class FrameworkAdapterRegistry:
             return adapter.is_available()
         except Exception:
             logger.warning("is_available() raised for adapter %r", name, exc_info=True)
-            return False
+            return False
+
+
+# Default registry (lazy, module-private). NOT exposed as a singleton getter.
+_default_registry: Optional[FrameworkAdapterRegistry] = None
+_default_lock = threading.Lock()
+
+
+def get_default_registry() -> FrameworkAdapterRegistry:
+    """Return the process-default registry. Prefer DI; use this only at the edge."""
+    global _default_registry
+    if _default_registry is None:
+        with _default_lock:
+            if _default_registry is None:
+                _default_registry = FrameworkAdapterRegistry()
+    return _default_registry

src/praisonai/praisonai/framework_adapters/validators.py

@@ -5,7 +5,7 @@ Provides early validation of framework availability to fail fast at CLI entry
 rather than inside run() methods after expensive setup work.
 """
 
-from .registry import FrameworkAdapterRegistry
+from .registry import get_default_registry
 
 
 # Install hints for common frameworks
@@ -26,7 +26,7 @@ def assert_framework_available(name: str) -> None:
     Raises:
         ImportError: If framework is not available with actionable install hint
     """
-    registry = FrameworkAdapterRegistry.get_instance()
+    registry = get_default_registry()
     
     if not registry.is_available(name):
         hint = _INSTALL_HINTS.get(name, f"pip install {name}")

src/praisonai/praisonai/integrations/registry.py

@@ -11,10 +11,10 @@ Features:
 - Backward compatibility with existing get_available_integrations()
 
 Usage:
-    from praisonai.integrations.registry import ExternalAgentRegistry
+    from praisonai.integrations.registry import get_default_registry
     
-    # Get singleton registry
-    registry = ExternalAgentRegistry.get_instance()
+    # Get default registry (or inject custom for multi-tenant)
+    registry = get_default_registry()
     
     # Register custom integration
     registry.register('my-agent', MyCustomIntegration)
@@ -30,67 +30,50 @@ import threading
 from typing import Dict, Type, Optional, Any, List
 
 from .base import BaseCLIIntegration
+from .._registry import PluginRegistry
 
 
-class ExternalAgentRegistry:
+def _claude_code_loader():
+    from .claude_code import ClaudeCodeIntegration
+    return ClaudeCodeIntegration
+
+def _gemini_cli_loader():
+    from .gemini_cli import GeminiCLIIntegration
+    return GeminiCLIIntegration
+
+def _codex_cli_loader():
+    from .codex_cli import CodexCLIIntegration
+    return CodexCLIIntegration
+
+def _cursor_cli_loader():
+    from .cursor_cli import CursorCLIIntegration
+    return CursorCLIIntegration
+
+# Built-in external agent integrations with lazy loading
+_BUILTIN_INTEGRATIONS = {
+    "claude": _claude_code_loader,
+    "gemini": _gemini_cli_loader,
+    "codex": _codex_cli_loader,
+    "cursor": _cursor_cli_loader,
+}
+
+
+class ExternalAgentRegistry(PluginRegistry[BaseCLIIntegration]):
     """
     Registry for external CLI integrations.
     
     Provides centralized management of external agent integrations
     with support for dynamic registration and availability checking.
     
-    Uses singleton pattern to ensure consistent state across the application.
+    Uses dependency injection pattern instead of singleton.
     """
     
-    _instance: Optional['ExternalAgentRegistry'] = None
-    _instance_lock = threading.Lock()
-    
     def __init__(self):
         """Initialize the registry with built-in integrations."""
-        self._integrations: Dict[str, Type[BaseCLIIntegration]] = {}
-        self._lock = threading.Lock()
-        self._register_builtin_integrations()
-    
-    @classmethod
-    def get_instance(cls) -> 'ExternalAgentRegistry':
-        """
-        Get the singleton registry instance.
-        
-        Returns:
-            ExternalAgentRegistry: The singleton registry
-        """
-        if cls._instance is None:
-            with cls._instance_lock:
-                if cls._instance is None:
-                    cls._instance = cls()
-        return cls._instance
-    
-    def _register_builtin_integrations(self):
-        """Register built-in integrations."""
-        # Lazy imports to avoid circular dependencies and performance impact
-        try:
-            from .claude_code import ClaudeCodeIntegration
-            self._integrations['claude'] = ClaudeCodeIntegration
-        except ImportError:
-            pass
-        
-        try:
-            from .gemini_cli import GeminiCLIIntegration
-            self._integrations['gemini'] = GeminiCLIIntegration
-        except ImportError:
-            pass
-        
-        try:
-            from .codex_cli import CodexCLIIntegration
-            self._integrations['codex'] = CodexCLIIntegration
-        except ImportError:
-            pass
-        
-        try:
-            from .cursor_cli import CursorCLIIntegration
-            self._integrations['cursor'] = CursorCLIIntegration
-        except ImportError:
-            pass
+        super().__init__(
+            entry_point_group="praisonai.external_agents", 
+            builtins=_BUILTIN_INTEGRATIONS
+        )
     
     def register(self, name: str, integration_class: Type[BaseCLIIntegration]) -> None:
         """
@@ -108,24 +91,19 @@ class ExternalAgentRegistry:
                 f"Integration class {integration_class.__name__} must inherit from BaseCLIIntegration"
             )
         
-        # Thread-safe registration
-        with self._lock:
-            self._integrations[name] = integration_class
+        # Delegate to parent
+        super().register(name, integration_class)
     
-    def unregister(self, name: str) -> bool:
+    # Backward compatibility methods
+    def list_registered(self) -> List[str]:
         """
-        Unregister an external agent integration.
+        List all registered integration names.
         
-        Args:
-            name: Name of the integration to unregister
-            
         Returns:
-            bool: True if the integration was found and removed, False otherwise
+            List[str]: List of registered integration names
         """
-        # Thread-safe unregistration with atomic check-then-delete
-        with self._lock:
-            return self._integrations.pop(name, None) is not None
-    
+        return self.list_names()
+        
     def create(self, name: str, **kwargs: Any) -> Optional[BaseCLIIntegration]:
         """
         Create an instance of the specified integration.
@@ -137,23 +115,10 @@ class ExternalAgentRegistry:
         Returns:
             BaseCLIIntegration: Instance of the integration, or None if not found
         """
-        with self._lock:
-            integration_class = self._integrations.get(name)
-        
-        if integration_class is None:
+        try:
+            return super().create(name, **kwargs)
+        except ValueError:
             return None
-        
-        return integration_class(**kwargs)
-    
-    def list_registered(self) -> List[str]:
-        """
-        List all registered integration names.
-        
-        Returns:
-            List[str]: List of registered integration names
-        """
-        with self._lock:
-            return list(self._integrations.keys())
     
     async def get_available(self) -> Dict[str, bool]:
         """
@@ -165,8 +130,9 @@ class ExternalAgentRegistry:
         import inspect
         availability = {}
         
+        # Get snapshot of all items from parent class
         with self._lock:
-            snapshot = list(self._integrations.items())
+            snapshot = list(self._items.items())
         
         for name, integration_class in snapshot:
             try:
@@ -201,15 +167,30 @@ class ExternalAgentRegistry:
         return [name for name, available in availability.items() if available]
 
 
-# Factory functions for convenient access
+# Default registry (lazy, module-private). NOT exposed as a singleton getter.
+_default_registry: Optional[ExternalAgentRegistry] = None
+_default_lock = threading.Lock()
+
+
+def get_default_registry() -> ExternalAgentRegistry:
+    """Return the process-default registry. Prefer DI; use this only at the edge.""" 
+    global _default_registry
+    if _default_registry is None:
+        with _default_lock:
+            if _default_registry is None:
+                _default_registry = ExternalAgentRegistry()
+    return _default_registry
+
+
+# Factory functions for convenient access - using default registry
 def get_registry() -> ExternalAgentRegistry:
     """
-    Get the singleton external agent registry.
+    Get the default external agent registry.
     
     Returns:
-        ExternalAgentRegistry: The singleton registry instance
+        ExternalAgentRegistry: The default registry instance
     """
-    return ExternalAgentRegistry.get_instance()
+    return get_default_registry()
 
 
 def register_integration(name: str, integration_class: Type[BaseCLIIntegration]) -> None:
@@ -220,7 +201,7 @@ def register_integration(name: str, integration_class: Type[BaseCLIIntegration])
         name: Unique name for the integration
         integration_class: The integration class (must inherit from BaseCLIIntegration)
     """
-    registry = get_registry()
+    registry = get_default_registry()
     registry.register(name, integration_class)
 
 
@@ -235,7 +216,7 @@ def create_integration(name: str, **kwargs: Any) -> Optional[BaseCLIIntegration]
     Returns:
         BaseCLIIntegration: Instance of the integration, or None if not found
     """
-    registry = get_registry()
+    registry = get_default_registry()
     return registry.create(name, **kwargs)
 
 
@@ -249,7 +230,7 @@ def get_available_integrations() -> Dict[str, bool]:
         Dict[str, bool]: Mapping of integration name to availability status
     """
     import asyncio
-    registry = get_registry()
+    registry = get_default_registry()
     
     from .._async_bridge import run_sync
     return run_sync(registry.get_available())

src/praisonai/praisonai/jobs/models.py

@@ -7,7 +7,7 @@ Defines the data structures for job submission, status, and results.
 import uuid
 from enum import Enum
 from typing import Optional, Dict, Any, List
-from datetime import datetime
+from datetime import datetime, timezone
 from pydantic import BaseModel, Field, field_validator
 import socket
 import ipaddress
@@ -177,7 +177,7 @@ class Job(BaseModel):
     run_id: Optional[str] = Field(None)
     
     # Timestamps
-    created_at: datetime = Field(default_factory=datetime.utcnow)
+    created_at: datetime = Field(default_factory=lambda: datetime.now(timezone.utc))
     started_at: Optional[datetime] = Field(None)
     completed_at: Optional[datetime] = Field(None)
     
@@ -194,7 +194,7 @@ class Job(BaseModel):
         """Calculate job duration."""
         if self.started_at is None:
             return None
-        end_time = self.completed_at or datetime.utcnow()
+        end_time = self.completed_at or datetime.now(timezone.utc)
         return (end_time - self.started_at).total_seconds()
     
     @property
@@ -247,26 +247,26 @@ class Job(BaseModel):
     def start(self):
         """Mark job as started."""
         self.status = JobStatus.RUNNING
-        self.started_at = datetime.utcnow()
+        self.started_at = datetime.now(timezone.utc)
     
     def succeed(self, result: Any, metrics: Optional[Dict[str, Any]] = None):
         """Mark job as succeeded."""
         self.status = JobStatus.SUCCEEDED
         self.result = result
         self.metrics = metrics
-        self.completed_at = datetime.utcnow()
+        self.completed_at = datetime.now(timezone.utc)
         self.progress_percentage = 100.0
     
     def fail(self, error: str):
         """Mark job as failed."""
         self.status = JobStatus.FAILED
         self.error = error
-        self.completed_at = datetime.utcnow()
+        self.completed_at = datetime.now(timezone.utc)
     
     def cancel(self):
         """Mark job as cancelled."""
         self.status = JobStatus.CANCELLED
-        self.completed_at = datetime.utcnow()
+        self.completed_at = datetime.now(timezone.utc)
         self._cancel_requested = True
     
     def update_progress(

src/praisonai/praisonai/jobs/router.py

@@ -7,7 +7,7 @@ Provides HTTP endpoints for job management.
 import asyncio
 import logging
 from typing import Optional
-from datetime import datetime
+from datetime import datetime, timezone
 
 from fastapi import APIRouter, HTTPException, Header, Request, Query, Response
 from sse_starlette.sse import EventSourceResponse
@@ -304,7 +304,7 @@ def create_router(store: JobStore, executor: JobExecutor) -> APIRouter:
                         # Send heartbeat
                         yield {
                             "event": "heartbeat",
-                            "data": f'{{"timestamp": "{datetime.utcnow().isoformat()}"}}'
+                            "data": f'{{"timestamp": "{datetime.now(timezone.utc).isoformat()}"}}'
                         }
             finally:
                 executor.unregister_progress_callback(job_id)

src/praisonai/praisonai/scheduler/shared.py

@@ -64,7 +64,8 @@ def safe_call(cb, *args) -> None:
 
     Supports both sync and async callables. When called from a running event
     loop with a coroutine-returning callback, schedules it on the loop; when
-    called from sync code, runs it to completion via asyncio.run.
+    called from sync code, runs it via the shared persistent loop instead
+    of creating + tearing down a fresh one per call.
     """
     if cb is None:
         return
@@ -78,9 +79,11 @@ def safe_call(cb, *args) -> None:
             try:
                 loop = asyncio.get_running_loop()
             except RuntimeError:
-                # No running loop, use asyncio.run
+                # No loop here: dispatch to the shared persistent loop instead
+                # of creating + tearing down a fresh one.
                 try:
-                    asyncio.run(result)
+                    from .._async_bridge import run_sync
+                    run_sync(result)
                 except Exception as e:
                     log.error("Scheduler async callback raised: %s", e)
             else:

src/praisonai/praisonai/tool_resolver.py

@@ -30,6 +30,7 @@ import threading
 from pathlib import Path
 from typing import Any, Callable, Dict, List, Mapping, Optional
 from types import MappingProxyType
+from ._safe_loader import load_user_module
 
 logger = logging.getLogger(__name__)
 
@@ -74,31 +75,16 @@ class ToolResolver:
             if self._local_tools_loaded:  # Double-check inside lock
                 return self._local_tools_cache
             
-            # Security: Require explicit opt-in for local tools loading
-            if os.environ.get("PRAISONAI_ALLOW_LOCAL_TOOLS", "").lower() != "true":
-                logger.debug("Local tools loading disabled. Set PRAISONAI_ALLOW_LOCAL_TOOLS=true to enable.")
-                self._local_tools_cache = MappingProxyType({})
-                self._local_tools_loaded = True
-                return self._local_tools_cache
-            
             tools_path = Path(self._tools_py_path)
-            if not tools_path.exists():
-                logger.debug(f"No local tools.py found at {tools_path}")
-                self._local_tools_cache = MappingProxyType({})
-                self._local_tools_loaded = True
-                return self._local_tools_cache
-            
             try:
-                spec = importlib.util.spec_from_file_location("tools", str(tools_path))
-                if spec is None or spec.loader is None:
-                    logger.warning(f"Could not load spec for {tools_path}")
+                # Use the same safe loader as other tools.py loading paths
+                module = load_user_module(self._tools_py_path, name="tools")
+                if module is None:
+                    logger.debug(f"Local tools loading disabled or tools.py not found at {self._tools_py_path}")
                     self._local_tools_cache = MappingProxyType({})
                     self._local_tools_loaded = True
                     return self._local_tools_cache
                 
-                module = importlib.util.module_from_spec(spec)
-                spec.loader.exec_module(module)
-                
                 # Build cache locally, then freeze
                 cache: Dict[str, Callable] = {}
                 for name, obj in inspect.getmembers(module):
@@ -108,13 +94,13 @@ class ToolResolver:
                         cache[name] = obj
                         logger.debug(f"Loaded local tool: {name}")
                 
-                logger.info(f"Loaded {len(cache)} tools from {tools_path}")
+                logger.info(f"Loaded {len(cache)} tools from {self._tools_py_path}")
                 
                 # Create immutable view to prevent concurrent modification
                 self._local_tools_cache = MappingProxyType(cache)
                 
             except Exception as e:
-                logger.warning(f"Error loading tools from {tools_path}: {e}")
+                logger.warning(f"Error loading tools from {self._tools_py_path}: {e}")
                 self._local_tools_cache = MappingProxyType({})
             
             self._local_tools_loaded = True
@@ -381,6 +367,58 @@ class ToolResolver:
         with self._local_tools_lock:
             self._local_tools_cache = MappingProxyType({})
             self._local_tools_loaded = False
+    
+    def get_local_callables(self) -> List[Callable]:
+        """Get functions exposed by tools.py (path A semantics).
+        
+        Returns:
+            List of callable functions from tools.py
+        """
+        local_tools = self._load_local_tools()
+        return list(local_tools.values())
+    
+    def get_local_tool_classes(self) -> Dict[str, Any]:
+        """Get BaseTool/langchain class instances from tools.py (path B semantics).
+        
+        Returns:
+            Dictionary mapping class names to instantiated tool objects
+        """
+        try:
+            # Use the same safe loader to get the module
+            module = load_user_module(self._tools_py_path, name="tools_module")
+            if module is None:
+                return {}
+            
+            # Import the necessary classes (matching agents_generator.py logic)
+            BaseTool = None
+            PRAISONAI_TOOLS_AVAILABLE = False
+            try:
+                from praisonai_tools import BaseTool
+                PRAISONAI_TOOLS_AVAILABLE = True
+            except ImportError:
+                try:
+                    from praisonai.tools import BaseTool
+                    PRAISONAI_TOOLS_AVAILABLE = True
+                except ImportError:
+                    pass
+            
+            result = {}
+            for name, obj in inspect.getmembers(module, 
+                lambda x: inspect.isclass(x) and (
+                    x.__module__.startswith('langchain_community.tools') or 
+                    (PRAISONAI_TOOLS_AVAILABLE and BaseTool and issubclass(x, BaseTool))
+                ) and x is not BaseTool):
+                try:
+                    result[name] = obj()
+                    logger.debug(f"Loaded local tool class: {name}")
+                except Exception as e:
+                    logger.warning(f"Error instantiating tool class {name}: {e}")
+                    continue
+            
+            return result
+        except Exception as e:
+            logger.warning(f"Error loading tool classes from {self._tools_py_path}: {e}")
+            return {}
 
 
 # Convenience functions that construct resolver explicitly (no global singleton)

src/praisonai/praisonai/version.py

@@ -1 +1 @@
-__version__ = "4.6.37"
+__version__ = "4.6.38"

src/praisonai/pyproject.toml

@@ -12,9 +12,9 @@ dependencies = [
     "rich>=13.7",
     "markdown>=3.5",
     "pyparsing>=3.0.0",
-    "praisonaiagents>=1.6.37",
+    "praisonaiagents>=1.6.38",
     "python-dotenv>=0.19.0",
-    "litellm>=1.81.0,<=1.82.6",
+    "litellm>=1.83.14,<2",
     "PyYAML>=6.0",
     "mcp>=1.20.0",
     "typer>=0.9.0",

src/praisonai/tests/unit/bots/test_dlq.py

@@ -0,0 +1,160 @@
+"""N4 — Inbound Dead-Letter Queue for BotSessionManager.
+
+Tests written first (TDD). Implementation in praisonai/bots/_dlq.py.
+"""
+from __future__ import annotations
+
+import pytest
+
+
+# ─── Smoke / basic API ───────────────────────────────────────────────
+class TestDLQBasic:
+    def test_import_and_construct(self, tmp_path):
+        from praisonai.bots import InboundDLQ
+        dlq = InboundDLQ(path=tmp_path / "dlq.sqlite")
+        assert dlq.path == tmp_path / "dlq.sqlite"
+        assert dlq.size() == 0
+
+    def test_enqueue_then_size_one(self, tmp_path):
+        from praisonai.bots import InboundDLQ
+        dlq = InboundDLQ(path=tmp_path / "dlq.sqlite")
+        dlq.enqueue(
+            platform="telegram",
+            user_id="12345",
+            prompt="hello",
+            error="LLMTimeout",
+        )
+        assert dlq.size() == 1
+
+    def test_list_returns_entries(self, tmp_path):
+        from praisonai.bots import InboundDLQ
+        dlq = InboundDLQ(path=tmp_path / "dlq.sqlite")
+        dlq.enqueue(platform="discord", user_id="u1", prompt="hi", error="X")
+        dlq.enqueue(platform="discord", user_id="u2", prompt="hey", error="Y")
+        entries = dlq.list()
+        assert len(entries) == 2
+        # newest first
+        assert entries[0].user_id in {"u1", "u2"}
+
+    def test_purge_clears_queue(self, tmp_path):
+        from praisonai.bots import InboundDLQ
+        dlq = InboundDLQ(path=tmp_path / "dlq.sqlite")
+        dlq.enqueue(platform="t", user_id="u", prompt="p", error="e")
+        assert dlq.size() == 1
+        dlq.purge()
+        assert dlq.size() == 0
+
+
+# ─── Persistence ─────────────────────────────────────────────────────
+class TestDLQPersistence:
+    def test_survives_restart(self, tmp_path):
+        from praisonai.bots import InboundDLQ
+        path = tmp_path / "dlq.sqlite"
+        dlq1 = InboundDLQ(path=path)
+        dlq1.enqueue(platform="t", user_id="u", prompt="hi", error="e")
+
+        dlq2 = InboundDLQ(path=path)
+        assert dlq2.size() == 1
+
+
+# ─── Bounds & TTL ────────────────────────────────────────────────────
+class TestDLQBounds:
+    def test_max_size_drops_oldest(self, tmp_path):
+        from praisonai.bots import InboundDLQ
+        dlq = InboundDLQ(path=tmp_path / "dlq.sqlite", max_size=3)
+        for i in range(5):
+            dlq.enqueue(
+                platform="t", user_id=f"u{i}",
+                prompt=f"msg{i}", error="boom",
+            )
+        assert dlq.size() == 3
+        # Newest 3 retained
+        users = {e.user_id for e in dlq.list()}
+        assert users == {"u2", "u3", "u4"}
+
+    def test_ttl_evicts_old(self, tmp_path):
+        from praisonai.bots import InboundDLQ
+        dlq = InboundDLQ(
+            path=tmp_path / "dlq.sqlite",
+            ttl_seconds=0,  # everything is "expired" immediately
+        )
+        dlq.enqueue(platform="t", user_id="u", prompt="p", error="e")
+        # Enqueue itself runs eviction
+        dlq.evict_expired()
+        assert dlq.size() == 0
+
+
+# ─── Replay ──────────────────────────────────────────────────────────
+class TestDLQReplay:
+    @pytest.mark.asyncio
+    async def test_replay_invokes_callback_per_entry(self, tmp_path):
+        from praisonai.bots import InboundDLQ
+        dlq = InboundDLQ(path=tmp_path / "dlq.sqlite")
+        dlq.enqueue(platform="t", user_id="u1", prompt="m1", error="e")
+        dlq.enqueue(platform="t", user_id="u2", prompt="m2", error="e")
+
+        seen = []
+
+        async def replayer(entry):
+            seen.append((entry.user_id, entry.prompt))
+            return True  # success → drop entry
+
+        succeeded, failed = await dlq.replay(replayer)
+        assert succeeded == 2
+        assert failed == 0
+        assert dlq.size() == 0
+        assert {x[0] for x in seen} == {"u1", "u2"}
+
+    @pytest.mark.asyncio
+    async def test_replay_keeps_failed_entries(self, tmp_path):
+        from praisonai.bots import InboundDLQ
+        dlq = InboundDLQ(path=tmp_path / "dlq.sqlite")
+        dlq.enqueue(platform="t", user_id="u", prompt="m", error="e")
+
+        async def failing_replayer(entry):
+            return False
+
+        succeeded, failed = await dlq.replay(failing_replayer)
+        assert succeeded == 0
+        assert failed == 1
+        assert dlq.size() == 1  # entry retained
+
+
+# ─── Wired into BotSessionManager.chat() ─────────────────────────────
+class TestSessionManagerEnqueuesOnFailure:
+    @pytest.mark.asyncio
+    async def test_chat_enqueues_when_agent_raises(self, tmp_path):
+        from praisonai.bots import BotSessionManager, InboundDLQ
+
+        class FailingAgent:
+            chat_history = []
+            def chat(self, prompt):
+                raise RuntimeError("LLM 503")
+
+        dlq = InboundDLQ(path=tmp_path / "dlq.sqlite")
+        mgr = BotSessionManager(platform="telegram", dlq=dlq)
+
+        with pytest.raises(RuntimeError):
+            await mgr.chat(FailingAgent(), "12345", "hello")
+
+        assert dlq.size() == 1
+        e = dlq.list()[0]
+        assert e.platform == "telegram"
+        assert e.user_id == "12345"
+        assert e.prompt == "hello"
+        assert "LLM 503" in e.error
+
+    @pytest.mark.asyncio
+    async def test_chat_no_dlq_when_no_dlq_configured(self, tmp_path):
+        """Default behaviour preserved: no DLQ, error bubbles up."""
+        from praisonai.bots import BotSessionManager
+
+        class FailingAgent:
+            chat_history = []
+            def chat(self, prompt):
+                raise RuntimeError("LLM 503")
+
+        mgr = BotSessionManager(platform="telegram")  # no dlq=
+        with pytest.raises(RuntimeError):
+            await mgr.chat(FailingAgent(), "12345", "hello")
+        # No exception about DLQ; nothing persisted (default behaviour)

src/praisonai/tests/unit/scheduler/test_async_agent_scheduler.py

@@ -170,7 +170,7 @@ class TestStopTimeoutCancelPath:
         scheduler._ensure_async_primitives()
 
         # Simulate a task that raises a plain Exception when awaited after cancel
-        future = asyncio.get_event_loop().create_future()
+        future = asyncio.get_running_loop().create_future()
         future.set_exception(RuntimeError("task blew up"))
         scheduler._task = future
         scheduler._stop_event.set()
@@ -273,7 +273,7 @@ class TestAsyncAgentSchedulerLifecycle:
     @pytest.mark.asyncio
     async def test_get_stats_initial_state(self):
         scheduler = _make_scheduler()
-        stats = scheduler.get_stats()
+        stats = await scheduler.get_stats()
         assert stats["is_running"] is False
         assert stats["total_executions"] == 0
         assert stats["successful_executions"] == 0