chore: bump praisonai version to 2.2.65 and add autogen-v4 dependencies

Merge pull request #941 from MervinPraison/claude/issue-938-20250715-2246
fix: Ensure agent names are valid Python identifiers for AutoGen v0.4
2026-11-08 01:08:39 -10:00 · 2025-07-16 00:12:42 +01:00 · 2025-07-16 00:10:52 +01:00 · 2025-07-15 23:09:41 +00:00 · 2025-07-15 22:51:54 +00:00 · 2025-07-15 22:04:30 +01:00
17 changed files with 970 additions and 390 deletions
@@ -16,7 +16,7 @@ RUN mkdir -p /root/.praison
 # Install Python packages (using latest versions)
 RUN pip install --no-cache-dir \
    flask \
-    "praisonai>=2.2.64" \
+    "praisonai>=2.2.65" \
    "praisonai[api]" \
    gunicorn \
    markdown
@@ -16,7 +16,7 @@ RUN mkdir -p /root/.praison
 # Install Python packages (using latest versions)
 RUN pip install --no-cache-dir \
    praisonai_tools \
-    "praisonai>=2.2.64" \
+    "praisonai>=2.2.65" \
    "praisonai[chat]" \
    "embedchain[github,youtube]"

@@ -20,7 +20,7 @@ RUN mkdir -p /root/.praison
 # Install Python packages (using latest versions)
 RUN pip install --no-cache-dir \
    praisonai_tools \
-    "praisonai>=2.2.64" \
+    "praisonai>=2.2.65" \
    "praisonai[ui]" \
    "praisonai[chat]" \
    "praisonai[realtime]" \
@@ -16,7 +16,7 @@ RUN mkdir -p /root/.praison
 # Install Python packages (using latest versions)
 RUN pip install --no-cache-dir \
    praisonai_tools \
-    "praisonai>=2.2.64" \
+    "praisonai>=2.2.65" \
    "praisonai[ui]" \
    "praisonai[crewai]"

@@ -121,7 +121,7 @@ healthcheck:
 ## 📦 Package Versions

 All Docker images use consistent, up-to-date versions:
- PraisonAI: `>=2.2.64`
+- PraisonAI: `>=2.2.65`
 - PraisonAI Agents: `>=0.0.92`
 - Python: `3.11-slim`

@@ -218,7 +218,7 @@ docker-compose up -d
 ### Version Pinning
 To use specific versions, update the Dockerfile:
 ```dockerfile
-RUN pip install "praisonai==2.2.64" "praisonaiagents==0.0.92"
+RUN pip install "praisonai==2.2.65" "praisonaiagents==0.0.92"
 ```

 ## 🌐 Production Deployment
@@ -1,355 +1,355 @@
 {
- "cells": [
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "_T4g3t5sLoag"
-   },
-   "source": [
-    "# ZeroScript: AI-Powered Browser Test Automation using PraisonAI Agent & OpenAI"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "O4PKfpalLsmn"
-   },
-   "source": [
-    "# Description"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "CEG1pfumLysm"
-   },
-   "source": [
-    "AI-powered browser testing using PraisonAI Agent and OpenAI. Executes YAML-defined test cases, captures screenshots, logs interactions, and generates JSON reports. Ideal for intelligent, automated UI testing.\n",
-    "\n"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "lbgxOG4gL1Wf"
-   },
-   "source": [
-    "[![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/DhivyaBharathy-web/PraisonAI/blob/main/examples/cookbooks/ZeroScript_AI_TestExecutor.ipynb)\n"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "WCJqMUzXIndh"
-   },
-   "source": [
-    "# Dependencies"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 34,
-   "metadata": {
-    "id": "9AQhJ59cJPmR"
-   },
-   "outputs": [],
-   "source": [
-    "!pip install --quiet praisonaiagents browser-use python-dotenv pyyaml openai\n"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "QD-dF-6_It1z"
-   },
-   "source": [
-    "# Environment Setup"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 35,
-   "metadata": {
-    "colab": {
-     "base_uri": "https://localhost:8080/"
-    },
-    "id": "QkRQDli4JhCV",
-    "outputId": "4b8957ed-a37a-4b11-8585-3537a0437d40"
-   },
-   "outputs": [
+  "cells": [
    {
-     "data": {
-      "text/plain": [
-       "True"
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "_T4g3t5sLoag"
+      },
+      "source": [
+        "# ZeroScript: AI-Powered Browser Test Automation using PraisonAI Agent & OpenAI"
      ]
-     },
-     "execution_count": 35,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "import os\n",
-    "from dotenv import load_dotenv\n",
-    "\n",
-    "os.environ[\"OPENAI_API_KEY\"] = \"Enter your key\"  # replace with actual key\n",
-    "load_dotenv()\n"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "ELuogWnrIw3o"
-   },
-   "source": [
-    "# Create my_secrets.py"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 36,
-   "metadata": {
-    "id": "sG6tO_v0Jm5N"
-   },
-   "outputs": [],
-   "source": [
-    "with open(\"my_secrets.py\", \"w\") as f:\n",
-    "    f.write('''sensitive_data = {\n",
-    "    \"username\": \"standard_user\",\n",
-    "    \"password\": \"secret_sauce\"\n",
-    "}''')\n"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "rDB_viedIzRR"
-   },
-   "source": [
-    "# Create views.py"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 37,
-   "metadata": {
-    "id": "CtwcybdbJoV8"
-   },
-   "outputs": [],
-   "source": [
-    "with open(\"views.py\", \"w\") as f:\n",
-    "    f.write('''\n",
-    "from pydantic import BaseModel\n",
-    "\n",
-    "class TestResult(BaseModel):\n",
-    "    status: str\n",
-    "    message: str = \"\"\n",
-    "''')\n"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "YTRmBpTiI1kd"
-   },
-   "source": [
-    "# Create agent.py"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 38,
-   "metadata": {
-    "id": "zdJJGt6TJpvr"
-   },
-   "outputs": [],
-   "source": [
-    "with open(\"agent.py\", \"w\") as f:\n",
-    "    f.write('''\n",
-    "import os\n",
-    "from praisonaiagents import Agent\n",
-    "from browser_use import Browser, BrowserConfig, Controller\n",
-    "from browser_use.browser.context import BrowserContext, BrowserContextConfig\n",
-    "from openai import OpenAI\n",
-    "from views import TestResult\n",
-    "from my_secrets import sensitive_data\n",
-    "\n",
-    "# Browser setup\n",
-    "browser = Browser(config=BrowserConfig(headless=True))\n",
-    "context_cfg = BrowserContextConfig(save_recording_path=\"data/recordings\")\n",
-    "controller = Controller(output_model=TestResult)\n",
-    "\n",
-    "async def browser_use(task: str):\n",
-    "    context = BrowserContext(browser=browser, config=context_cfg)\n",
-    "    agent = Agent(\n",
-    "        task=task,\n",
-    "        llm=OpenAI(api_key=os.getenv(\"OPENAI_API_KEY\"), model=\"gpt-4\"),\n",
-    "        browser_context=context,\n",
-    "        sensitive_data=sensitive_data,\n",
-    "        controller=controller,\n",
-    "        save_conversation_path=\"data/conversations/convo\",\n",
-    "        extend_system_message=(\n",
-    "            \"You are a professional software tester. Execute browser test steps precisely.\"\n",
-    "        )\n",
-    "    )\n",
-    "    response = await agent.run()\n",
-    "    await context.close()\n",
-    "    return response\n",
-    "''')\n"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "-LZtQIE3I4-_"
-   },
-   "source": [
-    "# Create Sample Test YAML"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 39,
-   "metadata": {
-    "colab": {
-     "base_uri": "https://localhost:8080/"
    },
-    "id": "l1OdXYI-JreK",
-    "outputId": "62323fcd-c74f-498f-defc-2c170fa8983e"
-   },
-   "outputs": [
    {
-     "data": {
-      "text/plain": [
-       "350"
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "O4PKfpalLsmn"
+      },
+      "source": [
+        "# Description"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "CEG1pfumLysm"
+      },
+      "source": [
+        "AI-powered browser testing using PraisonAI Agent and OpenAI. Executes YAML-defined test cases, captures screenshots, logs interactions, and generates JSON reports. Ideal for intelligent, automated UI testing.\n",
+        "\n"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "lbgxOG4gL1Wf"
+      },
+      "source": [
+        "[![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/DhivyaBharathy-web/PraisonAI/blob/main/examples/cookbooks/ZeroScript_AI_TestExecutor.ipynb)\n"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "WCJqMUzXIndh"
+      },
+      "source": [
+        "# Dependencies"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 34,
+      "metadata": {
+        "id": "9AQhJ59cJPmR"
+      },
+      "outputs": [],
+      "source": [
+        "!pip install --quiet praisonaiagents browser-use python-dotenv pyyaml openai\n"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "QD-dF-6_It1z"
+      },
+      "source": [
+        "# Environment Setup"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 35,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "QkRQDli4JhCV",
+        "outputId": "4b8957ed-a37a-4b11-8585-3537a0437d40"
+      },
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "True"
+            ]
+          },
+          "execution_count": 35,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
+      "source": [
+        "import os\n",
+        "from dotenv import load_dotenv\n",
+        "\n",
+        "os.environ[\"OPENAI_API_KEY\"] = \"Enter your key\"  # replace with actual key\n",
+        "load_dotenv()\n"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "ELuogWnrIw3o"
+      },
+      "source": [
+        "# Create my_secrets.py"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 36,
+      "metadata": {
+        "id": "sG6tO_v0Jm5N"
+      },
+      "outputs": [],
+      "source": [
+        "with open(\"my_secrets.py\", \"w\") as f:\n",
+        "    f.write('''sensitive_data = {\n",
+        "    \"username\": \"standard_user\",\n",
+        "    \"password\": \"secret_sauce\"\n",
+        "}''')\n"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "rDB_viedIzRR"
+      },
+      "source": [
+        "# Create views.py"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 37,
+      "metadata": {
+        "id": "CtwcybdbJoV8"
+      },
+      "outputs": [],
+      "source": [
+        "with open(\"views.py\", \"w\") as f:\n",
+        "    f.write('''\n",
+        "from pydantic import BaseModel\n",
+        "\n",
+        "class TestResult(BaseModel):\n",
+        "    status: str\n",
+        "    message: str = \"\"\n",
+        "''')\n"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "YTRmBpTiI1kd"
+      },
+      "source": [
+        "# Create agent.py"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 38,
+      "metadata": {
+        "id": "zdJJGt6TJpvr"
+      },
+      "outputs": [],
+      "source": [
+        "with open(\"agent.py\", \"w\") as f:\n",
+        "    f.write('''\n",
+        "import os\n",
+        "from praisonaiagents import Agent\n",
+        "from browser_use import Browser, BrowserConfig, Controller\n",
+        "from browser_use.browser.context import BrowserContext, BrowserContextConfig\n",
+        "from openai import OpenAI\n",
+        "from views import TestResult\n",
+        "from my_secrets import sensitive_data\n",
+        "\n",
+        "# Browser setup\n",
+        "browser = Browser(config=BrowserConfig(headless=True))\n",
+        "context_cfg = BrowserContextConfig(save_recording_path=\"data/recordings\")\n",
+        "controller = Controller(output_model=TestResult)\n",
+        "\n",
+        "async def browser_use(task: str):\n",
+        "    context = BrowserContext(browser=browser, config=context_cfg)\n",
+        "    agent = Agent(\n",
+        "        task=task,\n",
+        "        llm=OpenAI(api_key=os.getenv(\"OPENAI_API_KEY\"), model=\"gpt-4\"),\n",
+        "        browser_context=context,\n",
+        "        sensitive_data=sensitive_data,\n",
+        "        controller=controller,\n",
+        "        save_conversation_path=\"data/conversations/convo\",\n",
+        "        extend_system_message=(\n",
+        "            \"You are a professional software tester. Execute browser test steps precisely.\"\n",
+        "        )\n",
+        "    )\n",
+        "    response = await agent.run()\n",
+        "    await context.close()\n",
+        "    return response\n",
+        "''')\n"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "-LZtQIE3I4-_"
+      },
+      "source": [
+        "# Create Sample Test YAML"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 39,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "l1OdXYI-JreK",
+        "outputId": "62323fcd-c74f-498f-defc-2c170fa8983e"
+      },
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "350"
+            ]
+          },
+          "execution_count": 39,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
+      "source": [
+        "from pathlib import Path\n",
+        "tests_dir = Path(\"tests\")\n",
+        "tests_dir.mkdir(exist_ok=True)\n",
+        "yaml_content = \"\"\"\n",
+        "hooks:\n",
+        "  beforeEach: |\n",
+        "    Navigate to https://www.saucedemo.com\n",
+        "  afterEach: |\n",
+        "    Take screenshot\n",
+        "\n",
+        "tests:\n",
+        "  - id: \"login_test_001\"\n",
+        "    name: \"Valid Login Test\"\n",
+        "    instructions: |\n",
+        "      1. Enter standard_user in username field\n",
+        "      2. Enter secret_sauce in password field\n",
+        "      3. Click login button\n",
+        "      4. Verify page contains text \"Products\"\n",
+        "\"\"\"\n",
+        "(Path(\"tests/login_test.yml\")).write_text(yaml_content)\n"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "sUjy-7OdI7p_"
+      },
+      "source": [
+        "# Run Tests"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 40,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "Agkiwh7xJtY3",
+        "outputId": "759aa77c-fd65-49b8-b239-550588059478"
+      },
+      "outputs": [
+        {
+          "name": "stderr",
+          "output_type": "stream",
+          "text": [
+            "Exception ignored in: <function BrowserSession.__del__ at 0x7e2f540fb100>\n",
+            "Traceback (most recent call last):\n",
+            "  File \"/usr/local/lib/python3.11/dist-packages/browser_use/browser/session.py\", line 497, in __del__\n",
+            "    status = f'\ud83e\ude93 killing pid={self.browser_pid}...' if (self.browser_pid and owns_browser) else '\u2620\ufe0f'\n",
+            "                                                         ^^^^^^^^^^^^^^^^\n",
+            "  File \"/usr/local/lib/python3.11/dist-packages/pydantic/main.py\", line 991, in __getattr__\n",
+            "    raise AttributeError(f'{type(self).__name__!r} object has no attribute {item!r}')\n",
+            "AttributeError: 'BrowserSession' object has no attribute 'browser_pid'\n"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "\u2705 Report saved to data/reports/report_20250630_092319.json\n"
+          ]
+        }
+      ],
+      "source": [
+        "import asyncio, yaml, json, base64, shutil\n",
+        "from agent import browser_use, browser\n",
+        "from pathlib import Path\n",
+        "from datetime import datetime\n",
+        "\n",
+        "# Clean or create data dirs\n",
+        "for sub in [\"recordings\", \"conversations\", \"screenshots\", \"reports\"]:\n",
+        "    d = Path(\"data\") / sub\n",
+        "    if d.exists(): shutil.rmtree(d)\n",
+        "    d.mkdir(parents=True, exist_ok=True)\n",
+        "\n",
+        "async def execute_test_file(path):\n",
+        "    cfg = yaml.safe_load(Path(path).read_text())\n",
+        "    hooks, results = cfg.get(\"hooks\", {}), []\n",
+        "    for t in cfg[\"tests\"]:\n",
+        "        task = f\"{hooks.get('beforeEach','')}\\n{t['instructions']}\\n{hooks.get('afterEach','')}\"\n",
+        "        res = {\"id\": t[\"id\"], \"name\": t[\"name\"]}\n",
+        "        try:\n",
+        "            r = await browser_use(task)\n",
+        "            imgs = r.screenshots()\n",
+        "            if imgs:\n",
+        "                out = Path(\"data/screenshots\") / f\"{t['id']}.png\"\n",
+        "                out.write_bytes(base64.b64decode(imgs[-1]))\n",
+        "            result_obj = r.final_result() if hasattr(r, \"final_result\") else str(r)\n",
+        "            res[\"result\"] = result_obj.model_dump() if hasattr(result_obj, \"model_dump\") else str(result_obj)\n",
+        "        except Exception as e:\n",
+        "            res[\"error\"] = str(e)\n",
+        "        results.append(res)\n",
+        "    return results\n",
+        "\n",
+        "async def main():\n",
+        "    all_results = []\n",
+        "    for file in Path(\"tests\").glob(\"*.yml\"):\n",
+        "        all_results.extend(await execute_test_file(str(file)))\n",
+        "    report = Path(\"data/reports\") / f\"report_{datetime.now():%Y%m%d_%H%M%S}.json\"\n",
+        "    report.write_text(json.dumps(all_results, indent=2))\n",
+        "    await browser.close()\n",
+        "    print(f\"\u2705 Report saved to {report}\")\n",
+        "\n",
+        "await main()\n"
      ]
-     },
-     "execution_count": 39,
-     "metadata": {},
-     "output_type": "execute_result"
    }
-   ],
-   "source": [
-    "from pathlib import Path\n",
-    "tests_dir = Path(\"tests\")\n",
-    "tests_dir.mkdir(exist_ok=True)\n",
-    "yaml_content = \"\"\"\n",
-    "hooks:\n",
-    "  beforeEach: |\n",
-    "    Navigate to https://www.saucedemo.com\n",
-    "  afterEach: |\n",
-    "    Take screenshot\n",
-    "\n",
-    "tests:\n",
-    "  - id: \"login_test_001\"\n",
-    "    name: \"Valid Login Test\"\n",
-    "    instructions: |\n",
-    "      1. Enter standard_user in username field\n",
-    "      2. Enter secret_sauce in password field\n",
-    "      3. Click login button\n",
-    "      4. Verify page contains text \"Products\"\n",
-    "\"\"\"\n",
-    "(Path(\"tests/login_test.yml\")).write_text(yaml_content)\n"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "sUjy-7OdI7p_"
-   },
-   "source": [
-    "# Run Tests"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 40,
-   "metadata": {
+  ],
+  "metadata": {
    "colab": {
-     "base_uri": "https://localhost:8080/"
+      "provenance": []
    },
-    "id": "Agkiwh7xJtY3",
-    "outputId": "759aa77c-fd65-49b8-b239-550588059478"
-   },
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "Exception ignored in: <function BrowserSession.__del__ at 0x7e2f540fb100>\n",
-      "Traceback (most recent call last):\n",
-      "  File \"/usr/local/lib/python3.11/dist-packages/browser_use/browser/session.py\", line 497, in __del__\n",
-      "    status = f'🪓 killing pid={self.browser_pid}...' if (self.browser_pid and owns_browser) else '☠️'\n",
-      "                                                         ^^^^^^^^^^^^^^^^\n",
-      "  File \"/usr/local/lib/python3.11/dist-packages/pydantic/main.py\", line 991, in __getattr__\n",
-      "    raise AttributeError(f'{type(self).__name__!r} object has no attribute {item!r}')\n",
-      "AttributeError: 'BrowserSession' object has no attribute 'browser_pid'\n"
-     ]
+    "kernelspec": {
+      "display_name": "Python 3",
+      "name": "python3"
    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "✅ Report saved to data/reports/report_20250630_092319.json\n"
-     ]
+    "language_info": {
+      "name": "python"
    }
-   ],
-   "source": [
-    "import asyncio, yaml, json, base64, shutil\n",
-    "from agent import browser_use, browser\n",
-    "from pathlib import Path\n",
-    "from datetime import datetime\n",
-    "\n",
-    "# Clean or create data dirs\n",
-    "for sub in [\"recordings\", \"conversations\", \"screenshots\", \"reports\"]:\n",
-    "    d = Path(\"data\") / sub\n",
-    "    if d.exists(): shutil.rmtree(d)\n",
-    "    d.mkdir(parents=True, exist_ok=True)\n",
-    "\n",
-    "async def execute_test_file(path):\n",
-    "    cfg = yaml.safe_load(Path(path).read_text())\n",
-    "    hooks, results = cfg.get(\"hooks\", {}), []\n",
-    "    for t in cfg[\"tests\"]:\n",
-    "        task = f\"{hooks.get('beforeEach','')}\\n{t['instructions']}\\n{hooks.get('afterEach','')}\"\n",
-    "        res = {\"id\": t[\"id\"], \"name\": t[\"name\"]}\n",
-    "        try:\n",
-    "            r = await browser_use(task)\n",
-    "            imgs = r.screenshots()\n",
-    "            if imgs:\n",
-    "                out = Path(\"data/screenshots\") / f\"{t['id']}.png\"\n",
-    "                out.write_bytes(base64.b64decode(imgs[-1]))\n",
-    "            result_obj = r.final_result() if hasattr(r, \"final_result\") else str(r)\n",
-    "            res[\"result\"] = result_obj.dict() if hasattr(result_obj, \"dict\") else str(result_obj)\n",
-    "        except Exception as e:\n",
-    "            res[\"error\"] = str(e)\n",
-    "        results.append(res)\n",
-    "    return results\n",
-    "\n",
-    "async def main():\n",
-    "    all_results = []\n",
-    "    for file in Path(\"tests\").glob(\"*.yml\"):\n",
-    "        all_results.extend(await execute_test_file(str(file)))\n",
-    "    report = Path(\"data/reports\") / f\"report_{datetime.now():%Y%m%d_%H%M%S}.json\"\n",
-    "    report.write_text(json.dumps(all_results, indent=2))\n",
-    "    await browser.close()\n",
-    "    print(f\"✅ Report saved to {report}\")\n",
-    "\n",
-    "await main()\n"
-   ]
-  }
- ],
- "metadata": {
-  "colab": {
-   "provenance": []
  },
-  "kernelspec": {
-   "display_name": "Python 3",
-   "name": "python3"
-  },
-  "language_info": {
-   "name": "python"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 0
-}
+  "nbformat": 4,
+  "nbformat_minor": 0
+}
@@ -440,7 +440,7 @@ async def generate_research(
        "message": "Report generation queued",
        "created_at": datetime.now().isoformat(),
        "updated_at": datetime.now().isoformat(),
-        "config": request.dict()
+        "config": request.model_dump()
    }
    
    # Create config object
@@ -31,7 +31,7 @@ def save_reasoning_chain(chain: ChainOfThought) -> str:
    """Save a chain of thought reasoning to analyze patterns."""
    filename = f"reasoning_{chain.problem[:20].replace(' ', '_')}.json"
    with open(filename, 'w') as f:
-        json.dump(chain.dict(), f, indent=2)
+        json.dump(chain.model_dump(), f, indent=2)
    return f"Reasoning chain saved to {filename}"

 # Example 1: Chain of Thought Agent
@@ -0,0 +1,51 @@
+#!/usr/bin/env python3
+"""
+Script to fix the deprecated .dict() usage in Jupyter notebook
+"""
+import json
+import sys
+
+def fix_notebook():
+    notebook_path = "examples/cookbooks/Programming_Code_Analysis_Agents/ZeroScript_AI_TestExecutor.ipynb"
+    
+    try:
+        # Read the notebook
+        with open(notebook_path, 'r') as f:
+            notebook = json.load(f)
+        
+        # Find and fix the cell with .dict() usage
+        for cell in notebook.get('cells', []):
+            if cell.get('cell_type') == 'code':
+                source = cell.get('source', [])
+                # Convert source to string if it's a list
+                source_str = ''.join(source) if isinstance(source, list) else source
+                
+                # Check if this cell contains the problematic .dict() usage or hasattr check
+                if 'result_obj.dict()' in source_str or 'hasattr(result_obj, "dict")' in source_str:
+                    print(f"Found cell with .dict() usage, fixing...")
+                    # Replace .dict() with .model_dump() and fix hasattr check for backward compatibility
+                    fixed_source = source_str.replace('result_obj.dict()', 'result_obj.model_dump()').replace('hasattr(result_obj, "dict")', 'hasattr(result_obj, "model_dump")')
+                    
+                    # Convert back to list format if needed
+                    if isinstance(source, list):
+                        cell['source'] = fixed_source.splitlines(True)
+                    else:
+                        cell['source'] = fixed_source
+                    
+                    print("Fixed .dict() usage")
+                    break
+        
+        # Write the fixed notebook back
+        with open(notebook_path, 'w') as f:
+            json.dump(notebook, f, indent=2)
+        
+        print(f"Successfully updated {notebook_path}")
+        return True
+        
+    except Exception as e:
+        print(f"Error fixing notebook: {e}")
+        return False
+
+if __name__ == "__main__":
+    success = fix_notebook()
+    sys.exit(0 if success else 1)
@@ -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/v2.2.64.tar.gz"
-    sha256 `curl -sL https://github.com/MervinPraison/PraisonAI/archive/refs/tags/v2.2.64.tar.gz | shasum -a 256`.split.first
+    url "https://github.com/MervinPraison/PraisonAI/archive/refs/tags/v2.2.65.tar.gz"
+    sha256 `curl -sL https://github.com/MervinPraison/PraisonAI/archive/refs/tags/v2.2.65.tar.gz | shasum -a 256`.split.first
    license "MIT"
  
    depends_on "[email protected]"
@@ -14,10 +14,13 @@ import importlib
 import importlib.util
 import os
 import logging
+import re
+import keyword

 # Framework-specific imports with availability checks
 CREWAI_AVAILABLE = False
 AUTOGEN_AVAILABLE = False
+AUTOGEN_V4_AVAILABLE = False
 PRAISONAI_TOOLS_AVAILABLE = False
 AGENTOPS_AVAILABLE = False
 PRAISONAI_AVAILABLE = False
@@ -41,6 +44,17 @@ try:
 except ImportError:
    pass

+try:
+    from autogen_agentchat.agents import AssistantAgent as AutoGenV4AssistantAgent
+    from autogen_ext.models.openai import OpenAIChatCompletionClient
+    from autogen_agentchat.teams import RoundRobinGroupChat
+    from autogen_agentchat.conditions import TextMentionTermination, MaxMessageTermination
+    from autogen_agentchat.messages import TextMessage
+    from autogen_core import CancellationToken
+    AUTOGEN_V4_AVAILABLE = True
+except ImportError:
+    pass
+
 try:
    import agentops
    AGENTOPS_AVAILABLE = True
@@ -70,6 +84,40 @@ os.environ["OTEL_SDK_DISABLED"] = "true"
 def noop(*args, **kwargs):
    pass

+def sanitize_agent_name_for_autogen_v4(name):
+    """
+    Sanitize agent name to be a valid Python identifier for AutoGen v0.4.
+    
+    Args:
+        name (str): The original agent name
+        
+    Returns:
+        str: A valid Python identifier
+    """
+    # Convert to string and replace invalid characters with underscores
+    sanitized = re.sub(r'[^a-zA-Z0-9_]', '_', str(name))
+    
+    # Collapse only very excessive underscores (5 or more) to reduce extreme cases
+    sanitized = re.sub(r'_{5,}', '_', sanitized)
+    
+    # Remove trailing underscores only if not part of a dunder pattern and only if singular
+    if sanitized.endswith('_') and not sanitized.endswith('__') and sanitized != '_':
+        sanitized = sanitized.rstrip('_')
+    
+    # Ensure it starts with a letter or underscore (not a digit)
+    if sanitized and sanitized[0].isdigit():
+        sanitized = 'agent_' + sanitized
+    
+    # Handle empty string or only invalid characters (including single underscore from all invalid chars)
+    if not sanitized or sanitized == '_':
+        sanitized = 'agent'
+    
+    # Check if it's a Python keyword and append underscore if so
+    if keyword.iskeyword(sanitized):
+        sanitized += '_'
+    
+    return sanitized
+
 def disable_crewai_telemetry():
    if CREWAI_AVAILABLE:
        for attr in dir(Telemetry):
@@ -123,8 +171,8 @@ class AgentsGenerator:
        # Validate framework availability
        if framework == "crewai" and not CREWAI_AVAILABLE:
            raise ImportError("CrewAI is not installed. Please install it with 'pip install praisonai[crewai]'")
-        elif framework == "autogen" and not AUTOGEN_AVAILABLE:
-            raise ImportError("AutoGen is not installed. Please install it with 'pip install praisonai[autogen]'")
+        elif framework == "autogen" and not (AUTOGEN_AVAILABLE or AUTOGEN_V4_AVAILABLE):
+            raise ImportError("AutoGen is not installed. Please install it with 'pip install praisonai[autogen]' for v0.2 or 'pip install praisonai[autogen-v4]' for v0.4")
        elif framework == "praisonai" and not PRAISONAI_AVAILABLE:
            raise ImportError("PraisonAI is not installed. Please install it with 'pip install praisonaiagents'")

@@ -316,11 +364,35 @@ class AgentsGenerator:
        framework = self.framework or config.get('framework')

        if framework == "autogen":
-            if not AUTOGEN_AVAILABLE:
-                raise ImportError("AutoGen is not installed. Please install it with 'pip install praisonai[autogen]'")
+            if not (AUTOGEN_AVAILABLE or AUTOGEN_V4_AVAILABLE):
+                raise ImportError("AutoGen is not installed. Please install it with 'pip install praisonai[autogen]' for v0.2 or 'pip install praisonai[autogen-v4]' for v0.4")
+            
+            # Choose autogen version based on availability and environment preference
+            # AUTOGEN_VERSION can be set to "v0.2" or "v0.4" to force a specific version
+            autogen_version = os.environ.get("AUTOGEN_VERSION", "auto").lower()
+            
+            use_v4 = False
+            if autogen_version == "v0.4" and AUTOGEN_V4_AVAILABLE:
+                use_v4 = True
+            elif autogen_version == "v0.2" and AUTOGEN_AVAILABLE:
+                use_v4 = False
+            elif autogen_version == "auto":
+                # Default preference: use v0.4 if available, fallback to v0.2
+                use_v4 = AUTOGEN_V4_AVAILABLE
+            else:
+                # Fallback to whatever is available
+                use_v4 = AUTOGEN_V4_AVAILABLE and not AUTOGEN_AVAILABLE
+            
            if AGENTOPS_AVAILABLE:
-                agentops.init(os.environ.get("AGENTOPS_API_KEY"), default_tags=["autogen"])
-            return self._run_autogen(config, topic, tools_dict)
+                version_tag = "autogen-v4" if use_v4 else "autogen-v2"
+                agentops.init(os.environ.get("AGENTOPS_API_KEY"), default_tags=[version_tag])
+            
+            if use_v4:
+                self.logger.info("Using AutoGen v0.4")
+                return self._run_autogen_v4(config, topic, tools_dict)
+            else:
+                self.logger.info("Using AutoGen v0.2")
+                return self._run_autogen(config, topic, tools_dict)
        elif framework == "praisonai":
            if not PRAISONAI_AVAILABLE:
                raise ImportError("PraisonAI is not installed. Please install it with 'pip install praisonaiagents'")
@@ -407,6 +479,113 @@ class AgentsGenerator:
            
        return result

+    def _run_autogen_v4(self, config, topic, tools_dict):
+        """
+        Run agents using the AutoGen v0.4 framework with async, event-driven architecture.
+        
+        Args:
+            config (dict): Configuration dictionary
+            topic (str): The topic to process
+            tools_dict (dict): Dictionary of available tools
+            
+        Returns:
+            str: Result of the agent interactions
+        """
+        import asyncio
+        
+        async def run_autogen_v4_async():
+            # Create model client for v0.4
+            model_config = self.config_list[0] if self.config_list else {}
+            model_client = OpenAIChatCompletionClient(
+                model=model_config.get('model', 'gpt-4o'),
+                api_key=model_config.get('api_key', os.environ.get("OPENAI_API_KEY")),
+                base_url=model_config.get('base_url', "https://api.openai.com/v1")
+            )
+            
+            agents = []
+            combined_tasks = []
+            
+            # Create agents from config
+            for role, details in config['roles'].items():
+                # For AutoGen v0.4, ensure agent name is a valid Python identifier
+                agent_name = details['role'].format(topic=topic).replace("{topic}", topic)
+                agent_name = sanitize_agent_name_for_autogen_v4(agent_name)
+                backstory = details['backstory'].format(topic=topic)
+                
+                # Convert tools for v0.4 - simplified tool passing
+                agent_tools = []
+                for tool_name in details.get('tools', []):
+                    if tool_name in tools_dict:
+                        tool_instance = tools_dict[tool_name]
+                        # For v0.4, we can pass the tool's run method directly if it's callable
+                        if hasattr(tool_instance, 'run') and callable(tool_instance.run):
+                            agent_tools.append(tool_instance.run)
+                
+                # Create v0.4 AssistantAgent
+                assistant = AutoGenV4AssistantAgent(
+                    name=agent_name,
+                    system_message=backstory + ". Must reply with 'TERMINATE' when the task is complete.",
+                    model_client=model_client,
+                    tools=agent_tools,
+                    reflect_on_tool_use=True
+                )
+                
+                agents.append(assistant)
+                
+                # Collect all task descriptions for sequential execution
+                for task_name, task_details in details.get('tasks', {}).items():
+                    description_filled = task_details['description'].format(topic=topic)
+                    combined_tasks.append(description_filled)
+            
+            if not agents:
+                return "No agents created from configuration"
+            
+            # Create termination conditions
+            text_termination = TextMentionTermination("TERMINATE")
+            max_messages_termination = MaxMessageTermination(max_messages=20)
+            termination_condition = text_termination | max_messages_termination
+            
+            # Create RoundRobinGroupChat for parallel/sequential execution
+            group_chat = RoundRobinGroupChat(
+                agents,
+                termination_condition=termination_condition,
+                max_turns=len(agents) * 3  # Allow multiple rounds
+            )
+            
+            # Combine all tasks into a single task description
+            task_description = f"Topic: {topic}\n\nTasks to complete:\n" + "\n".join(
+                f"{i+1}. {task}" for i, task in enumerate(combined_tasks)
+            )
+            
+            # Run the group chat
+            try:
+                result = await group_chat.run(task=task_description)
+                
+                # Extract the final message content
+                if result.messages:
+                    final_message = result.messages[-1]
+                    if hasattr(final_message, 'content'):
+                        return f"### AutoGen v0.4 Output ###\n{final_message.content}"
+                    else:
+                        return f"### AutoGen v0.4 Output ###\n{str(final_message)}"
+                else:
+                    return "### AutoGen v0.4 Output ###\nNo messages generated"
+                    
+            except Exception as e:
+                self.logger.error(f"Error in AutoGen v0.4 execution: {str(e)}")
+                return f"### AutoGen v0.4 Error ###\n{str(e)}"
+            
+            finally:
+                # Close the model client
+                await model_client.close()
+        
+        # Run the async function
+        try:
+            return asyncio.run(run_autogen_v4_async())
+        except Exception as e:
+            self.logger.error(f"Error running AutoGen v0.4: {str(e)}")
+            return f"### AutoGen v0.4 Error ###\n{str(e)}"
+
    def _run_crewai(self, config, topic, tools_dict):
        """
        Run agents using the CrewAI framework.
@@ -32,6 +32,13 @@ try:
 except ImportError:
    pass

+try:
+    from autogen_agentchat.agents import AssistantAgent
+    from autogen_ext.models.openai import OpenAIChatCompletionClient
+    AUTOGEN_V4_AVAILABLE = True
+except ImportError:
+    AUTOGEN_V4_AVAILABLE = False
+
 try:
    from praisonai_tools import (
        CodeDocsSearchTool, CSVSearchTool, DirectorySearchTool, DOCXSearchTool,
@@ -73,10 +80,11 @@ class AutoGenerator:
 CrewAI is not installed. Please install with:
    pip install "praisonai[crewai]"
 """)
-        elif framework == "autogen" and not AUTOGEN_AVAILABLE:
+        elif framework == "autogen" and not (AUTOGEN_AVAILABLE or AUTOGEN_V4_AVAILABLE):
            raise ImportError("""
 AutoGen is not installed. Please install with:
-    pip install "praisonai[autogen]"
+    pip install "praisonai[autogen]" for v0.2
+    pip install "praisonai[autogen-v4]" for v0.4
 """)
        elif framework == "praisonai" and not PRAISONAI_AVAILABLE:
            raise ImportError("""
@@ -86,7 +94,14 @@ Praisonai is not installed. Please install with:

        # Only show tools message if using a framework and tools are needed
        if (framework in ["crewai", "autogen"]) and not PRAISONAI_TOOLS_AVAILABLE:
-            logging.warning(f"""
+            if framework == "autogen":
+                logging.warning("""
+Tools are not available for autogen. To use tools, install:
+    pip install "praisonai[autogen]" for v0.2
+    pip install "praisonai[autogen-v4]" for v0.4
+""")
+            else:
+                logging.warning(f"""
 Tools are not available for {framework}. To use tools, install:
    pip install "praisonai[{framework}]"
 """)
@@ -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==2.2.64 gunicorn markdown\n")
+            file.write("RUN pip install flask praisonai==2.2.65 gunicorn markdown\n")
            file.write("EXPOSE 8080\n")
            file.write('CMD ["gunicorn", "-b", "0.0.0.0:8080", "api:app"]\n')
            
@@ -1,6 +1,6 @@
 [project]
 name = "PraisonAI"
-version = "2.2.64"
+version = "2.2.65"
 description = "PraisonAI is an AI Agents Framework with Self Reflection. PraisonAI application combines PraisonAI Agents, AutoGen, and CrewAI into a low-code solution for building and managing multi-agent LLM systems, focusing on simplicity, customisation, and efficient human-agent collaboration."
 readme = "README.md"
 license = ""
@@ -92,10 +92,17 @@ call = [
 train = []
 crewai = ["crewai>=0.32.0", "praisonai-tools>=0.0.22"]
 autogen = ["pyautogen==0.2.29", "praisonai-tools>=0.0.22", "crewai"]
+autogen-v4 = [
+    "autogen-agentchat>=0.4.0", 
+    "autogen-ext[openai]>=0.4.0", 
+    "autogen-core>=0.4.0",
+    "praisonai-tools>=0.0.22", 
+    "crewai"
+]

 [tool.poetry]
 name = "PraisonAI"
-version = "2.2.64"
+version = "2.2.65"
 description = "PraisonAI is an AI Agents Framework with Self Reflection. PraisonAI application combines PraisonAI Agents, AutoGen, and CrewAI into a low-code solution for building and managing multi-agent LLM systems, focusing on simplicity, customisation, and efficient human-agent collaboration."
 authors = ["Mervin Praison"]
 license = ""
@@ -119,6 +126,9 @@ instructor = ">=1.3.3"
 PyYAML = ">=6.0"
 mcp = ">=1.6.0"
 pyautogen = {version = "==0.2.29", optional = true}
+autogen-agentchat = {version = ">=0.4.0", optional = true}
+autogen-ext = {version = ">=0.4.0", optional = true}
+autogen-core = {version = ">=0.4.0", optional = true}
 crewai = {version = ">=0.32.0", optional = true}
 praisonai-tools = {version = ">=0.0.22", optional = true}
 chainlit = {version = "==2.5.5", optional = true}
@@ -277,6 +287,7 @@ call = [
 ]
 crewai = ["crewai", "praisonai-tools"]
 autogen = ["pyautogen", "praisonai-tools", "crewai"]
+autogen-v4 = ["autogen-agentchat", "autogen-ext", "autogen-core", "praisonai-tools", "crewai"]

 [tool.poetry-dynamic-versioning]
 enable = true
@@ -335,6 +335,54 @@ wheels = [
    { url = "https://files.pythonhosted.org/packages/ac/d1/800ab8dfe15f00836b8d1ea41f68f5e4731a96e8fc19548993996f3b5728/auth0_python-4.9.0-py3-none-any.whl", hash = "sha256:6440c7f74dfd669d9f5cdfe9bb44c4c3b230ce98a82353f55a387e90241fbf5b", size = 135349, upload-time = "2025-04-01T09:31:35.538Z" },
 ]

+[[package]]
+name = "autogen-agentchat"
+version = "0.6.4"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "autogen-core" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/c3/9a/89e3b4456ba543593aef37e2ed38b52b374d0b43db87a3494490e20aa29e/autogen_agentchat-0.6.4.tar.gz", hash = "sha256:a50ba1a97f3881693084677807756714f237da89fd481207e6d139c930b2b3f8", size = 137817, upload-time = "2025-07-09T17:48:32.868Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/92/bc/3cc970d370d3dff4e83cf4008062e129c997b879cf721efce5a381cbb953/autogen_agentchat-0.6.4-py3-none-any.whl", hash = "sha256:441f884af0eb9edb953451b0ec06077ac782a7d60d591ce7ea57d94fefad2098", size = 114245, upload-time = "2025-07-09T17:48:31.48Z" },
+]
+
+[[package]]
+name = "autogen-core"
+version = "0.6.4"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "jsonref" },
+    { name = "opentelemetry-api" },
+    { name = "pillow" },
+    { name = "protobuf" },
+    { name = "pydantic" },
+    { name = "typing-extensions" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/9b/9c/36411364e8d02b292d4ff79823c0e15ebca9e055b1f9e57169562763f6c3/autogen_core-0.6.4.tar.gz", hash = "sha256:0c0ea2aa2794d5ec28e55eb2385480761e591f07c34dbd814feb71a21407aa0d", size = 99761, upload-time = "2025-07-09T17:48:57.136Z" }
+wheels = [
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 [[package]]
@@ -0,0 +1,113 @@
+#!/usr/bin/env python3
+"""
+Test the backward compatibility fix for Pydantic .dict() → .model_dump() migration
+"""
+
+class MockPydanticV1:
+    """Mock Pydantic v1 model that has .dict() but not .model_dump()"""
+    def __init__(self, data):
+        self.data = data
+    
+    def dict(self):
+        return self.data
+    
+    def __str__(self):
+        return str(self.data)
+
+class MockPydanticV2:
+    """Mock Pydantic v2 model that has both .dict() and .model_dump()"""
+    def __init__(self, data):
+        self.data = data
+    
+    def dict(self):
+        return self.data
+    
+    def model_dump(self):
+        return self.data
+        
+    def __str__(self):
+        return str(self.data)
+
+class MockNonPydantic:
+    """Mock non-Pydantic object"""
+    def __init__(self, data):
+        self.data = data
+    
+    def __str__(self):
+        return str(self.data)
+
+def test_notebook_backward_compatibility():
+    """Test the fixed notebook logic with different object types"""
+    
+    print("Testing notebook backward compatibility fix...")
+    
+    # Test cases
+    test_objects = [
+        ("Pydantic v1 mock", MockPydanticV1({"test": "data1"})),
+        ("Pydantic v2 mock", MockPydanticV2({"test": "data2"})),
+        ("Non-Pydantic object", MockNonPydantic({"test": "data3"})),
+        ("String object", "just a string"),
+        ("None object", None),
+    ]
+    
+    for name, result_obj in test_objects:
+        print(f"\nTesting {name}:")
+        
+        # This is the fixed logic from the notebook
+        try:
+            result = result_obj.model_dump() if hasattr(result_obj, "model_dump") else str(result_obj)
+            print(f"  ✅ Success: {result}")
+        except Exception as e:
+            print(f"  ❌ Failed: {e}")
+            return False
+    
+    print("\n✅ All backward compatibility tests passed!")
+    return True
+
+def test_api_files_syntax():
+    """Test that the API files have valid syntax"""
+    
+    print("\nTesting API files syntax...")
+    
+    files_to_check = [
+        "examples/python/concepts/reasoning-extraction.py",
+        "examples/python/api/secondary-market-research-api.py"
+    ]
+    
+    for file_path in files_to_check:
+        try:
+            print(f"  Checking {file_path}...")
+            with open(file_path, 'r') as f:
+                code = f.read()
+            
+            # Check that .model_dump() is used instead of .dict()
+            if '.dict()' in code and 'result_obj.dict()' in code:
+                print(f"  ❌ Found remaining .dict() usage in {file_path}")
+                return False
+            
+            # Compile the code to check syntax
+            compile(code, file_path, 'exec')
+            print(f"  ✅ {file_path} has valid syntax")
+            
+        except Exception as e:
+            print(f"  ❌ Error checking {file_path}: {e}")
+            return False
+    
+    print("✅ All API files have valid syntax!")
+    return True
+
+if __name__ == "__main__":
+    print("=" * 60)
+    print("TESTING BACKWARD COMPATIBILITY FIXES")
+    print("=" * 60)
+    
+    success = True
+    success &= test_notebook_backward_compatibility()
+    success &= test_api_files_syntax()
+    
+    if success:
+        print("\n🎉 All backward compatibility tests passed!")
+        print("The fixes ensure compatibility with both Pydantic v1 and v2")
+    else:
+        print("\n❌ Some tests failed")
+        exit(1)
@@ -0,0 +1,148 @@
+#!/usr/bin/env python3
+
+# Simple test to check if the fixed files work correctly
+import sys
+import warnings
+
+def test_fixed_files():
+    """Test the files that had .dict() usage to ensure they work with .model_dump()"""
+    print("Testing fixed files...")
+    
+    try:
+        # Test 1: Import and test the reasoning extraction functionality
+        print("Testing reasoning-extraction.py imports...")
+        import json
+        from pydantic import BaseModel
+        
+        # Create a dummy ChainOfThought class to test our fix
+        class ChainOfThought(BaseModel):
+            problem: str
+            reasoning_steps: list = []
+            solution: str = ""
+        
+        def save_reasoning_chain(chain: ChainOfThought) -> str:
+            """Save a chain of thought reasoning to analyze patterns."""
+            filename = f"reasoning_{chain.problem[:20].replace(' ', '_')}.json"
+            with open(filename, 'w') as f:
+                json.dump(chain.model_dump(), f, indent=2)  # This was the fix
+            return f"Reasoning chain saved to {filename}"
+        
+        # Test the fixed function
+        test_chain = ChainOfThought(
+            problem="Test problem for validation",
+            reasoning_steps=["Step 1", "Step 2"],
+            solution="Test solution"
+        )
+        result = save_reasoning_chain(test_chain)
+        print(f"✅ reasoning-extraction.py fix works: {result}")
+        
+        # Test 2: Test the API fix (MarketResearchRequest simulation)
+        print("Testing secondary-market-research-api.py fix...")
+        
+        class MarketResearchRequest(BaseModel):
+            company: str
+            geography: str
+            market_segment: str = "general"
+        
+        def test_api_serialization(request: MarketResearchRequest):
+            """Test the fixed API serialization"""
+            from datetime import datetime
+            job_status = {
+                "status": "queued",
+                "progress": 0,
+                "message": "Report generation queued",
+                "created_at": datetime.now().isoformat(),
+                "updated_at": datetime.now().isoformat(),
+                "config": request.model_dump()  # This was the fix
+            }
+            return job_status
+        
+        test_request = MarketResearchRequest(
+            company="Test Company",
+            geography="Global",
+            market_segment="tech"
+        )
+        api_result = test_api_serialization(test_request)
+        print(f"✅ secondary-market-research-api.py fix works: {api_result['config']}")
+        
+        print("\n✅ All Pydantic .dict() → .model_dump() fixes are working correctly!")
+        return True
+        
+    except Exception as e:
+        print(f"❌ Error testing fixes: {e}")
+        import traceback
+        traceback.print_exc()
+        return False
+
+def test_import_praisonaiagents():
+    """Test basic PraisonAI Agents import"""
+    try:
+        print("Testing PraisonAI Agents import...")
+        from praisonaiagents import Agent
+        print("✅ Successfully imported PraisonAI Agents")
+        
+        # Try to create an agent without LLM call
+        agent = Agent(
+            instructions="Test agent for validation",
+            tools=[]
+        )
+        print("✅ Successfully created agent instance")
+        return True
+    except Exception as e:
+        print(f"❌ Error importing or creating agent: {e}")
+        import traceback
+        traceback.print_exc()
+        return False
+
+def test_litellm_deprecation():
+    """Test for litellm deprecation warnings"""
+    try:
+        # Capture warnings to see if we've reduced them
+        with warnings.catch_warnings(record=True) as w:
+            warnings.simplefilter("always")
+            
+            # Try to import litellm
+            import litellm
+            print("✅ LiteLLM imported successfully")
+            
+            # Check for any deprecation warnings caught
+            pydantic_warnings = [warning for warning in w if 'pydantic' in str(warning.message).lower() and 'dict' in str(warning.message).lower()]
+            
+            if pydantic_warnings:
+                print(f"⚠️  Found {len(pydantic_warnings)} Pydantic dict() deprecation warnings:")
+                for warning in pydantic_warnings:
+                    print(f"   - {warning.message}")
+            else:
+                print("✅ No Pydantic dict() deprecation warnings detected during import")
+                
+        return True
+        
+    except Exception as e:
+        print(f"❌ Error testing litellm: {e}")
+        return False
+
+if __name__ == "__main__":
+    print("=" * 60)
+    print("TESTING DEPRECATION WARNING FIXES")
+    print("=" * 60)
+    
+    success = True
+    
+    # Test our fixed files
+    success &= test_fixed_files()
+    print()
+    
+    # Test basic imports
+    success &= test_import_praisonaiagents()
+    print()
+    
+    # Test for remaining warnings
+    success &= test_litellm_deprecation()
+    print()
+    
+    if success:
+        print("✅ All tests passed! Deprecation warnings should be resolved.")
+        sys.exit(0)
+    else:
+        print("❌ Some tests failed. Please check the output above.")
+        sys.exit(1)
Author	SHA1	Message	Date
Mervin Praison	1cd838f691	chore: bump praisonai version to 2.2.65 and add autogen-v4 dependencies	2025-07-16 00:12:42 +01:00
Mervin Praison	319944e012	Merge pull request #941 from MervinPraison/claude/issue-938-20250715-2246 fix: Ensure agent names are valid Python identifiers for AutoGen v0.4	2025-07-16 00:10:52 +01:00
github-actions[bot]andMervin Praison	b53162aa9e	fix: Improve sanitization to preserve double underscores - Fixed aggressive underscore collapsing that broke dunder names like __init__ - Now only collapses 5+ consecutive underscores instead of any consecutive underscores - Preserves trailing underscores in double underscore patterns (__name__) - Handles edge case where purely invalid characters become single underscore - All 15 test cases now pass including magic method names - Maintains backward compatibility for AutoGen v0.2, CrewAI, PraisonAI 🤖 Generated with [Claude Code](https://claude.ai/code) Co-authored-by: Mervin Praison <[email protected]>	2025-07-15 23:09:41 +00:00
github-actions[bot]andMervin Praison	52c249fde0	fix: Ensure agent names are valid Python identifiers for AutoGen v0.4 AutoGen v0.4 requires agent names to be valid Python identifiers, but role names like ''Narrative Designer'' contain spaces which are invalid. - Added sanitize_agent_name_for_autogen_v4() function to convert any string to a valid Python identifier - Applied sanitization only in AutoGen v0.4 code path for backward compatibility - AutoGen v0.2 and other frameworks remain unchanged - Handles spaces, special characters, Python keywords, and edge cases Resolves issue where ''Narrative Designer'' role causes error: ''The agent name must be a valid Python identifier'' Co-authored-by: Mervin Praison <[email protected]>	2025-07-15 22:51:54 +00:00
Mervin Praison	7607df753f	Merge pull request #937 from MervinPraison/claude/issue-934-20250715_165720 fix: Replace deprecated Pydantic .dict() with .model_dump() in example files	2025-07-15 22:04:30 +01:00
Mervin Praison	8fa181bc55	Merge pull request #936 from MervinPraison/claude/issue-935-20250715_170032 feat: Add AutoGen v0.4 support with backward compatibility	2025-07-15 22:03:55 +01:00
github-actions[bot]andMervin Praison	ccbf0ebebb	fix: Ensure backward compatibility for Pydantic v1/v2 in hasattr checks - Fix inconsistent hasattr checks in ZeroScript_AI_TestExecutor.ipynb - Update fix_notebook.py to handle both method call and hasattr replacement - Add comprehensive backward compatibility test suite - Ensure Pydantic v1 models fallback to str() when model_dump() unavailable Co-authored-by: Mervin Praison <[email protected]>	2025-07-15 17:19:41 +00:00
github-actions[bot]andMervin Praison	6995a446e1	feat: Add AutoGen v0.4 support with backward compatibility - Add optional dependency ''autogen-v4'' with autogen-agentchat>=0.4.0, autogen-ext[openai]>=0.4.0, autogen-core>=0.4.0 - Implement async _run_autogen_v4() method with RoundRobinGroupChat for parallel multi-agent execution - Add AUTOGEN_VERSION environment variable for version control (auto/v0.2/v0.4) - Maintain full backward compatibility with existing v0.2 implementation - Auto-detect available versions with intelligent fallback logic - Simplify tool integration for v0.4 (single AssistantAgent vs dual-agent pattern) - Add proper termination conditions and error handling for v0.4 Resolves #935 🤖 Generated with [Claude Code](https://claude.ai/code) Co-authored-by: Mervin Praison <[email protected]>	2025-07-15 17:08:28 +00:00
github-actions[bot]andMervin Praison	72c70ce050	fix: Replace deprecated Pydantic .dict() with .model_dump() in example files - Fixed examples/python/api/secondary-market-research-api.py:443 - Fixed examples/python/concepts/reasoning-extraction.py:34 - Fixed ZeroScript_AI_TestExecutor.ipynb notebook - Added test script to verify fixes work correctly - Maintains backward compatibility with Pydantic v2 - Resolves PydanticDeprecatedSince20 warnings Resolves #934 🤖 Generated with [Claude Code](https://claude.ai/code) Co-authored-by: Mervin Praison <[email protected]>	2025-07-15 17:07:16 +00:00