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DONG, JERRY
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added changes per github comments and run precommit
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‎notebook/agentchat_postresponse_secret_redaction.ipynb

+50-51
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@@ -29,13 +29,13 @@
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"source": [
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"## Requirements\n",
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"\n",
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"AutoGen requires `Python>=3.8`. To run this notebook example, please install pyautogen:\n",
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"AutoGen requires `Python>=3.8`. To run this notebook example, please install autogen-agentchat:\n",
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"\n",
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"````{=mdx}\n",
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":::info Requirements\n",
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"Install `pyautogen`:\n",
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"```bash\n",
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"pip install pyautogen\n",
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"pip install autogen-agentchat~=0.2\n",
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"```\n",
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"\n",
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"For more information, please refer to the [installation guide](/docs/installation/).\n",
@@ -49,14 +49,14 @@
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"metadata": {},
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"outputs": [],
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"source": [
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"from typing import Dict, Union, Optional\n",
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"import os\n",
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"import copy\n",
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"import os\n",
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"from typing import Dict, Optional, Union\n",
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"\n",
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"import autogen\n",
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"from autogen import ConversableAgent, Agent\n",
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"from autogen.coding import LocalCommandLineCodeExecutor\n",
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"from autogen.code_utils import create_virtual_env"
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"from autogen import Agent, ConversableAgent\n",
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"from autogen.code_utils import create_virtual_env\n",
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"from autogen.coding import LocalCommandLineCodeExecutor"
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]
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},
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{
@@ -72,24 +72,27 @@
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"metadata": {},
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"outputs": [],
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"source": [
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"os.environ['VENV_DIR'] = \"<Your venv directory that is used for code executor agent>\"\n",
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"os.environ['TEMP_FILE_DIR'] = \"<Your directory for temporary code files>\"\n",
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"os.environ['LLM_API_KEY'] = \"<Your API key for llm config>\"\n",
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"os.environ['LLM_API_TYPE'] = \"<Your API type for llm config>\"\n",
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"os.environ['LLM_API_VERSION'] = \"<Your API version for llm config>\"\n",
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"os.environ['LLM_API_URL'] = \"<Your API Url for llm config>\"\n",
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"os.environ[\"VENV_DIR\"] = \"<Your venv directory that is used for code executor agent>\"\n",
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"os.environ[\"TEMP_FILE_DIR\"] = \"<Your directory for temporary code files>\"\n",
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"os.environ[\"LLM_API_KEY\"] = \"<Your API key for llm config>\"\n",
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"os.environ[\"LLM_API_TYPE\"] = \"<Your API type for llm config>\"\n",
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"os.environ[\"LLM_API_VERSION\"] = \"<Your API version for llm config>\"\n",
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"os.environ[\"LLM_API_URL\"] = \"<Your API Url for llm config>\"\n",
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"\n",
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"# Get the env variables\n",
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"venv_dir = os.environ['VENV_DIR']\n",
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"temp_file_fir = os.environ['TEMP_FILE_DIR'] \n",
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"venv_dir = os.environ[\"VENV_DIR\"]\n",
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"temp_file_fir = os.environ[\"TEMP_FILE_DIR\"]\n",
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"\n",
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"llm_config = {\n",
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" \"config_list\": [{\n",
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" \"model\": \"gpt-4\", \n",
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" \"api_key\": os.environ[\"LLM_API_KEY\"], \n",
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" \"api_type\": os.environ[\"LLM_API_TYPE\"], \n",
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" \"api_version\": os.environ[\"LLM_API_VERSION\"], \n",
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" \"base_url\": os.environ[\"LLM_API_URL\"]}],\n",
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" \"config_list\": [\n",
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" {\n",
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" \"model\": \"gpt-4\",\n",
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" \"api_key\": os.environ[\"LLM_API_KEY\"],\n",
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" \"api_type\": os.environ[\"LLM_API_TYPE\"],\n",
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" \"api_version\": os.environ[\"LLM_API_VERSION\"],\n",
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" \"base_url\": os.environ[\"LLM_API_URL\"],\n",
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" }\n",
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" ],\n",
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"}\n",
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"\n",
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"# The string that sensitive data will be redated to\n",
@@ -116,17 +119,13 @@
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"metadata": {},
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"outputs": [],
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"source": [
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"executor = LocalCommandLineCodeExecutor(\n",
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" timeout=10, \n",
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" work_dir=temp_file_fir, \n",
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" virtual_env_context=venv_context\n",
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")\n",
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"executor = LocalCommandLineCodeExecutor(timeout=10, work_dir=temp_file_fir, virtual_env_context=venv_context)\n",
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"\n",
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"code_executor_agent = ConversableAgent(\n",
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" \"code_executor_agent\",\n",
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" llm_config=False,\n",
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" code_execution_config={\"executor\": executor}, \n",
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" human_input_mode=\"NEVER\", \n",
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" code_execution_config={\"executor\": executor},\n",
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" human_input_mode=\"NEVER\",\n",
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" max_consecutive_auto_reply=1,\n",
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")\n",
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"\n",
@@ -136,7 +135,7 @@
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" llm_config=llm_config,\n",
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" system_message=\"DO NOT display any thing that is sensitive\",\n",
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" max_consecutive_auto_reply=1,\n",
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" code_execution_config={\"use_docker\": False}\n",
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" code_execution_config={\"use_docker\": False},\n",
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")"
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]
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},
@@ -155,25 +154,27 @@
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"metadata": {},
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"outputs": [],
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"source": [
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"def transform_generated_response(message: Union[Dict, str], sender: Optional[Agent] = None, recipient: Agent = None, silent: bool = None ) -> Union[Dict, str]:\n",
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" temp_message = copy.deepcopy(message)\n",
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" all_secrets = sorted(env_secrets.values(), key=len, reverse=True)\n",
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" if isinstance(temp_message, Dict):\n",
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" for secret in all_secrets:\n",
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" if isinstance(temp_message[\"content\"], str):\n",
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" if secret != '' and secret in temp_message[\"content\"]:\n",
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" temp_message[\"content\"] = temp_message[\"content\"].replace(secret, replacementString)\n",
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" elif isinstance(temp_message[\"content\"], list):\n",
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" for item in temp_message[\"content\"]:\n",
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" if item[\"type\"] == \"text\":\n",
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" if secret != '' and secret in item[\"text\"]:\n",
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" item[\"text\"] = item[\"text\"].replace(secret, replacementString)\n",
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" if isinstance(temp_message, str):\n",
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" for secret in all_secrets:\n",
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" if secret != '' and secret in temp_message:\n",
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" temp_message = temp_message.replace(secret, replacementString)\n",
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"def transform_generated_response(\n",
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" message: Union[Dict, str], sender: Optional[Agent] = None, recipient: Agent = None, silent: bool = None\n",
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") -> Union[Dict, str]:\n",
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" temp_message = copy.deepcopy(message)\n",
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" all_secrets = sorted(env_secrets.values(), key=len, reverse=True)\n",
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" if isinstance(temp_message, Dict):\n",
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" for secret in all_secrets:\n",
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" if isinstance(temp_message[\"content\"], str):\n",
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" if secret != \"\" and secret in temp_message[\"content\"]:\n",
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" temp_message[\"content\"] = temp_message[\"content\"].replace(secret, replacementString)\n",
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" elif isinstance(temp_message[\"content\"], list):\n",
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" for item in temp_message[\"content\"]:\n",
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" if item[\"type\"] == \"text\":\n",
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" if secret != \"\" and secret in item[\"text\"]:\n",
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" item[\"text\"] = item[\"text\"].replace(secret, replacementString)\n",
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" if isinstance(temp_message, str):\n",
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" for secret in all_secrets:\n",
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" if secret != \"\" and secret in temp_message:\n",
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" temp_message = temp_message.replace(secret, replacementString)\n",
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"\n",
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" return temp_message"
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" return temp_message"
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]
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},
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{
@@ -209,7 +210,7 @@
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"metadata": {},
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"outputs": [],
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"source": [
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"agent_message =\"\"\"Run the code and show me the printed variable.\n",
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"agent_message = \"\"\"Run the code and show me the printed variable.\n",
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"The code block is below:\n",
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"```python\n",
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"import os\n",
@@ -258,9 +259,7 @@
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}
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],
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"source": [
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"result = proxy_agent.initiate_chat(\n",
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" code_executor_agent, message=agent_message, clear_history=False\n",
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")"
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"result = proxy_agent.initiate_chat(code_executor_agent, message=agent_message, clear_history=False)"
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]
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},
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{

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