nbqa adedd to pre-commit, added black and ruff for notebooks (microso…

…ft#1171) * nbqa adedd to pre-commit, added black and ruff for notebooks * polishing * polishing * polishing
johnwayne087 · Jan 8, 2024 · 1c4ae3d · 1c4ae3d
1 parent 643a031
commit 1c4ae3d
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Showing 47 changed files with 2,235 additions and 2,265 deletions.
diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
@@ -43,3 +43,9 @@ repos:
               website/yarn.lock |
               notebook/.*
             )$
+  - repo: https://github.com/nbQA-dev/nbQA
+    rev: 1.7.1
+    hooks:
+      - id: nbqa-ruff
+        args: ["--fix"]
+      - id: nbqa-black
diff --git a/notebook/Async_human_input.ipynb b/notebook/Async_human_input.ipynb
diff --git a/notebook/agentchat_MathChat.ipynb b/notebook/agentchat_MathChat.ipynb
@@ -52,7 +52,10 @@
    "metadata": {},
    "outputs": [],
    "source": [
+    "import os\n",
+    "\n",
     "import autogen\n",
+    "from autogen.agentchat.contrib.math_user_proxy_agent import MathUserProxyAgent\n",
     "\n",
     "config_list = autogen.config_list_from_json(\n",
     "    \"OAI_CONFIG_LIST\",\n",
@@ -70,7 +73,7 @@
     "            \"gpt-35-turbo-v0301\",\n",
     "            \"gpt\",\n",
     "        }\n",
-    "    }\n",
+    "    },\n",
     ")"
    ]
   },
@@ -126,23 +129,21 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from autogen.agentchat.contrib.math_user_proxy_agent import MathUserProxyAgent\n",
-    "\n",
     "# 1. create an AssistantAgent instance named \"assistant\"\n",
     "assistant = autogen.AssistantAgent(\n",
-    "    name=\"assistant\", \n",
+    "    name=\"assistant\",\n",
     "    system_message=\"You are a helpful assistant.\",\n",
     "    llm_config={\n",
     "        \"timeout\": 600,\n",
     "        \"seed\": 42,\n",
     "        \"config_list\": config_list,\n",
-    "    }\n",
+    "    },\n",
     ")\n",
     "\n",
     "# 2. create the MathUserProxyAgent instance named \"mathproxyagent\"\n",
     "# By default, the human_input_mode is \"NEVER\", which means the agent will not ask for human input.\n",
     "mathproxyagent = MathUserProxyAgent(\n",
-    "    name=\"mathproxyagent\", \n",
+    "    name=\"mathproxyagent\",\n",
     "    human_input_mode=\"NEVER\",\n",
     "    code_execution_config={\"use_docker\": False},\n",
     ")"
@@ -176,7 +177,9 @@
     "# given a math problem, we use the mathproxyagent to generate a prompt to be sent to the assistant as the initial message.\n",
     "# the assistant receives the message and generates a response. The response will be sent back to the mathproxyagent for processing.\n",
     "# The conversation continues until the termination condition is met, in MathChat, the termination condition is the detect of \"\\boxed{}\" in the response.\n",
-    "math_problem = \"Find all $x$ that satisfy the inequality $(2x+10)(x+3)<(3x+9)(x+8)$. Express your answer in interval notation.\"\n",
+    "math_problem = (\n",
+    "    \"Find all $x$ that satisfy the inequality $(2x+10)(x+3)<(3x+9)(x+8)$. Express your answer in interval notation.\"\n",
+    ")\n",
     "mathproxyagent.initiate_chat(assistant, problem=math_problem)"
    ]
   },
@@ -291,7 +294,6 @@
    "outputs": [],
    "source": [
     "# The wolfram alpha app id is required for this example (the assistant may choose to query Wolfram Alpha).\n",
-    "import os\n",
     "if \"WOLFRAM_ALPHA_APPID\" not in os.environ:\n",
     "    os.environ[\"WOLFRAM_ALPHA_APPID\"] = open(\"wolfram.txt\").read().strip()\n",
     "\n",

diff --git a/notebook/agentchat_RetrieveChat.ipynb b/notebook/agentchat_RetrieveChat.ipynb
@@ -79,7 +79,18 @@
     }
    ],
    "source": [
+    "import json\n",
+    "import os\n",
+    "\n",
+    "import chromadb\n",
+    "\n",
     "import autogen\n",
+    "from autogen.agentchat.contrib.retrieve_assistant_agent import RetrieveAssistantAgent\n",
+    "from autogen.agentchat.contrib.retrieve_user_proxy_agent import RetrieveUserProxyAgent\n",
+    "\n",
+    "# Accepted file formats for that can be stored in\n",
+    "# a vector database instance\n",
+    "from autogen.retrieve_utils import TEXT_FORMATS\n",
     "\n",
     "config_list = autogen.config_list_from_json(\n",
     "    env_or_file=\"OAI_CONFIG_LIST\",\n",
@@ -161,10 +172,6 @@
     }
    ],
    "source": [
-    "# Accepted file formats for that can be stored in \n",
-    "# a vector database instance\n",
-    "from autogen.retrieve_utils import TEXT_FORMATS\n",
-    "\n",
     "print(\"Accepted file formats for `docs_path`:\")\n",
     "print(TEXT_FORMATS)"
    ]
@@ -175,11 +182,6 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from autogen.agentchat.contrib.retrieve_assistant_agent import RetrieveAssistantAgent\n",
-    "from autogen.agentchat.contrib.retrieve_user_proxy_agent import RetrieveUserProxyAgent\n",
-    "import chromadb\n",
-    "import os\n",
-    "\n",
     "# 1. create an RetrieveAssistantAgent instance named \"assistant\"\n",
     "assistant = RetrieveAssistantAgent(\n",
     "    name=\"assistant\",\n",
@@ -210,7 +212,7 @@
     "        \"docs_path\": [\n",
     "            \"https://raw.githubusercontent.com/microsoft/FLAML/main/website/docs/Examples/Integrate%20-%20Spark.md\",\n",
     "            \"https://raw.githubusercontent.com/microsoft/FLAML/main/website/docs/Research.md\",\n",
-    "            os.path.join(os.path.abspath(''), \"..\", \"website\", \"docs\"),\n",
+    "            os.path.join(os.path.abspath(\"\"), \"..\", \"website\", \"docs\"),\n",
     "        ],\n",
     "        \"custom_text_types\": [\"mdx\"],\n",
     "        \"chunk_token_size\": 2000,\n",
@@ -219,7 +221,7 @@
     "        \"embedding_model\": \"all-mpnet-base-v2\",\n",
     "        \"get_or_create\": True,  # set to False if you don't want to reuse an existing collection, but you'll need to remove the collection manually\n",
     "    },\n",
-    "    code_execution_config=False, # set to False if you don't want to execute the code\n",
+    "    code_execution_config=False,  # set to False if you don't want to execute the code\n",
     ")"
    ]
   },
@@ -525,7 +527,9 @@
     "# The conversation continues until the termination condition is met, in RetrieveChat, the termination condition when no human-in-loop is no code block detected.\n",
     "# With human-in-loop, the conversation will continue until the user says \"exit\".\n",
     "code_problem = \"How can I use FLAML to perform a classification task and use spark to do parallel training. Train 30 seconds and force cancel jobs if time limit is reached.\"\n",
-    "ragproxyagent.initiate_chat(assistant, problem=code_problem, search_string=\"spark\")  # search_string is used as an extra filter for the embeddings search, in this case, we only want to search documents that contain \"spark\"."
+    "ragproxyagent.initiate_chat(\n",
+    "    assistant, problem=code_problem, search_string=\"spark\"\n",
+    ")  # search_string is used as an extra filter for the embeddings search, in this case, we only want to search documents that contain \"spark\"."
    ]
   },
   {
@@ -2122,8 +2126,6 @@
     }
    ],
    "source": [
-    "import json\n",
-    "\n",
     "# queries_file = \"https://huggingface.co/datasets/thinkall/NaturalQuestionsQA/resolve/main/queries.jsonl\"\n",
     "queries = \"\"\"{\"_id\": \"ce2342e1feb4e119cb273c05356b33309d38fa132a1cbeac2368a337e38419b8\", \"text\": \"what is non controlling interest on balance sheet\", \"metadata\": {\"answer\": [\"the portion of a subsidiary corporation 's stock that is not owned by the parent corporation\"]}}\n",
     "{\"_id\": \"3a10ff0e520530c0aa33b2c7e8d989d78a8cd5d699201fc4b13d3845010994ee\", \"text\": \"how many episodes are in chicago fire season 4\", \"metadata\": {\"answer\": [\"23\"]}}\n",
@@ -2645,7 +2647,7 @@
     "\n",
     "    # reset the assistant. Always reset the assistant before starting a new conversation.\n",
     "    assistant.reset()\n",
-    "    \n",
+    "\n",
     "    qa_problem = questions[i]\n",
     "    ragproxyagent.initiate_chat(assistant, problem=qa_problem, n_results=30)"
    ]
@@ -2724,7 +2726,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "#create the RetrieveUserProxyAgent instance named \"ragproxyagent\"\n",
+    "# create the RetrieveUserProxyAgent instance named \"ragproxyagent\"\n",
     "corpus_file = \"https://huggingface.co/datasets/thinkall/2WikiMultihopQA/resolve/main/corpus.txt\"\n",
     "\n",
     "# Create a new collection for NaturalQuestions dataset\n",
@@ -2762,8 +2764,6 @@
     }
    ],
    "source": [
-    "import json\n",
-    "\n",
     "# queries_file = \"https://huggingface.co/datasets/thinkall/2WikiMultihopQA/resolve/main/queries.jsonl\"\n",
     "queries = \"\"\"{\"_id\": \"61a46987092f11ebbdaeac1f6bf848b6\", \"text\": \"Which film came out first, Blind Shaft or The Mask Of Fu Manchu?\", \"metadata\": {\"answer\": [\"The Mask Of Fu Manchu\"]}}\n",
     "{\"_id\": \"a7b9672009c311ebbdb0ac1f6bf848b6\", \"text\": \"Are North Marion High School (Oregon) and Seoul High School both located in the same country?\", \"metadata\": {\"answer\": [\"no\"]}}\n",
@@ -3075,7 +3075,7 @@
     "\n",
     "    # reset the assistant. Always reset the assistant before starting a new conversation.\n",
     "    assistant.reset()\n",
-    "    \n",
+    "\n",
     "    qa_problem = questions[i]\n",
     "    ragproxyagent.initiate_chat(assistant, problem=qa_problem, n_results=10)"
    ]