{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# ClearML\n",
    "\n",
    "> [ClearML](https://github.com/allegroai/clearml) is a ML/DL development and production suite, it contains 5 main modules:\n",
    "> - `Experiment Manager` - Automagical experiment tracking, environments and results\n",
    "> - `MLOps` - Orchestration, Automation & Pipelines solution for ML/DL jobs (K8s / Cloud / bare-metal)\n",
    "> - `Data-Management` - Fully differentiable data management & version control solution on top of object-storage (S3 / GS / Azure / NAS)\n",
    "> - `Model-Serving` - cloud-ready Scalable model serving solution!\n",
    "    Deploy new model endpoints in under 5 minutes\n",
    "    Includes optimized GPU serving support backed by Nvidia-Triton\n",
    "    with out-of-the-box Model Monitoring\n",
    "> - `Fire Reports` - Create and share rich MarkDown documents supporting embeddable online content\n",
    "\n",
    "In order to properly keep track of your langchain experiments and their results, you can enable the `ClearML` integration. We use the `ClearML Experiment Manager` that neatly tracks and organizes all your experiment runs.\n",
    "\n",
    "<a target=\"_blank\" href=\"https://colab.research.google.com/github/hwchase17/langchain/blob/master/docs/ecosystem/clearml_tracking.html\">\n",
    "  <img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/>\n",
    "</a>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "## Installation and Setup"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "!pip install clearml\n",
    "!pip install pandas\n",
    "!pip install textstat\n",
    "!pip install spacy\n",
    "!python -m spacy download en_core_web_sm"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Getting API Credentials\n",
    "\n",
    "We'll be using quite some APIs in this notebook, here is a list and where to get them:\n",
    "\n",
    "- ClearML: https://app.clear.ml/settings/workspace-configuration\n",
    "- OpenAI: https://platform.openai.com/account/api-keys\n",
    "- SerpAPI (google search): https://serpapi.com/dashboard"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "\n",
    "os.environ[\"CLEARML_API_ACCESS_KEY\"] = \"\"\n",
    "os.environ[\"CLEARML_API_SECRET_KEY\"] = \"\"\n",
    "\n",
    "os.environ[\"OPENAI_API_KEY\"] = \"\"\n",
    "os.environ[\"SERPAPI_API_KEY\"] = \"\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Callbacks"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "from langchain.callbacks import ClearMLCallbackHandler"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The clearml callback is currently in beta and is subject to change based on updates to `langchain`. Please report any issues to https://github.com/allegroai/clearml/issues with the tag `langchain`.\n"
     ]
    }
   ],
   "source": [
    "from datetime import datetime\n",
    "from langchain.callbacks import StdOutCallbackHandler\n",
    "from langchain.llms import OpenAI\n",
    "\n",
    "# Setup and use the ClearML Callback\n",
    "clearml_callback = ClearMLCallbackHandler(\n",
    "    task_type=\"inference\",\n",
    "    project_name=\"langchain_callback_demo\",\n",
    "    task_name=\"llm\",\n",
    "    tags=[\"test\"],\n",
    "    # Change the following parameters based on the amount of detail you want tracked\n",
    "    visualize=True,\n",
    "    complexity_metrics=True,\n",
    "    stream_logs=True,\n",
    ")\n",
    "callbacks = [StdOutCallbackHandler(), clearml_callback]\n",
    "# Get the OpenAI model ready to go\n",
    "llm = OpenAI(temperature=0, callbacks=callbacks)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Scenario 1: Just an LLM\n",
    "\n",
    "First, let's just run a single LLM a few times and capture the resulting prompt-answer conversation in ClearML"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'action': 'on_llm_start', 'name': 'OpenAI', 'step': 3, 'starts': 2, 'ends': 1, 'errors': 0, 'text_ctr': 0, 'chain_starts': 0, 'chain_ends': 0, 'llm_starts': 2, 'llm_ends': 1, 'llm_streams': 0, 'tool_starts': 0, 'tool_ends': 0, 'agent_ends': 0, 'prompts': 'Tell me a joke'}\n",
      "{'action': 'on_llm_start', 'name': 'OpenAI', 'step': 3, 'starts': 2, 'ends': 1, 'errors': 0, 'text_ctr': 0, 'chain_starts': 0, 'chain_ends': 0, 'llm_starts': 2, 'llm_ends': 1, 'llm_streams': 0, 'tool_starts': 0, 'tool_ends': 0, 'agent_ends': 0, 'prompts': 'Tell me a poem'}\n",
      "{'action': 'on_llm_start', 'name': 'OpenAI', 'step': 3, 'starts': 2, 'ends': 1, 'errors': 0, 'text_ctr': 0, 'chain_starts': 0, 'chain_ends': 0, 'llm_starts': 2, 'llm_ends': 1, 'llm_streams': 0, 'tool_starts': 0, 'tool_ends': 0, 'agent_ends': 0, 'prompts': 'Tell me a joke'}\n",
      "{'action': 'on_llm_start', 'name': 'OpenAI', 'step': 3, 'starts': 2, 'ends': 1, 'errors': 0, 'text_ctr': 0, 'chain_starts': 0, 'chain_ends': 0, 'llm_starts': 2, 'llm_ends': 1, 'llm_streams': 0, 'tool_starts': 0, 'tool_ends': 0, 'agent_ends': 0, 'prompts': 'Tell me a poem'}\n",
      "{'action': 'on_llm_start', 'name': 'OpenAI', 'step': 3, 'starts': 2, 'ends': 1, 'errors': 0, 'text_ctr': 0, 'chain_starts': 0, 'chain_ends': 0, 'llm_starts': 2, 'llm_ends': 1, 'llm_streams': 0, 'tool_starts': 0, 'tool_ends': 0, 'agent_ends': 0, 'prompts': 'Tell me a joke'}\n",
      "{'action': 'on_llm_start', 'name': 'OpenAI', 'step': 3, 'starts': 2, 'ends': 1, 'errors': 0, 'text_ctr': 0, 'chain_starts': 0, 'chain_ends': 0, 'llm_starts': 2, 'llm_ends': 1, 'llm_streams': 0, 'tool_starts': 0, 'tool_ends': 0, 'agent_ends': 0, 'prompts': 'Tell me a poem'}\n",
      "{'action': 'on_llm_end', 'token_usage_prompt_tokens': 24, 'token_usage_completion_tokens': 138, 'token_usage_total_tokens': 162, 'model_name': 'text-davinci-003', 'step': 4, 'starts': 2, 'ends': 2, 'errors': 0, 'text_ctr': 0, 'chain_starts': 0, 'chain_ends': 0, 'llm_starts': 2, 'llm_ends': 2, 'llm_streams': 0, 'tool_starts': 0, 'tool_ends': 0, 'agent_ends': 0, 'text': '\\n\\nQ: What did the fish say when it hit the wall?\\nA: Dam!', 'generation_info_finish_reason': 'stop', 'generation_info_logprobs': None, 'flesch_reading_ease': 109.04, 'flesch_kincaid_grade': 1.3, 'smog_index': 0.0, 'coleman_liau_index': -1.24, 'automated_readability_index': 0.3, 'dale_chall_readability_score': 5.5, 'difficult_words': 0, 'linsear_write_formula': 5.5, 'gunning_fog': 5.2, 'text_standard': '5th and 6th grade', 'fernandez_huerta': 133.58, 'szigriszt_pazos': 131.54, 'gutierrez_polini': 62.3, 'crawford': -0.2, 'gulpease_index': 79.8, 'osman': 116.91}\n",
      "{'action': 'on_llm_end', 'token_usage_prompt_tokens': 24, 'token_usage_completion_tokens': 138, 'token_usage_total_tokens': 162, 'model_name': 'text-davinci-003', 'step': 4, 'starts': 2, 'ends': 2, 'errors': 0, 'text_ctr': 0, 'chain_starts': 0, 'chain_ends': 0, 'llm_starts': 2, 'llm_ends': 2, 'llm_streams': 0, 'tool_starts': 0, 'tool_ends': 0, 'agent_ends': 0, 'text': '\\n\\nRoses are red,\\nViolets are blue,\\nSugar is sweet,\\nAnd so are you.', 'generation_info_finish_reason': 'stop', 'generation_info_logprobs': None, 'flesch_reading_ease': 83.66, 'flesch_kincaid_grade': 4.8, 'smog_index': 0.0, 'coleman_liau_index': 3.23, 'automated_readability_index': 3.9, 'dale_chall_readability_score': 6.71, 'difficult_words': 2, 'linsear_write_formula': 6.5, 'gunning_fog': 8.28, 'text_standard': '6th and 7th grade', 'fernandez_huerta': 115.58, 'szigriszt_pazos': 112.37, 'gutierrez_polini': 54.83, 'crawford': 1.4, 'gulpease_index': 72.1, 'osman': 100.17}\n",
      "{'action': 'on_llm_end', 'token_usage_prompt_tokens': 24, 'token_usage_completion_tokens': 138, 'token_usage_total_tokens': 162, 'model_name': 'text-davinci-003', 'step': 4, 'starts': 2, 'ends': 2, 'errors': 0, 'text_ctr': 0, 'chain_starts': 0, 'chain_ends': 0, 'llm_starts': 2, 'llm_ends': 2, 'llm_streams': 0, 'tool_starts': 0, 'tool_ends': 0, 'agent_ends': 0, 'text': '\\n\\nQ: What did the fish say when it hit the wall?\\nA: Dam!', 'generation_info_finish_reason': 'stop', 'generation_info_logprobs': None, 'flesch_reading_ease': 109.04, 'flesch_kincaid_grade': 1.3, 'smog_index': 0.0, 'coleman_liau_index': -1.24, 'automated_readability_index': 0.3, 'dale_chall_readability_score': 5.5, 'difficult_words': 0, 'linsear_write_formula': 5.5, 'gunning_fog': 5.2, 'text_standard': '5th and 6th grade', 'fernandez_huerta': 133.58, 'szigriszt_pazos': 131.54, 'gutierrez_polini': 62.3, 'crawford': -0.2, 'gulpease_index': 79.8, 'osman': 116.91}\n",
      "{'action': 'on_llm_end', 'token_usage_prompt_tokens': 24, 'token_usage_completion_tokens': 138, 'token_usage_total_tokens': 162, 'model_name': 'text-davinci-003', 'step': 4, 'starts': 2, 'ends': 2, 'errors': 0, 'text_ctr': 0, 'chain_starts': 0, 'chain_ends': 0, 'llm_starts': 2, 'llm_ends': 2, 'llm_streams': 0, 'tool_starts': 0, 'tool_ends': 0, 'agent_ends': 0, 'text': '\\n\\nRoses are red,\\nViolets are blue,\\nSugar is sweet,\\nAnd so are you.', 'generation_info_finish_reason': 'stop', 'generation_info_logprobs': None, 'flesch_reading_ease': 83.66, 'flesch_kincaid_grade': 4.8, 'smog_index': 0.0, 'coleman_liau_index': 3.23, 'automated_readability_index': 3.9, 'dale_chall_readability_score': 6.71, 'difficult_words': 2, 'linsear_write_formula': 6.5, 'gunning_fog': 8.28, 'text_standard': '6th and 7th grade', 'fernandez_huerta': 115.58, 'szigriszt_pazos': 112.37, 'gutierrez_polini': 54.83, 'crawford': 1.4, 'gulpease_index': 72.1, 'osman': 100.17}\n",
      "{'action': 'on_llm_end', 'token_usage_prompt_tokens': 24, 'token_usage_completion_tokens': 138, 'token_usage_total_tokens': 162, 'model_name': 'text-davinci-003', 'step': 4, 'starts': 2, 'ends': 2, 'errors': 0, 'text_ctr': 0, 'chain_starts': 0, 'chain_ends': 0, 'llm_starts': 2, 'llm_ends': 2, 'llm_streams': 0, 'tool_starts': 0, 'tool_ends': 0, 'agent_ends': 0, 'text': '\\n\\nQ: What did the fish say when it hit the wall?\\nA: Dam!', 'generation_info_finish_reason': 'stop', 'generation_info_logprobs': None, 'flesch_reading_ease': 109.04, 'flesch_kincaid_grade': 1.3, 'smog_index': 0.0, 'coleman_liau_index': -1.24, 'automated_readability_index': 0.3, 'dale_chall_readability_score': 5.5, 'difficult_words': 0, 'linsear_write_formula': 5.5, 'gunning_fog': 5.2, 'text_standard': '5th and 6th grade', 'fernandez_huerta': 133.58, 'szigriszt_pazos': 131.54, 'gutierrez_polini': 62.3, 'crawford': -0.2, 'gulpease_index': 79.8, 'osman': 116.91}\n",
      "{'action': 'on_llm_end', 'token_usage_prompt_tokens': 24, 'token_usage_completion_tokens': 138, 'token_usage_total_tokens': 162, 'model_name': 'text-davinci-003', 'step': 4, 'starts': 2, 'ends': 2, 'errors': 0, 'text_ctr': 0, 'chain_starts': 0, 'chain_ends': 0, 'llm_starts': 2, 'llm_ends': 2, 'llm_streams': 0, 'tool_starts': 0, 'tool_ends': 0, 'agent_ends': 0, 'text': '\\n\\nRoses are red,\\nViolets are blue,\\nSugar is sweet,\\nAnd so are you.', 'generation_info_finish_reason': 'stop', 'generation_info_logprobs': None, 'flesch_reading_ease': 83.66, 'flesch_kincaid_grade': 4.8, 'smog_index': 0.0, 'coleman_liau_index': 3.23, 'automated_readability_index': 3.9, 'dale_chall_readability_score': 6.71, 'difficult_words': 2, 'linsear_write_formula': 6.5, 'gunning_fog': 8.28, 'text_standard': '6th and 7th grade', 'fernandez_huerta': 115.58, 'szigriszt_pazos': 112.37, 'gutierrez_polini': 54.83, 'crawford': 1.4, 'gulpease_index': 72.1, 'osman': 100.17}\n",
      "{'action_records':           action    name  step  starts  ends  errors  text_ctr  chain_starts  \\\n",
      "0   on_llm_start  OpenAI     1       1     0       0         0             0   \n",
      "1   on_llm_start  OpenAI     1       1     0       0         0             0   \n",
      "2   on_llm_start  OpenAI     1       1     0       0         0             0   \n",
      "3   on_llm_start  OpenAI     1       1     0       0         0             0   \n",
      "4   on_llm_start  OpenAI     1       1     0       0         0             0   \n",
      "5   on_llm_start  OpenAI     1       1     0       0         0             0   \n",
      "6     on_llm_end     NaN     2       1     1       0         0             0   \n",
      "7     on_llm_end     NaN     2       1     1       0         0             0   \n",
      "8     on_llm_end     NaN     2       1     1       0         0             0   \n",
      "9     on_llm_end     NaN     2       1     1       0         0             0   \n",
      "10    on_llm_end     NaN     2       1     1       0         0             0   \n",
      "11    on_llm_end     NaN     2       1     1       0         0             0   \n",
      "12  on_llm_start  OpenAI     3       2     1       0         0             0   \n",
      "13  on_llm_start  OpenAI     3       2     1       0         0             0   \n",
      "14  on_llm_start  OpenAI     3       2     1       0         0             0   \n",
      "15  on_llm_start  OpenAI     3       2     1       0         0             0   \n",
      "16  on_llm_start  OpenAI     3       2     1       0         0             0   \n",
      "17  on_llm_start  OpenAI     3       2     1       0         0             0   \n",
      "18    on_llm_end     NaN     4       2     2       0         0             0   \n",
      "19    on_llm_end     NaN     4       2     2       0         0             0   \n",
      "20    on_llm_end     NaN     4       2     2       0         0             0   \n",
      "21    on_llm_end     NaN     4       2     2       0         0             0   \n",
      "22    on_llm_end     NaN     4       2     2       0         0             0   \n",
      "23    on_llm_end     NaN     4       2     2       0         0             0   \n",
      "\n",
      "    chain_ends  llm_starts  ...  difficult_words  linsear_write_formula  \\\n",
      "0            0           1  ...              NaN                    NaN   \n",
      "1            0           1  ...              NaN                    NaN   \n",
      "2            0           1  ...              NaN                    NaN   \n",
      "3            0           1  ...              NaN                    NaN   \n",
      "4            0           1  ...              NaN                    NaN   \n",
      "5            0           1  ...              NaN                    NaN   \n",
      "6            0           1  ...              0.0                    5.5   \n",
      "7            0           1  ...              2.0                    6.5   \n",
      "8            0           1  ...              0.0                    5.5   \n",
      "9            0           1  ...              2.0                    6.5   \n",
      "10           0           1  ...              0.0                    5.5   \n",
      "11           0           1  ...              2.0                    6.5   \n",
      "12           0           2  ...              NaN                    NaN   \n",
      "13           0           2  ...              NaN                    NaN   \n",
      "14           0           2  ...              NaN                    NaN   \n",
      "15           0           2  ...              NaN                    NaN   \n",
      "16           0           2  ...              NaN                    NaN   \n",
      "17           0           2  ...              NaN                    NaN   \n",
      "18           0           2  ...              0.0                    5.5   \n",
      "19           0           2  ...              2.0                    6.5   \n",
      "20           0           2  ...              0.0                    5.5   \n",
      "21           0           2  ...              2.0                    6.5   \n",
      "22           0           2  ...              0.0                    5.5   \n",
      "23           0           2  ...              2.0                    6.5   \n",
      "\n",
      "    gunning_fog      text_standard  fernandez_huerta szigriszt_pazos  \\\n",
      "0           NaN                NaN               NaN             NaN   \n",
      "1           NaN                NaN               NaN             NaN   \n",
      "2           NaN                NaN               NaN             NaN   \n",
      "3           NaN                NaN               NaN             NaN   \n",
      "4           NaN                NaN               NaN             NaN   \n",
      "5           NaN                NaN               NaN             NaN   \n",
      "6          5.20  5th and 6th grade            133.58          131.54   \n",
      "7          8.28  6th and 7th grade            115.58          112.37   \n",
      "8          5.20  5th and 6th grade            133.58          131.54   \n",
      "9          8.28  6th and 7th grade            115.58          112.37   \n",
      "10         5.20  5th and 6th grade            133.58          131.54   \n",
      "11         8.28  6th and 7th grade            115.58          112.37   \n",
      "12          NaN                NaN               NaN             NaN   \n",
      "13          NaN                NaN               NaN             NaN   \n",
      "14          NaN                NaN               NaN             NaN   \n",
      "15          NaN                NaN               NaN             NaN   \n",
      "16          NaN                NaN               NaN             NaN   \n",
      "17          NaN                NaN               NaN             NaN   \n",
      "18         5.20  5th and 6th grade            133.58          131.54   \n",
      "19         8.28  6th and 7th grade            115.58          112.37   \n",
      "20         5.20  5th and 6th grade            133.58          131.54   \n",
      "21         8.28  6th and 7th grade            115.58          112.37   \n",
      "22         5.20  5th and 6th grade            133.58          131.54   \n",
      "23         8.28  6th and 7th grade            115.58          112.37   \n",
      "\n",
      "    gutierrez_polini  crawford  gulpease_index   osman  \n",
      "0                NaN       NaN             NaN     NaN  \n",
      "1                NaN       NaN             NaN     NaN  \n",
      "2                NaN       NaN             NaN     NaN  \n",
      "3                NaN       NaN             NaN     NaN  \n",
      "4                NaN       NaN             NaN     NaN  \n",
      "5                NaN       NaN             NaN     NaN  \n",
      "6              62.30      -0.2            79.8  116.91  \n",
      "7              54.83       1.4            72.1  100.17  \n",
      "8              62.30      -0.2            79.8  116.91  \n",
      "9              54.83       1.4            72.1  100.17  \n",
      "10             62.30      -0.2            79.8  116.91  \n",
      "11             54.83       1.4            72.1  100.17  \n",
      "12               NaN       NaN             NaN     NaN  \n",
      "13               NaN       NaN             NaN     NaN  \n",
      "14               NaN       NaN             NaN     NaN  \n",
      "15               NaN       NaN             NaN     NaN  \n",
      "16               NaN       NaN             NaN     NaN  \n",
      "17               NaN       NaN             NaN     NaN  \n",
      "18             62.30      -0.2            79.8  116.91  \n",
      "19             54.83       1.4            72.1  100.17  \n",
      "20             62.30      -0.2            79.8  116.91  \n",
      "21             54.83       1.4            72.1  100.17  \n",
      "22             62.30      -0.2            79.8  116.91  \n",
      "23             54.83       1.4            72.1  100.17  \n",
      "\n",
      "[24 rows x 39 columns], 'session_analysis':     prompt_step         prompts    name  output_step  \\\n",
      "0             1  Tell me a joke  OpenAI            2   \n",
      "1             1  Tell me a poem  OpenAI            2   \n",
      "2             1  Tell me a joke  OpenAI            2   \n",
      "3             1  Tell me a poem  OpenAI            2   \n",
      "4             1  Tell me a joke  OpenAI            2   \n",
      "5             1  Tell me a poem  OpenAI            2   \n",
      "6             3  Tell me a joke  OpenAI            4   \n",
      "7             3  Tell me a poem  OpenAI            4   \n",
      "8             3  Tell me a joke  OpenAI            4   \n",
      "9             3  Tell me a poem  OpenAI            4   \n",
      "10            3  Tell me a joke  OpenAI            4   \n",
      "11            3  Tell me a poem  OpenAI            4   \n",
      "\n",
      "                                               output  \\\n",
      "0   \\n\\nQ: What did the fish say when it hit the w...   \n",
      "1   \\n\\nRoses are red,\\nViolets are blue,\\nSugar i...   \n",
      "2   \\n\\nQ: What did the fish say when it hit the w...   \n",
      "3   \\n\\nRoses are red,\\nViolets are blue,\\nSugar i...   \n",
      "4   \\n\\nQ: What did the fish say when it hit the w...   \n",
      "5   \\n\\nRoses are red,\\nViolets are blue,\\nSugar i...   \n",
      "6   \\n\\nQ: What did the fish say when it hit the w...   \n",
      "7   \\n\\nRoses are red,\\nViolets are blue,\\nSugar i...   \n",
      "8   \\n\\nQ: What did the fish say when it hit the w...   \n",
      "9   \\n\\nRoses are red,\\nViolets are blue,\\nSugar i...   \n",
      "10  \\n\\nQ: What did the fish say when it hit the w...   \n",
      "11  \\n\\nRoses are red,\\nViolets are blue,\\nSugar i...   \n",
      "\n",
      "    token_usage_total_tokens  token_usage_prompt_tokens  \\\n",
      "0                        162                         24   \n",
      "1                        162                         24   \n",
      "2                        162                         24   \n",
      "3                        162                         24   \n",
      "4                        162                         24   \n",
      "5                        162                         24   \n",
      "6                        162                         24   \n",
      "7                        162                         24   \n",
      "8                        162                         24   \n",
      "9                        162                         24   \n",
      "10                       162                         24   \n",
      "11                       162                         24   \n",
      "\n",
      "    token_usage_completion_tokens  flesch_reading_ease  flesch_kincaid_grade  \\\n",
      "0                             138               109.04                   1.3   \n",
      "1                             138                83.66                   4.8   \n",
      "2                             138               109.04                   1.3   \n",
      "3                             138                83.66                   4.8   \n",
      "4                             138               109.04                   1.3   \n",
      "5                             138                83.66                   4.8   \n",
      "6                             138               109.04                   1.3   \n",
      "7                             138                83.66                   4.8   \n",
      "8                             138               109.04                   1.3   \n",
      "9                             138                83.66                   4.8   \n",
      "10                            138               109.04                   1.3   \n",
      "11                            138                83.66                   4.8   \n",
      "\n",
      "    ...  difficult_words  linsear_write_formula  gunning_fog  \\\n",
      "0   ...                0                    5.5         5.20   \n",
      "1   ...                2                    6.5         8.28   \n",
      "2   ...                0                    5.5         5.20   \n",
      "3   ...                2                    6.5         8.28   \n",
      "4   ...                0                    5.5         5.20   \n",
      "5   ...                2                    6.5         8.28   \n",
      "6   ...                0                    5.5         5.20   \n",
      "7   ...                2                    6.5         8.28   \n",
      "8   ...                0                    5.5         5.20   \n",
      "9   ...                2                    6.5         8.28   \n",
      "10  ...                0                    5.5         5.20   \n",
      "11  ...                2                    6.5         8.28   \n",
      "\n",
      "        text_standard  fernandez_huerta  szigriszt_pazos  gutierrez_polini  \\\n",
      "0   5th and 6th grade            133.58           131.54             62.30   \n",
      "1   6th and 7th grade            115.58           112.37             54.83   \n",
      "2   5th and 6th grade            133.58           131.54             62.30   \n",
      "3   6th and 7th grade            115.58           112.37             54.83   \n",
      "4   5th and 6th grade            133.58           131.54             62.30   \n",
      "5   6th and 7th grade            115.58           112.37             54.83   \n",
      "6   5th and 6th grade            133.58           131.54             62.30   \n",
      "7   6th and 7th grade            115.58           112.37             54.83   \n",
      "8   5th and 6th grade            133.58           131.54             62.30   \n",
      "9   6th and 7th grade            115.58           112.37             54.83   \n",
      "10  5th and 6th grade            133.58           131.54             62.30   \n",
      "11  6th and 7th grade            115.58           112.37             54.83   \n",
      "\n",
      "   crawford  gulpease_index   osman  \n",
      "0      -0.2            79.8  116.91  \n",
      "1       1.4            72.1  100.17  \n",
      "2      -0.2            79.8  116.91  \n",
      "3       1.4            72.1  100.17  \n",
      "4      -0.2            79.8  116.91  \n",
      "5       1.4            72.1  100.17  \n",
      "6      -0.2            79.8  116.91  \n",
      "7       1.4            72.1  100.17  \n",
      "8      -0.2            79.8  116.91  \n",
      "9       1.4            72.1  100.17  \n",
      "10     -0.2            79.8  116.91  \n",
      "11      1.4            72.1  100.17  \n",
      "\n",
      "[12 rows x 24 columns]}\n",
      "2023-03-29 14:00:25,948 - clearml.Task - INFO - Completed model upload to https://files.clear.ml/langchain_callback_demo/llm.988bd727b0e94a29a3ac0ee526813545/models/simple_sequential\n"
     ]
    }
   ],
   "source": [
    "# SCENARIO 1 - LLM\n",
    "llm_result = llm.generate([\"Tell me a joke\", \"Tell me a poem\"] * 3)\n",
    "# After every generation run, use flush to make sure all the metrics\n",
    "# prompts and other output are properly saved separately\n",
    "clearml_callback.flush_tracker(langchain_asset=llm, name=\"simple_sequential\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "At this point you can already go to https://app.clear.ml and take a look at the resulting ClearML Task that was created.\n",
    "\n",
    "Among others, you should see that this notebook is saved along with any git information. The model JSON that contains the used parameters is saved as an artifact, there are also console logs and under the plots section, you'll find tables that represent the flow of the chain.\n",
    "\n",
    "Finally, if you enabled visualizations, these are stored as HTML files under debug samples."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Scenario 2: Creating an agent with tools\n",
    "\n",
    "To show a more advanced workflow, let's create an agent with access to tools. The way ClearML tracks the results is not different though, only the table will look slightly different as there are other types of actions taken when compared to the earlier, simpler example.\n",
    "\n",
    "You can now also see the use of the `finish=True` keyword, which will fully close the ClearML Task, instead of just resetting the parameters and prompts for a new conversation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "\u001b[1m> Entering new AgentExecutor chain...\u001b[0m\n",
      "{'action': 'on_chain_start', 'name': 'AgentExecutor', 'step': 1, 'starts': 1, 'ends': 0, 'errors': 0, 'text_ctr': 0, 'chain_starts': 1, 'chain_ends': 0, 'llm_starts': 0, 'llm_ends': 0, 'llm_streams': 0, 'tool_starts': 0, 'tool_ends': 0, 'agent_ends': 0, 'input': 'Who is the wife of the person who sang summer of 69?'}\n",
      "{'action': 'on_llm_start', 'name': 'OpenAI', 'step': 2, 'starts': 2, 'ends': 0, 'errors': 0, 'text_ctr': 0, 'chain_starts': 1, 'chain_ends': 0, 'llm_starts': 1, 'llm_ends': 0, 'llm_streams': 0, 'tool_starts': 0, 'tool_ends': 0, 'agent_ends': 0, 'prompts': 'Answer the following questions as best you can. You have access to the following tools:\\n\\nSearch: A search engine. Useful for when you need to answer questions about current events. Input should be a search query.\\nCalculator: Useful for when you need to answer questions about math.\\n\\nUse the following format:\\n\\nQuestion: the input question you must answer\\nThought: you should always think about what to do\\nAction: the action to take, should be one of [Search, Calculator]\\nAction Input: the input to the action\\nObservation: the result of the action\\n... (this Thought/Action/Action Input/Observation can repeat N times)\\nThought: I now know the final answer\\nFinal Answer: the final answer to the original input question\\n\\nBegin!\\n\\nQuestion: Who is the wife of the person who sang summer of 69?\\nThought:'}\n",
      "{'action': 'on_llm_end', 'token_usage_prompt_tokens': 189, 'token_usage_completion_tokens': 34, 'token_usage_total_tokens': 223, 'model_name': 'text-davinci-003', 'step': 3, 'starts': 2, 'ends': 1, 'errors': 0, 'text_ctr': 0, 'chain_starts': 1, 'chain_ends': 0, 'llm_starts': 1, 'llm_ends': 1, 'llm_streams': 0, 'tool_starts': 0, 'tool_ends': 0, 'agent_ends': 0, 'text': ' I need to find out who sang summer of 69 and then find out who their wife is.\\nAction: Search\\nAction Input: \"Who sang summer of 69\"', 'generation_info_finish_reason': 'stop', 'generation_info_logprobs': None, 'flesch_reading_ease': 91.61, 'flesch_kincaid_grade': 3.8, 'smog_index': 0.0, 'coleman_liau_index': 3.41, 'automated_readability_index': 3.5, 'dale_chall_readability_score': 6.06, 'difficult_words': 2, 'linsear_write_formula': 5.75, 'gunning_fog': 5.4, 'text_standard': '3rd and 4th grade', 'fernandez_huerta': 121.07, 'szigriszt_pazos': 119.5, 'gutierrez_polini': 54.91, 'crawford': 0.9, 'gulpease_index': 72.7, 'osman': 92.16}\n",
      "\u001b[32;1m\u001b[1;3m I need to find out who sang summer of 69 and then find out who their wife is.\n",
      "Action: Search\n",
      "Action Input: \"Who sang summer of 69\"\u001b[0m{'action': 'on_agent_action', 'tool': 'Search', 'tool_input': 'Who sang summer of 69', 'log': ' I need to find out who sang summer of 69 and then find out who their wife is.\\nAction: Search\\nAction Input: \"Who sang summer of 69\"', 'step': 4, 'starts': 3, 'ends': 1, 'errors': 0, 'text_ctr': 0, 'chain_starts': 1, 'chain_ends': 0, 'llm_starts': 1, 'llm_ends': 1, 'llm_streams': 0, 'tool_starts': 1, 'tool_ends': 0, 'agent_ends': 0}\n",
      "{'action': 'on_tool_start', 'input_str': 'Who sang summer of 69', 'name': 'Search', 'description': 'A search engine. Useful for when you need to answer questions about current events. Input should be a search query.', 'step': 5, 'starts': 4, 'ends': 1, 'errors': 0, 'text_ctr': 0, 'chain_starts': 1, 'chain_ends': 0, 'llm_starts': 1, 'llm_ends': 1, 'llm_streams': 0, 'tool_starts': 2, 'tool_ends': 0, 'agent_ends': 0}\n",
      "\n",
      "Observation: \u001b[36;1m\u001b[1;3mBryan Adams - Summer Of 69 (Official Music Video).\u001b[0m\n",
      "Thought:{'action': 'on_tool_end', 'output': 'Bryan Adams - Summer Of 69 (Official Music Video).', 'step': 6, 'starts': 4, 'ends': 2, 'errors': 0, 'text_ctr': 0, 'chain_starts': 1, 'chain_ends': 0, 'llm_starts': 1, 'llm_ends': 1, 'llm_streams': 0, 'tool_starts': 2, 'tool_ends': 1, 'agent_ends': 0}\n",
      "{'action': 'on_llm_start', 'name': 'OpenAI', 'step': 7, 'starts': 5, 'ends': 2, 'errors': 0, 'text_ctr': 0, 'chain_starts': 1, 'chain_ends': 0, 'llm_starts': 2, 'llm_ends': 1, 'llm_streams': 0, 'tool_starts': 2, 'tool_ends': 1, 'agent_ends': 0, 'prompts': 'Answer the following questions as best you can. You have access to the following tools:\\n\\nSearch: A search engine. Useful for when you need to answer questions about current events. Input should be a search query.\\nCalculator: Useful for when you need to answer questions about math.\\n\\nUse the following format:\\n\\nQuestion: the input question you must answer\\nThought: you should always think about what to do\\nAction: the action to take, should be one of [Search, Calculator]\\nAction Input: the input to the action\\nObservation: the result of the action\\n... (this Thought/Action/Action Input/Observation can repeat N times)\\nThought: I now know the final answer\\nFinal Answer: the final answer to the original input question\\n\\nBegin!\\n\\nQuestion: Who is the wife of the person who sang summer of 69?\\nThought: I need to find out who sang summer of 69 and then find out who their wife is.\\nAction: Search\\nAction Input: \"Who sang summer of 69\"\\nObservation: Bryan Adams - Summer Of 69 (Official Music Video).\\nThought:'}\n",
      "{'action': 'on_llm_end', 'token_usage_prompt_tokens': 242, 'token_usage_completion_tokens': 28, 'token_usage_total_tokens': 270, 'model_name': 'text-davinci-003', 'step': 8, 'starts': 5, 'ends': 3, 'errors': 0, 'text_ctr': 0, 'chain_starts': 1, 'chain_ends': 0, 'llm_starts': 2, 'llm_ends': 2, 'llm_streams': 0, 'tool_starts': 2, 'tool_ends': 1, 'agent_ends': 0, 'text': ' I need to find out who Bryan Adams is married to.\\nAction: Search\\nAction Input: \"Who is Bryan Adams married to\"', 'generation_info_finish_reason': 'stop', 'generation_info_logprobs': None, 'flesch_reading_ease': 94.66, 'flesch_kincaid_grade': 2.7, 'smog_index': 0.0, 'coleman_liau_index': 4.73, 'automated_readability_index': 4.0, 'dale_chall_readability_score': 7.16, 'difficult_words': 2, 'linsear_write_formula': 4.25, 'gunning_fog': 4.2, 'text_standard': '4th and 5th grade', 'fernandez_huerta': 124.13, 'szigriszt_pazos': 119.2, 'gutierrez_polini': 52.26, 'crawford': 0.7, 'gulpease_index': 74.7, 'osman': 84.2}\n",
      "\u001b[32;1m\u001b[1;3m I need to find out who Bryan Adams is married to.\n",
      "Action: Search\n",
      "Action Input: \"Who is Bryan Adams married to\"\u001b[0m{'action': 'on_agent_action', 'tool': 'Search', 'tool_input': 'Who is Bryan Adams married to', 'log': ' I need to find out who Bryan Adams is married to.\\nAction: Search\\nAction Input: \"Who is Bryan Adams married to\"', 'step': 9, 'starts': 6, 'ends': 3, 'errors': 0, 'text_ctr': 0, 'chain_starts': 1, 'chain_ends': 0, 'llm_starts': 2, 'llm_ends': 2, 'llm_streams': 0, 'tool_starts': 3, 'tool_ends': 1, 'agent_ends': 0}\n",
      "{'action': 'on_tool_start', 'input_str': 'Who is Bryan Adams married to', 'name': 'Search', 'description': 'A search engine. Useful for when you need to answer questions about current events. Input should be a search query.', 'step': 10, 'starts': 7, 'ends': 3, 'errors': 0, 'text_ctr': 0, 'chain_starts': 1, 'chain_ends': 0, 'llm_starts': 2, 'llm_ends': 2, 'llm_streams': 0, 'tool_starts': 4, 'tool_ends': 1, 'agent_ends': 0}\n",
      "\n",
      "Observation: \u001b[36;1m\u001b[1;3mBryan Adams has never married. In the 1990s, he was in a relationship with Danish model Cecilie Thomsen. In 2011, Bryan and Alicia Grimaldi, his ...\u001b[0m\n",
      "Thought:{'action': 'on_tool_end', 'output': 'Bryan Adams has never married. In the 1990s, he was in a relationship with Danish model Cecilie Thomsen. In 2011, Bryan and Alicia Grimaldi, his ...', 'step': 11, 'starts': 7, 'ends': 4, 'errors': 0, 'text_ctr': 0, 'chain_starts': 1, 'chain_ends': 0, 'llm_starts': 2, 'llm_ends': 2, 'llm_streams': 0, 'tool_starts': 4, 'tool_ends': 2, 'agent_ends': 0}\n",
      "{'action': 'on_llm_start', 'name': 'OpenAI', 'step': 12, 'starts': 8, 'ends': 4, 'errors': 0, 'text_ctr': 0, 'chain_starts': 1, 'chain_ends': 0, 'llm_starts': 3, 'llm_ends': 2, 'llm_streams': 0, 'tool_starts': 4, 'tool_ends': 2, 'agent_ends': 0, 'prompts': 'Answer the following questions as best you can. You have access to the following tools:\\n\\nSearch: A search engine. Useful for when you need to answer questions about current events. Input should be a search query.\\nCalculator: Useful for when you need to answer questions about math.\\n\\nUse the following format:\\n\\nQuestion: the input question you must answer\\nThought: you should always think about what to do\\nAction: the action to take, should be one of [Search, Calculator]\\nAction Input: the input to the action\\nObservation: the result of the action\\n... (this Thought/Action/Action Input/Observation can repeat N times)\\nThought: I now know the final answer\\nFinal Answer: the final answer to the original input question\\n\\nBegin!\\n\\nQuestion: Who is the wife of the person who sang summer of 69?\\nThought: I need to find out who sang summer of 69 and then find out who their wife is.\\nAction: Search\\nAction Input: \"Who sang summer of 69\"\\nObservation: Bryan Adams - Summer Of 69 (Official Music Video).\\nThought: I need to find out who Bryan Adams is married to.\\nAction: Search\\nAction Input: \"Who is Bryan Adams married to\"\\nObservation: Bryan Adams has never married. In the 1990s, he was in a relationship with Danish model Cecilie Thomsen. In 2011, Bryan and Alicia Grimaldi, his ...\\nThought:'}\n",
      "{'action': 'on_llm_end', 'token_usage_prompt_tokens': 314, 'token_usage_completion_tokens': 18, 'token_usage_total_tokens': 332, 'model_name': 'text-davinci-003', 'step': 13, 'starts': 8, 'ends': 5, 'errors': 0, 'text_ctr': 0, 'chain_starts': 1, 'chain_ends': 0, 'llm_starts': 3, 'llm_ends': 3, 'llm_streams': 0, 'tool_starts': 4, 'tool_ends': 2, 'agent_ends': 0, 'text': ' I now know the final answer.\\nFinal Answer: Bryan Adams has never been married.', 'generation_info_finish_reason': 'stop', 'generation_info_logprobs': None, 'flesch_reading_ease': 81.29, 'flesch_kincaid_grade': 3.7, 'smog_index': 0.0, 'coleman_liau_index': 5.75, 'automated_readability_index': 3.9, 'dale_chall_readability_score': 7.37, 'difficult_words': 1, 'linsear_write_formula': 2.5, 'gunning_fog': 2.8, 'text_standard': '3rd and 4th grade', 'fernandez_huerta': 115.7, 'szigriszt_pazos': 110.84, 'gutierrez_polini': 49.79, 'crawford': 0.7, 'gulpease_index': 85.4, 'osman': 83.14}\n",
      "\u001b[32;1m\u001b[1;3m I now know the final answer.\n",
      "Final Answer: Bryan Adams has never been married.\u001b[0m\n",
      "{'action': 'on_agent_finish', 'output': 'Bryan Adams has never been married.', 'log': ' I now know the final answer.\\nFinal Answer: Bryan Adams has never been married.', 'step': 14, 'starts': 8, 'ends': 6, 'errors': 0, 'text_ctr': 0, 'chain_starts': 1, 'chain_ends': 0, 'llm_starts': 3, 'llm_ends': 3, 'llm_streams': 0, 'tool_starts': 4, 'tool_ends': 2, 'agent_ends': 1}\n",
      "\n",
      "\u001b[1m> Finished chain.\u001b[0m\n",
      "{'action': 'on_chain_end', 'outputs': 'Bryan Adams has never been married.', 'step': 15, 'starts': 8, 'ends': 7, 'errors': 0, 'text_ctr': 0, 'chain_starts': 1, 'chain_ends': 1, 'llm_starts': 3, 'llm_ends': 3, 'llm_streams': 0, 'tool_starts': 4, 'tool_ends': 2, 'agent_ends': 1}\n",
      "{'action_records':              action    name  step  starts  ends  errors  text_ctr  \\\n",
      "0      on_llm_start  OpenAI     1       1     0       0         0   \n",
      "1      on_llm_start  OpenAI     1       1     0       0         0   \n",
      "2      on_llm_start  OpenAI     1       1     0       0         0   \n",
      "3      on_llm_start  OpenAI     1       1     0       0         0   \n",
      "4      on_llm_start  OpenAI     1       1     0       0         0   \n",
      "..              ...     ...   ...     ...   ...     ...       ...   \n",
      "66      on_tool_end     NaN    11       7     4       0         0   \n",
      "67     on_llm_start  OpenAI    12       8     4       0         0   \n",
      "68       on_llm_end     NaN    13       8     5       0         0   \n",
      "69  on_agent_finish     NaN    14       8     6       0         0   \n",
      "70     on_chain_end     NaN    15       8     7       0         0   \n",
      "\n",
      "    chain_starts  chain_ends  llm_starts  ...  gulpease_index  osman  input  \\\n",
      "0              0           0           1  ...             NaN    NaN    NaN   \n",
      "1              0           0           1  ...             NaN    NaN    NaN   \n",
      "2              0           0           1  ...             NaN    NaN    NaN   \n",
      "3              0           0           1  ...             NaN    NaN    NaN   \n",
      "4              0           0           1  ...             NaN    NaN    NaN   \n",
      "..           ...         ...         ...  ...             ...    ...    ...   \n",
      "66             1           0           2  ...             NaN    NaN    NaN   \n",
      "67             1           0           3  ...             NaN    NaN    NaN   \n",
      "68             1           0           3  ...            85.4  83.14    NaN   \n",
      "69             1           0           3  ...             NaN    NaN    NaN   \n",
      "70             1           1           3  ...             NaN    NaN    NaN   \n",
      "\n",
      "    tool  tool_input                                                log  \\\n",
      "0    NaN         NaN                                                NaN   \n",
      "1    NaN         NaN                                                NaN   \n",
      "2    NaN         NaN                                                NaN   \n",
      "3    NaN         NaN                                                NaN   \n",
      "4    NaN         NaN                                                NaN   \n",
      "..   ...         ...                                                ...   \n",
      "66   NaN         NaN                                                NaN   \n",
      "67   NaN         NaN                                                NaN   \n",
      "68   NaN         NaN                                                NaN   \n",
      "69   NaN         NaN   I now know the final answer.\\nFinal Answer: B...   \n",
      "70   NaN         NaN                                                NaN   \n",
      "\n",
      "    input_str  description                                             output  \\\n",
      "0         NaN          NaN                                                NaN   \n",
      "1         NaN          NaN                                                NaN   \n",
      "2         NaN          NaN                                                NaN   \n",
      "3         NaN          NaN                                                NaN   \n",
      "4         NaN          NaN                                                NaN   \n",
      "..        ...          ...                                                ...   \n",
      "66        NaN          NaN  Bryan Adams has never married. In the 1990s, h...   \n",
      "67        NaN          NaN                                                NaN   \n",
      "68        NaN          NaN                                                NaN   \n",
      "69        NaN          NaN                Bryan Adams has never been married.   \n",
      "70        NaN          NaN                                                NaN   \n",
      "\n",
      "                                outputs  \n",
      "0                                   NaN  \n",
      "1                                   NaN  \n",
      "2                                   NaN  \n",
      "3                                   NaN  \n",
      "4                                   NaN  \n",
      "..                                  ...  \n",
      "66                                  NaN  \n",
      "67                                  NaN  \n",
      "68                                  NaN  \n",
      "69                                  NaN  \n",
      "70  Bryan Adams has never been married.  \n",
      "\n",
      "[71 rows x 47 columns], 'session_analysis':    prompt_step                                            prompts    name  \\\n",
      "0            2  Answer the following questions as best you can...  OpenAI   \n",
      "1            7  Answer the following questions as best you can...  OpenAI   \n",
      "2           12  Answer the following questions as best you can...  OpenAI   \n",
      "\n",
      "   output_step                                             output  \\\n",
      "0            3   I need to find out who sang summer of 69 and ...   \n",
      "1            8   I need to find out who Bryan Adams is married...   \n",
      "2           13   I now know the final answer.\\nFinal Answer: B...   \n",
      "\n",
      "   token_usage_total_tokens  token_usage_prompt_tokens  \\\n",
      "0                       223                        189   \n",
      "1                       270                        242   \n",
      "2                       332                        314   \n",
      "\n",
      "   token_usage_completion_tokens  flesch_reading_ease  flesch_kincaid_grade  \\\n",
      "0                             34                91.61                   3.8   \n",
      "1                             28                94.66                   2.7   \n",
      "2                             18                81.29                   3.7   \n",
      "\n",
      "   ...  difficult_words  linsear_write_formula  gunning_fog  \\\n",
      "0  ...                2                   5.75          5.4   \n",
      "1  ...                2                   4.25          4.2   \n",
      "2  ...                1                   2.50          2.8   \n",
      "\n",
      "       text_standard  fernandez_huerta  szigriszt_pazos  gutierrez_polini  \\\n",
      "0  3rd and 4th grade            121.07           119.50             54.91   \n",
      "1  4th and 5th grade            124.13           119.20             52.26   \n",
      "2  3rd and 4th grade            115.70           110.84             49.79   \n",
      "\n",
      "  crawford  gulpease_index  osman  \n",
      "0      0.9            72.7  92.16  \n",
      "1      0.7            74.7  84.20  \n",
      "2      0.7            85.4  83.14  \n",
      "\n",
      "[3 rows x 24 columns]}\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Could not update last created model in Task 988bd727b0e94a29a3ac0ee526813545, Task status 'completed' cannot be updated\n"
     ]
    }
   ],
   "source": [
    "from langchain.agents import initialize_agent, load_tools\n",
    "from langchain.agents import AgentType\n",
    "\n",
    "# SCENARIO 2 - Agent with Tools\n",
    "tools = load_tools([\"serpapi\", \"llm-math\"], llm=llm, callbacks=callbacks)\n",
    "agent = initialize_agent(\n",
    "    tools,\n",
    "    llm,\n",
    "    agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION,\n",
    "    callbacks=callbacks,\n",
    ")\n",
    "agent.run(\"Who is the wife of the person who sang summer of 69?\")\n",
    "clearml_callback.flush_tracker(\n",
    "    langchain_asset=agent, name=\"Agent with Tools\", finish=True\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Tips and Next Steps\n",
    "\n",
    "- Make sure you always use a unique `name` argument for the `clearml_callback.flush_tracker` function. If not, the model parameters used for a run will override the previous run!\n",
    "\n",
    "- If you close the ClearML Callback using `clearml_callback.flush_tracker(..., finish=True)` the Callback cannot be used anymore. Make a new one if you want to keep logging.\n",
    "\n",
    "- Check out the rest of the open source ClearML ecosystem, there is a data version manager, a remote execution agent, automated pipelines and much more!\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.6"
  },
  "vscode": {
   "interpreter": {
    "hash": "a53ebf4a859167383b364e7e7521d0add3c2dbbdecce4edf676e8c4634ff3fbb"
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
