ProvidersMoreClearMLOn this pageClearMLClearML is a ML/DL development and production suite, it contains 5 main modules:Experiment Manager - Automagical experiment tracking, environments and resultsMLOps - Orchestration, Automation & Pipelines solution for ML/DL jobs (K8s / Cloud / bare-metal)Data-Management - Fully differentiable data management & version control solution on top of object-storage (S3 / GS / Azure / NAS)Model-Serving - cloud-ready Scalable model serving solution!
Deploy new model endpoints in under 5 minutes
Includes optimized GPU serving support backed by Nvidia-Triton
with out-of-the-box Model MonitoringFire Reports - Create and share rich MarkDown documents supporting embeddable online contentIn 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.Installation and Setup​pip install clearmlpip install pandaspip install textstatpip install spacypython -m spacy download en_core_web_smGetting API Credentials​We'll be using quite some APIs in this notebook, here is a list and where to get them:ClearML: https://app.clear.ml/settings/workspace-configurationOpenAI: https://platform.openai.com/account/api-keysSerpAPI (google search): https://serpapi.com/dashboardimport osos.environ["CLEARML_API_ACCESS_KEY"] = ""os.environ["CLEARML_API_SECRET_KEY"] = ""os.environ["OPENAI_API_KEY"] = ""os.environ["SERPAPI_API_KEY"] = ""Callbacks​from langchain.callbacks import ClearMLCallbackHandlerfrom datetime import datetimefrom langchain.callbacks import StdOutCallbackHandlerfrom langchain.llms import OpenAI# Setup and use the ClearML Callbackclearml_callback = ClearMLCallbackHandler(    task_type="inference",    project_name="langchain_callback_demo",    task_name="llm",    tags=["test"],    # Change the following parameters based on the amount of detail you want tracked    visualize=True,    complexity_metrics=True,    stream_logs=True,)callbacks = [StdOutCallbackHandler(), clearml_callback]# Get the OpenAI model ready to gollm = OpenAI(temperature=0, callbacks=callbacks)    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`.Scenario 1: Just an LLM​First, let's just run a single LLM a few times and capture the resulting prompt-answer conversation in ClearML# SCENARIO 1 - LLMllm_result = llm.generate(["Tell me a joke", "Tell me a poem"] * 3)# After every generation run, use flush to make sure all the metrics# prompts and other output are properly saved separatelyclearml_callback.flush_tracker(langchain_asset=llm, name="simple_sequential")    {'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'}    {'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'}    {'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'}    {'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'}    {'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'}    {'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'}    {'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}    {'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}    {'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}    {'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}    {'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}    {'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}    {'action_records':           action    name  step  starts  ends  errors  text_ctr  chain_starts  \    0   on_llm_start  OpenAI     1       1     0       0         0             0       1   on_llm_start  OpenAI     1       1     0       0         0             0       2   on_llm_start  OpenAI     1       1     0       0         0             0       3   on_llm_start  OpenAI     1       1     0       0         0             0       4   on_llm_start  OpenAI     1       1     0       0         0             0       5   on_llm_start  OpenAI     1       1     0       0         0             0       6     on_llm_end     NaN     2       1     1       0         0             0       7     on_llm_end     NaN     2       1     1       0         0             0       8     on_llm_end     NaN     2       1     1       0         0             0       9     on_llm_end     NaN     2       1     1       0         0             0       10    on_llm_end     NaN     2       1     1       0         0             0       11    on_llm_end     NaN     2       1     1       0         0             0       12  on_llm_start  OpenAI     3       2     1       0         0             0       13  on_llm_start  OpenAI     3       2     1       0         0             0       14  on_llm_start  OpenAI     3       2     1       0         0             0       15  on_llm_start  OpenAI     3       2     1       0         0             0       16  on_llm_start  OpenAI     3       2     1       0         0             0       17  on_llm_start  OpenAI     3       2     1       0         0             0       18    on_llm_end     NaN     4       2     2       0         0             0       19    on_llm_end     NaN     4       2     2       0         0             0       20    on_llm_end     NaN     4       2     2       0         0             0       21    on_llm_end     NaN     4       2     2       0         0             0       22    on_llm_end     NaN     4       2     2       0         0             0       23    on_llm_end     NaN     4       2     2       0         0             0               chain_ends  llm_starts  ...  difficult_words  linsear_write_formula  \    0            0           1  ...              NaN                    NaN       1            0           1  ...              NaN                    NaN       2            0           1  ...              NaN                    NaN       3            0           1  ...              NaN                    NaN       4            0           1  ...              NaN                    NaN       5            0           1  ...              NaN                    NaN       6            0           1  ...              0.0                    5.5       7            0           1  ...              2.0                    6.5       8            0           1  ...              0.0                    5.5       9            0           1  ...              2.0                    6.5       10           0           1  ...              0.0                    5.5       11           0           1  ...              2.0                    6.5       12           0           2  ...              NaN                    NaN       13           0           2  ...              NaN                    NaN       14           0           2  ...              NaN                    NaN       15           0           2  ...              NaN                    NaN       16           0           2  ...              NaN                    NaN       17           0           2  ...              NaN                    NaN       18           0           2  ...              0.0                    5.5       19           0           2  ...              2.0                    6.5       20           0           2  ...              0.0                    5.5       21           0           2  ...              2.0                    6.5       22           0           2  ...              0.0                    5.5       23           0           2  ...              2.0                    6.5               gunning_fog      text_standard  fernandez_huerta szigriszt_pazos  \    0           NaN                NaN               NaN             NaN       1           NaN                NaN               NaN             NaN       2           NaN                NaN               NaN             NaN       3           NaN                NaN               NaN             NaN       4           NaN                NaN               NaN             NaN       5           NaN                NaN               NaN             NaN       6          5.20  5th and 6th grade            133.58          131.54       7          8.28  6th and 7th grade            115.58          112.37       8          5.20  5th and 6th grade            133.58          131.54       9          8.28  6th and 7th grade            115.58          112.37       10         5.20  5th and 6th grade            133.58          131.54       11         8.28  6th and 7th grade            115.58          112.37       12          NaN                NaN               NaN             NaN       13          NaN                NaN               NaN             NaN       14          NaN                NaN               NaN             NaN       15          NaN                NaN               NaN             NaN       16          NaN                NaN               NaN             NaN       17          NaN                NaN               NaN             NaN       18         5.20  5th and 6th grade            133.58          131.54       19         8.28  6th and 7th grade            115.58          112.37       20         5.20  5th and 6th grade            133.58          131.54       21         8.28  6th and 7th grade            115.58          112.37       22         5.20  5th and 6th grade            133.58          131.54       23         8.28  6th and 7th grade            115.58          112.37               gutierrez_polini  crawford  gulpease_index   osman      0                NaN       NaN             NaN     NaN      1                NaN       NaN             NaN     NaN      2                NaN       NaN             NaN     NaN      3                NaN       NaN             NaN     NaN      4                NaN       NaN             NaN     NaN      5                NaN       NaN             NaN     NaN      6              62.30      -0.2            79.8  116.91      7              54.83       1.4            72.1  100.17      8              62.30      -0.2            79.8  116.91      9              54.83       1.4            72.1  100.17      10             62.30      -0.2            79.8  116.91      11             54.83       1.4            72.1  100.17      12               NaN       NaN             NaN     NaN      13               NaN       NaN             NaN     NaN      14               NaN       NaN             NaN     NaN      15               NaN       NaN             NaN     NaN      16               NaN       NaN             NaN     NaN      17               NaN       NaN             NaN     NaN      18             62.30      -0.2            79.8  116.91      19             54.83       1.4            72.1  100.17      20             62.30      -0.2            79.8  116.91      21             54.83       1.4            72.1  100.17      22             62.30      -0.2            79.8  116.91      23             54.83       1.4            72.1  100.17          [24 rows x 39 columns], 'session_analysis':     prompt_step         prompts    name  output_step  \    0             1  Tell me a joke  OpenAI            2       1             1  Tell me a poem  OpenAI            2       2             1  Tell me a joke  OpenAI            2       3             1  Tell me a poem  OpenAI            2       4             1  Tell me a joke  OpenAI            2       5             1  Tell me a poem  OpenAI            2       6             3  Tell me a joke  OpenAI            4       7             3  Tell me a poem  OpenAI            4       8             3  Tell me a joke  OpenAI            4       9             3  Tell me a poem  OpenAI            4       10            3  Tell me a joke  OpenAI            4       11            3  Tell me a poem  OpenAI            4                                                          output  \    0   \n\nQ: What did the fish say when it hit the w...       1   \n\nRoses are red,\nViolets are blue,\nSugar i...       2   \n\nQ: What did the fish say when it hit the w...       3   \n\nRoses are red,\nViolets are blue,\nSugar i...       4   \n\nQ: What did the fish say when it hit the w...       5   \n\nRoses are red,\nViolets are blue,\nSugar i...       6   \n\nQ: What did the fish say when it hit the w...       7   \n\nRoses are red,\nViolets are blue,\nSugar i...       8   \n\nQ: What did the fish say when it hit the w...       9   \n\nRoses are red,\nViolets are blue,\nSugar i...       10  \n\nQ: What did the fish say when it hit the w...       11  \n\nRoses are red,\nViolets are blue,\nSugar i...               token_usage_total_tokens  token_usage_prompt_tokens  \    0                        162                         24       1                        162                         24       2                        162                         24       3                        162                         24       4                        162                         24       5                        162                         24       6                        162                         24       7                        162                         24       8                        162                         24       9                        162                         24       10                       162                         24       11                       162                         24               token_usage_completion_tokens  flesch_reading_ease  flesch_kincaid_grade  \    0                             138               109.04                   1.3       1                             138                83.66                   4.8       2                             138               109.04                   1.3       3                             138                83.66                   4.8       4                             138               109.04                   1.3       5                             138                83.66                   4.8       6                             138               109.04                   1.3       7                             138                83.66                   4.8       8                             138               109.04                   1.3       9                             138                83.66                   4.8       10                            138               109.04                   1.3       11                            138                83.66                   4.8               ...  difficult_words  linsear_write_formula  gunning_fog  \    0   ...                0                    5.5         5.20       1   ...                2                    6.5         8.28       2   ...                0                    5.5         5.20       3   ...                2                    6.5         8.28       4   ...                0                    5.5         5.20       5   ...                2                    6.5         8.28       6   ...                0                    5.5         5.20       7   ...                2                    6.5         8.28       8   ...                0                    5.5         5.20       9   ...                2                    6.5         8.28       10  ...                0                    5.5         5.20       11  ...                2                    6.5         8.28                   text_standard  fernandez_huerta  szigriszt_pazos  gutierrez_polini  \    0   5th and 6th grade            133.58           131.54             62.30       1   6th and 7th grade            115.58           112.37             54.83       2   5th and 6th grade            133.58           131.54             62.30       3   6th and 7th grade            115.58           112.37             54.83       4   5th and 6th grade            133.58           131.54             62.30       5   6th and 7th grade            115.58           112.37             54.83       6   5th and 6th grade            133.58           131.54             62.30       7   6th and 7th grade            115.58           112.37             54.83       8   5th and 6th grade            133.58           131.54             62.30       9   6th and 7th grade            115.58           112.37             54.83       10  5th and 6th grade            133.58           131.54             62.30       11  6th and 7th grade            115.58           112.37             54.83              crawford  gulpease_index   osman      0      -0.2            79.8  116.91      1       1.4            72.1  100.17      2      -0.2            79.8  116.91      3       1.4            72.1  100.17      4      -0.2            79.8  116.91      5       1.4            72.1  100.17      6      -0.2            79.8  116.91      7       1.4            72.1  100.17      8      -0.2            79.8  116.91      9       1.4            72.1  100.17      10     -0.2            79.8  116.91      11      1.4            72.1  100.17          [12 rows x 24 columns]}    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_sequentialAt this point you can already go to https://app.clear.ml and take a look at the resulting ClearML Task that was created.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.Finally, if you enabled visualizations, these are stored as HTML files under debug samples.Scenario 2: Creating an agent with tools​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.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.from langchain.agents import initialize_agent, load_toolsfrom langchain.agents import AgentType# SCENARIO 2 - Agent with Toolstools = load_tools(["serpapi", "llm-math"], llm=llm, callbacks=callbacks)agent = initialize_agent(    tools,    llm,    agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION,    callbacks=callbacks,)agent.run("Who is the wife of the person who sang summer of 69?")clearml_callback.flush_tracker(    langchain_asset=agent, name="Agent with Tools", finish=True)            > Entering new AgentExecutor chain...    {'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?'}    {'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:'}    {'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}     I need to find out who sang summer of 69 and then find out who their wife is.    Action: Search    Action Input: "Who sang summer of 69"{'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}    {'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}        Observation: Bryan Adams - Summer Of 69 (Official Music Video).    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}    {'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:'}    {'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}     I need to find out who Bryan Adams is married to.    Action: Search    Action Input: "Who is Bryan Adams married to"{'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}    {'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}        Observation: 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 ...    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_s