ClearML
ClearML 是一个机器学习/深度学习开发和生产套件，包含以下5个主要模块：
实验管理器- 自动化实验跟踪、环境和结果MLOps- 用于机器学习/深度学习作业的编排、自动化和流水线解决方案（K8s / 云 / 金属）数据管理- 基于对象存储（S3 / GS / Azure / NAS）的完全可区分的数据管理和版本控制解决方案模型服务- 云就绪的可扩展模型服务解决方案！在不到5分钟内部署新的模型端点
包括由Nvidia-Triton支持的优化GPU服务
具备开箱即用的模型监控功能
火报告- 创建和共享支持嵌入式在线内容的丰富的Markdown文档
为了正确跟踪您的langchain实验及其结果，您可以启用ClearML集成。我们使用ClearML实验管理器来整洁地跟踪和组织所有实验运行。
安装和设置
%pip install --upgrade --quiet clearml
%pip install --upgrade --quiet pandas
%pip install --upgrade --quiet textstat
%pip install --upgrade --quiet spacy
!python -m spacy download en_core_web_sm
获取API凭据
我们将在本笔记本中使用一些API，以下是这些API的列表以及获取它们的位置：
ClearML: https://app.clear.ml/settings/workspace-configuration
SerpAPI (google search): https://serpapi.com/dashboard
import os
os.environ["CLEARML_API_ACCESS_KEY"] = ""
os.environ["CLEARML_API_SECRET_KEY"] = ""
os.environ["OPENAI_API_KEY"] = ""
os.environ["SERPAPI_API_KEY"] = ""
回调函数
from langchain_community.callbacks import ClearMLCallbackHandler
from langchain_core.callbacks import StdOutCallbackHandler
from langchain_openai import OpenAI
# 设置并使用ClearML回调函数
clearml_callback = ClearMLCallbackHandler(
task_type="inference",
project_name="langchain_callback_demo",
task_name="llm",
tags=["test"],
# 根据您想要跟踪的详细程度更改以下参数
visualize=True,
complexity_metrics=True,
stream_logs=True,
)
callbacks = [StdOutCallbackHandler(), clearml_callback]
# 准备好OpenAI模型
llm = OpenAI(temperature=0, callbacks=callbacks)
clearml回调函数目前处于测试阶段，可能会根据`langchain`的更新而发生变化。请将任何问题报告给https://github.com/allegroai/clearml/issues，并使用标签`langchain`。
场景1：只有一个LLM
首先，让我们运行几次单个LLM，并在ClearML中捕获生成的提示-回答对话。
# 场景1 - LLM
llm_result = llm.generate(["Tell me a joke", "Tell me a poem"] * 3)
# 在每次生成运行之后，使用flush确保所有指标、提示和其他输出都被正确保存
clearml_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 text_standard fernandez_huerta szigriszt_pazos gutierrez_polini crawford gulpease_index osman
0 ... 0 5.5 5.20 5th and 6th grade 133.58 131.54 62.30 -0.2 79.8 116.91
1 ... 2 6.5 8.28 6th and 7th grade 115.58 112.37 54.83 1.4 72.1 100.17
2 ... 0 5.5 5.20 5th and 6th grade 133.58 131.54 62.30 -0.2 79.8 116.91
3 ... 2 6.5 8.28 6th and 7th grade 115.58 112.37 54.83 1.4 72.1 100.17
4 ... 0 5.5 5.20 5th and 6th grade 133.58 131.54 62.30 -0.2 79.8 116.91
5 ... 2 6.5 8.28 6th and 7th grade 115.58 112.37 54.83 1.4 72.1 100.17
6 ... 0 5.5 5.20 5th and 6th grade 133.58 131.54 62.30 -0.2 79.8 116.91
7 ... 2 6.5 8.28 6th and 7th grade 115.58 112.37 54.83 1.4 72.1 100.17
8 ... 0 5.5 5.20 5th and 6th grade 133.58 131.54 62.30 -0.2 79.8 116.91
9 ... 2 6.5 8.28 6th and 7th grade 115.58 112.37 54.83 1.4 72.1 100.17
10 ... 0 5.5 5.20 5th and 6th grade 133.58 131.54 62.30 -0.2 79.8 116.91
11 ... 2 6.5 8.28 6th and 7th grade 115.58 112.37 54.83 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_sequential
此时，您可以访问 https://app.clear.ml 并查看生成的 ClearML 任务。
在其他内容中，您会看到此笔记本与任何 git 信息一起保存。包含所使用参数的模型 JSON 保存为一个 artifact，还有控制台日志，在绘图部分，您会找到代表链路流程的表格。
最后，如果您启用了可视化功能，这些将以 HTML 文件的形式存储在调试样本下。
情景 2：使用工具创建代理
为了展示一个更高级的工作流程，让我们创建一个可以访问工具的代理。尽管 ClearML 跟踪结果的方式并没有不同，但由于与之前简单示例相比采取了其他类型的操作，表格看起来会略有不同。
现在您还可以看到使用 finish=True 关键字，这将完全关闭 ClearML 任务，而不仅仅是重置参数并提示进行新的对话。
from langchain.agents import AgentType, initialize_agent, load_tools
# 情景 2 - 带工具的代理
tools = 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
)
> 进入新的 AgentExecutor 链...
{'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}
观察: Bryan Adams - Summer Of 69 (官方音乐视频)。
思考:{'action': 'on_tool_end', 'output': 'Bryan Adams - Summer Of 69 (官方音乐视频)', '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': '尽力回答以下问题。您可以使用以下工具：\n\n搜索：搜索引擎。在需要回答有关当前事件的问题时很有用。输入应该是一个搜索查询。\n计算器：在需要回答数学问题时很有用。\n\n使用以下格式：\n\n问题：您必须回答的问题\n思考：您应该考虑要做什么\n行动：采取的行动，应该是[搜索，计算器]中的一个\n行动输入：行动的输入\n观察：行动的结果\n... (这个思考/行动/行动输入/观察可以重复N次)\n思考：我现在知道最终答案\n最终答案：原始输入问题的最终答案\n\n开始！\n\n问题：谁是演唱 Summer of 69 的人的妻子？\n思考：我需要找出谁演唱了 Summer of 69，然后找出他们的妻子是谁。\n行动：搜索\n行动输入："谁演唱了 Summer of 69"\n观察：Bryan Adams - Summer Of 69 (官方音乐视频)。\n思考:'}
{'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': '我需要找出 Bryan Adams 结婚了没有。\n行动：搜索\n行动输入："Bryan Adams 结婚了吗"', '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}
我需要找出 Bryan Adams 结婚了没有。
行动：搜索
行动输入："Bryan Adams 结婚了吗"{'action': 'on_agent_action', 'tool': 'Search', 'tool_input': 'Bryan Adams 结婚了吗', 'log': '我需要找出 Bryan Adams 结婚了没有。\n行动：搜索\n行动输入："Bryan Adams 结婚了吗"', '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': 'Bryan Adams 结婚了吗', 'name': '搜索', 'description': '搜索引擎。在需要回答有关当前事件的问题时很有用。输入应该是一个搜索查询。', '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}
观察: Bryan Adams 从未结婚。在1990年代，他与丹麦模特 Cecilie Thomsen 有过一段感情。2011年，Bryan 和 Alicia Grimaldi，他...
思考:{'action': 'on_tool_end', 'output': 'Bryan Adams 从未结婚。在1990年代，他与丹麦模特 Cecilie Thomsen 有过一段感情。2011年，Bryan 和 Alicia Grimaldi，他...', '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}
OpenAI 自然语言处理模型完成了一个任务
在这个任务中，OpenAI 的自然语言处理模型开始了一个包含多个步骤的流程。在第 12 步，模型开始了一个新的任务，其中包括 8 个起始步骤和 4 个结束步骤。在这个过程中，模型没有出现错误，也没有生成文本内容。
在这个任务中，模型被要求回答以下问题，并可以使用搜索引擎和计算器等工具来辅助回答问题。模型首先被问到：“谁是演唱《夏日 69》的人的妻子？”模型通过搜索发现是 Bryan Adams，并继续搜索得知 Bryan Adams 从未结过婚。最终，模型得出结论：Bryan Adams 从未结过婚。
这个任务的最终答案是：Bryan Adams 从未结过婚。
任务记录
模型名称：text-davinci-003
完成步骤：13
总起始步骤数：8
总结束步骤数：5
错误数：0
文本生成次数：0
链条起始次数：1
链条结束次数：0
LLM（大型语言模型）起始次数：3
LLM（大型语言模型）结束次数：3
工具起始次数：4
工具结束次数：2
代理结束次数：0
最终答案
Bryan Adams 从未结过婚。
完成链条。
69 1 0 3 ... NaN NaN NaN
70 1 1 3 ... NaN NaN NaN
tool tool_input log \
0 NaN NaN NaN
1 NaN NaN NaN
2 NaN NaN NaN
3 NaN NaN NaN
4 NaN NaN NaN
.. ... ... ...
66 NaN NaN NaN
67 NaN NaN NaN
68 NaN NaN NaN
69 NaN NaN 现在我知道最终答案。\n最终答案：Bryan Adams从未结过婚。
70 NaN NaN NaN
input_str description output \
0 NaN NaN NaN
1 NaN NaN NaN
2 NaN NaN NaN
3 NaN NaN NaN
4 NaN NaN NaN
.. ... ... ...
66 NaN NaN Bryan Adams从未结过婚。在1990年代，他与维多利亚的秘密模特儿Cecil...
67 NaN NaN NaN
68 NaN NaN NaN
69 NaN NaN Bryan Adams从未结过婚。
70 NaN NaN NaN
outputs
0 NaN
1 NaN
2 NaN
3 NaN
4 NaN
.. ...
66 NaN
67 NaN
68 NaN
69 NaN
70 Bryan Adams从未结过婚。
[71 rows x 47 columns], 'session_analysis': prompt_step prompts name \
0 2 尽力回答以下问题... OpenAI
1 7 尽力回答以下问题... OpenAI
2 12 尽力回答以下问题... OpenAI
output_step output \
0 3 我需要找出谁唱了《69的夏天》以及...
1 8 我需要找出Bryan Adams是否结婚...
2 13 现在我知道最终答案。\n最终答案：Bryan Adams从未结过婚。
token_usage_total_tokens token_usage_prompt_tokens \
0 223 189
1 270 242
2 332 314
token_usage_completion_tokens flesch_reading_ease flesch_kincaid_grade \
0 34 91.61 3.8
1 28 94.66 2.7
2 18 81.29 3.7
... difficult_words linsear_write_formula gunning_fog \
0 ... 2 5.75 5.4
1 ... 2 4.25 4.2
2 ... 1 2.50 2.8
text_standard fernandez_huerta szigriszt_pazos gutierrez_polini \
0 3rd and 4th grade 121.07 119.50 54.91
1 4th and 5th grade 124.13 119.20 52.26
2 3rd and 4th grade 115.70 110.84 49.79
crawford gulpease_index osman
0 0.9 72.7 92.16
1 0.7 74.7 84.20
2 0.7 85.4 83.14
[3 rows x 24 columns]}
``````output
无法更新任务 988bd727b0e94a29a3ac0ee526813545 中最后创建的模型，任务状态“已完成”无法被更新
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- 如果使用 `clearml_callback.flush_tracker(..., finish=True)` 关闭 ClearML 回调，则无法再使用该回调。如果要继续记录，请创建一个新的回调。
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