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b3feff302ceb-8 | '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 | https://python.langchain.com/docs/integrations/providers/clearml_tracking |
b3feff302ceb-9 | 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': | https://python.langchain.com/docs/integrations/providers/clearml_tracking |
b3feff302ceb-10 | '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': | https://python.langchain.com/docs/integrations/providers/clearml_tracking |
b3feff302ceb-11 | '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, | https://python.langchain.com/docs/integrations/providers/clearml_tracking |
b3feff302ceb-12 | 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, | https://python.langchain.com/docs/integrations/providers/clearml_tracking |
b3feff302ceb-13 | 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 | https://python.langchain.com/docs/integrations/providers/clearml_tracking |
b3feff302ceb-14 | 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 | https://python.langchain.com/docs/integrations/providers/clearml_tracking |
b3feff302ceb-15 | 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 | https://python.langchain.com/docs/integrations/providers/clearml_tracking |
b3feff302ceb-16 | 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 | https://python.langchain.com/docs/integrations/providers/clearml_tracking |
b3feff302ceb-17 | 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 | https://python.langchain.com/docs/integrations/providers/clearml_tracking |
b3feff302ceb-18 | 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 | https://python.langchain.com/docs/integrations/providers/clearml_tracking |
b3feff302ceb-19 | 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 | https://python.langchain.com/docs/integrations/providers/clearml_tracking |
b3feff302ceb-20 | 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 | https://python.langchain.com/docs/integrations/providers/clearml_tracking |
b3feff302ceb-21 | 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 ... | https://python.langchain.com/docs/integrations/providers/clearml_tracking |
b3feff302ceb-22 | 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 | https://python.langchain.com/docs/integrations/providers/clearml_tracking |
b3feff302ceb-23 | 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 | https://python.langchain.com/docs/integrations/providers/clearml_tracking |
b3feff302ceb-24 | 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 | https://python.langchain.com/docs/integrations/providers/clearml_tracking |
b3feff302ceb-25 | 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 | https://python.langchain.com/docs/integrations/providers/clearml_tracking |
b3feff302ceb-26 | 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 | https://python.langchain.com/docs/integrations/providers/clearml_tracking |
b3feff302ceb-27 | 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 | https://python.langchain.com/docs/integrations/providers/clearml_tracking |
b3feff302ceb-28 | 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 | https://python.langchain.com/docs/integrations/providers/clearml_tracking |
b3feff302ceb-29 | 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 | https://python.langchain.com/docs/integrations/providers/clearml_tracking |
b3feff302ceb-30 | 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 | https://python.langchain.com/docs/integrations/providers/clearml_tracking |
b3feff302ceb-31 | 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 | https://python.langchain.com/docs/integrations/providers/clearml_tracking |
b3feff302ceb-32 | \ 0 162 24 1 162 24 2 162 24 3 162 24 4 162 24 5 162 24 6 162 | https://python.langchain.com/docs/integrations/providers/clearml_tracking |
b3feff302ceb-33 | 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 | https://python.langchain.com/docs/integrations/providers/clearml_tracking |
b3feff302ceb-34 | 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 | https://python.langchain.com/docs/integrations/providers/clearml_tracking |
b3feff302ceb-35 | 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 | https://python.langchain.com/docs/integrations/providers/clearml_tracking |
b3feff302ceb-36 | 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 | https://python.langchain.com/docs/integrations/providers/clearml_tracking |
b3feff302ceb-37 | ... 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 | https://python.langchain.com/docs/integrations/providers/clearml_tracking |
b3feff302ceb-38 | ... 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 | https://python.langchain.com/docs/integrations/providers/clearml_tracking |
b3feff302ceb-39 | 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 | https://python.langchain.com/docs/integrations/providers/clearml_tracking |
b3feff302ceb-40 | 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 | https://python.langchain.com/docs/integrations/providers/clearml_tracking |
b3feff302ceb-41 | 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, | https://python.langchain.com/docs/integrations/providers/clearml_tracking |
b3feff302ceb-42 | 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, | https://python.langchain.com/docs/integrations/providers/clearml_tracking |
b3feff302ceb-43 | 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': | https://python.langchain.com/docs/integrations/providers/clearml_tracking |
b3feff302ceb-44 | {'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 | https://python.langchain.com/docs/integrations/providers/clearml_tracking |
b3feff302ceb-45 | 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 | https://python.langchain.com/docs/integrations/providers/clearml_tracking |
b3feff302ceb-46 | '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 | https://python.langchain.com/docs/integrations/providers/clearml_tracking |
b3feff302ceb-47 | 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', | https://python.langchain.com/docs/integrations/providers/clearml_tracking |
b3feff302ceb-48 | 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': | https://python.langchain.com/docs/integrations/providers/clearml_tracking |
b3feff302ceb-49 | '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_starts': 2, 'llm_ends': 2, 'llm_streams': 0, 'tool_starts': 4, 'tool_ends': 2, 'agent_ends': 0} {'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 | https://python.langchain.com/docs/integrations/providers/clearml_tracking |
b3feff302ceb-50 | 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:'} {'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, | https://python.langchain.com/docs/integrations/providers/clearml_tracking |
b3feff302ceb-51 | 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} I now know the final answer. Final Answer: Bryan Adams has never been married. {'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, | https://python.langchain.com/docs/integrations/providers/clearml_tracking |
b3feff302ceb-52 | 1, 'chain_ends': 0, 'llm_starts': 3, 'llm_ends': 3, 'llm_streams': 0, 'tool_starts': 4, 'tool_ends': 2, 'agent_ends': 1} > Finished chain. {'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} {'action_records': action name step starts ends errors text_ctr \ 0 on_llm_start OpenAI 1 1 0 0 0 1 on_llm_start OpenAI 1 1 0 0 0 2 on_llm_start OpenAI 1 1 0 0 0 3 | https://python.langchain.com/docs/integrations/providers/clearml_tracking |
b3feff302ceb-53 | 0 3 on_llm_start OpenAI 1 1 0 0 0 4 on_llm_start OpenAI 1 1 0 0 0 .. ... ... ... ... ... ... ... 66 on_tool_end NaN 11 7 4 0 0 67 on_llm_start OpenAI 12 8 4 0 0 68 on_llm_end NaN 13 8 5 0 0 69 on_agent_finish NaN 14 8 6 0 | https://python.langchain.com/docs/integrations/providers/clearml_tracking |
b3feff302ceb-54 | 6 0 0 70 on_chain_end NaN 15 8 7 0 0 chain_starts chain_ends llm_starts ... gulpease_index osman input \ 0 0 0 1 ... NaN NaN NaN 1 0 0 1 ... NaN NaN NaN 2 0 0 1 ... NaN NaN NaN 3 0 0 1 ... NaN NaN NaN | https://python.langchain.com/docs/integrations/providers/clearml_tracking |
b3feff302ceb-55 | NaN NaN NaN 4 0 0 1 ... NaN NaN NaN .. ... ... ... ... ... ... ... 66 1 0 2 ... NaN NaN NaN 67 1 0 3 ... NaN NaN NaN 68 1 0 3 ... 85.4 83.14 NaN 69 1 0 3 | https://python.langchain.com/docs/integrations/providers/clearml_tracking |
b3feff302ceb-56 | 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 | https://python.langchain.com/docs/integrations/providers/clearml_tracking |
b3feff302ceb-57 | NaN 3 NaN NaN NaN 4 NaN NaN NaN .. ... ... ... 66 NaN NaN NaN 67 NaN NaN NaN 68 NaN NaN | https://python.langchain.com/docs/integrations/providers/clearml_tracking |
b3feff302ceb-58 | NaN 69 NaN NaN I now know the final answer.\nFinal Answer: B... 70 NaN NaN NaN input_str description output \ 0 NaN NaN NaN 1 NaN NaN NaN 2 NaN NaN | https://python.langchain.com/docs/integrations/providers/clearml_tracking |
b3feff302ceb-59 | NaN 3 NaN NaN NaN 4 NaN NaN NaN .. ... ... ... 66 NaN NaN Bryan Adams has never married. In the 1990s, h... 67 NaN NaN NaN 68 NaN | https://python.langchain.com/docs/integrations/providers/clearml_tracking |
b3feff302ceb-60 | NaN 68 NaN NaN NaN 69 NaN NaN Bryan Adams has never been married. 70 NaN NaN NaN outputs 0 NaN 1 NaN 2 NaN 3 | https://python.langchain.com/docs/integrations/providers/clearml_tracking |
b3feff302ceb-61 | NaN 4 NaN .. ... 66 NaN 67 NaN 68 NaN 69 NaN 70 Bryan Adams has never been married. [71 rows x 47 columns], 'session_analysis': prompt_step prompts name \ 0 2 Answer the following questions as best you can... OpenAI | https://python.langchain.com/docs/integrations/providers/clearml_tracking |
b3feff302ceb-62 | 2 Answer the following questions as best you can... OpenAI 1 7 Answer the following questions as best you can... OpenAI 2 12 Answer the following questions as best you can... OpenAI output_step output \ 0 3 I need to find out who sang summer of 69 and ... 1 8 I need to find out who Bryan Adams is married... 2 13 I now know the final answer.\nFinal Answer: B... token_usage_total_tokens token_usage_prompt_tokens \ 0 223 189 1 270 242 2 | https://python.langchain.com/docs/integrations/providers/clearml_tracking |
b3feff302ceb-63 | 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 | https://python.langchain.com/docs/integrations/providers/clearml_tracking |
b3feff302ceb-64 | 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 | https://python.langchain.com/docs/integrations/providers/clearml_tracking |
b3feff302ceb-65 | 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]} Could not update last created model in Task 988bd727b0e94a29a3ac0ee526813545, Task status 'completed' cannot be updatedTips and Next Steps​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!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.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!PreviousClarifaiNextCnosDBInstallation and SetupGetting API CredentialsCallbacksScenario 1: Just an LLMScenario 2: Creating an agent with toolsTips and Next StepsCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright © 2023 LangChain, Inc. | https://python.langchain.com/docs/integrations/providers/clearml_tracking |
8f4b81787d23-0 | YouTube | 🦜�🔗 Langchain | https://python.langchain.com/docs/integrations/providers/youtube |
8f4b81787d23-1 | Skip to main content🦜�🔗 LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKIntegrationsCallbacksChat modelsDocument loadersDocument transformersLLMsMemoryRetrieversText embedding modelsAgent toolkitsToolsVector storesGrouped by providerWandB TracingAI21 LabsAimAirbyteAirtableAleph AlphaAlibaba Cloud OpensearchAmazon API GatewayAnalyticDBAnnoyAnyscaleApifyArangoDBArgillaArthurArxivAtlasDBAwaDBAWS S3 DirectoryAZLyricsAzure Blob StorageAzure Cognitive SearchAzure OpenAIBananaBasetenBeamBedrockBiliBiliBlackboardBrave SearchCassandraCerebriumAIChaindeskChromaClarifaiClearMLCnosDBCohereCollege ConfidentialCometConfluenceC TransformersDatabricksDatadog TracingDatadog LogsDataForSEODeepInfraDeep LakeDiffbotDiscordDocugamiDuckDBElasticsearchEverNoteFacebook ChatFigmaFlyteForefrontAIGitGitBookGoldenGoogle BigQueryGoogle Cloud StorageGoogle DriveGoogle SearchGoogle SerperGooseAIGPT4AllGraphsignalGrobidGutenbergHacker NewsHazy ResearchHeliconeHologresHugging FaceiFixitIMSDbInfinoJinaLanceDBLangChain Decorators ✨Llama.cppMarqoMediaWikiDumpMetalMicrosoft OneDriveMicrosoft PowerPointMicrosoft WordMilvusMLflow AI GatewayMLflowModalModelScopeModern TreasuryMomentoMotherduckMyScaleNLPCloudNotion DBObsidianOpenAIOpenLLMOpenSearchOpenWeatherMapPetalsPGVectorPineconePipelineAIPortkeyPredibasePrediction GuardPromptLayerPsychicQdrantRay ServeRebuffRedditRedisReplicateRoamRocksetRunhouseRWKV-4SageMaker EndpointSearxNG Search APISerpAPIShale | https://python.langchain.com/docs/integrations/providers/youtube |
8f4b81787d23-2 | EndpointSearxNG Search APISerpAPIShale ProtocolSingleStoreDBscikit-learnSlackspaCySpreedlyStarRocksStochasticAIStripeTairTelegramTigris2MarkdownTrelloTruLensTwitterTypesenseUnstructuredVectaraVespaWeights & BiasesWeatherWeaviateWhatsAppWhyLabsWikipediaWolfram AlphaWriterYeager.aiYouTubeZepZillizIntegrationsGrouped by providerYouTubeOn this pageYouTubeYouTube is an online video sharing and social media platform by Google. | https://python.langchain.com/docs/integrations/providers/youtube |
8f4b81787d23-3 | We download the YouTube transcripts and video information.Installation and Setup​pip install youtube-transcript-apipip install pytubeSee a usage example.Document Loader​See a usage example.from langchain.document_loaders import YoutubeLoaderfrom langchain.document_loaders import GoogleApiYoutubeLoaderPreviousYeager.aiNextZepInstallation and SetupDocument LoaderCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright © 2023 LangChain, Inc. | https://python.langchain.com/docs/integrations/providers/youtube |
e32cbaa4d442-0 | LanceDB | 🦜�🔗 Langchain | https://python.langchain.com/docs/integrations/providers/lancedb |
e32cbaa4d442-1 | Skip to main content🦜�🔗 LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKIntegrationsCallbacksChat modelsDocument loadersDocument transformersLLMsMemoryRetrieversText embedding modelsAgent toolkitsToolsVector storesGrouped by providerWandB TracingAI21 LabsAimAirbyteAirtableAleph AlphaAlibaba Cloud OpensearchAmazon API GatewayAnalyticDBAnnoyAnyscaleApifyArangoDBArgillaArthurArxivAtlasDBAwaDBAWS S3 DirectoryAZLyricsAzure Blob StorageAzure Cognitive SearchAzure OpenAIBananaBasetenBeamBedrockBiliBiliBlackboardBrave SearchCassandraCerebriumAIChaindeskChromaClarifaiClearMLCnosDBCohereCollege ConfidentialCometConfluenceC TransformersDatabricksDatadog TracingDatadog LogsDataForSEODeepInfraDeep LakeDiffbotDiscordDocugamiDuckDBElasticsearchEverNoteFacebook ChatFigmaFlyteForefrontAIGitGitBookGoldenGoogle BigQueryGoogle Cloud StorageGoogle DriveGoogle SearchGoogle SerperGooseAIGPT4AllGraphsignalGrobidGutenbergHacker NewsHazy ResearchHeliconeHologresHugging FaceiFixitIMSDbInfinoJinaLanceDBLangChain Decorators ✨Llama.cppMarqoMediaWikiDumpMetalMicrosoft OneDriveMicrosoft PowerPointMicrosoft WordMilvusMLflow AI GatewayMLflowModalModelScopeModern TreasuryMomentoMotherduckMyScaleNLPCloudNotion DBObsidianOpenAIOpenLLMOpenSearchOpenWeatherMapPetalsPGVectorPineconePipelineAIPortkeyPredibasePrediction GuardPromptLayerPsychicQdrantRay ServeRebuffRedditRedisReplicateRoamRocksetRunhouseRWKV-4SageMaker EndpointSearxNG Search APISerpAPIShale | https://python.langchain.com/docs/integrations/providers/lancedb |
e32cbaa4d442-2 | EndpointSearxNG Search APISerpAPIShale ProtocolSingleStoreDBscikit-learnSlackspaCySpreedlyStarRocksStochasticAIStripeTairTelegramTigris2MarkdownTrelloTruLensTwitterTypesenseUnstructuredVectaraVespaWeights & BiasesWeatherWeaviateWhatsAppWhyLabsWikipediaWolfram AlphaWriterYeager.aiYouTubeZepZillizIntegrationsGrouped by providerLanceDBOn this pageLanceDBThis page covers how to use LanceDB within LangChain. | https://python.langchain.com/docs/integrations/providers/lancedb |
e32cbaa4d442-3 | It is broken into two parts: installation and setup, and then references to specific LanceDB wrappers.Installation and Setup​Install the Python SDK with pip install lancedbWrappers​VectorStore​There exists a wrapper around LanceDB databases, allowing you to use it as a vectorstore,
whether for semantic search or example selection.To import this vectorstore:from langchain.vectorstores import LanceDBFor a more detailed walkthrough of the LanceDB wrapper, see this notebookPreviousJinaNextLangChain Decorators ✨Installation and SetupWrappersVectorStoreCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright © 2023 LangChain, Inc. | https://python.langchain.com/docs/integrations/providers/lancedb |
e1169fb7ff9a-0 | Chroma | 🦜�🔗 Langchain | https://python.langchain.com/docs/integrations/providers/chroma |
e1169fb7ff9a-1 | Skip to main content🦜�🔗 LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKIntegrationsCallbacksChat modelsDocument loadersDocument transformersLLMsMemoryRetrieversText embedding modelsAgent toolkitsToolsVector storesGrouped by providerWandB TracingAI21 LabsAimAirbyteAirtableAleph AlphaAlibaba Cloud OpensearchAmazon API GatewayAnalyticDBAnnoyAnyscaleApifyArangoDBArgillaArthurArxivAtlasDBAwaDBAWS S3 DirectoryAZLyricsAzure Blob StorageAzure Cognitive SearchAzure OpenAIBananaBasetenBeamBedrockBiliBiliBlackboardBrave SearchCassandraCerebriumAIChaindeskChromaClarifaiClearMLCnosDBCohereCollege ConfidentialCometConfluenceC TransformersDatabricksDatadog TracingDatadog LogsDataForSEODeepInfraDeep LakeDiffbotDiscordDocugamiDuckDBElasticsearchEverNoteFacebook ChatFigmaFlyteForefrontAIGitGitBookGoldenGoogle BigQueryGoogle Cloud StorageGoogle DriveGoogle SearchGoogle SerperGooseAIGPT4AllGraphsignalGrobidGutenbergHacker NewsHazy ResearchHeliconeHologresHugging FaceiFixitIMSDbInfinoJinaLanceDBLangChain Decorators ✨Llama.cppMarqoMediaWikiDumpMetalMicrosoft OneDriveMicrosoft PowerPointMicrosoft WordMilvusMLflow AI GatewayMLflowModalModelScopeModern TreasuryMomentoMotherduckMyScaleNLPCloudNotion DBObsidianOpenAIOpenLLMOpenSearchOpenWeatherMapPetalsPGVectorPineconePipelineAIPortkeyPredibasePrediction GuardPromptLayerPsychicQdrantRay ServeRebuffRedditRedisReplicateRoamRocksetRunhouseRWKV-4SageMaker EndpointSearxNG Search APISerpAPIShale | https://python.langchain.com/docs/integrations/providers/chroma |
e1169fb7ff9a-2 | EndpointSearxNG Search APISerpAPIShale ProtocolSingleStoreDBscikit-learnSlackspaCySpreedlyStarRocksStochasticAIStripeTairTelegramTigris2MarkdownTrelloTruLensTwitterTypesenseUnstructuredVectaraVespaWeights & BiasesWeatherWeaviateWhatsAppWhyLabsWikipediaWolfram AlphaWriterYeager.aiYouTubeZepZillizIntegrationsGrouped by providerChromaOn this pageChromaChroma is a database for building AI applications with embeddings.Installation and Setup​pip install chromadbVectorStore​There exists a wrapper around Chroma vector databases, allowing you to use it as a vectorstore, | https://python.langchain.com/docs/integrations/providers/chroma |
e1169fb7ff9a-3 | whether for semantic search or example selection.from langchain.vectorstores import ChromaFor a more detailed walkthrough of the Chroma wrapper, see this notebookRetriever​See a usage example.from langchain.retrievers import SelfQueryRetrieverPreviousChaindeskNextClarifaiInstallation and SetupVectorStoreRetrieverCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright © 2023 LangChain, Inc. | https://python.langchain.com/docs/integrations/providers/chroma |
28c8be21c115-0 | Microsoft Word | 🦜�🔗 Langchain | https://python.langchain.com/docs/integrations/providers/microsoft_word |
28c8be21c115-1 | Skip to main content🦜�🔗 LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKIntegrationsCallbacksChat modelsDocument loadersDocument transformersLLMsMemoryRetrieversText embedding modelsAgent toolkitsToolsVector storesGrouped by providerWandB TracingAI21 LabsAimAirbyteAirtableAleph AlphaAlibaba Cloud OpensearchAmazon API GatewayAnalyticDBAnnoyAnyscaleApifyArangoDBArgillaArthurArxivAtlasDBAwaDBAWS S3 DirectoryAZLyricsAzure Blob StorageAzure Cognitive SearchAzure OpenAIBananaBasetenBeamBedrockBiliBiliBlackboardBrave SearchCassandraCerebriumAIChaindeskChromaClarifaiClearMLCnosDBCohereCollege ConfidentialCometConfluenceC TransformersDatabricksDatadog TracingDatadog LogsDataForSEODeepInfraDeep LakeDiffbotDiscordDocugamiDuckDBElasticsearchEverNoteFacebook ChatFigmaFlyteForefrontAIGitGitBookGoldenGoogle BigQueryGoogle Cloud StorageGoogle DriveGoogle SearchGoogle SerperGooseAIGPT4AllGraphsignalGrobidGutenbergHacker NewsHazy ResearchHeliconeHologresHugging FaceiFixitIMSDbInfinoJinaLanceDBLangChain Decorators ✨Llama.cppMarqoMediaWikiDumpMetalMicrosoft OneDriveMicrosoft PowerPointMicrosoft WordMilvusMLflow AI GatewayMLflowModalModelScopeModern TreasuryMomentoMotherduckMyScaleNLPCloudNotion DBObsidianOpenAIOpenLLMOpenSearchOpenWeatherMapPetalsPGVectorPineconePipelineAIPortkeyPredibasePrediction GuardPromptLayerPsychicQdrantRay ServeRebuffRedditRedisReplicateRoamRocksetRunhouseRWKV-4SageMaker EndpointSearxNG Search APISerpAPIShale | https://python.langchain.com/docs/integrations/providers/microsoft_word |
28c8be21c115-2 | EndpointSearxNG Search APISerpAPIShale ProtocolSingleStoreDBscikit-learnSlackspaCySpreedlyStarRocksStochasticAIStripeTairTelegramTigris2MarkdownTrelloTruLensTwitterTypesenseUnstructuredVectaraVespaWeights & BiasesWeatherWeaviateWhatsAppWhyLabsWikipediaWolfram AlphaWriterYeager.aiYouTubeZepZillizIntegrationsGrouped by providerMicrosoft WordOn this pageMicrosoft WordMicrosoft Word is a word processor developed by Microsoft.Installation and Setup​There isn't any special setup for it.Document Loader​See a usage example.from langchain.document_loaders import UnstructuredWordDocumentLoaderPreviousMicrosoft PowerPointNextMilvusInstallation and SetupDocument LoaderCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright © 2023 LangChain, Inc. | https://python.langchain.com/docs/integrations/providers/microsoft_word |
8c7ded6c091e-0 | Bedrock | 🦜�🔗 Langchain | https://python.langchain.com/docs/integrations/providers/bedrock |
8c7ded6c091e-1 | Skip to main content🦜�🔗 LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKIntegrationsCallbacksChat modelsDocument loadersDocument transformersLLMsMemoryRetrieversText embedding modelsAgent toolkitsToolsVector storesGrouped by providerWandB TracingAI21 LabsAimAirbyteAirtableAleph AlphaAlibaba Cloud OpensearchAmazon API GatewayAnalyticDBAnnoyAnyscaleApifyArangoDBArgillaArthurArxivAtlasDBAwaDBAWS S3 DirectoryAZLyricsAzure Blob StorageAzure Cognitive SearchAzure OpenAIBananaBasetenBeamBedrockBiliBiliBlackboardBrave SearchCassandraCerebriumAIChaindeskChromaClarifaiClearMLCnosDBCohereCollege ConfidentialCometConfluenceC TransformersDatabricksDatadog TracingDatadog LogsDataForSEODeepInfraDeep LakeDiffbotDiscordDocugamiDuckDBElasticsearchEverNoteFacebook ChatFigmaFlyteForefrontAIGitGitBookGoldenGoogle BigQueryGoogle Cloud StorageGoogle DriveGoogle SearchGoogle SerperGooseAIGPT4AllGraphsignalGrobidGutenbergHacker NewsHazy ResearchHeliconeHologresHugging FaceiFixitIMSDbInfinoJinaLanceDBLangChain Decorators ✨Llama.cppMarqoMediaWikiDumpMetalMicrosoft OneDriveMicrosoft PowerPointMicrosoft WordMilvusMLflow AI GatewayMLflowModalModelScopeModern TreasuryMomentoMotherduckMyScaleNLPCloudNotion DBObsidianOpenAIOpenLLMOpenSearchOpenWeatherMapPetalsPGVectorPineconePipelineAIPortkeyPredibasePrediction GuardPromptLayerPsychicQdrantRay ServeRebuffRedditRedisReplicateRoamRocksetRunhouseRWKV-4SageMaker EndpointSearxNG Search APISerpAPIShale | https://python.langchain.com/docs/integrations/providers/bedrock |
8c7ded6c091e-2 | EndpointSearxNG Search APISerpAPIShale ProtocolSingleStoreDBscikit-learnSlackspaCySpreedlyStarRocksStochasticAIStripeTairTelegramTigris2MarkdownTrelloTruLensTwitterTypesenseUnstructuredVectaraVespaWeights & BiasesWeatherWeaviateWhatsAppWhyLabsWikipediaWolfram AlphaWriterYeager.aiYouTubeZepZillizIntegrationsGrouped by providerBedrockOn this pageBedrockAmazon Bedrock is a fully managed service that makes FMs from leading AI startups and Amazon available via an API, so you can choose from a wide range of FMs to find the model that is best suited for your use case.Installation and Setup​pip install boto3LLM​See a usage example.from langchain import BedrockText Embedding Models​See a usage example.from langchain.embeddings import BedrockEmbeddingsPreviousBeamNextBiliBiliInstallation and SetupLLMText Embedding ModelsCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright © 2023 LangChain, Inc. | https://python.langchain.com/docs/integrations/providers/bedrock |
2235ce4c0d4d-0 | WhyLabs | 🦜�🔗 Langchain | https://python.langchain.com/docs/integrations/providers/whylabs_profiling |
2235ce4c0d4d-1 | Skip to main content🦜�🔗 LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKIntegrationsCallbacksChat modelsDocument loadersDocument transformersLLMsMemoryRetrieversText embedding modelsAgent toolkitsToolsVector storesGrouped by providerWandB TracingAI21 LabsAimAirbyteAirtableAleph AlphaAlibaba Cloud OpensearchAmazon API GatewayAnalyticDBAnnoyAnyscaleApifyArangoDBArgillaArthurArxivAtlasDBAwaDBAWS S3 DirectoryAZLyricsAzure Blob StorageAzure Cognitive SearchAzure OpenAIBananaBasetenBeamBedrockBiliBiliBlackboardBrave SearchCassandraCerebriumAIChaindeskChromaClarifaiClearMLCnosDBCohereCollege ConfidentialCometConfluenceC TransformersDatabricksDatadog TracingDatadog LogsDataForSEODeepInfraDeep LakeDiffbotDiscordDocugamiDuckDBElasticsearchEverNoteFacebook ChatFigmaFlyteForefrontAIGitGitBookGoldenGoogle BigQueryGoogle Cloud StorageGoogle DriveGoogle SearchGoogle SerperGooseAIGPT4AllGraphsignalGrobidGutenbergHacker NewsHazy ResearchHeliconeHologresHugging FaceiFixitIMSDbInfinoJinaLanceDBLangChain Decorators ✨Llama.cppMarqoMediaWikiDumpMetalMicrosoft OneDriveMicrosoft PowerPointMicrosoft WordMilvusMLflow AI GatewayMLflowModalModelScopeModern TreasuryMomentoMotherduckMyScaleNLPCloudNotion DBObsidianOpenAIOpenLLMOpenSearchOpenWeatherMapPetalsPGVectorPineconePipelineAIPortkeyPredibasePrediction GuardPromptLayerPsychicQdrantRay ServeRebuffRedditRedisReplicateRoamRocksetRunhouseRWKV-4SageMaker EndpointSearxNG Search APISerpAPIShale | https://python.langchain.com/docs/integrations/providers/whylabs_profiling |
2235ce4c0d4d-2 | EndpointSearxNG Search APISerpAPIShale ProtocolSingleStoreDBscikit-learnSlackspaCySpreedlyStarRocksStochasticAIStripeTairTelegramTigris2MarkdownTrelloTruLensTwitterTypesenseUnstructuredVectaraVespaWeights & BiasesWeatherWeaviateWhatsAppWhyLabsWikipediaWolfram AlphaWriterYeager.aiYouTubeZepZillizIntegrationsGrouped by providerWhyLabsOn this pageWhyLabsWhyLabs is an observability platform designed to monitor data pipelines and ML applications for data quality regressions, data drift, and model performance degradation. Built on top of an open-source package called whylogs, the platform enables Data Scientists and Engineers to:Set up in minutes: Begin generating statistical profiles of any dataset using whylogs, the lightweight open-source library.Upload dataset profiles to the WhyLabs platform for centralized and customizable monitoring/alerting of dataset features as well as model inputs, outputs, and performance.Integrate seamlessly: interoperable with any data pipeline, ML infrastructure, or framework. Generate real-time insights into your existing data flow. See more about our integrations here.Scale to terabytes: handle your large-scale data, keeping compute requirements low. Integrate with either batch or streaming data pipelines.Maintain data privacy: WhyLabs relies statistical profiles created via whylogs so your actual data never leaves your environment! | https://python.langchain.com/docs/integrations/providers/whylabs_profiling |
2235ce4c0d4d-3 | Enable observability to detect inputs and LLM issues faster, deliver continuous improvements, and avoid costly incidents.Installation and Setup​%pip install langkit openai langchainMake sure to set the required API keys and config required to send telemetry to WhyLabs:WhyLabs API Key: https://whylabs.ai/whylabs-free-sign-upOrg and Dataset https://docs.whylabs.ai/docs/whylabs-onboardingOpenAI: https://platform.openai.com/account/api-keysThen you can set them like this:import osos.environ["OPENAI_API_KEY"] = ""os.environ["WHYLABS_DEFAULT_ORG_ID"] = ""os.environ["WHYLABS_DEFAULT_DATASET_ID"] = ""os.environ["WHYLABS_API_KEY"] = ""Note: the callback supports directly passing in these variables to the callback, when no auth is directly passed in it will default to the environment. Passing in auth directly allows for writing profiles to multiple projects or organizations in WhyLabs.Callbacks​Here's a single LLM integration with OpenAI, which will log various out of the box metrics and send telemetry to WhyLabs for monitoring.from langchain.callbacks import WhyLabsCallbackHandlerfrom langchain.llms import OpenAIwhylabs = WhyLabsCallbackHandler.from_params()llm = OpenAI(temperature=0, callbacks=[whylabs])result = llm.generate(["Hello, World!"])print(result) generations=[[Generation(text="\n\nMy name is John and I'm excited to learn more about programming.", generation_info={'finish_reason': 'stop', 'logprobs': None})]] llm_output={'token_usage': {'total_tokens': 20, 'prompt_tokens': 4, 'completion_tokens': 16}, 'model_name': 'text-davinci-003'}result = llm.generate( [ | https://python.langchain.com/docs/integrations/providers/whylabs_profiling |
2235ce4c0d4d-4 | = llm.generate( [ "Can you give me 3 SSNs so I can understand the format?", "Can you give me 3 fake email addresses?", "Can you give me 3 fake US mailing addresses?", ])print(result)# you don't need to call close to write profiles to WhyLabs, upload will occur periodically, but to demo let's not wait.whylabs.close() generations=[[Generation(text='\n\n1. 123-45-6789\n2. 987-65-4321\n3. 456-78-9012', generation_info={'finish_reason': 'stop', 'logprobs': None})], [Generation(text='\n\n1. [email protected]\n2. [email protected]\n3. [email protected]', generation_info={'finish_reason': 'stop', 'logprobs': None})], [Generation(text='\n\n1. 123 Main Street, Anytown, USA 12345\n2. 456 Elm Street, Nowhere, USA 54321\n3. 789 Pine Avenue, Somewhere, USA 98765', generation_info={'finish_reason': 'stop', 'logprobs': None})]] llm_output={'token_usage': {'total_tokens': 137, 'prompt_tokens': 33, 'completion_tokens': 104}, 'model_name': 'text-davinci-003'}PreviousWhatsAppNextWikipediaInstallation and SetupCallbacksCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright © 2023 LangChain, Inc. | https://python.langchain.com/docs/integrations/providers/whylabs_profiling |
e886cf7b67bc-0 | Roam | 🦜�🔗 Langchain | https://python.langchain.com/docs/integrations/providers/roam |
e886cf7b67bc-1 | Skip to main content🦜�🔗 LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKIntegrationsCallbacksChat modelsDocument loadersDocument transformersLLMsMemoryRetrieversText embedding modelsAgent toolkitsToolsVector storesGrouped by providerWandB TracingAI21 LabsAimAirbyteAirtableAleph AlphaAlibaba Cloud OpensearchAmazon API GatewayAnalyticDBAnnoyAnyscaleApifyArangoDBArgillaArthurArxivAtlasDBAwaDBAWS S3 DirectoryAZLyricsAzure Blob StorageAzure Cognitive SearchAzure OpenAIBananaBasetenBeamBedrockBiliBiliBlackboardBrave SearchCassandraCerebriumAIChaindeskChromaClarifaiClearMLCnosDBCohereCollege ConfidentialCometConfluenceC TransformersDatabricksDatadog TracingDatadog LogsDataForSEODeepInfraDeep LakeDiffbotDiscordDocugamiDuckDBElasticsearchEverNoteFacebook ChatFigmaFlyteForefrontAIGitGitBookGoldenGoogle BigQueryGoogle Cloud StorageGoogle DriveGoogle SearchGoogle SerperGooseAIGPT4AllGraphsignalGrobidGutenbergHacker NewsHazy ResearchHeliconeHologresHugging FaceiFixitIMSDbInfinoJinaLanceDBLangChain Decorators ✨Llama.cppMarqoMediaWikiDumpMetalMicrosoft OneDriveMicrosoft PowerPointMicrosoft WordMilvusMLflow AI GatewayMLflowModalModelScopeModern TreasuryMomentoMotherduckMyScaleNLPCloudNotion DBObsidianOpenAIOpenLLMOpenSearchOpenWeatherMapPetalsPGVectorPineconePipelineAIPortkeyPredibasePrediction GuardPromptLayerPsychicQdrantRay ServeRebuffRedditRedisReplicateRoamRocksetRunhouseRWKV-4SageMaker EndpointSearxNG Search APISerpAPIShale | https://python.langchain.com/docs/integrations/providers/roam |
e886cf7b67bc-2 | EndpointSearxNG Search APISerpAPIShale ProtocolSingleStoreDBscikit-learnSlackspaCySpreedlyStarRocksStochasticAIStripeTairTelegramTigris2MarkdownTrelloTruLensTwitterTypesenseUnstructuredVectaraVespaWeights & BiasesWeatherWeaviateWhatsAppWhyLabsWikipediaWolfram AlphaWriterYeager.aiYouTubeZepZillizIntegrationsGrouped by providerRoamOn this pageRoamROAM is a note-taking tool for networked thought, designed to create a personal knowledge base.Installation and Setup​There isn't any special setup for it.Document Loader​See a usage example.from langchain.document_loaders import RoamLoaderPreviousReplicateNextRocksetInstallation and SetupDocument LoaderCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright © 2023 LangChain, Inc. | https://python.langchain.com/docs/integrations/providers/roam |
ff3c85879d5e-0 | AZLyrics | 🦜�🔗 Langchain | https://python.langchain.com/docs/integrations/providers/azlyrics |
ff3c85879d5e-1 | Skip to main content🦜�🔗 LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKIntegrationsCallbacksChat modelsDocument loadersDocument transformersLLMsMemoryRetrieversText embedding modelsAgent toolkitsToolsVector storesGrouped by providerWandB TracingAI21 LabsAimAirbyteAirtableAleph AlphaAlibaba Cloud OpensearchAmazon API GatewayAnalyticDBAnnoyAnyscaleApifyArangoDBArgillaArthurArxivAtlasDBAwaDBAWS S3 DirectoryAZLyricsAzure Blob StorageAzure Cognitive SearchAzure OpenAIBananaBasetenBeamBedrockBiliBiliBlackboardBrave SearchCassandraCerebriumAIChaindeskChromaClarifaiClearMLCnosDBCohereCollege ConfidentialCometConfluenceC TransformersDatabricksDatadog TracingDatadog LogsDataForSEODeepInfraDeep LakeDiffbotDiscordDocugamiDuckDBElasticsearchEverNoteFacebook ChatFigmaFlyteForefrontAIGitGitBookGoldenGoogle BigQueryGoogle Cloud StorageGoogle DriveGoogle SearchGoogle SerperGooseAIGPT4AllGraphsignalGrobidGutenbergHacker NewsHazy ResearchHeliconeHologresHugging FaceiFixitIMSDbInfinoJinaLanceDBLangChain Decorators ✨Llama.cppMarqoMediaWikiDumpMetalMicrosoft OneDriveMicrosoft PowerPointMicrosoft WordMilvusMLflow AI GatewayMLflowModalModelScopeModern TreasuryMomentoMotherduckMyScaleNLPCloudNotion DBObsidianOpenAIOpenLLMOpenSearchOpenWeatherMapPetalsPGVectorPineconePipelineAIPortkeyPredibasePrediction GuardPromptLayerPsychicQdrantRay ServeRebuffRedditRedisReplicateRoamRocksetRunhouseRWKV-4SageMaker EndpointSearxNG Search APISerpAPIShale | https://python.langchain.com/docs/integrations/providers/azlyrics |
ff3c85879d5e-2 | EndpointSearxNG Search APISerpAPIShale ProtocolSingleStoreDBscikit-learnSlackspaCySpreedlyStarRocksStochasticAIStripeTairTelegramTigris2MarkdownTrelloTruLensTwitterTypesenseUnstructuredVectaraVespaWeights & BiasesWeatherWeaviateWhatsAppWhyLabsWikipediaWolfram AlphaWriterYeager.aiYouTubeZepZillizIntegrationsGrouped by providerAZLyricsOn this pageAZLyricsAZLyrics is a large, legal, every day growing collection of lyrics.Installation and Setup​There isn't any special setup for it.Document Loader​See a usage example.from langchain.document_loaders import AZLyricsLoaderPreviousAWS S3 DirectoryNextAzure Blob StorageInstallation and SetupDocument LoaderCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright © 2023 LangChain, Inc. | https://python.langchain.com/docs/integrations/providers/azlyrics |
a4cba2dd4ff0-0 | DeepInfra | 🦜�🔗 Langchain | https://python.langchain.com/docs/integrations/providers/deepinfra |
a4cba2dd4ff0-1 | Skip to main content🦜�🔗 LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKIntegrationsCallbacksChat modelsDocument loadersDocument transformersLLMsMemoryRetrieversText embedding modelsAgent toolkitsToolsVector storesGrouped by providerWandB TracingAI21 LabsAimAirbyteAirtableAleph AlphaAlibaba Cloud OpensearchAmazon API GatewayAnalyticDBAnnoyAnyscaleApifyArangoDBArgillaArthurArxivAtlasDBAwaDBAWS S3 DirectoryAZLyricsAzure Blob StorageAzure Cognitive SearchAzure OpenAIBananaBasetenBeamBedrockBiliBiliBlackboardBrave SearchCassandraCerebriumAIChaindeskChromaClarifaiClearMLCnosDBCohereCollege ConfidentialCometConfluenceC TransformersDatabricksDatadog TracingDatadog LogsDataForSEODeepInfraDeep LakeDiffbotDiscordDocugamiDuckDBElasticsearchEverNoteFacebook ChatFigmaFlyteForefrontAIGitGitBookGoldenGoogle BigQueryGoogle Cloud StorageGoogle DriveGoogle SearchGoogle SerperGooseAIGPT4AllGraphsignalGrobidGutenbergHacker NewsHazy ResearchHeliconeHologresHugging FaceiFixitIMSDbInfinoJinaLanceDBLangChain Decorators ✨Llama.cppMarqoMediaWikiDumpMetalMicrosoft OneDriveMicrosoft PowerPointMicrosoft WordMilvusMLflow AI GatewayMLflowModalModelScopeModern TreasuryMomentoMotherduckMyScaleNLPCloudNotion DBObsidianOpenAIOpenLLMOpenSearchOpenWeatherMapPetalsPGVectorPineconePipelineAIPortkeyPredibasePrediction GuardPromptLayerPsychicQdrantRay ServeRebuffRedditRedisReplicateRoamRocksetRunhouseRWKV-4SageMaker EndpointSearxNG Search APISerpAPIShale | https://python.langchain.com/docs/integrations/providers/deepinfra |
a4cba2dd4ff0-2 | EndpointSearxNG Search APISerpAPIShale ProtocolSingleStoreDBscikit-learnSlackspaCySpreedlyStarRocksStochasticAIStripeTairTelegramTigris2MarkdownTrelloTruLensTwitterTypesenseUnstructuredVectaraVespaWeights & BiasesWeatherWeaviateWhatsAppWhyLabsWikipediaWolfram AlphaWriterYeager.aiYouTubeZepZillizIntegrationsGrouped by providerDeepInfraOn this pageDeepInfraThis page covers how to use the DeepInfra ecosystem within LangChain. | https://python.langchain.com/docs/integrations/providers/deepinfra |
a4cba2dd4ff0-3 | It is broken into two parts: installation and setup, and then references to specific DeepInfra wrappers.Installation and Setup​Get your DeepInfra api key from this link here.Get an DeepInfra api key and set it as an environment variable (DEEPINFRA_API_TOKEN)Available Models​DeepInfra provides a range of Open Source LLMs ready for deployment.
You can list supported models here.
google/flan* models can be viewed here.You can view a list of request and response parameters hereWrappers​LLM​There exists an DeepInfra LLM wrapper, which you can access withfrom langchain.llms import DeepInfraPreviousDataForSEONextDeep LakeInstallation and SetupAvailable ModelsWrappersLLMCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright © 2023 LangChain, Inc. | https://python.langchain.com/docs/integrations/providers/deepinfra |
caf2077db0ea-0 | Obsidian | 🦜�🔗 Langchain | https://python.langchain.com/docs/integrations/providers/obsidian |
caf2077db0ea-1 | Skip to main content🦜�🔗 LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKIntegrationsCallbacksChat modelsDocument loadersDocument transformersLLMsMemoryRetrieversText embedding modelsAgent toolkitsToolsVector storesGrouped by providerWandB TracingAI21 LabsAimAirbyteAirtableAleph AlphaAlibaba Cloud OpensearchAmazon API GatewayAnalyticDBAnnoyAnyscaleApifyArangoDBArgillaArthurArxivAtlasDBAwaDBAWS S3 DirectoryAZLyricsAzure Blob StorageAzure Cognitive SearchAzure OpenAIBananaBasetenBeamBedrockBiliBiliBlackboardBrave SearchCassandraCerebriumAIChaindeskChromaClarifaiClearMLCnosDBCohereCollege ConfidentialCometConfluenceC TransformersDatabricksDatadog TracingDatadog LogsDataForSEODeepInfraDeep LakeDiffbotDiscordDocugamiDuckDBElasticsearchEverNoteFacebook ChatFigmaFlyteForefrontAIGitGitBookGoldenGoogle BigQueryGoogle Cloud StorageGoogle DriveGoogle SearchGoogle SerperGooseAIGPT4AllGraphsignalGrobidGutenbergHacker NewsHazy ResearchHeliconeHologresHugging FaceiFixitIMSDbInfinoJinaLanceDBLangChain Decorators ✨Llama.cppMarqoMediaWikiDumpMetalMicrosoft OneDriveMicrosoft PowerPointMicrosoft WordMilvusMLflow AI GatewayMLflowModalModelScopeModern TreasuryMomentoMotherduckMyScaleNLPCloudNotion DBObsidianOpenAIOpenLLMOpenSearchOpenWeatherMapPetalsPGVectorPineconePipelineAIPortkeyPredibasePrediction GuardPromptLayerPsychicQdrantRay ServeRebuffRedditRedisReplicateRoamRocksetRunhouseRWKV-4SageMaker EndpointSearxNG Search APISerpAPIShale | https://python.langchain.com/docs/integrations/providers/obsidian |
caf2077db0ea-2 | EndpointSearxNG Search APISerpAPIShale ProtocolSingleStoreDBscikit-learnSlackspaCySpreedlyStarRocksStochasticAIStripeTairTelegramTigris2MarkdownTrelloTruLensTwitterTypesenseUnstructuredVectaraVespaWeights & BiasesWeatherWeaviateWhatsAppWhyLabsWikipediaWolfram AlphaWriterYeager.aiYouTubeZepZillizIntegrationsGrouped by providerObsidianOn this pageObsidianObsidian is a powerful and extensible knowledge base | https://python.langchain.com/docs/integrations/providers/obsidian |
caf2077db0ea-3 | that works on top of your local folder of plain text files.Installation and Setup​All instructions are in examples below.Document Loader​See a usage example.from langchain.document_loaders import ObsidianLoaderPreviousNotion DBNextOpenAIInstallation and SetupDocument LoaderCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright © 2023 LangChain, Inc. | https://python.langchain.com/docs/integrations/providers/obsidian |
7e9dff2fc789-0 | Cassandra | 🦜�🔗 Langchain | https://python.langchain.com/docs/integrations/providers/cassandra |
7e9dff2fc789-1 | Skip to main content🦜�🔗 LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKIntegrationsCallbacksChat modelsDocument loadersDocument transformersLLMsMemoryRetrieversText embedding modelsAgent toolkitsToolsVector storesGrouped by providerWandB TracingAI21 LabsAimAirbyteAirtableAleph AlphaAlibaba Cloud OpensearchAmazon API GatewayAnalyticDBAnnoyAnyscaleApifyArangoDBArgillaArthurArxivAtlasDBAwaDBAWS S3 DirectoryAZLyricsAzure Blob StorageAzure Cognitive SearchAzure OpenAIBananaBasetenBeamBedrockBiliBiliBlackboardBrave SearchCassandraCerebriumAIChaindeskChromaClarifaiClearMLCnosDBCohereCollege ConfidentialCometConfluenceC TransformersDatabricksDatadog TracingDatadog LogsDataForSEODeepInfraDeep LakeDiffbotDiscordDocugamiDuckDBElasticsearchEverNoteFacebook ChatFigmaFlyteForefrontAIGitGitBookGoldenGoogle BigQueryGoogle Cloud StorageGoogle DriveGoogle SearchGoogle SerperGooseAIGPT4AllGraphsignalGrobidGutenbergHacker NewsHazy ResearchHeliconeHologresHugging FaceiFixitIMSDbInfinoJinaLanceDBLangChain Decorators ✨Llama.cppMarqoMediaWikiDumpMetalMicrosoft OneDriveMicrosoft PowerPointMicrosoft WordMilvusMLflow AI GatewayMLflowModalModelScopeModern TreasuryMomentoMotherduckMyScaleNLPCloudNotion DBObsidianOpenAIOpenLLMOpenSearchOpenWeatherMapPetalsPGVectorPineconePipelineAIPortkeyPredibasePrediction GuardPromptLayerPsychicQdrantRay ServeRebuffRedditRedisReplicateRoamRocksetRunhouseRWKV-4SageMaker EndpointSearxNG Search APISerpAPIShale | https://python.langchain.com/docs/integrations/providers/cassandra |
7e9dff2fc789-2 | EndpointSearxNG Search APISerpAPIShale ProtocolSingleStoreDBscikit-learnSlackspaCySpreedlyStarRocksStochasticAIStripeTairTelegramTigris2MarkdownTrelloTruLensTwitterTypesenseUnstructuredVectaraVespaWeights & BiasesWeatherWeaviateWhatsAppWhyLabsWikipediaWolfram AlphaWriterYeager.aiYouTubeZepZillizIntegrationsGrouped by providerCassandraOn this pageCassandraApache Cassandra® is a free and open-source, distributed, wide-column | https://python.langchain.com/docs/integrations/providers/cassandra |
7e9dff2fc789-3 | store, NoSQL database management system designed to handle large amounts of data across many commodity servers,
providing high availability with no single point of failure. Cassandra offers support for clusters spanning
multiple datacenters, with asynchronous masterless replication allowing low latency operations for all clients.
Cassandra was designed to implement a combination of Amazon's Dynamo distributed storage and replication
techniques combined with Google's Bigtable data and storage engine model.Installation and Setup​pip install cassandra-driverpip install cassioVector Store​See a usage example.from langchain.memory import CassandraChatMessageHistoryMemory​See a usage example.from langchain.memory import CassandraChatMessageHistoryPreviousBrave SearchNextCerebriumAIInstallation and SetupVector StoreMemoryCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright © 2023 LangChain, Inc. | https://python.langchain.com/docs/integrations/providers/cassandra |
f405dc64e46e-0 | AtlasDB | 🦜�🔗 Langchain | https://python.langchain.com/docs/integrations/providers/atlas |
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