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Unnamed: 0 int64 0 4.66k	page content stringlengths 23 2k	description stringlengths 8 925	output stringlengths 38 2.93k
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3,103	'id': 'yPw4WjoAAAAJ', 'link': 'https://scholar.google.com/citations?user=yPw4WjoAAAAJ&hl=en&oi=sra'}]}, {'position': 9, 'title': 'ChatGPT and other large language models are ' 'double-edged swords', 'data_cid': 'So0q8TRvxhYJ', 'link': 'https://pubs.rsna.org/doi/full/10.1148/radiol.230163', 'publication': 'Y Shen, L Heacock, J Elias, KD Hentel, B ' 'Reig, G Shih‚Ä¶ - Radiology, 2023 - ' 'pubs.rsna.org', 'snippet': '‚Ä¶ Large Language Models (LLMs) are deep ' 'learning models trained to understand and ' 'generate natural language. Recent studies ' 'demonstrated that LLMs achieve great success ' 'in a ‚Ä¶', 'inline_links': {'cited_by': {'cites_id': '1641121387398204746', 'total': 231, 'link': 'https://scholar.google.com/scholar?cites=1641121387398204746&as_sdt=5,33&sciodt=0,33&hl=en'}, 'versions': {'cluster_id': '1641121387398204746', 'total': 3, 'link': 'https://scholar.google.com/scholar?cluster=1641121387398204746&hl=en&as_sdt=0,33'}, 'related_articles_link': 'https://scholar.google.com/scholar?q=related:So0q8TRvxhYJ:scholar.google.com/&scioq=Large+Language+Models&hl=en&as_sdt=0,33'}, 'authors': [{'name': 'Y Shen',	This notebook shows examples of how to use SearchApi to search the web. Go to https://www.searchapi.io/ to sign up for a free account and get API key.	This notebook shows examples of how to use SearchApi to search the web. Go to https://www.searchapi.io/ to sign up for a free account and get API key. ->: 'id': 'yPw4WjoAAAAJ', 'link': 'https://scholar.google.com/citations?user=yPw4WjoAAAAJ&hl=en&oi=sra'}]}, {'position': 9, 'title': 'ChatGPT and other large language models are ' 'double-edged swords', 'data_cid': 'So0q8TRvxhYJ', 'link': 'https://pubs.rsna.org/doi/full/10.1148/radiol.230163', 'publication': 'Y Shen, L Heacock, J Elias, KD Hentel, B ' 'Reig, G Shih‚Ä¶ - Radiology, 2023 - ' 'pubs.rsna.org', 'snippet': '‚Ä¶ Large Language Models (LLMs) are deep ' 'learning models trained to understand and ' 'generate natural language. Recent studies ' 'demonstrated that LLMs achieve great success ' 'in a ‚Ä¶', 'inline_links': {'cited_by': {'cites_id': '1641121387398204746', 'total': 231, 'link': 'https://scholar.google.com/scholar?cites=1641121387398204746&as_sdt=5,33&sciodt=0,33&hl=en'}, 'versions': {'cluster_id': '1641121387398204746', 'total': 3, 'link': 'https://scholar.google.com/scholar?cluster=1641121387398204746&hl=en&as_sdt=0,33'}, 'related_articles_link': 'https://scholar.google.com/scholar?q=related:So0q8TRvxhYJ:scholar.google.com/&scioq=Large+Language+Models&hl=en&as_sdt=0,33'}, 'authors': [{'name': 'Y Shen',
3,104	'Y Shen', 'id': 'XaeN2zgAAAAJ', 'link': 'https://scholar.google.com/citations?user=XaeN2zgAAAAJ&hl=en&oi=sra'}, {'name': 'L Heacock', 'id': 'tYYM5IkAAAAJ', 'link': 'https://scholar.google.com/citations?user=tYYM5IkAAAAJ&hl=en&oi=sra'}]}, {'position': 10, 'title': 'Pythia: A suite for analyzing large language ' 'models across training and scaling', 'data_cid': 'aaIDvsMAD8QJ', 'link': 'https://proceedings.mlr.press/v202/biderman23a.html', 'publication': 'S Biderman, H Schoelkopf‚Ä¶ - ' 'International ‚Ä¶, 2023 - ' 'proceedings.mlr.press', 'snippet': '‚Ä¶ large language models, we prioritize ' 'consistency in model ‚Ä¶ out the most ' 'performance from each model. For example, we ' '‚Ä¶ models, as it is becoming widely used for ' 'the largest models, ‚Ä¶', 'inline_links': {'cited_by': {'cites_id': '14127511396791067241', 'total': 89, 'link': 'https://scholar.google.com/scholar?cites=14127511396791067241&as_sdt=5,33&sciodt=0,33&hl=en'}, 'versions': {'cluster_id': '14127511396791067241', 'total': 3, 'link': 'https://scholar.google.com/scholar?cluster=14127511396791067241&hl=en&as_sdt=0,33'},	This notebook shows examples of how to use SearchApi to search the web. Go to https://www.searchapi.io/ to sign up for a free account and get API key.	This notebook shows examples of how to use SearchApi to search the web. Go to https://www.searchapi.io/ to sign up for a free account and get API key. ->: 'Y Shen', 'id': 'XaeN2zgAAAAJ', 'link': 'https://scholar.google.com/citations?user=XaeN2zgAAAAJ&hl=en&oi=sra'}, {'name': 'L Heacock', 'id': 'tYYM5IkAAAAJ', 'link': 'https://scholar.google.com/citations?user=tYYM5IkAAAAJ&hl=en&oi=sra'}]}, {'position': 10, 'title': 'Pythia: A suite for analyzing large language ' 'models across training and scaling', 'data_cid': 'aaIDvsMAD8QJ', 'link': 'https://proceedings.mlr.press/v202/biderman23a.html', 'publication': 'S Biderman, H Schoelkopf‚Ä¶ - ' 'International ‚Ä¶, 2023 - ' 'proceedings.mlr.press', 'snippet': '‚Ä¶ large language models, we prioritize ' 'consistency in model ‚Ä¶ out the most ' 'performance from each model. For example, we ' '‚Ä¶ models, as it is becoming widely used for ' 'the largest models, ‚Ä¶', 'inline_links': {'cited_by': {'cites_id': '14127511396791067241', 'total': 89, 'link': 'https://scholar.google.com/scholar?cites=14127511396791067241&as_sdt=5,33&sciodt=0,33&hl=en'}, 'versions': {'cluster_id': '14127511396791067241', 'total': 3, 'link': 'https://scholar.google.com/scholar?cluster=14127511396791067241&hl=en&as_sdt=0,33'},
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3,107	'5': 'https://scholar.google.com/scholar?start=40&q=Large+Language+Models&hl=en&as_sdt=0,33', '6': 'https://scholar.google.com/scholar?start=50&q=Large+Language+Models&hl=en&as_sdt=0,33', '7': 'https://scholar.google.com/scholar?start=60&q=Large+Language+Models&hl=en&as_sdt=0,33', '8': 'https://scholar.google.com/scholar?start=70&q=Large+Language+Models&hl=en&as_sdt=0,33', '9': 'https://scholar.google.com/scholar?start=80&q=Large+Language+Models&hl=en&as_sdt=0,33', '10': 'https://scholar.google.com/scholar?start=90&q=Large+Language+Models&hl=en&as_sdt=0,33'}}}PreviousSearch ToolsNextSearxNG SearchUsing as part of a Self Ask With Search ChainCustom parametersGetting results with metadataCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright ¬© 2023 LangChain, Inc.	This notebook shows examples of how to use SearchApi to search the web. Go to https://www.searchapi.io/ to sign up for a free account and get API key.	This notebook shows examples of how to use SearchApi to search the web. Go to https://www.searchapi.io/ to sign up for a free account and get API key. ->: '5': 'https://scholar.google.com/scholar?start=40&q=Large+Language+Models&hl=en&as_sdt=0,33', '6': 'https://scholar.google.com/scholar?start=50&q=Large+Language+Models&hl=en&as_sdt=0,33', '7': 'https://scholar.google.com/scholar?start=60&q=Large+Language+Models&hl=en&as_sdt=0,33', '8': 'https://scholar.google.com/scholar?start=70&q=Large+Language+Models&hl=en&as_sdt=0,33', '9': 'https://scholar.google.com/scholar?start=80&q=Large+Language+Models&hl=en&as_sdt=0,33', '10': 'https://scholar.google.com/scholar?start=90&q=Large+Language+Models&hl=en&as_sdt=0,33'}}}PreviousSearch ToolsNextSearxNG SearchUsing as part of a Self Ask With Search ChainCustom parametersGetting results with metadataCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright ¬© 2023 LangChain, Inc.
3,108	OpenWeatherMap \| ğŸ¦œï¸�ğŸ”— Langchain	This notebook goes over how to use the OpenWeatherMap component to fetch weather information.	This notebook goes over how to use the OpenWeatherMap component to fetch weather information. ->: OpenWeatherMap \| ğŸ¦œï¸�ğŸ”— Langchain
3,109	Skip to main contentğŸ¦œï¸�ğŸ”— LangChainDocsUse casesIntegrationsAPICommunityChat our docsLangSmithJS/TS DocsSearchCTRLKProvidersAnthropicAWSGoogleMicrosoftOpenAIMoreComponentsLLMsChat modelsDocument loadersDocument transformersText embedding modelsVector storesRetrieversToolsAlpha VantageApifyArXivAWS LambdaShell (bash)Bearly Code InterpreterBing SearchBrave SearchChatGPT PluginsDall-E Image GeneratorDataForSeoDuckDuckGo SearchEden AIEleven Labs Text2SpeechFile SystemGolden QueryGoogle DriveGoogle PlacesGoogle SearchGoogle SerperGradioGraphQLHuggingFace Hub ToolsHuman as a toolIFTTT WebHooksLemon AgentMetaphor SearchNuclia UnderstandingOpenWeatherMapPubMedRequestsSceneXplainSearch ToolsSearchApiSearxNG SearchSerpAPITwilioWikipediaWolfram AlphaYahoo Finance NewsYouTubeZapier Natural Language ActionsAgents and toolkitsMemoryCallbacksChat loadersComponentsToolsOpenWeatherMapOn this pageOpenWeatherMapThis notebook goes over how to use the OpenWeatherMap component to fetch weather information.First, you need to sign up for an OpenWeatherMap API key:Go to OpenWeatherMap and sign up for an API key herepip install pyowmThen we will need to set some environment variables:Save your API KEY into OPENWEATHERMAP_API_KEY env variableUse the wrapperâ€‹from langchain.utilities import OpenWeatherMapAPIWrapperimport osos.environ["OPENWEATHERMAP_API_KEY"] = ""weather = OpenWeatherMapAPIWrapper()weather_data = weather.run("London,GB")print(weather_data) In London,GB, the current weather is as follows: Detailed status: broken clouds Wind speed: 2.57 m/s, direction: 240Â° Humidity: 55% Temperature: - Current: 20.12Â°C - High: 21.75Â°C - Low: 18.68Â°C - Feels like: 19.62Â°C Rain: {} Heat index: None Cloud cover: 75%Use the toolâ€‹from langchain.llms import OpenAIfrom langchain.agents import load_tools, initialize_agent, AgentTypeimport osos.environ["OPENAI_API_KEY"] = ""os.environ["OPENWEATHERMAP_API_KEY"] = ""llm =	This notebook goes over how to use the OpenWeatherMap component to fetch weather information.	This notebook goes over how to use the OpenWeatherMap component to fetch weather information. ->: Skip to main contentğŸ¦œï¸�ğŸ”— LangChainDocsUse casesIntegrationsAPICommunityChat our docsLangSmithJS/TS DocsSearchCTRLKProvidersAnthropicAWSGoogleMicrosoftOpenAIMoreComponentsLLMsChat modelsDocument loadersDocument transformersText embedding modelsVector storesRetrieversToolsAlpha VantageApifyArXivAWS LambdaShell (bash)Bearly Code InterpreterBing SearchBrave SearchChatGPT PluginsDall-E Image GeneratorDataForSeoDuckDuckGo SearchEden AIEleven Labs Text2SpeechFile SystemGolden QueryGoogle DriveGoogle PlacesGoogle SearchGoogle SerperGradioGraphQLHuggingFace Hub ToolsHuman as a toolIFTTT WebHooksLemon AgentMetaphor SearchNuclia UnderstandingOpenWeatherMapPubMedRequestsSceneXplainSearch ToolsSearchApiSearxNG SearchSerpAPITwilioWikipediaWolfram AlphaYahoo Finance NewsYouTubeZapier Natural Language ActionsAgents and toolkitsMemoryCallbacksChat loadersComponentsToolsOpenWeatherMapOn this pageOpenWeatherMapThis notebook goes over how to use the OpenWeatherMap component to fetch weather information.First, you need to sign up for an OpenWeatherMap API key:Go to OpenWeatherMap and sign up for an API key herepip install pyowmThen we will need to set some environment variables:Save your API KEY into OPENWEATHERMAP_API_KEY env variableUse the wrapperâ€‹from langchain.utilities import OpenWeatherMapAPIWrapperimport osos.environ["OPENWEATHERMAP_API_KEY"] = ""weather = OpenWeatherMapAPIWrapper()weather_data = weather.run("London,GB")print(weather_data) In London,GB, the current weather is as follows: Detailed status: broken clouds Wind speed: 2.57 m/s, direction: 240Â° Humidity: 55% Temperature: - Current: 20.12Â°C - High: 21.75Â°C - Low: 18.68Â°C - Feels like: 19.62Â°C Rain: {} Heat index: None Cloud cover: 75%Use the toolâ€‹from langchain.llms import OpenAIfrom langchain.agents import load_tools, initialize_agent, AgentTypeimport osos.environ["OPENAI_API_KEY"] = ""os.environ["OPENWEATHERMAP_API_KEY"] = ""llm =
3,110	""os.environ["OPENWEATHERMAP_API_KEY"] = ""llm = OpenAI(temperature=0)tools = load_tools(["openweathermap-api"], llm)agent_chain = initialize_agent( tools=tools, llm=llm, agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION, verbose=True)agent_chain.run("What's the weather like in London?") > Entering new AgentExecutor chain... I need to find out the current weather in London. Action: OpenWeatherMap Action Input: London,GB Observation: In London,GB, the current weather is as follows: Detailed status: broken clouds Wind speed: 2.57 m/s, direction: 240Â° Humidity: 56% Temperature: - Current: 20.11Â°C - High: 21.75Â°C - Low: 18.68Â°C - Feels like: 19.64Â°C Rain: {} Heat index: None Cloud cover: 75% Thought: I now know the current weather in London. Final Answer: The current weather in London is broken clouds, with a wind speed of 2.57 m/s, direction 240Â°, humidity of 56%, temperature of 20.11Â°C, high of 21.75Â°C, low of 18.68Â°C, and a heat index of None. > Finished chain. 'The current weather in London is broken clouds, with a wind speed of 2.57 m/s, direction 240Â°, humidity of 56%, temperature of 20.11Â°C, high of 21.75Â°C, low of 18.68Â°C, and a heat index of None.'PreviousNuclia UnderstandingNextPubMedUse the wrapperUse the toolCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright Â© 2023 LangChain, Inc.	This notebook goes over how to use the OpenWeatherMap component to fetch weather information.	This notebook goes over how to use the OpenWeatherMap component to fetch weather information. ->: ""os.environ["OPENWEATHERMAP_API_KEY"] = ""llm = OpenAI(temperature=0)tools = load_tools(["openweathermap-api"], llm)agent_chain = initialize_agent( tools=tools, llm=llm, agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION, verbose=True)agent_chain.run("What's the weather like in London?") > Entering new AgentExecutor chain... I need to find out the current weather in London. Action: OpenWeatherMap Action Input: London,GB Observation: In London,GB, the current weather is as follows: Detailed status: broken clouds Wind speed: 2.57 m/s, direction: 240Â° Humidity: 56% Temperature: - Current: 20.11Â°C - High: 21.75Â°C - Low: 18.68Â°C - Feels like: 19.64Â°C Rain: {} Heat index: None Cloud cover: 75% Thought: I now know the current weather in London. Final Answer: The current weather in London is broken clouds, with a wind speed of 2.57 m/s, direction 240Â°, humidity of 56%, temperature of 20.11Â°C, high of 21.75Â°C, low of 18.68Â°C, and a heat index of None. > Finished chain. 'The current weather in London is broken clouds, with a wind speed of 2.57 m/s, direction 240Â°, humidity of 56%, temperature of 20.11Â°C, high of 21.75Â°C, low of 18.68Â°C, and a heat index of None.'PreviousNuclia UnderstandingNextPubMedUse the wrapperUse the toolCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright Â© 2023 LangChain, Inc.
3,111	Lemon Agent \| ü¶úÔ∏èüîó Langchain	Lemon Agent helps you build powerful AI assistants in minutes and automate workflows by allowing for accurate and reliable read and write operations in tools like Airtable, Hubspot, Discord, Notion, Slack and Github.	Lemon Agent helps you build powerful AI assistants in minutes and automate workflows by allowing for accurate and reliable read and write operations in tools like Airtable, Hubspot, Discord, Notion, Slack and Github. ->: Lemon Agent \| ü¶úÔ∏èüîó Langchain
3,112	Skip to main contentü¶úÔ∏èüîó LangChainDocsUse casesIntegrationsAPICommunityChat our docsLangSmithJS/TS DocsSearchCTRLKProvidersAnthropicAWSGoogleMicrosoftOpenAIMoreComponentsLLMsChat modelsDocument loadersDocument transformersText embedding modelsVector storesRetrieversToolsAlpha VantageApifyArXivAWS LambdaShell (bash)Bearly Code InterpreterBing SearchBrave SearchChatGPT PluginsDall-E Image GeneratorDataForSeoDuckDuckGo SearchEden AIEleven Labs Text2SpeechFile SystemGolden QueryGoogle DriveGoogle PlacesGoogle SearchGoogle SerperGradioGraphQLHuggingFace Hub ToolsHuman as a toolIFTTT WebHooksLemon AgentMetaphor SearchNuclia UnderstandingOpenWeatherMapPubMedRequestsSceneXplainSearch ToolsSearchApiSearxNG SearchSerpAPITwilioWikipediaWolfram AlphaYahoo Finance NewsYouTubeZapier Natural Language ActionsAgents and toolkitsMemoryCallbacksChat loadersComponentsToolsLemon AgentOn this pageLemon AgentLemon Agent helps you build powerful AI assistants in minutes and automate workflows by allowing for accurate and reliable read and write operations in tools like Airtable, Hubspot, Discord, Notion, Slack and Github.See full docs here.Most connectors available today are focused on read-only operations, limiting the potential of LLMs. Agents, on the other hand, have a tendency to hallucinate from time to time due to missing context or instructions.With Lemon AI, it is possible to give your agents access to well-defined APIs for reliable read and write operations. In addition, Lemon AI functions allow you to further reduce the risk of hallucinations by providing a way to statically define workflows that the model can rely on in case of uncertainty.Quick Start‚ÄãThe following quick start demonstrates how to use Lemon AI in combination with Agents to automate workflows that involve interaction with internal tooling.1. Install Lemon AI‚ÄãRequires Python 3.8.1 and above.To use Lemon AI in your Python project run pip install lemonaiThis will install the corresponding Lemon AI client	Lemon Agent helps you build powerful AI assistants in minutes and automate workflows by allowing for accurate and reliable read and write operations in tools like Airtable, Hubspot, Discord, Notion, Slack and Github.	Lemon Agent helps you build powerful AI assistants in minutes and automate workflows by allowing for accurate and reliable read and write operations in tools like Airtable, Hubspot, Discord, Notion, Slack and Github. ->: Skip to main contentü¶úÔ∏èüîó LangChainDocsUse casesIntegrationsAPICommunityChat our docsLangSmithJS/TS DocsSearchCTRLKProvidersAnthropicAWSGoogleMicrosoftOpenAIMoreComponentsLLMsChat modelsDocument loadersDocument transformersText embedding modelsVector storesRetrieversToolsAlpha VantageApifyArXivAWS LambdaShell (bash)Bearly Code InterpreterBing SearchBrave SearchChatGPT PluginsDall-E Image GeneratorDataForSeoDuckDuckGo SearchEden AIEleven Labs Text2SpeechFile SystemGolden QueryGoogle DriveGoogle PlacesGoogle SearchGoogle SerperGradioGraphQLHuggingFace Hub ToolsHuman as a toolIFTTT WebHooksLemon AgentMetaphor SearchNuclia UnderstandingOpenWeatherMapPubMedRequestsSceneXplainSearch ToolsSearchApiSearxNG SearchSerpAPITwilioWikipediaWolfram AlphaYahoo Finance NewsYouTubeZapier Natural Language ActionsAgents and toolkitsMemoryCallbacksChat loadersComponentsToolsLemon AgentOn this pageLemon AgentLemon Agent helps you build powerful AI assistants in minutes and automate workflows by allowing for accurate and reliable read and write operations in tools like Airtable, Hubspot, Discord, Notion, Slack and Github.See full docs here.Most connectors available today are focused on read-only operations, limiting the potential of LLMs. Agents, on the other hand, have a tendency to hallucinate from time to time due to missing context or instructions.With Lemon AI, it is possible to give your agents access to well-defined APIs for reliable read and write operations. In addition, Lemon AI functions allow you to further reduce the risk of hallucinations by providing a way to statically define workflows that the model can rely on in case of uncertainty.Quick Start‚ÄãThe following quick start demonstrates how to use Lemon AI in combination with Agents to automate workflows that involve interaction with internal tooling.1. Install Lemon AI‚ÄãRequires Python 3.8.1 and above.To use Lemon AI in your Python project run pip install lemonaiThis will install the corresponding Lemon AI client
3,113	will install the corresponding Lemon AI client which you can then import into your script.The tool uses Python packages langchain and loguru. In case of any installation errors with Lemon AI, install both packages first and then install the Lemon AI package.2. Launch the Server‚ÄãThe interaction of your agents and all tools provided by Lemon AI is handled by the Lemon AI Server. To use Lemon AI you need to run the server on your local machine so the Lemon AI Python client can connect to it.3. Use Lemon AI with Langchain‚ÄãLemon AI automatically solves given tasks by finding the right combination of relevant tools or uses Lemon AI Functions as an alternative. The following example demonstrates how to retrieve a user from Hackernews and write it to a table in Airtable:(Optional) Define your Lemon AI Functions‚ÄãSimilar to OpenAI functions, Lemon AI provides the option to define workflows as reusable functions. These functions can be defined for use cases where it is especially important to move as close as possible to near-deterministic behavior. Specific workflows can be defined in a separate lemonai.json:[ { "name": "Hackernews Airtable User Workflow", "description": "retrieves user data from Hackernews and appends it to a table in Airtable", "tools": ["hackernews-get-user", "airtable-append-data"] }]Your model will have access to these functions and will prefer them over self-selecting tools to solve a given task. All you have to do is to let the agent know that it should use a given function by including the function name in the prompt.Include Lemon AI in your Langchain project‚Äãimport osfrom lemonai import execute_workflowfrom langchain.llms import OpenAILoad API Keys and Access Tokens‚ÄãTo use tools that require authentication, you have to store the corresponding access credentials in your environment in the format "{tool name}_{authentication string}" where the authentication string is one of ["API_KEY", "SECRET_KEY", "SUBSCRIPTION_KEY",	Lemon Agent helps you build powerful AI assistants in minutes and automate workflows by allowing for accurate and reliable read and write operations in tools like Airtable, Hubspot, Discord, Notion, Slack and Github.	Lemon Agent helps you build powerful AI assistants in minutes and automate workflows by allowing for accurate and reliable read and write operations in tools like Airtable, Hubspot, Discord, Notion, Slack and Github. ->: will install the corresponding Lemon AI client which you can then import into your script.The tool uses Python packages langchain and loguru. In case of any installation errors with Lemon AI, install both packages first and then install the Lemon AI package.2. Launch the Server‚ÄãThe interaction of your agents and all tools provided by Lemon AI is handled by the Lemon AI Server. To use Lemon AI you need to run the server on your local machine so the Lemon AI Python client can connect to it.3. Use Lemon AI with Langchain‚ÄãLemon AI automatically solves given tasks by finding the right combination of relevant tools or uses Lemon AI Functions as an alternative. The following example demonstrates how to retrieve a user from Hackernews and write it to a table in Airtable:(Optional) Define your Lemon AI Functions‚ÄãSimilar to OpenAI functions, Lemon AI provides the option to define workflows as reusable functions. These functions can be defined for use cases where it is especially important to move as close as possible to near-deterministic behavior. Specific workflows can be defined in a separate lemonai.json:[ { "name": "Hackernews Airtable User Workflow", "description": "retrieves user data from Hackernews and appends it to a table in Airtable", "tools": ["hackernews-get-user", "airtable-append-data"] }]Your model will have access to these functions and will prefer them over self-selecting tools to solve a given task. All you have to do is to let the agent know that it should use a given function by including the function name in the prompt.Include Lemon AI in your Langchain project‚Äãimport osfrom lemonai import execute_workflowfrom langchain.llms import OpenAILoad API Keys and Access Tokens‚ÄãTo use tools that require authentication, you have to store the corresponding access credentials in your environment in the format "{tool name}_{authentication string}" where the authentication string is one of ["API_KEY", "SECRET_KEY", "SUBSCRIPTION_KEY",
3,114	of ["API_KEY", "SECRET_KEY", "SUBSCRIPTION_KEY", "ACCESS_KEY"] for API keys or ["ACCESS_TOKEN", "SECRET_TOKEN"] for authentication tokens. Examples are "OPENAI_API_KEY", "BING_SUBSCRIPTION_KEY", "AIRTABLE_ACCESS_TOKEN".""" Load all relevant API Keys and Access Tokens into your environment variables """os.environ["OPENAI_API_KEY"] = "INSERT OPENAI API KEY HERE"os.environ["AIRTABLE_ACCESS_TOKEN"] = "INSERT AIRTABLE TOKEN HERE"hackernews_username = "INSERT HACKERNEWS USERNAME HERE"airtable_base_id = "INSERT BASE ID HERE"airtable_table_id = "INSERT TABLE ID HERE"""" Define your instruction to be given to your LLM """prompt = f"""Read information from Hackernews for user {hackernews_username} and then write the results toAirtable (baseId: {airtable_base_id}, tableId: {airtable_table_id}). Only write the fields "username", "karma"and "created_at_i". Please make sure that Airtable does NOT automatically convert the field types.""""""Use the Lemon AI execute_workflow wrapper to run your Langchain agent in combination with Lemon AI """model = OpenAI(temperature=0)execute_workflow(llm=model, prompt_string=prompt)4. Gain transparency on your Agent's decision making‚ÄãTo gain transparency on how your Agent interacts with Lemon AI tools to solve a given task, all decisions made, tools used and operations performed are written to a local lemonai.log file. Every time your LLM agent is interacting with the Lemon AI tool stack a corresponding log entry is created.2023-06-26T11:50:27.708785+0100 - b5f91c59-8487-45c2-800a-156eac0c7dae - hackernews-get-user2023-06-26T11:50:39.624035+0100 - b5f91c59-8487-45c2-800a-156eac0c7dae - airtable-append-data2023-06-26T11:58:32.925228+0100 - 5efe603c-9898-4143-b99a-55b50007ed9d - hackernews-get-user2023-06-26T11:58:43.988788+0100 - 5efe603c-9898-4143-b99a-55b50007ed9d - airtable-append-dataBy using the Lemon AI Analytics you can easily gain a better understanding of how frequently and in which order tools are used. As a result, you	Lemon Agent helps you build powerful AI assistants in minutes and automate workflows by allowing for accurate and reliable read and write operations in tools like Airtable, Hubspot, Discord, Notion, Slack and Github.	Lemon Agent helps you build powerful AI assistants in minutes and automate workflows by allowing for accurate and reliable read and write operations in tools like Airtable, Hubspot, Discord, Notion, Slack and Github. ->: of ["API_KEY", "SECRET_KEY", "SUBSCRIPTION_KEY", "ACCESS_KEY"] for API keys or ["ACCESS_TOKEN", "SECRET_TOKEN"] for authentication tokens. Examples are "OPENAI_API_KEY", "BING_SUBSCRIPTION_KEY", "AIRTABLE_ACCESS_TOKEN".""" Load all relevant API Keys and Access Tokens into your environment variables """os.environ["OPENAI_API_KEY"] = "INSERT OPENAI API KEY HERE"os.environ["AIRTABLE_ACCESS_TOKEN"] = "INSERT AIRTABLE TOKEN HERE"hackernews_username = "INSERT HACKERNEWS USERNAME HERE"airtable_base_id = "INSERT BASE ID HERE"airtable_table_id = "INSERT TABLE ID HERE"""" Define your instruction to be given to your LLM """prompt = f"""Read information from Hackernews for user {hackernews_username} and then write the results toAirtable (baseId: {airtable_base_id}, tableId: {airtable_table_id}). Only write the fields "username", "karma"and "created_at_i". Please make sure that Airtable does NOT automatically convert the field types.""""""Use the Lemon AI execute_workflow wrapper to run your Langchain agent in combination with Lemon AI """model = OpenAI(temperature=0)execute_workflow(llm=model, prompt_string=prompt)4. Gain transparency on your Agent's decision making‚ÄãTo gain transparency on how your Agent interacts with Lemon AI tools to solve a given task, all decisions made, tools used and operations performed are written to a local lemonai.log file. Every time your LLM agent is interacting with the Lemon AI tool stack a corresponding log entry is created.2023-06-26T11:50:27.708785+0100 - b5f91c59-8487-45c2-800a-156eac0c7dae - hackernews-get-user2023-06-26T11:50:39.624035+0100 - b5f91c59-8487-45c2-800a-156eac0c7dae - airtable-append-data2023-06-26T11:58:32.925228+0100 - 5efe603c-9898-4143-b99a-55b50007ed9d - hackernews-get-user2023-06-26T11:58:43.988788+0100 - 5efe603c-9898-4143-b99a-55b50007ed9d - airtable-append-dataBy using the Lemon AI Analytics you can easily gain a better understanding of how frequently and in which order tools are used. As a result, you
3,115	in which order tools are used. As a result, you can identify weak spots in your agent‚Äôs decision-making capabilities and move to a more deterministic behavior by defining Lemon AI functions.PreviousIFTTT WebHooksNextMetaphor SearchQuick Start1. Install Lemon AI2. Launch the Server3. Use Lemon AI with Langchain4. Gain transparency on your Agent's decision makingCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright ¬© 2023 LangChain, Inc.	Lemon Agent helps you build powerful AI assistants in minutes and automate workflows by allowing for accurate and reliable read and write operations in tools like Airtable, Hubspot, Discord, Notion, Slack and Github.	Lemon Agent helps you build powerful AI assistants in minutes and automate workflows by allowing for accurate and reliable read and write operations in tools like Airtable, Hubspot, Discord, Notion, Slack and Github. ->: in which order tools are used. As a result, you can identify weak spots in your agent‚Äôs decision-making capabilities and move to a more deterministic behavior by defining Lemon AI functions.PreviousIFTTT WebHooksNextMetaphor SearchQuick Start1. Install Lemon AI2. Launch the Server3. Use Lemon AI with Langchain4. Gain transparency on your Agent's decision makingCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright ¬© 2023 LangChain, Inc.
3,116	DuckDuckGo Search \| ü¶úÔ∏èüîó Langchain	This notebook goes over how to use the duck-duck-go search component.	This notebook goes over how to use the duck-duck-go search component. ->: DuckDuckGo Search \| ü¶úÔ∏èüîó Langchain
3,117	Skip to main contentü¶úÔ∏èüîó LangChainDocsUse casesIntegrationsAPICommunityChat our docsLangSmithJS/TS DocsSearchCTRLKProvidersAnthropicAWSGoogleMicrosoftOpenAIMoreComponentsLLMsChat modelsDocument loadersDocument transformersText embedding modelsVector storesRetrieversToolsAlpha VantageApifyArXivAWS LambdaShell (bash)Bearly Code InterpreterBing SearchBrave SearchChatGPT PluginsDall-E Image GeneratorDataForSeoDuckDuckGo SearchEden AIEleven Labs Text2SpeechFile SystemGolden QueryGoogle DriveGoogle PlacesGoogle SearchGoogle SerperGradioGraphQLHuggingFace Hub ToolsHuman as a toolIFTTT WebHooksLemon AgentMetaphor SearchNuclia UnderstandingOpenWeatherMapPubMedRequestsSceneXplainSearch ToolsSearchApiSearxNG SearchSerpAPITwilioWikipediaWolfram AlphaYahoo Finance NewsYouTubeZapier Natural Language ActionsAgents and toolkitsMemoryCallbacksChat loadersComponentsToolsDuckDuckGo SearchDuckDuckGo SearchThis notebook goes over how to use the duck-duck-go search component.# !pip install duckduckgo-searchfrom langchain.tools import DuckDuckGoSearchRunsearch = DuckDuckGoSearchRun()search.run("Obama's first name?") 'August 4, 1961 (age 61) Honolulu Hawaii Title / Office: presidency of the United States of America (2009-2017), United States United States Senate (2005-2008), United States ... (Show more) Political Affiliation: Democratic Party Awards And Honors: Barack Hussein Obama II (/ b …ô Àà r …ëÀê k h uÀê Àà s e…™ n o ä Àà b …ëÀê m …ô / b…ô-RAHK hoo-SAYN oh-BAH-m…ô; born August 4, 1961) is an American politician who served as the 44th president of the United States from 2009 to 2017. A member of the Democratic Party, he was the first African-American president of the United States. Obama previously served as a U.S. senator representing Illinois ... Answer (1 of 12): I see others have answered President Obama\'s name which is "Barack Hussein Obama". President Obama has received many comments about his name from the racists across US. It is worth noting that he never changed	This notebook goes over how to use the duck-duck-go search component.	This notebook goes over how to use the duck-duck-go search component. ->: Skip to main contentü¶úÔ∏èüîó LangChainDocsUse casesIntegrationsAPICommunityChat our docsLangSmithJS/TS DocsSearchCTRLKProvidersAnthropicAWSGoogleMicrosoftOpenAIMoreComponentsLLMsChat modelsDocument loadersDocument transformersText embedding modelsVector storesRetrieversToolsAlpha VantageApifyArXivAWS LambdaShell (bash)Bearly Code InterpreterBing SearchBrave SearchChatGPT PluginsDall-E Image GeneratorDataForSeoDuckDuckGo SearchEden AIEleven Labs Text2SpeechFile SystemGolden QueryGoogle DriveGoogle PlacesGoogle SearchGoogle SerperGradioGraphQLHuggingFace Hub ToolsHuman as a toolIFTTT WebHooksLemon AgentMetaphor SearchNuclia UnderstandingOpenWeatherMapPubMedRequestsSceneXplainSearch ToolsSearchApiSearxNG SearchSerpAPITwilioWikipediaWolfram AlphaYahoo Finance NewsYouTubeZapier Natural Language ActionsAgents and toolkitsMemoryCallbacksChat loadersComponentsToolsDuckDuckGo SearchDuckDuckGo SearchThis notebook goes over how to use the duck-duck-go search component.# !pip install duckduckgo-searchfrom langchain.tools import DuckDuckGoSearchRunsearch = DuckDuckGoSearchRun()search.run("Obama's first name?") 'August 4, 1961 (age 61) Honolulu Hawaii Title / Office: presidency of the United States of America (2009-2017), United States United States Senate (2005-2008), United States ... (Show more) Political Affiliation: Democratic Party Awards And Honors: Barack Hussein Obama II (/ b …ô Àà r …ëÀê k h uÀê Àà s e…™ n o ä Àà b …ëÀê m …ô / b…ô-RAHK hoo-SAYN oh-BAH-m…ô; born August 4, 1961) is an American politician who served as the 44th president of the United States from 2009 to 2017. A member of the Democratic Party, he was the first African-American president of the United States. Obama previously served as a U.S. senator representing Illinois ... Answer (1 of 12): I see others have answered President Obama\'s name which is "Barack Hussein Obama". President Obama has received many comments about his name from the racists across US. It is worth noting that he never changed
3,118	US. It is worth noting that he never changed his name. Also, it is worth noting that a simple search would have re... What is Barack Obama\'s full name? Updated: 11/11/2022 Wiki User ‚àô 6y ago Study now See answer (1) Best Answer Copy His full, birth name is Barack Hussein Obama, II. He was named after his... Alex Oliveira July 24, 2023 4:57pm Updated 0 seconds of 43 secondsVolume 0% 00:00 00:43 The man who drowned while paddleboarding on a pond outside the Obamas\' Martha\'s Vineyard estate has been...'To get more additional information (e.g. link, source) use DuckDuckGoSearchResults()from langchain.tools import DuckDuckGoSearchResultssearch = DuckDuckGoSearchResults()search.run("Obama") "[snippet: Barack Hussein Obama II (/ b …ô Àà r …ëÀê k h uÀê Àà s e…™ n o ä Àà b …ëÀê m …ô / b…ô-RAHK hoo-SAYN oh-BAH-m…ô; born August 4, 1961) is an American politician who served as the 44th president of the United States from 2009 to 2017. A member of the Democratic Party, he was the first African-American president of the United States. Obama previously served as a U.S. senator representing Illinois ..., title: Barack Obama - Wikipedia, link: https://en.wikipedia.org/wiki/Barack_Obama], [snippet: Barack Obama, in full Barack Hussein Obama II, (born August 4, 1961, Honolulu, Hawaii, U.S.), 44th president of the United States (2009-17) and the first African American to hold the office. Before winning the presidency, Obama represented Illinois in the U.S. Senate (2005-08). He was the third African American to be elected to that body ..., title: Barack Obama \| Biography, Parents, Education, Presidency, Books ..., link: https://www.britannica.com/biography/Barack-Obama], [snippet: Barack Obama 's tenure as the 44th president of the United States began with his first inauguration on January 20, 2009, and ended on January 20, 2017. A Democrat from Illinois, Obama took office following a decisive victory over Republican nominee John McCain in the 2008 presidential election. Four	This notebook goes over how to use the duck-duck-go search component.	This notebook goes over how to use the duck-duck-go search component. ->: US. It is worth noting that he never changed his name. Also, it is worth noting that a simple search would have re... What is Barack Obama\'s full name? Updated: 11/11/2022 Wiki User ‚àô 6y ago Study now See answer (1) Best Answer Copy His full, birth name is Barack Hussein Obama, II. He was named after his... Alex Oliveira July 24, 2023 4:57pm Updated 0 seconds of 43 secondsVolume 0% 00:00 00:43 The man who drowned while paddleboarding on a pond outside the Obamas\' Martha\'s Vineyard estate has been...'To get more additional information (e.g. link, source) use DuckDuckGoSearchResults()from langchain.tools import DuckDuckGoSearchResultssearch = DuckDuckGoSearchResults()search.run("Obama") "[snippet: Barack Hussein Obama II (/ b …ô Àà r …ëÀê k h uÀê Àà s e…™ n o ä Àà b …ëÀê m …ô / b…ô-RAHK hoo-SAYN oh-BAH-m…ô; born August 4, 1961) is an American politician who served as the 44th president of the United States from 2009 to 2017. A member of the Democratic Party, he was the first African-American president of the United States. Obama previously served as a U.S. senator representing Illinois ..., title: Barack Obama - Wikipedia, link: https://en.wikipedia.org/wiki/Barack_Obama], [snippet: Barack Obama, in full Barack Hussein Obama II, (born August 4, 1961, Honolulu, Hawaii, U.S.), 44th president of the United States (2009-17) and the first African American to hold the office. Before winning the presidency, Obama represented Illinois in the U.S. Senate (2005-08). He was the third African American to be elected to that body ..., title: Barack Obama \| Biography, Parents, Education, Presidency, Books ..., link: https://www.britannica.com/biography/Barack-Obama], [snippet: Barack Obama 's tenure as the 44th president of the United States began with his first inauguration on January 20, 2009, and ended on January 20, 2017. A Democrat from Illinois, Obama took office following a decisive victory over Republican nominee John McCain in the 2008 presidential election. Four
3,119	McCain in the 2008 presidential election. Four years later, in the 2012 presidential ..., title: Presidency of Barack Obama - Wikipedia, link: https://en.wikipedia.org/wiki/Presidency_of_Barack_Obama], [snippet: First published on Mon 24 Jul 2023 20.03 EDT. Barack Obama's personal chef died while paddleboarding near the ex-president's home on Martha's Vineyard over the weekend, Massachusetts state ..., title: Obama's personal chef dies while paddleboarding off Martha's Vineyard ..., link: https://www.theguardian.com/us-news/2023/jul/24/tafari-campbell-barack-obama-chef-drowns-marthas-vineyard]"You can also just search for news articles. Use the keyword backend="news"search = DuckDuckGoSearchResults(backend="news")search.run("Obama") "[date: 2023-07-26T12:01:22, title: 'My heart is broken': Former Obama White House chef mourned following apparent drowning death in Edgartown, snippet: Tafari Campbell of Dumfries, Va., had been paddle boarding in Edgartown Great Pond when he appeared to briefly struggle, submerged, and did not return to the surface, authorities have said. Crews ultimately found the 45-year-old's body Monday morning., source: The Boston Globe on MSN.com, link: https://www.msn.com/en-us/news/us/my-heart-is-broken-former-obama-white-house-chef-mourned-following-apparent-drowning-death-in-edgartown/ar-AA1elNB8], [date: 2023-07-25T18:44:00, title: Obama's chef drowns paddleboarding near former president's Edgartown vacation home, snippet: Campbell was visiting Martha's Vineyard, where the Obamas own a vacation home. He was not wearing a lifejacket when he fell off his paddleboard., source: YAHOO!News, link: https://news.yahoo.com/obama-chef-drowns-paddleboarding-near-184437491.html], [date: 2023-07-26T00:30:00, title: Obama's personal chef dies while paddleboarding off Martha's Vineyard, snippet: Tafari Campbell, who worked at the White House during Obama's presidency, was visiting the island while the family was away, source: The Guardian, link:	This notebook goes over how to use the duck-duck-go search component.	This notebook goes over how to use the duck-duck-go search component. ->: McCain in the 2008 presidential election. Four years later, in the 2012 presidential ..., title: Presidency of Barack Obama - Wikipedia, link: https://en.wikipedia.org/wiki/Presidency_of_Barack_Obama], [snippet: First published on Mon 24 Jul 2023 20.03 EDT. Barack Obama's personal chef died while paddleboarding near the ex-president's home on Martha's Vineyard over the weekend, Massachusetts state ..., title: Obama's personal chef dies while paddleboarding off Martha's Vineyard ..., link: https://www.theguardian.com/us-news/2023/jul/24/tafari-campbell-barack-obama-chef-drowns-marthas-vineyard]"You can also just search for news articles. Use the keyword backend="news"search = DuckDuckGoSearchResults(backend="news")search.run("Obama") "[date: 2023-07-26T12:01:22, title: 'My heart is broken': Former Obama White House chef mourned following apparent drowning death in Edgartown, snippet: Tafari Campbell of Dumfries, Va., had been paddle boarding in Edgartown Great Pond when he appeared to briefly struggle, submerged, and did not return to the surface, authorities have said. Crews ultimately found the 45-year-old's body Monday morning., source: The Boston Globe on MSN.com, link: https://www.msn.com/en-us/news/us/my-heart-is-broken-former-obama-white-house-chef-mourned-following-apparent-drowning-death-in-edgartown/ar-AA1elNB8], [date: 2023-07-25T18:44:00, title: Obama's chef drowns paddleboarding near former president's Edgartown vacation home, snippet: Campbell was visiting Martha's Vineyard, where the Obamas own a vacation home. He was not wearing a lifejacket when he fell off his paddleboard., source: YAHOO!News, link: https://news.yahoo.com/obama-chef-drowns-paddleboarding-near-184437491.html], [date: 2023-07-26T00:30:00, title: Obama's personal chef dies while paddleboarding off Martha's Vineyard, snippet: Tafari Campbell, who worked at the White House during Obama's presidency, was visiting the island while the family was away, source: The Guardian, link:
3,120	the family was away, source: The Guardian, link: https://www.theguardian.com/us-news/2023/jul/24/tafari-campbell-barack-obama-chef-drowns-marthas-vineyard], [date: 2023-07-24T21:54:00, title: Obama's chef ID'd as paddleboarder who drowned near former president's Martha's Vineyard estate, snippet: Former President Barack Obama's personal chef, Tafari Campbell, has been identified as the paddle boarder who drowned near the Obamas' Martha's Vineyard estate., source: Fox News, link: https://www.foxnews.com/politics/obamas-chef-idd-paddleboarder-who-drowned-near-former-presidents-marthas-vineyard-estate]"You can also directly pass a custom DuckDuckGoSearchAPIWrapper to DuckDuckGoSearchResults. Therefore, you have much more control over the search results.from langchain.utilities import DuckDuckGoSearchAPIWrapperwrapper = DuckDuckGoSearchAPIWrapper(region="de-de", time="d", max_results=2)search = DuckDuckGoSearchResults(api_wrapper=wrapper, backend="news")search.run("Obama") '[date: 2023-07-25T12:15:00, title: Barack + Michelle Obama: Sie trauern um Angestellten, snippet: Barack und Michelle Obama trauern um ihren ehemaligen K√ºchenchef Tafari Campbell. Der Familienvater verungl√ºckte am vergangenen Sonntag und wurde in einem Teich geborgen., source: Gala, link: https://www.gala.de/stars/news/barack---michelle-obama--sie-trauern-um-angestellten-23871228.html], [date: 2023-07-25T10:30:00, title: Barack Obama: Sein Koch (‚Ä†45) ist tot - diese Details sind bekannt, snippet: Tafari Campbell war fr√ºher im Wei√üen Haus eingestellt, arbeitete anschlie√üend weiter f√ºr Ex-Pr√§sident Barack Obama. Nun ist er gestorben. Diese Details sind bekannt., source: T-Online, link: https://www.t-online.de/unterhaltung/stars/id_100213226/barack-obama-sein-koch-45-ist-tot-diese-details-sind-bekannt.html], [date: 2023-07-25T05:33:23, title: Barack Obama: Sein Privatkoch ist bei einem tragischen Unfall gestorben, snippet: Barack Obama (61) und Michelle Obama (59) sind in tiefer Trauer. Ihr	This notebook goes over how to use the duck-duck-go search component.	This notebook goes over how to use the duck-duck-go search component. ->: the family was away, source: The Guardian, link: https://www.theguardian.com/us-news/2023/jul/24/tafari-campbell-barack-obama-chef-drowns-marthas-vineyard], [date: 2023-07-24T21:54:00, title: Obama's chef ID'd as paddleboarder who drowned near former president's Martha's Vineyard estate, snippet: Former President Barack Obama's personal chef, Tafari Campbell, has been identified as the paddle boarder who drowned near the Obamas' Martha's Vineyard estate., source: Fox News, link: https://www.foxnews.com/politics/obamas-chef-idd-paddleboarder-who-drowned-near-former-presidents-marthas-vineyard-estate]"You can also directly pass a custom DuckDuckGoSearchAPIWrapper to DuckDuckGoSearchResults. Therefore, you have much more control over the search results.from langchain.utilities import DuckDuckGoSearchAPIWrapperwrapper = DuckDuckGoSearchAPIWrapper(region="de-de", time="d", max_results=2)search = DuckDuckGoSearchResults(api_wrapper=wrapper, backend="news")search.run("Obama") '[date: 2023-07-25T12:15:00, title: Barack + Michelle Obama: Sie trauern um Angestellten, snippet: Barack und Michelle Obama trauern um ihren ehemaligen K√ºchenchef Tafari Campbell. Der Familienvater verungl√ºckte am vergangenen Sonntag und wurde in einem Teich geborgen., source: Gala, link: https://www.gala.de/stars/news/barack---michelle-obama--sie-trauern-um-angestellten-23871228.html], [date: 2023-07-25T10:30:00, title: Barack Obama: Sein Koch (‚Ä†45) ist tot - diese Details sind bekannt, snippet: Tafari Campbell war fr√ºher im Wei√üen Haus eingestellt, arbeitete anschlie√üend weiter f√ºr Ex-Pr√§sident Barack Obama. Nun ist er gestorben. Diese Details sind bekannt., source: T-Online, link: https://www.t-online.de/unterhaltung/stars/id_100213226/barack-obama-sein-koch-45-ist-tot-diese-details-sind-bekannt.html], [date: 2023-07-25T05:33:23, title: Barack Obama: Sein Privatkoch ist bei einem tragischen Unfall gestorben, snippet: Barack Obama (61) und Michelle Obama (59) sind in tiefer Trauer. Ihr
3,121	Michelle Obama (59) sind in tiefer Trauer. Ihr Privatkoch Tafari Campbell ist am Montag (24. Juli) ums Leben gekommen, er wurde nur 45 Jahre alt. Laut US-Polizei starb er bei ein, source: BUNTE.de, link: https://www.msn.com/de-de/unterhaltung/other/barack-obama-sein-privatkoch-ist-bei-einem-tragischen-unfall-gestorben/ar-AA1ejrAd], [date: 2023-07-25T02:25:00, title: Barack Obama: Privatkoch tot in See gefunden, snippet: Tafari Campbell kochte f√ºr Barack Obama im Wei√üen Haus - und auch privat nach dessen Abschied aus dem Pr√§sidentenamt. Nun machte die Polizei in einem Gew√§sser eine traurige Entdeckung., source: SPIEGEL, link: https://www.spiegel.de/panorama/justiz/barack-obama-leibkoch-tot-in-see-gefunden-a-3cdf6377-bee0-43f1-a200-a285742f9ffc]'PreviousDataForSeoNextEden AICommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright ¬© 2023 LangChain, Inc.	This notebook goes over how to use the duck-duck-go search component.	This notebook goes over how to use the duck-duck-go search component. ->: Michelle Obama (59) sind in tiefer Trauer. Ihr Privatkoch Tafari Campbell ist am Montag (24. Juli) ums Leben gekommen, er wurde nur 45 Jahre alt. Laut US-Polizei starb er bei ein, source: BUNTE.de, link: https://www.msn.com/de-de/unterhaltung/other/barack-obama-sein-privatkoch-ist-bei-einem-tragischen-unfall-gestorben/ar-AA1ejrAd], [date: 2023-07-25T02:25:00, title: Barack Obama: Privatkoch tot in See gefunden, snippet: Tafari Campbell kochte f√ºr Barack Obama im Wei√üen Haus - und auch privat nach dessen Abschied aus dem Pr√§sidentenamt. Nun machte die Polizei in einem Gew√§sser eine traurige Entdeckung., source: SPIEGEL, link: https://www.spiegel.de/panorama/justiz/barack-obama-leibkoch-tot-in-see-gefunden-a-3cdf6377-bee0-43f1-a200-a285742f9ffc]'PreviousDataForSeoNextEden AICommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright ¬© 2023 LangChain, Inc.
3,122	AWS Lambda \| ü¶úÔ∏èüîó Langchain	Amazon AWS Lambda is a serverless computing service provided by Amazon Web Services (AWS). It helps developers to build and run applications and services without provisioning or managing servers. This serverless architecture enables you to focus on writing and deploying code, while AWS automatically takes care of scaling, patching, and managing the infrastructure required to run your applications.	Amazon AWS Lambda is a serverless computing service provided by Amazon Web Services (AWS). It helps developers to build and run applications and services without provisioning or managing servers. This serverless architecture enables you to focus on writing and deploying code, while AWS automatically takes care of scaling, patching, and managing the infrastructure required to run your applications. ->: AWS Lambda \| ü¶úÔ∏èüîó Langchain
3,123	Skip to main contentü¶úÔ∏èüîó LangChainDocsUse casesIntegrationsAPICommunityChat our docsLangSmithJS/TS DocsSearchCTRLKProvidersAnthropicAWSGoogleMicrosoftOpenAIMoreComponentsLLMsChat modelsDocument loadersDocument transformersText embedding modelsVector storesRetrieversToolsAlpha VantageApifyArXivAWS LambdaShell (bash)Bearly Code InterpreterBing SearchBrave SearchChatGPT PluginsDall-E Image GeneratorDataForSeoDuckDuckGo SearchEden AIEleven Labs Text2SpeechFile SystemGolden QueryGoogle DriveGoogle PlacesGoogle SearchGoogle SerperGradioGraphQLHuggingFace Hub ToolsHuman as a toolIFTTT WebHooksLemon AgentMetaphor SearchNuclia UnderstandingOpenWeatherMapPubMedRequestsSceneXplainSearch ToolsSearchApiSearxNG SearchSerpAPITwilioWikipediaWolfram AlphaYahoo Finance NewsYouTubeZapier Natural Language ActionsAgents and toolkitsMemoryCallbacksChat loadersComponentsToolsAWS LambdaAWS LambdaAmazon AWS Lambda is a serverless computing service provided by Amazon Web Services (AWS). It helps developers to build and run applications and services without provisioning or managing servers. This serverless architecture enables you to focus on writing and deploying code, while AWS automatically takes care of scaling, patching, and managing the infrastructure required to run your applications.This notebook goes over how to use the AWS Lambda Tool.By including a awslambda in the list of tools provided to an Agent, you can grant your Agent the ability to invoke code running in your AWS Cloud for whatever purposes you need.When an Agent uses the AWS Lambda tool, it will provide an argument of type string which will in turn be passed into the Lambda function via the event parameter.First, you need to install boto3 python package.pip install boto3 > /dev/nullIn order for an agent to use the tool, you must provide it with the name and description that match the functionality of you lambda function's logic. You must also provide the name of your function. Note that because this tool is	Amazon AWS Lambda is a serverless computing service provided by Amazon Web Services (AWS). It helps developers to build and run applications and services without provisioning or managing servers. This serverless architecture enables you to focus on writing and deploying code, while AWS automatically takes care of scaling, patching, and managing the infrastructure required to run your applications.	Amazon AWS Lambda is a serverless computing service provided by Amazon Web Services (AWS). It helps developers to build and run applications and services without provisioning or managing servers. This serverless architecture enables you to focus on writing and deploying code, while AWS automatically takes care of scaling, patching, and managing the infrastructure required to run your applications. ->: Skip to main contentü¶úÔ∏èüîó LangChainDocsUse casesIntegrationsAPICommunityChat our docsLangSmithJS/TS DocsSearchCTRLKProvidersAnthropicAWSGoogleMicrosoftOpenAIMoreComponentsLLMsChat modelsDocument loadersDocument transformersText embedding modelsVector storesRetrieversToolsAlpha VantageApifyArXivAWS LambdaShell (bash)Bearly Code InterpreterBing SearchBrave SearchChatGPT PluginsDall-E Image GeneratorDataForSeoDuckDuckGo SearchEden AIEleven Labs Text2SpeechFile SystemGolden QueryGoogle DriveGoogle PlacesGoogle SearchGoogle SerperGradioGraphQLHuggingFace Hub ToolsHuman as a toolIFTTT WebHooksLemon AgentMetaphor SearchNuclia UnderstandingOpenWeatherMapPubMedRequestsSceneXplainSearch ToolsSearchApiSearxNG SearchSerpAPITwilioWikipediaWolfram AlphaYahoo Finance NewsYouTubeZapier Natural Language ActionsAgents and toolkitsMemoryCallbacksChat loadersComponentsToolsAWS LambdaAWS LambdaAmazon AWS Lambda is a serverless computing service provided by Amazon Web Services (AWS). It helps developers to build and run applications and services without provisioning or managing servers. This serverless architecture enables you to focus on writing and deploying code, while AWS automatically takes care of scaling, patching, and managing the infrastructure required to run your applications.This notebook goes over how to use the AWS Lambda Tool.By including a awslambda in the list of tools provided to an Agent, you can grant your Agent the ability to invoke code running in your AWS Cloud for whatever purposes you need.When an Agent uses the AWS Lambda tool, it will provide an argument of type string which will in turn be passed into the Lambda function via the event parameter.First, you need to install boto3 python package.pip install boto3 > /dev/nullIn order for an agent to use the tool, you must provide it with the name and description that match the functionality of you lambda function's logic. You must also provide the name of your function. Note that because this tool is
3,124	of your function. Note that because this tool is effectively just a wrapper around the boto3 library, you will need to run aws configure in order to make use of the tool. For more detail, see herefrom langchain.llms import OpenAIfrom langchain.agents import load_tools, initialize_agent, AgentTypellm = OpenAI(temperature=0)tools = load_tools( ["awslambda"], awslambda_tool_name="email-sender", awslambda_tool_description="sends an email with the specified content to [email protected]", function_name="testFunction1",)agent = initialize_agent( tools, llm, agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION, verbose=True)agent.run("Send an email to [email protected] saying hello world.")PreviousArXivNextShell (bash)CommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright ¬© 2023 LangChain, Inc.	Amazon AWS Lambda is a serverless computing service provided by Amazon Web Services (AWS). It helps developers to build and run applications and services without provisioning or managing servers. This serverless architecture enables you to focus on writing and deploying code, while AWS automatically takes care of scaling, patching, and managing the infrastructure required to run your applications.	Amazon AWS Lambda is a serverless computing service provided by Amazon Web Services (AWS). It helps developers to build and run applications and services without provisioning or managing servers. This serverless architecture enables you to focus on writing and deploying code, while AWS automatically takes care of scaling, patching, and managing the infrastructure required to run your applications. ->: of your function. Note that because this tool is effectively just a wrapper around the boto3 library, you will need to run aws configure in order to make use of the tool. For more detail, see herefrom langchain.llms import OpenAIfrom langchain.agents import load_tools, initialize_agent, AgentTypellm = OpenAI(temperature=0)tools = load_tools( ["awslambda"], awslambda_tool_name="email-sender", awslambda_tool_description="sends an email with the specified content to [email protected]", function_name="testFunction1",)agent = initialize_agent( tools, llm, agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION, verbose=True)agent.run("Send an email to [email protected] saying hello world.")PreviousArXivNextShell (bash)CommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright ¬© 2023 LangChain, Inc.
3,125	Google Search \| ü¶úÔ∏èüîó Langchain	This notebook goes over how to use the google search component.	This notebook goes over how to use the google search component. ->: Google Search \| ü¶úÔ∏èüîó Langchain
3,126	Skip to main contentü¶úÔ∏èüîó LangChainDocsUse casesIntegrationsAPICommunityChat our docsLangSmithJS/TS DocsSearchCTRLKProvidersAnthropicAWSGoogleMicrosoftOpenAIMoreComponentsLLMsChat modelsDocument loadersDocument transformersText embedding modelsVector storesRetrieversToolsAlpha VantageApifyArXivAWS LambdaShell (bash)Bearly Code InterpreterBing SearchBrave SearchChatGPT PluginsDall-E Image GeneratorDataForSeoDuckDuckGo SearchEden AIEleven Labs Text2SpeechFile SystemGolden QueryGoogle DriveGoogle PlacesGoogle SearchGoogle SerperGradioGraphQLHuggingFace Hub ToolsHuman as a toolIFTTT WebHooksLemon AgentMetaphor SearchNuclia UnderstandingOpenWeatherMapPubMedRequestsSceneXplainSearch ToolsSearchApiSearxNG SearchSerpAPITwilioWikipediaWolfram AlphaYahoo Finance NewsYouTubeZapier Natural Language ActionsAgents and toolkitsMemoryCallbacksChat loadersComponentsToolsGoogle SearchOn this pageGoogle SearchThis notebook goes over how to use the google search component.First, you need to set up the proper API keys and environment variables. To set it up, create the GOOGLE_API_KEY in the Google Cloud credential console (https://console.cloud.google.com/apis/credentials) and a GOOGLE_CSE_ID using the Programmable Search Engine (https://programmablesearchengine.google.com/controlpanel/create). Next, it is good to follow the instructions found here.Then we will need to set some environment variables.import osos.environ["GOOGLE_CSE_ID"] = ""os.environ["GOOGLE_API_KEY"] = ""from langchain.tools import Toolfrom langchain.utilities import GoogleSearchAPIWrappersearch = GoogleSearchAPIWrapper()tool = Tool( name="Google Search", description="Search Google for recent results.", func=search.run,)tool.run("Obama's first name?") "STATE OF HAWAII. 1 Child's First Name. (Type or print). 2. Sex. BARACK. 3. This Birth. CERTIFICATE OF LIVE BIRTH. FILE. NUMBER 151 le. lb. Middle Name. Barack Hussein Obama II is an American former politician who served as the 44th president of the	This notebook goes over how to use the google search component.	This notebook goes over how to use the google search component. ->: Skip to main contentü¶úÔ∏èüîó LangChainDocsUse casesIntegrationsAPICommunityChat our docsLangSmithJS/TS DocsSearchCTRLKProvidersAnthropicAWSGoogleMicrosoftOpenAIMoreComponentsLLMsChat modelsDocument loadersDocument transformersText embedding modelsVector storesRetrieversToolsAlpha VantageApifyArXivAWS LambdaShell (bash)Bearly Code InterpreterBing SearchBrave SearchChatGPT PluginsDall-E Image GeneratorDataForSeoDuckDuckGo SearchEden AIEleven Labs Text2SpeechFile SystemGolden QueryGoogle DriveGoogle PlacesGoogle SearchGoogle SerperGradioGraphQLHuggingFace Hub ToolsHuman as a toolIFTTT WebHooksLemon AgentMetaphor SearchNuclia UnderstandingOpenWeatherMapPubMedRequestsSceneXplainSearch ToolsSearchApiSearxNG SearchSerpAPITwilioWikipediaWolfram AlphaYahoo Finance NewsYouTubeZapier Natural Language ActionsAgents and toolkitsMemoryCallbacksChat loadersComponentsToolsGoogle SearchOn this pageGoogle SearchThis notebook goes over how to use the google search component.First, you need to set up the proper API keys and environment variables. To set it up, create the GOOGLE_API_KEY in the Google Cloud credential console (https://console.cloud.google.com/apis/credentials) and a GOOGLE_CSE_ID using the Programmable Search Engine (https://programmablesearchengine.google.com/controlpanel/create). Next, it is good to follow the instructions found here.Then we will need to set some environment variables.import osos.environ["GOOGLE_CSE_ID"] = ""os.environ["GOOGLE_API_KEY"] = ""from langchain.tools import Toolfrom langchain.utilities import GoogleSearchAPIWrappersearch = GoogleSearchAPIWrapper()tool = Tool( name="Google Search", description="Search Google for recent results.", func=search.run,)tool.run("Obama's first name?") "STATE OF HAWAII. 1 Child's First Name. (Type or print). 2. Sex. BARACK. 3. This Birth. CERTIFICATE OF LIVE BIRTH. FILE. NUMBER 151 le. lb. Middle Name. Barack Hussein Obama II is an American former politician who served as the 44th president of the
3,127	who served as the 44th president of the United States from 2009 to 2017. A member of the Democratic\xa0... When Barack Obama was elected president in 2008, he became the first African American to hold ... The Middle East remained a key foreign policy challenge. Jan 19, 2017 ... Jordan Barack Treasure, New York City, born in 2008 ... Jordan Barack Treasure made national news when he was the focus of a New York newspaper\xa0... Portrait of George Washington, the 1st President of the United States ... Portrait of Barack Obama, the 44th President of the United States\xa0... His full name is Barack Hussein Obama II. Since the ‚ÄúII‚Äù is simply because he was named for his father, his last name is Obama. Mar 22, 2008 ... Barry Obama decided that he didn't like his nickname. A few of his friends at Occidental College had already begun to call him Barack (his\xa0... Aug 18, 2017 ... It took him several seconds and multiple clues to remember former President Barack Obama's first name. Miller knew that every answer had to\xa0... Feb 9, 2015 ... Michael Jordan misspelled Barack Obama's first name on 50th-birthday gift ... Knowing Obama is a Chicagoan and huge basketball fan,\xa0... 4 days ago ... Barack Obama, in full Barack Hussein Obama II, (born August 4, 1961, Honolulu, Hawaii, U.S.), 44th president of the United States (2009‚Äì17) and\xa0..."Number of Results‚ÄãYou can use the k parameter to set the number of resultssearch = GoogleSearchAPIWrapper(k=1)tool = Tool( name="I'm Feeling Lucky", description="Search Google and return the first result.", func=search.run,)tool.run("python") 'The official home of the Python Programming Language.''The official home of the Python Programming Language.'Metadata Results‚ÄãRun query through GoogleSearch and return snippet, title, and link metadata.Snippet: The description of the result.Title: The title of the result.Link: The link to the result.search = GoogleSearchAPIWrapper()def top5_results(query): return	This notebook goes over how to use the google search component.	This notebook goes over how to use the google search component. ->: who served as the 44th president of the United States from 2009 to 2017. A member of the Democratic\xa0... When Barack Obama was elected president in 2008, he became the first African American to hold ... The Middle East remained a key foreign policy challenge. Jan 19, 2017 ... Jordan Barack Treasure, New York City, born in 2008 ... Jordan Barack Treasure made national news when he was the focus of a New York newspaper\xa0... Portrait of George Washington, the 1st President of the United States ... Portrait of Barack Obama, the 44th President of the United States\xa0... His full name is Barack Hussein Obama II. Since the ‚ÄúII‚Äù is simply because he was named for his father, his last name is Obama. Mar 22, 2008 ... Barry Obama decided that he didn't like his nickname. A few of his friends at Occidental College had already begun to call him Barack (his\xa0... Aug 18, 2017 ... It took him several seconds and multiple clues to remember former President Barack Obama's first name. Miller knew that every answer had to\xa0... Feb 9, 2015 ... Michael Jordan misspelled Barack Obama's first name on 50th-birthday gift ... Knowing Obama is a Chicagoan and huge basketball fan,\xa0... 4 days ago ... Barack Obama, in full Barack Hussein Obama II, (born August 4, 1961, Honolulu, Hawaii, U.S.), 44th president of the United States (2009‚Äì17) and\xa0..."Number of Results‚ÄãYou can use the k parameter to set the number of resultssearch = GoogleSearchAPIWrapper(k=1)tool = Tool( name="I'm Feeling Lucky", description="Search Google and return the first result.", func=search.run,)tool.run("python") 'The official home of the Python Programming Language.''The official home of the Python Programming Language.'Metadata Results‚ÄãRun query through GoogleSearch and return snippet, title, and link metadata.Snippet: The description of the result.Title: The title of the result.Link: The link to the result.search = GoogleSearchAPIWrapper()def top5_results(query): return
3,128	top5_results(query): return search.results(query, 5)tool = Tool( name="Google Search Snippets", description="Search Google for recent results.", func=top5_results,)PreviousGoogle PlacesNextGoogle SerperNumber of ResultsMetadata ResultsCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright ¬© 2023 LangChain, Inc.	This notebook goes over how to use the google search component.	This notebook goes over how to use the google search component. ->: top5_results(query): return search.results(query, 5)tool = Tool( name="Google Search Snippets", description="Search Google for recent results.", func=top5_results,)PreviousGoogle PlacesNextGoogle SerperNumber of ResultsMetadata ResultsCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright ¬© 2023 LangChain, Inc.
3,129	Metaphor Search \| ü¶úÔ∏èüîó Langchain	Metaphor is a search engine fully designed to be used by LLMs. You can search and then get the contents for any page.	Metaphor is a search engine fully designed to be used by LLMs. You can search and then get the contents for any page. ->: Metaphor Search \| ü¶úÔ∏èüîó Langchain
3,130	Skip to main contentü¶úÔ∏èüîó LangChainDocsUse casesIntegrationsAPICommunityChat our docsLangSmithJS/TS DocsSearchCTRLKProvidersAnthropicAWSGoogleMicrosoftOpenAIMoreComponentsLLMsChat modelsDocument loadersDocument transformersText embedding modelsVector storesRetrieversToolsAlpha VantageApifyArXivAWS LambdaShell (bash)Bearly Code InterpreterBing SearchBrave SearchChatGPT PluginsDall-E Image GeneratorDataForSeoDuckDuckGo SearchEden AIEleven Labs Text2SpeechFile SystemGolden QueryGoogle DriveGoogle PlacesGoogle SearchGoogle SerperGradioGraphQLHuggingFace Hub ToolsHuman as a toolIFTTT WebHooksLemon AgentMetaphor SearchNuclia UnderstandingOpenWeatherMapPubMedRequestsSceneXplainSearch ToolsSearchApiSearxNG SearchSerpAPITwilioWikipediaWolfram AlphaYahoo Finance NewsYouTubeZapier Natural Language ActionsAgents and toolkitsMemoryCallbacksChat loadersComponentsToolsMetaphor SearchOn this pageMetaphor SearchMetaphor is a search engine fully designed to be used by LLMs. You can search and then get the contents for any page.This notebook goes over how to use Metaphor search.First, you need to set up the proper API keys and environment variables. Get 1000 free searches/month here.Then enter your API key as an environment variable.import osos.environ["METAPHOR_API_KEY"] = "..."Using their SDK‚ÄãThis is the newer and more supported way to use the Metaphor API - via their SDK# !pip install metaphor-pythonfrom metaphor_python import Metaphorclient = Metaphor(api_key=os.environ["METAPHOR_API_KEY"])from langchain.agents import toolfrom typing import List@tooldef search(query: str): """Call search engine with a query.""" return client.search(query, use_autoprompt=True, num_results=5)@tooldef get_contents(ids: List[str]): """Get contents of a webpage. The ids passed in should be a list of ids as fetched from `search`. """ return client.get_contents(ids)@tooldef find_similar(url: str): """Get search results similar to a given URL. The url passed in	Metaphor is a search engine fully designed to be used by LLMs. You can search and then get the contents for any page.	Metaphor is a search engine fully designed to be used by LLMs. You can search and then get the contents for any page. ->: Skip to main contentü¶úÔ∏èüîó LangChainDocsUse casesIntegrationsAPICommunityChat our docsLangSmithJS/TS DocsSearchCTRLKProvidersAnthropicAWSGoogleMicrosoftOpenAIMoreComponentsLLMsChat modelsDocument loadersDocument transformersText embedding modelsVector storesRetrieversToolsAlpha VantageApifyArXivAWS LambdaShell (bash)Bearly Code InterpreterBing SearchBrave SearchChatGPT PluginsDall-E Image GeneratorDataForSeoDuckDuckGo SearchEden AIEleven Labs Text2SpeechFile SystemGolden QueryGoogle DriveGoogle PlacesGoogle SearchGoogle SerperGradioGraphQLHuggingFace Hub ToolsHuman as a toolIFTTT WebHooksLemon AgentMetaphor SearchNuclia UnderstandingOpenWeatherMapPubMedRequestsSceneXplainSearch ToolsSearchApiSearxNG SearchSerpAPITwilioWikipediaWolfram AlphaYahoo Finance NewsYouTubeZapier Natural Language ActionsAgents and toolkitsMemoryCallbacksChat loadersComponentsToolsMetaphor SearchOn this pageMetaphor SearchMetaphor is a search engine fully designed to be used by LLMs. You can search and then get the contents for any page.This notebook goes over how to use Metaphor search.First, you need to set up the proper API keys and environment variables. Get 1000 free searches/month here.Then enter your API key as an environment variable.import osos.environ["METAPHOR_API_KEY"] = "..."Using their SDK‚ÄãThis is the newer and more supported way to use the Metaphor API - via their SDK# !pip install metaphor-pythonfrom metaphor_python import Metaphorclient = Metaphor(api_key=os.environ["METAPHOR_API_KEY"])from langchain.agents import toolfrom typing import List@tooldef search(query: str): """Call search engine with a query.""" return client.search(query, use_autoprompt=True, num_results=5)@tooldef get_contents(ids: List[str]): """Get contents of a webpage. The ids passed in should be a list of ids as fetched from `search`. """ return client.get_contents(ids)@tooldef find_similar(url: str): """Get search results similar to a given URL. The url passed in
3,131	similar to a given URL. The url passed in should be a URL returned from `search` """ return client.find_similar(url, num_results=5)tools = [search, get_contents, find_similar]Use in an agent‚Äãfrom langchain.chat_models import ChatOpenAIllm = ChatOpenAI(temperature=0)from langchain.agents import OpenAIFunctionsAgentfrom langchain.schema import SystemMessagesystem_message = SystemMessage(content="You are a web researcher who uses search engines to look up information.")prompt = OpenAIFunctionsAgent.create_prompt(system_message=system_message)agent = OpenAIFunctionsAgent(llm=llm, tools=tools, prompt=prompt)from langchain.agents import AgentExecutoragent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)agent_executor.run("Find the hottest AI agent startups and what they do") > Entering new AgentExecutor chain... Invoking: `search` with `{'query': 'hottest AI agent startups'}` SearchResponse(results=[Result(title='A Search Engine for Machine Intelligence', url='https://bellow.ai/', id='bdYc6hvHww_JvLv9k8NhPA', score=0.19460266828536987, published_date='2023-01-01', author=None, extract=None), Result(title='Adept: Useful General Intelligence', url='https://www.adept.ai/', id='aNBppxBZvQRZMov6sFVj9g', score=0.19103890657424927, published_date='2000-01-01', author=None, extract=None), Result(title='HiOperator \| Generative AI-Enhanced Customer Service', url='https://www.hioperator.com/', id='jieb6sB53mId3EDo0z-SDw', score=0.18549954891204834, published_date='2000-01-01', author=None, extract=None), Result(title='Home - Stylo', url='https://www.askstylo.com/', id='kUiCuCjJYMD4N0NXdCtqlQ', score=0.1837376356124878, published_date='2000-01-01', author=None, extract=None), Result(title='DirectAI', url='https://directai.io/?utm_source=twitter&utm_medium=raw_message&utm_campaign=first_launch', id='45iSS8KnJ9tL1ilPg3dL9A', score=0.1835256814956665, published_date='2023-01-01', author=None, extract=None),	Metaphor is a search engine fully designed to be used by LLMs. You can search and then get the contents for any page.	Metaphor is a search engine fully designed to be used by LLMs. You can search and then get the contents for any page. ->: similar to a given URL. The url passed in should be a URL returned from `search` """ return client.find_similar(url, num_results=5)tools = [search, get_contents, find_similar]Use in an agent‚Äãfrom langchain.chat_models import ChatOpenAIllm = ChatOpenAI(temperature=0)from langchain.agents import OpenAIFunctionsAgentfrom langchain.schema import SystemMessagesystem_message = SystemMessage(content="You are a web researcher who uses search engines to look up information.")prompt = OpenAIFunctionsAgent.create_prompt(system_message=system_message)agent = OpenAIFunctionsAgent(llm=llm, tools=tools, prompt=prompt)from langchain.agents import AgentExecutoragent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)agent_executor.run("Find the hottest AI agent startups and what they do") > Entering new AgentExecutor chain... Invoking: `search` with `{'query': 'hottest AI agent startups'}` SearchResponse(results=[Result(title='A Search Engine for Machine Intelligence', url='https://bellow.ai/', id='bdYc6hvHww_JvLv9k8NhPA', score=0.19460266828536987, published_date='2023-01-01', author=None, extract=None), Result(title='Adept: Useful General Intelligence', url='https://www.adept.ai/', id='aNBppxBZvQRZMov6sFVj9g', score=0.19103890657424927, published_date='2000-01-01', author=None, extract=None), Result(title='HiOperator \| Generative AI-Enhanced Customer Service', url='https://www.hioperator.com/', id='jieb6sB53mId3EDo0z-SDw', score=0.18549954891204834, published_date='2000-01-01', author=None, extract=None), Result(title='Home - Stylo', url='https://www.askstylo.com/', id='kUiCuCjJYMD4N0NXdCtqlQ', score=0.1837376356124878, published_date='2000-01-01', author=None, extract=None), Result(title='DirectAI', url='https://directai.io/?utm_source=twitter&utm_medium=raw_message&utm_campaign=first_launch', id='45iSS8KnJ9tL1ilPg3dL9A', score=0.1835256814956665, published_date='2023-01-01', author=None, extract=None),
3,132	author=None, extract=None), Result(title='Sidekick AI \| Customer Service Automated', url='https://www.sidekickai.co/', id='nCoPMUtqWQqhUvsdTjJT6A', score=0.18215584754943848, published_date='2020-01-01', author=None, extract=None), Result(title='Hebbia - Search, Reinvented', url='https://www.hebbia.ai/', id='Zy0YaekZdd4rurPQKkys7A', score=0.1799020767211914, published_date='2023-01-01', author=None, extract=None), Result(title='AI.XYZ', url='https://www.ai.xyz/', id='A5c1ePEvsaQeml2Kui_-vA', score=0.1797989457845688, published_date='2023-01-01', author=None, extract=None), Result(title='Halist AI', url='https://halist.ai/', id='-lKPLSb4N4dgMZlTgoDvJg', score=0.17975398898124695, published_date='2023-03-01', author=None, extract=None), Result(title='Clone your best expert', url='https://airin.ai/', id='_XIjx1YLPfI4cKePIEc_bQ', score=0.17957791686058044, published_date='2016-02-12', author=None, extract=None)], api=<metaphor_python.api.Metaphor object at 0x104192140>) Invoking: `get_contents` with `{'ids': ['bdYc6hvHww_JvLv9k8NhPA', 'aNBppxBZvQRZMov6sFVj9g', 'jieb6sB53mId3EDo0z-SDw', 'kUiCuCjJYMD4N0NXdCtqlQ', '45iSS8KnJ9tL1ilPg3dL9A', 'nCoPMUtqWQqhUvsdTjJT6A', 'Zy0YaekZdd4rurPQKkys7A', 'A5c1ePEvsaQeml2Kui_-vA', '-lKPLSb4N4dgMZlTgoDvJg', '_XIjx1YLPfI4cKePIEc_bQ']}` GetContentsResponse(contents=[DocumentContent(id='bdYc6hvHww_JvLv9k8NhPA', url='https://bellow.ai/', title='A Search Engine for Machine Intelligence', extract="<div><div><h2>More Opinions</h2><p>Get responses from multiple AIs</p><p>Don't rely on a single source of truth, explore the full space of machine intelligence and get highly tailored results.</p></div></div>"), DocumentContent(id='aNBppxBZvQRZMov6sFVj9g', url='https://www.adept.ai/', title='Adept: Useful General Intelligence', extract='<div><div><p>Useful <br />General <br />Intelligence</p></div>'), DocumentContent(id='jieb6sB53mId3EDo0z-SDw', url='https://www.hioperator.com/', title='HiOperator \| Generative AI-Enhanced Customer	Metaphor is a search engine fully designed to be used by LLMs. You can search and then get the contents for any page.	Metaphor is a search engine fully designed to be used by LLMs. You can search and then get the contents for any page. ->: author=None, extract=None), Result(title='Sidekick AI \| Customer Service Automated', url='https://www.sidekickai.co/', id='nCoPMUtqWQqhUvsdTjJT6A', score=0.18215584754943848, published_date='2020-01-01', author=None, extract=None), Result(title='Hebbia - Search, Reinvented', url='https://www.hebbia.ai/', id='Zy0YaekZdd4rurPQKkys7A', score=0.1799020767211914, published_date='2023-01-01', author=None, extract=None), Result(title='AI.XYZ', url='https://www.ai.xyz/', id='A5c1ePEvsaQeml2Kui_-vA', score=0.1797989457845688, published_date='2023-01-01', author=None, extract=None), Result(title='Halist AI', url='https://halist.ai/', id='-lKPLSb4N4dgMZlTgoDvJg', score=0.17975398898124695, published_date='2023-03-01', author=None, extract=None), Result(title='Clone your best expert', url='https://airin.ai/', id='_XIjx1YLPfI4cKePIEc_bQ', score=0.17957791686058044, published_date='2016-02-12', author=None, extract=None)], api=<metaphor_python.api.Metaphor object at 0x104192140>) Invoking: `get_contents` with `{'ids': ['bdYc6hvHww_JvLv9k8NhPA', 'aNBppxBZvQRZMov6sFVj9g', 'jieb6sB53mId3EDo0z-SDw', 'kUiCuCjJYMD4N0NXdCtqlQ', '45iSS8KnJ9tL1ilPg3dL9A', 'nCoPMUtqWQqhUvsdTjJT6A', 'Zy0YaekZdd4rurPQKkys7A', 'A5c1ePEvsaQeml2Kui_-vA', '-lKPLSb4N4dgMZlTgoDvJg', '_XIjx1YLPfI4cKePIEc_bQ']}` GetContentsResponse(contents=[DocumentContent(id='bdYc6hvHww_JvLv9k8NhPA', url='https://bellow.ai/', title='A Search Engine for Machine Intelligence', extract="<div><div><h2>More Opinions</h2><p>Get responses from multiple AIs</p><p>Don't rely on a single source of truth, explore the full space of machine intelligence and get highly tailored results.</p></div></div>"), DocumentContent(id='aNBppxBZvQRZMov6sFVj9g', url='https://www.adept.ai/', title='Adept: Useful General Intelligence', extract='<div><div><p>Useful <br />General <br />Intelligence</p></div>'), DocumentContent(id='jieb6sB53mId3EDo0z-SDw', url='https://www.hioperator.com/', title='HiOperator \| Generative AI-Enhanced Customer
3,133	\| Generative AI-Enhanced Customer Service', extract="<div><div><div><div><div><h2>Generative AI-Enhanced Customer Support Automation</h2><p>Flexible, Scalable Customer Support</p></div><div><p></p></div></div><p></p></div><div><div><p>Why HiOperator?</p><h2>Truly scalable customer service</h2><p>A digital-first customer service provider that changes all the rules of what's possible. Scalable. 100% US-Based. Effortless. HiOperator is the digital payoff.</p></div><p></p></div><div><div><p>Next-Gen Customer Service</p><h2>Scaling with HiOperator's Superagents</h2><p>HiOperator is only possible in the digital era. Our revolutionary software connects with your systems to empower our agents to learn quickly and deliver incredible accuracy. </p></div><div><div><p></p><div><h3>Train Us Once</h3><p>We handle all of the recruiting, hiring, and training moving forward. Never have to deal with another classroom retraining or head count headaches.</p></div></div><div><div><h3>Send Us Tickets</h3><p>We pull tickets automatically from your preferred CRM vendor into our custom system. You have full control over <strong>how</strong> and <strong>when</strong> we get tickets.</p></div><p></p></div><div><p></p><div><h3>Pay per resolution</h3><p>We charge for each conversation we solve. No onboarding fees. No hourly rates. Pay for what you use.</p></div></div></div></div><div><p>Customer Experience</p><h2>Insights &√Ç\xa0News</h2></div><div><div><h2>Let's transform your customer service.</h2><p>We can onboard in a matter of days and we offer highly flexible contracts. Whether you need a large team to handle your support or some overflow assistance, getting started is easy.</p></div><p>We can onboard in a matter of days and we offer highly flexible contracts. Whether you need a large team to handle your support or some overflow assistance, getting started is easy.</p></div></div>"), DocumentContent(id='kUiCuCjJYMD4N0NXdCtqlQ', url='https://www.askstylo.com/', title='Home - Stylo',	Metaphor is a search engine fully designed to be used by LLMs. You can search and then get the contents for any page.	Metaphor is a search engine fully designed to be used by LLMs. You can search and then get the contents for any page. ->: \| Generative AI-Enhanced Customer Service', extract="<div><div><div><div><div><h2>Generative AI-Enhanced Customer Support Automation</h2><p>Flexible, Scalable Customer Support</p></div><div><p></p></div></div><p></p></div><div><div><p>Why HiOperator?</p><h2>Truly scalable customer service</h2><p>A digital-first customer service provider that changes all the rules of what's possible. Scalable. 100% US-Based. Effortless. HiOperator is the digital payoff.</p></div><p></p></div><div><div><p>Next-Gen Customer Service</p><h2>Scaling with HiOperator's Superagents</h2><p>HiOperator is only possible in the digital era. Our revolutionary software connects with your systems to empower our agents to learn quickly and deliver incredible accuracy. </p></div><div><div><p></p><div><h3>Train Us Once</h3><p>We handle all of the recruiting, hiring, and training moving forward. Never have to deal with another classroom retraining or head count headaches.</p></div></div><div><div><h3>Send Us Tickets</h3><p>We pull tickets automatically from your preferred CRM vendor into our custom system. You have full control over <strong>how</strong> and <strong>when</strong> we get tickets.</p></div><p></p></div><div><p></p><div><h3>Pay per resolution</h3><p>We charge for each conversation we solve. No onboarding fees. No hourly rates. Pay for what you use.</p></div></div></div></div><div><p>Customer Experience</p><h2>Insights &√Ç\xa0News</h2></div><div><div><h2>Let's transform your customer service.</h2><p>We can onboard in a matter of days and we offer highly flexible contracts. Whether you need a large team to handle your support or some overflow assistance, getting started is easy.</p></div><p>We can onboard in a matter of days and we offer highly flexible contracts. Whether you need a large team to handle your support or some overflow assistance, getting started is easy.</p></div></div>"), DocumentContent(id='kUiCuCjJYMD4N0NXdCtqlQ', url='https://www.askstylo.com/', title='Home - Stylo',
3,134	title='Home - Stylo', extract='<div><div><header><div><p></p><h2>Stop angry customers from breaking support</h2><p></p></div></header><div><p></p><h2><em> </em><strong><em>√¢\x80\x9cWe solve 99 tickets perfectly </em>√∞\x9f\x98\x87<em> but the 1 we miss lands in the CEO√¢\x80\x99s inbox </em>√∞\x9f\x98¬´<em>√¢\x80\x9d<br /></em></strong></h2><p></p><div><p><strong>√¢\x80\x8d</strong>That 1 costly ticket breaks your process, metrics, and the will of your team. Angry customers make support teams less effective, which makes customers angrier in return.<strong><br />√¢\x80\x8d</strong><br />Stylo is AI that tells you where to most effectively spend your time to improve the customer experience. This leads to happier customers, employees, and reduces churn.</p><p>√¢\x80\x8d<strong>No setup, no learning curve, just plug it in and go.</strong></p></div></div><div><div><p></p><div><p>√¢\x80\x9cI√¢\x80\x99m able to better manage the team because I can pinpoint gaps in the team√¢\x80\x99s knowledge or training, and find room for process improvements.√¢\x80\x9d</p><p></p></div></div></div></div>'), DocumentContent(id='45iSS8KnJ9tL1ilPg3dL9A', url='https://directai.io/?utm_source=twitter&utm_medium=raw_message&utm_campaign=first_launch', title='DirectAI', extract="<div><div><div><h2>Vision models without training data.<br /></h2><p>Build and deploy powerful computer vision models with plain language.<br />No code or training required.</p></div><div><h2>Fundamentally different.</h2><p>We use large language models and zero-shot learning to instantly build models that fit your description.</p><br /></div><div><div><p></p><h2>We're removing the last major barrier to creating custom models - <br />training data.</h2><p></p></div><div><table><colgroup></colgroup><thead><tr><th><p>Deploy and iterate in seconds with DirectAI</p></th></tr></thead><tbody><tr><td>‚Ä¢ Don't spend time assembling training data.</td></tr><tr><td>‚Ä¢ Don't pay a third party to label your	Metaphor is a search engine fully designed to be used by LLMs. You can search and then get the contents for any page.	Metaphor is a search engine fully designed to be used by LLMs. You can search and then get the contents for any page. ->: title='Home - Stylo', extract='<div><div><header><div><p></p><h2>Stop angry customers from breaking support</h2><p></p></div></header><div><p></p><h2><em> </em><strong><em>√¢\x80\x9cWe solve 99 tickets perfectly </em>√∞\x9f\x98\x87<em> but the 1 we miss lands in the CEO√¢\x80\x99s inbox </em>√∞\x9f\x98¬´<em>√¢\x80\x9d<br /></em></strong></h2><p></p><div><p><strong>√¢\x80\x8d</strong>That 1 costly ticket breaks your process, metrics, and the will of your team. Angry customers make support teams less effective, which makes customers angrier in return.<strong><br />√¢\x80\x8d</strong><br />Stylo is AI that tells you where to most effectively spend your time to improve the customer experience. This leads to happier customers, employees, and reduces churn.</p><p>√¢\x80\x8d<strong>No setup, no learning curve, just plug it in and go.</strong></p></div></div><div><div><p></p><div><p>√¢\x80\x9cI√¢\x80\x99m able to better manage the team because I can pinpoint gaps in the team√¢\x80\x99s knowledge or training, and find room for process improvements.√¢\x80\x9d</p><p></p></div></div></div></div>'), DocumentContent(id='45iSS8KnJ9tL1ilPg3dL9A', url='https://directai.io/?utm_source=twitter&utm_medium=raw_message&utm_campaign=first_launch', title='DirectAI', extract="<div><div><div><h2>Vision models without training data.<br /></h2><p>Build and deploy powerful computer vision models with plain language.<br />No code or training required.</p></div><div><h2>Fundamentally different.</h2><p>We use large language models and zero-shot learning to instantly build models that fit your description.</p><br /></div><div><div><p></p><h2>We're removing the last major barrier to creating custom models - <br />training data.</h2><p></p></div><div><table><colgroup></colgroup><thead><tr><th><p>Deploy and iterate in seconds with DirectAI</p></th></tr></thead><tbody><tr><td>‚Ä¢ Don't spend time assembling training data.</td></tr><tr><td>‚Ä¢ Don't pay a third party to label your
3,135	Don't pay a third party to label your data.</td></tr><tr><td>‚Ä¢ Don't pay to train your model.</td></tr><tr><td>‚Ä¢ Don't spend months finetuning your model's behavior.</td></tr></tbody></table></div></div><div><h2>Venture-backed.<p>Based in NYC.</p><p>We're changing how people use AI in the real world.</p><p>Come talk to us on .</p></h2></div></div></div>"), DocumentContent(id='nCoPMUtqWQqhUvsdTjJT6A', url='https://www.sidekickai.co/', title='Sidekick AI \| Customer Service Automated', extract='<div><div><div><div><div><div><div><p>Hi, I am an AI named Jenny, working at Pizza Planet. How can I help you today?</p></div><div><p>How much are large pizzas with 1 topping?</p></div><div><p>For most toppings, a large with one topping would be $10.99.</p></div><div><p>Ok, can I order a large with pepperoni</p></div><div><p>Sure! Takeout or delivery?</p></div><div><p>Alright, order placed. See you at 5 pm!</p></div></div><div><p></p></div></div><p></p></div><div><p>Meet Sidekick</p><div><p>\n Sidekick is an AI agent built to hold natural and dynamic conversations with your customers and talk just like a human.</p><p>Built on the world\'s most advanced AI models, Sidekick pushes the state of the art in natural conversation and converses seamlessly with your customers.\n </p></div><p>Try it out ‚ûú</p><p>Try it out ‚Üì</p></div><div><p>An AI agent designed for <strong>service-led growth.</strong></p><div><div><p></p><p>Personal</p><p>Every customer is different, and has unique needs. Our agents are built to provide personalized service depending on the customer\'s needs.</p></div><div><p></p><p>Fast</p><p>Unlike humans, our Sidekicks respond near-instantly, any time of the day. Your customers won\'t wait for service ever again.</p></div><div><p></p><p>Effective</p><p>Customers love great service, and Sidekick delivers. Grow revenue by solving issues in minutes instead of hours, and providing personalized support to each customer.</p></div></div></div><div><p>Integrating with	Metaphor is a search engine fully designed to be used by LLMs. You can search and then get the contents for any page.	Metaphor is a search engine fully designed to be used by LLMs. You can search and then get the contents for any page. ->: Don't pay a third party to label your data.</td></tr><tr><td>‚Ä¢ Don't pay to train your model.</td></tr><tr><td>‚Ä¢ Don't spend months finetuning your model's behavior.</td></tr></tbody></table></div></div><div><h2>Venture-backed.<p>Based in NYC.</p><p>We're changing how people use AI in the real world.</p><p>Come talk to us on .</p></h2></div></div></div>"), DocumentContent(id='nCoPMUtqWQqhUvsdTjJT6A', url='https://www.sidekickai.co/', title='Sidekick AI \| Customer Service Automated', extract='<div><div><div><div><div><div><div><p>Hi, I am an AI named Jenny, working at Pizza Planet. How can I help you today?</p></div><div><p>How much are large pizzas with 1 topping?</p></div><div><p>For most toppings, a large with one topping would be $10.99.</p></div><div><p>Ok, can I order a large with pepperoni</p></div><div><p>Sure! Takeout or delivery?</p></div><div><p>Alright, order placed. See you at 5 pm!</p></div></div><div><p></p></div></div><p></p></div><div><p>Meet Sidekick</p><div><p>\n Sidekick is an AI agent built to hold natural and dynamic conversations with your customers and talk just like a human.</p><p>Built on the world\'s most advanced AI models, Sidekick pushes the state of the art in natural conversation and converses seamlessly with your customers.\n </p></div><p>Try it out ‚ûú</p><p>Try it out ‚Üì</p></div><div><p>An AI agent designed for <strong>service-led growth.</strong></p><div><div><p></p><p>Personal</p><p>Every customer is different, and has unique needs. Our agents are built to provide personalized service depending on the customer\'s needs.</p></div><div><p></p><p>Fast</p><p>Unlike humans, our Sidekicks respond near-instantly, any time of the day. Your customers won\'t wait for service ever again.</p></div><div><p></p><p>Effective</p><p>Customers love great service, and Sidekick delivers. Grow revenue by solving issues in minutes instead of hours, and providing personalized support to each customer.</p></div></div></div><div><p>Integrating with
3,136	with <strong>your tools.</strong></p></div><div><p><strong>Wherever </strong>your customers are.</p><p>\n Sidekick takes an omnichannel approach to customer service, aggregating all customer interactions across all platforms in one area. Currently most social media platforms are supported, along with website embeddings and API integration.\n </p><div><div><div><p>On the web.</p><div><p>Sidekick makes adding a live chat to your website as simple as copy and pasting a single line of code.</p><p>Chat bubbles discretely sit in the bottom right corner and provide a smooth conversation experience, with AI and human agents alike.</p></div></div><p></p><p></p></div><div><div><p>On Facebook.</p><div><p>Sidekick integrates with your Facebook pages to make live customer service one click away.</p><p>Customers can reach your agent and get service without ever leaving Messenger.</p></div></div><p></p><p></p></div><div><div><p>On Instagram.</p><div><p>E-Commerce on Instagram is especially demanding for customer service.</p><p>Sidekick integrates easily with Instagram accounts to put a live agent one click away.</p></div></div><p></p><p></p></div><div><div><p>On Twitter.</p><div><p>Customers are spending more time on Twitter, which means businesses should provide customer service right on the platform.</p><p>Sidekick integrates easily with Twitter accounts to put a live agent one click away.</p></div></div><p></p><p></p></div><div><div><p>Anywhere you want.</p><div><p>Our API provides programmatic access to your Sidekick agent to integrate into your own app.</p><p>We\'ve built simple abstractions over the chat interface to make it easy to work with our API.</p></div></div><div><div><p>Endpoints</p><div><p>POST</p><p>https://www.api.sidekickai.co/converse</p></div></div><div><p>Sample Request</p><div><pre>{\n "access_token": "KjZUZBWAOKwgLWAlVFyL",\n "conversation_id": "23874",\n "body": "How much is a large 2 topping?"\n}</pre></div></div><div><p>Sample Response</p><div><pre>{\n	Metaphor is a search engine fully designed to be used by LLMs. You can search and then get the contents for any page.	Metaphor is a search engine fully designed to be used by LLMs. You can search and then get the contents for any page. ->: with <strong>your tools.</strong></p></div><div><p><strong>Wherever </strong>your customers are.</p><p>\n Sidekick takes an omnichannel approach to customer service, aggregating all customer interactions across all platforms in one area. Currently most social media platforms are supported, along with website embeddings and API integration.\n </p><div><div><div><p>On the web.</p><div><p>Sidekick makes adding a live chat to your website as simple as copy and pasting a single line of code.</p><p>Chat bubbles discretely sit in the bottom right corner and provide a smooth conversation experience, with AI and human agents alike.</p></div></div><p></p><p></p></div><div><div><p>On Facebook.</p><div><p>Sidekick integrates with your Facebook pages to make live customer service one click away.</p><p>Customers can reach your agent and get service without ever leaving Messenger.</p></div></div><p></p><p></p></div><div><div><p>On Instagram.</p><div><p>E-Commerce on Instagram is especially demanding for customer service.</p><p>Sidekick integrates easily with Instagram accounts to put a live agent one click away.</p></div></div><p></p><p></p></div><div><div><p>On Twitter.</p><div><p>Customers are spending more time on Twitter, which means businesses should provide customer service right on the platform.</p><p>Sidekick integrates easily with Twitter accounts to put a live agent one click away.</p></div></div><p></p><p></p></div><div><div><p>Anywhere you want.</p><div><p>Our API provides programmatic access to your Sidekick agent to integrate into your own app.</p><p>We\'ve built simple abstractions over the chat interface to make it easy to work with our API.</p></div></div><div><div><p>Endpoints</p><div><p>POST</p><p>https://www.api.sidekickai.co/converse</p></div></div><div><p>Sample Request</p><div><pre>{\n "access_token": "KjZUZBWAOKwgLWAlVFyL",\n "conversation_id": "23874",\n "body": "How much is a large 2 topping?"\n}</pre></div></div><div><p>Sample Response</p><div><pre>{\n
3,137	Response</p><div><pre>{\n "response": "A large'), DocumentContent(id='Zy0YaekZdd4rurPQKkys7A', url='https://www.hebbia.ai/', title='Hebbia - Search, Reinvented', extract="<div><div><h2>Direct to the point <br />with cutting-edge AI.</h2><p>Stop relying on archaic software, traditional Q&A emails, or waiting for deal partners. Get answers on your own time with accuracy that you can't replicate with humans. <br />√¢\x80\x8d<br /></p><p>Hebbia√Ç\xa0retrieves <strong>every</strong> answer, even insights humans overlook. <br /></p></div>"), DocumentContent(id='A5c1ePEvsaQeml2Kui_-vA', url='https://www.ai.xyz/', title='AI.XYZ', extract='<div><div>\n \n \n<article>\n \n \n \n \n \n<div><div>\n<p><h2><strong>Go be human</strong></h2></p>\n</div><div><p>\n</p><h4>Let your AI deal with the rest</h4>\n<p></p></div><div><p>Design your own AI with AI.XYZ</p></div><div>\n \n \n \n <p></p>\n \n </div></div>\n \n \n \n \n<div><p>\n</p><h3><strong>The digital world was designed to make us more productive but now navigating it all has become its own job.</strong></h3>\n<p></p></div>\n \n \n \n \n<section>\n <div>\n \n \n \n \n \n \n \n \n <p></p>\n \n \n </div>\n <div><div><p>\n</p><h2><strong>Take life a little easier</strong></h2>\n<p></p></div><div>\n \n \n \n <p></p>\n \n </div><div><p>\n</p><h2><strong>Tackles info<br />overload</strong></h2>\n<p></p></div><div><p>\n</p><h4>‚ÄúLike ChatGPT, but way more proactive and useful because it‚Äôs designed by me, for only me‚Äù</h4>\n<p></p></div><div>\n \n \n \n <p></p>\n \n </div><div><p>\n</p><h2><strong>Never sits<br />around</strong></h2>\n<p></p></div><div><p>\n</p><h4>‚ÄúEven if I‚Äôm not interacting with it, my AI looks for ways to simplify my day, surprising me with useful ideas‚Äù</h4>\n<p></p></div><div>\n \n \n \n <p></p>\n \n </div><div><p>\n</p><h2><strong>Supports and<br />inspires</strong></h2>\n<p></p></div><div><p>\n</p><h4>‚ÄúIt takes things off my plate, but also cheers me on throughout the day ‚Äî helping me	Metaphor is a search engine fully designed to be used by LLMs. You can search and then get the contents for any page.	Metaphor is a search engine fully designed to be used by LLMs. You can search and then get the contents for any page. ->: Response</p><div><pre>{\n "response": "A large'), DocumentContent(id='Zy0YaekZdd4rurPQKkys7A', url='https://www.hebbia.ai/', title='Hebbia - Search, Reinvented', extract="<div><div><h2>Direct to the point <br />with cutting-edge AI.</h2><p>Stop relying on archaic software, traditional Q&A emails, or waiting for deal partners. Get answers on your own time with accuracy that you can't replicate with humans. <br />√¢\x80\x8d<br /></p><p>Hebbia√Ç\xa0retrieves <strong>every</strong> answer, even insights humans overlook. <br /></p></div>"), DocumentContent(id='A5c1ePEvsaQeml2Kui_-vA', url='https://www.ai.xyz/', title='AI.XYZ', extract='<div><div>\n \n \n<article>\n \n \n \n \n \n<div><div>\n<p><h2><strong>Go be human</strong></h2></p>\n</div><div><p>\n</p><h4>Let your AI deal with the rest</h4>\n<p></p></div><div><p>Design your own AI with AI.XYZ</p></div><div>\n \n \n \n <p></p>\n \n </div></div>\n \n \n \n \n<div><p>\n</p><h3><strong>The digital world was designed to make us more productive but now navigating it all has become its own job.</strong></h3>\n<p></p></div>\n \n \n \n \n<section>\n <div>\n \n \n \n \n \n \n \n \n <p></p>\n \n \n </div>\n <div><div><p>\n</p><h2><strong>Take life a little easier</strong></h2>\n<p></p></div><div>\n \n \n \n <p></p>\n \n </div><div><p>\n</p><h2><strong>Tackles info<br />overload</strong></h2>\n<p></p></div><div><p>\n</p><h4>‚ÄúLike ChatGPT, but way more proactive and useful because it‚Äôs designed by me, for only me‚Äù</h4>\n<p></p></div><div>\n \n \n \n <p></p>\n \n </div><div><p>\n</p><h2><strong>Never sits<br />around</strong></h2>\n<p></p></div><div><p>\n</p><h4>‚ÄúEven if I‚Äôm not interacting with it, my AI looks for ways to simplify my day, surprising me with useful ideas‚Äù</h4>\n<p></p></div><div>\n \n \n \n <p></p>\n \n </div><div><p>\n</p><h2><strong>Supports and<br />inspires</strong></h2>\n<p></p></div><div><p>\n</p><h4>‚ÄúIt takes things off my plate, but also cheers me on throughout the day ‚Äî helping me
3,138	cheers me on throughout the day ‚Äî helping me navigate it all‚Äù</h4>\n<p></p></div></div>\n \n \n</section>\n \n \n \n \n<div><div><p>\n</p><h2><strong>Create your AI in 3 simple steps:</strong></h2>\n<p></p></div><div>\n<p><strong>STEP ONE</strong></p><h2><strong>Pick a face and voice</strong></h2><h4>Choose from our library of characters or add your own unique face and voice.</h4>\n</div><div>\n \n \n \n <p></p>\n \n </div><div>\n<p><strong>STEP TWO</strong></p><h2><strong>Create your AI‚Äôs persona and memory</strong></h2><h4>Decide who your AI is, its purpose and what it will help you with. Paste information that you want your AI to know.</h4>\n</div><div>\n \n \n \n <p></p>\n \n </div><div>\n<p><strong>STEP THREE</strong></p><h2><strong>Get started</strong></h2><h4>Ask your AI to help you with ideas and support throughout your day. Eventually it will be able to proactively support you.</h4>\n</div><div>\n \n \n \n <p></p>\n \n </div></div>\n \n \n \n \n<section>\n <div>\n \n \n \n \n \n \n \n \n <p></p>\n \n \n </div>\n <div><p>\n</p><h2><strong>Start training your AI to do things for you</strong></h2>\n<p></p></div>\n \n \n</section>\n \n</article>\n \n \n \n \n \n </div></div'), DocumentContent(id='-lKPLSb4N4dgMZlTgoDvJg', url='https://halist.ai/', title='Halist AI', extract='<div><div>\n<p><a href="/app/">Start for free</a></p><p>\nPowered by OpenAI GPT-3 and GPT-4.\n</p>\n<h2>ChatGPT. Lightning-fast and private. Everywhere.</h2>\n<h2>Optimized access to the AI on mobile.</h2>\n<p></p><p>\nTo install Halist on <b>iPhone</b>, open the web app in Safari and tap the "Share" icon. Then, tap "Add to Home Screen" and follow the prompts.\nTo install on <b>Android</b>, open the website in Chrome and tap the three dots in the top right corner. Then, tap "Add to Home screen" and follow the prompts.\n</p>\n</div></div>'), DocumentContent(id='_XIjx1YLPfI4cKePIEc_bQ', url='https://airin.ai/', title='Clone your best expert', extract='<div><section><section><div><p>	Metaphor is a search engine fully designed to be used by LLMs. You can search and then get the contents for any page.	Metaphor is a search engine fully designed to be used by LLMs. You can search and then get the contents for any page. ->: cheers me on throughout the day ‚Äî helping me navigate it all‚Äù</h4>\n<p></p></div></div>\n \n \n</section>\n \n \n \n \n<div><div><p>\n</p><h2><strong>Create your AI in 3 simple steps:</strong></h2>\n<p></p></div><div>\n<p><strong>STEP ONE</strong></p><h2><strong>Pick a face and voice</strong></h2><h4>Choose from our library of characters or add your own unique face and voice.</h4>\n</div><div>\n \n \n \n <p></p>\n \n </div><div>\n<p><strong>STEP TWO</strong></p><h2><strong>Create your AI‚Äôs persona and memory</strong></h2><h4>Decide who your AI is, its purpose and what it will help you with. Paste information that you want your AI to know.</h4>\n</div><div>\n \n \n \n <p></p>\n \n </div><div>\n<p><strong>STEP THREE</strong></p><h2><strong>Get started</strong></h2><h4>Ask your AI to help you with ideas and support throughout your day. Eventually it will be able to proactively support you.</h4>\n</div><div>\n \n \n \n <p></p>\n \n </div></div>\n \n \n \n \n<section>\n <div>\n \n \n \n \n \n \n \n \n <p></p>\n \n \n </div>\n <div><p>\n</p><h2><strong>Start training your AI to do things for you</strong></h2>\n<p></p></div>\n \n \n</section>\n \n</article>\n \n \n \n \n \n </div></div'), DocumentContent(id='-lKPLSb4N4dgMZlTgoDvJg', url='https://halist.ai/', title='Halist AI', extract='<div><div>\n<p><a href="/app/">Start for free</a></p><p>\nPowered by OpenAI GPT-3 and GPT-4.\n</p>\n<h2>ChatGPT. Lightning-fast and private. Everywhere.</h2>\n<h2>Optimized access to the AI on mobile.</h2>\n<p></p><p>\nTo install Halist on <b>iPhone</b>, open the web app in Safari and tap the "Share" icon. Then, tap "Add to Home Screen" and follow the prompts.\nTo install on <b>Android</b>, open the website in Chrome and tap the three dots in the top right corner. Then, tap "Add to Home screen" and follow the prompts.\n</p>\n</div></div>'), DocumentContent(id='_XIjx1YLPfI4cKePIEc_bQ', url='https://airin.ai/', title='Clone your best expert', extract='<div><section><section><div><p>
3,139	expert', extract='<div><section><section><div><p> Airin clones how your top expert solves problems in as little as 2 hours. Airin creates an AI companion for the rest of your team by focusing on the patterns in your expert‚Äôs questions and hypotheses, not their answers. <a href="/how-it-works">Learn how it works </a></p></div></section><section><div><p> Your customers, agents, sales teams, and consultants can independently solve a wider-range of complex problems with an AI companion. This eliminates the need to maintain large teams of specialized experts. </p></div></section><section><div><p> Airin automates remote coaching for new hires and dramatically reduces time to productivity. New employees partner with your AI companion and meet productivity standards in half the time. </p></div></section></section>')])Here are some of the hottest AI agent startups and what they do: 1. [Bellow AI](https://bellow.ai/): This startup provides a search engine for machine intelligence. It allows users to get responses from multiple AIs, exploring the full space of machine intelligence and getting highly tailored results. 2. [Adept AI](https://www.adept.ai/): Adept is focused on creating useful general intelligence. 3. [HiOperator](https://www.hioperator.com/): HiOperator offers generative AI-enhanced customer support automation. It provides scalable, digital-first customer service and uses its software to empower agents to learn quickly and deliver accurate results. 4. [Stylo](https://www.askstylo.com/): Stylo uses AI to help manage customer support, identifying where to most effectively spend time to improve the customer experience. 5. [DirectAI](https://directai.io/): DirectAI allows users to build and deploy powerful computer vision models with plain language, without the need for code or training. 6. [Sidekick AI](https://www.sidekickai.co/): Sidekick AI is built to hold natural and dynamic conversations with customers, providing	Metaphor is a search engine fully designed to be used by LLMs. You can search and then get the contents for any page.	Metaphor is a search engine fully designed to be used by LLMs. You can search and then get the contents for any page. ->: expert', extract='<div><section><section><div><p> Airin clones how your top expert solves problems in as little as 2 hours. Airin creates an AI companion for the rest of your team by focusing on the patterns in your expert‚Äôs questions and hypotheses, not their answers. <a href="/how-it-works">Learn how it works </a></p></div></section><section><div><p> Your customers, agents, sales teams, and consultants can independently solve a wider-range of complex problems with an AI companion. This eliminates the need to maintain large teams of specialized experts. </p></div></section><section><div><p> Airin automates remote coaching for new hires and dramatically reduces time to productivity. New employees partner with your AI companion and meet productivity standards in half the time. </p></div></section></section>')])Here are some of the hottest AI agent startups and what they do: 1. [Bellow AI](https://bellow.ai/): This startup provides a search engine for machine intelligence. It allows users to get responses from multiple AIs, exploring the full space of machine intelligence and getting highly tailored results. 2. [Adept AI](https://www.adept.ai/): Adept is focused on creating useful general intelligence. 3. [HiOperator](https://www.hioperator.com/): HiOperator offers generative AI-enhanced customer support automation. It provides scalable, digital-first customer service and uses its software to empower agents to learn quickly and deliver accurate results. 4. [Stylo](https://www.askstylo.com/): Stylo uses AI to help manage customer support, identifying where to most effectively spend time to improve the customer experience. 5. [DirectAI](https://directai.io/): DirectAI allows users to build and deploy powerful computer vision models with plain language, without the need for code or training. 6. [Sidekick AI](https://www.sidekickai.co/): Sidekick AI is built to hold natural and dynamic conversations with customers, providing