4 Commits (e367ee71e722001987d75fa0140bb95cf40d3ec6)

Author	SHA1	Message	Date
blob42	3d54b05863	searx: add install instructions, update doc and notebooks (#1420) ... - Added instructions on setting up self hosted searx - Add notebook example with agent - Use `localhost:8888` as example url to stay consistent since public instances are not really usable. Co-authored-by: blob42 <spike@w530>	1 year ago
Ankush Gola	7b5e160d28	Make Tools own model, add ToolKit Concept (#1095) ... Follow-up of @hinthornw's PR: - Migrate the Tool abstraction to a separate file (`BaseTool`). - `Tool` implementation of `BaseTool` takes in function and coroutine to more easily maintain backwards compatibility - Add a Toolkit abstraction that can own the generation of tools around a shared concept or state --------- Co-authored-by: William FH <13333726+hinthornw@users.noreply.github.com> Co-authored-by: Harrison Chase <hw.chase.17@gmail.com> Co-authored-by: Francisco Ingham <fpingham@gmail.com> Co-authored-by: Dhruv Anand <105786647+dhruv-anand-aintech@users.noreply.github.com> Co-authored-by: cragwolfe <cragcw@gmail.com> Co-authored-by: Anton Troynikov <atroyn@users.noreply.github.com> Co-authored-by: Oliver Klingefjord <oliver@klingefjord.com> Co-authored-by: William Fu-Hinthorn <whinthorn@Williams-MBP-3.attlocal.net> Co-authored-by: Bruno Bornsztein <bruno.bornsztein@gmail.com>	1 year ago
rogerserper	e46cd3b7db	Google Search API integration with serper.dev (wrapper, tests, docs, … (#909) ... Adds Google Search integration with [Serper](https://serper.dev) a low-cost alternative to SerpAPI (10x cheaper + generous free tier). Includes documentation, tests and examples. Hopefully I am not missing anything. Developers can sign up for a free account at [serper.dev](https://serper.dev) and obtain an api key. ## Usage ```python from langchain.utilities import GoogleSerperAPIWrapper from langchain.llms.openai import OpenAI from langchain.agents import initialize_agent, Tool import os os.environ["SERPER_API_KEY"] = "" os.environ['OPENAI_API_KEY'] = "" llm = OpenAI(temperature=0) search = GoogleSerperAPIWrapper() tools = [ Tool( name="Intermediate Answer", func=search.run ) ] self_ask_with_search = initialize_agent(tools, llm, agent="self-ask-with-search", verbose=True) self_ask_with_search.run("What is the hometown of the reigning men's U.S. Open champion?") ``` ### Output ``` Entering new AgentExecutor chain... Yes. Follow up: Who is the reigning men's U.S. Open champion? Intermediate answer: Current champions Carlos Alcaraz, 2022 men's singles champion. Follow up: Where is Carlos Alcaraz from? Intermediate answer: El Palmar, Spain So the final answer is: El Palmar, Spain > Finished chain. 'El Palmar, Spain' ```	1 year ago
Harrison Chase	985496f4be	Docs refactor (#480) ... Big docs refactor! Motivation is to make it easier for people to find resources they are looking for. To accomplish this, there are now three main sections: - Getting Started: steps for getting started, walking through most core functionality - Modules: these are different modules of functionality that langchain provides. Each part here has a "getting started", "how to", "key concepts" and "reference" section (except in a few select cases where it didnt easily fit). - Use Cases: this is to separate use cases (like summarization, question answering, evaluation, etc) from the modules, and provide a different entry point to the code base. There is also a full reference section, as well as extra resources (glossary, gallery, etc) Co-authored-by: Shreya Rajpal <ShreyaR@users.noreply.github.com>	1 year ago