Langchain api chain.

• Langchain api chain com to sign up to OpenAI and generate an API key. Returns This page covers how to use the SearchApi Google Search API within LangChain. retrievers. api. __call__ is that this method expects inputs to be passed directly in as positional arguments or keyword arguments, whereas Chain. type (e. combine_documents import create_stuff_documents_chain prompt = ChatPromptTemplate. adapters ¶. Like building any type of software, at some point you'll need to debug when building with LLMs. prompts import ChatPromptTemplate from langchain. Concretely, the framework consists of the following open-source libraries: langchain-core: Base abstractions and LangChain Expression Language. Still, this is a great way to get started with LangChain - a lot of features can be built with just some prompting and an LLM call! Important LangChain primitives like LLMs, parsers, prompts, retrievers, and agents implement the LangChain Runnable Interface. The relevant tool to answer this is the GetWeather function. prompt import API_RESPONSE_PROMPT Class that extends BaseChain and represents a chain specifically designed for making API requests and processing API responses. This can be useful to apply on both user input, but also on the output of a Language Model. documents import Document from langchain_core. ernie_functions. com. invoke ({"question": "What is LangChain?" API Reference: ChatPromptTemplate | OllamaLLM "Sounds like a plan!\n\nTo answer what LangChain is, let's break it down step by step. In order to construct such a chain, we will pass in: operation, llm, requests=Requests(), verbose=True, return_intermediate_steps=True, # Return request and response text. run, description = "useful for when you need to ask with search",)] Jul 3, 2023 · Prepare chain inputs, including adding inputs from memory. Agent is a class that uses an LLM to choose a sequence of actions to take. GraphQAChain [source] ¶ Bases: Chain. If True, only To access OpenAI models you'll need to create an OpenAI account, get an API key, and install the langchain-openai integration package. Jul 3, 2023 · class langchain. OpenAIModerationChain [source] ¶. The LangChain Expression Language (LCEL) offers a declarative method to build production-grade programs that harness the power of LLMs. langchain==0. Deployment: Turn any chain into an API with LangServe. \n\n**Step 1: Understand the Context**\nLangChain seems to be related to language or programming, possibly in an AI context. We first call llm_chain on each document individually, passing in the page_content and any other kwargs. You can find your API key in the Azure portal under your Azure OpenAI resource. requests import Requests from langchain langchain-core defines the base abstractions for the LangChain ecosystem. A list of built-in Runnables can be found in the LangChain Core API Reference. Deploy and scale with LangGraph Platform, with APIs for state management, a visual studio for debugging, and multiple deployment options. However, all that is being done under the hood is constructing a chain with LCEL. Parameters: inputs (Dict[str, Any] | Any) – Dictionary of inputs, or single input if chain expects only one param. DocumentTransformer: Object that performs a transformation on a list of Document objects. This highlights functionality that is core to using LangChain. There are two primary ways to interface LLMs with external APIs: Functions: For example, OpenAI functions is one popular means of doing this. Welcome to the LangChain Python API reference. agents ¶. chains. If your API requires authentication or other headers, you can pass the chain a headers property in the config object. Ollama bundles model weights, configuration, and data into a single package, defined by a Modelfile. 以前のバージョンのLangChainで使用されていた、サブクラス化によって構築されたチェーン。 今後LCELベースのチェーンに置き換えられる予定で、新たにチェーンを構築する際にはLCELの使用が推奨されています。 Welcome to the LangChain Python API reference. That's where LangServe comes in. langgraph : Orchestration framework for combining LangChain components into production-ready applications with persistence, streaming, and other key features. to make GET, POST, PATCH, PUT, and DELETE requests to an API. LLMChainExtractor. If you're looking to get started with chat models, vector stores, or other LangChain components from a specific provider, check out our supported integrations. combine_documents. Help us out by providing feedback on this documentation page: Dec 9, 2024 · LangChain Runnable and the LangChain Expression Language (LCEL). graph_qa. invoke (** fields) for chunk in llm. chains. output = chain("whats the most expensive shirt?") Feb 6, 2025 · LangChain is a Python module that allows you to develop applications powered by language models. chain_filter. The __call__ method is the primary way to. OpenAPIEndpointChain¶ class langchain. Returns chain. How to migrate from v0. LLMChainFilter 使用LangChain通常需要与一个或多个模型提供程序、数据存储、API等进行集成。 LangChain中的Chain链由链接组成，可以是像LLM或 Runnables created using the LangChain Expression Language (LCEL) can also be run asynchronously as they implement the full Runnable Interface. base. LLM-generated interface: Use an LLM with access to API documentation to create an interface. tools. Bases: Chain Pass input through a moderation endpoint. APIs act as the "front door" for applications to access data, business logic, or functionality from your backend services. Execute the chain. Adapters are used to adapt LangChain models to other APIs. Chains refer to sequences of calls - whether to an LLM, a tool, or a data preprocessing step. In Chains, a sequence of actions is hardcoded. LangChain Expression Language is a way to create arbitrary custom chains. document_compressors. Returns How to debug your LLM apps. html Chain that makes API calls and summarizes the responses to answer a question. When contributing an implementation to LangChain, carefully document Execute the chain. CPAL improves upon the program-aided language ( PAL ) by incorporating causal structure to prevent hallucination in language models, particularly when dealing with complex narratives and math problems with Create a RunnableBinding from a Runnable and kwargs. , and provide a simple interface to this sequence. 19¶ langchain_community. (Python only) LangSmith: A developer platform that lets you debug, test, evaluate, and monitor chains built on any LLM framework and seamlessly integrates with LangChain. Dec 9, 2024 · """Chain that makes API calls and summarizes the responses to answer a question. Output is streamed as Log objects, which include a list of jsonpatch ops that describe how the state of the run has changed in each step, and the final state of the run. Stream all output from a runnable, as reported to the callback system. arangodb. Returns: May 8, 2024 · Source code for langchain. 0 chains to the new abstractions. The primary supported way to do this is with LCEL. There are two types of off-the-shelf chains that LangChain supports: Chains that are built with LCEL. This application will translate text from English into another language. How to: return structured data from an LLM; How to: use a chat model to call tools; How to: stream runnables; How to: debug your LLM apps; LangChain Expression Language (LCEL) LangChain Expression Language is a way to create arbitrary custom chains. Jan 29, 2025 · LangChainの基本要素 1. Standard parameters Many chat models have standardized parameters that can be used to configure the model: Jan 23, 2024 · 前两周本地搭建了Llama环境以后，试图想要解决一下真实的问题，所以进行了新的探索和尝试。 希望达到的效果是，根据用户提的针对性问题，生成API request并且查询获得结果，对API返回的结果进行有上下文的推理。 … Prepare chain inputs, including adding inputs from memory. Chat models Bedrock Chat . openapi import OpenAPISpec from langchain_core. inputs (Union[Dict[str, Any], Any]) – Dictionary of inputs, or single input if chain expects only one param. Now that we've built an application, we need to serve it. prompts import ChatPromptTemplate from langchain_openai import ChatOpenAI # Define API spec. We can now construct a chain to interact with it. GraphQAChain SearchApi tool. Apr 11, 2024 · Then click Create API Key. 2. Returns Should contain all inputs specified in Chain. api_models import APIOperation from langchain_community. API Key; Azure Active Directory (AAD) Using the API key is the easiest way to get started. LangChain comes with a built-in chain for this workflow that is designed to work with Neo4j: GraphCypherQAChain chains. execute a Chain. If True, only Asynchronously execute the chain. langchain: A package for higher level components (e. Convenience method for executing chain. Document compressor that uses an LLM chain to extract the relevant parts of documents. Dec 9, 2024 · from typing import Any from langchain. The SearchApi tool connects your agents and chains to the internet. @langchain/core: Base abstractions and LangChain Expression Language. assign() calls, but LangChain also includes an . Programs created using LCEL and LangChain Runnables inherently support synchronous, asynchronous, batch, and streaming operations. chat_models import ChatOpenAI from langchain_core. @langchain/community: Third party integrations. map_reduce. Still, this is a great way to get started with LangChain - a lot of features can be built with just some prompting and an LLM call! LangChain's products work seamlessly together to provide an integrated solution for every step of the application development journey. Chain（チェーン） LangChainでの開発は「Chainを組み立てる」ことが基本です。たとえば以下のような処理を一つのChainとして定義できます。 ユーザーから質問を受け取る; 必要に応じてデータベースを検索 In this guide, we will go over the basic ways to create Chains and Agents that call Tools. It is built on the Runnable protocol. However, some of the input schemas for legacy chains may be incomplete/incorrect, leading to errors. To improve your LLM application development, pair LangChain with: LangSmith - Helpful for agent evals and observability. This class is deprecated. manager import CallbackManagerForLLMRun from langchain_core. Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models (FMs) from leading AI companies like AI21 Labs, Anthropic, Cohere, Meta, Stability AI, and Amazon via a single API, along with a broad set of capabilities you need to build generative AI applications with security, privacy, and responsible AI. In this quickstart we'll show you how to build a simple LLM application with LangChain. Use this method when you want to: take advantage of batched calls, need more output from the model than just the top generated value, are building chains that are agnostic to the underlying language model. 0 chains. Security Note: This API chain uses the requests toolkit. You can find more information on how to use AAD with Azure OpenAI here. This tutorial demonstrates text summarization using built-in chains and LangGraph. , some pre-built chains). Construct the chain by providing a question relevant to the provided API documentation. Legacy Chains LangServe works with both Runnables (constructed via LangChain Expression Language) and legacy chains (inheriting from Chain). Jul 3, 2023 · Prepare chain inputs, including adding inputs from memory. openai. The main difference between this method and Chain. These chains do not use from langchain. Prepare chain inputs, including adding inputs from memory. 提供关于所提供的 api 文档相关的问题以构造链。 Skip to main content LangChain 🦜️🔗 中文网，跟着LangChain一起学LLM/GPT开发 Concepts Python Docs JS/TS Docs [1m> Entering new AgentExecutor chain [0m [32;1m [1;3mAction: api_planner Action Input: I need to find the right API calls to create a playlist with the first song from Kind of Blue and name it Machine Blues [0m Observation: [36;1m [1;3m1. This takes inputs as a dictionary and returns a dictionary output. Important LangChain primitives like chat models, output parsers, prompts, retrievers, and agents implement the LangChain Runnable Interface. Docs: Detailed documentation on how to use DocumentTransformers; Integrations; Interface: API reference for the base interface. Combining documents by mapping a chain over them, then combining results. Tools allow us to extend the capabilities of a model beyond just outputting text/messages. How to: chain runnables; How to: stream runnables; How to: invoke runnables in parallel This tutorial demonstrates text summarization using built-in chains and LangGraph. If True, only new keys generated by this chain will be returned. llms import LLM from langchain_core. com/en/latest/chains/langchain. inputs (dict[str, Any] | Any) – Dictionary of inputs, or single input if chain expects only one param. moderation. While the LangChain framework can be used standalone, it also integrates seamlessly with any LangChain product, giving developers a full suite of tools when building LLM applications. If True, only Execute the chain. [1m> Entering new OpenAPIEndpointChain chain [0m [1m> Entering new APIRequesterChain chain [0m Prompt after formatting: [32;1m [1;3mYou are a helpful AI Assistant. 1. Nov 5, 2024 · 使用するAPIやサービスによっては、追加のパッケージのインストールや設定が必要な場合があります。 APIの使用には料金が発生する場合があるため、利用規約と料金体系を確認してください。 以上の手順で、LangChainを使用するための基本的な環境が整います。 from typing import Any from langchain. LangChain provides the smoothest path to high quality agents. Legacy Chains. , via invoke, batch, transform, or stream or async variants) Defaults to None. utils. The key to using models with tools is correctly prompting a model and parsing its response so that it chooses the right tools and provides the Convenience method for executing chain. that are narrowly-scoped to only include necessary permissions. . from_messages ([("system", "What are langchain-community: Community-driven components for LangChain. LangServe helps developers deploy LangChain chains as a REST API. %pip install --upgrade --quiet llamaapi Access Google's Generative AI models, including the Gemini family, directly via the Gemini API or experiment rapidly using Google AI Studio. A model call will fail, or model output will be misformatted, or there will be some nested model calls and it won't be clear where along the way an incorrect output was created. The universal invocation protocol (Runnables) along with a syntax for combining components (LangChain Expression Language) are also defined here. inputs (Union[Dict[str, Any], Any]) – Dictionary of raw inputs, or single input if chain expects only one param. However, if you have complex security requirements - you may want to use Azure Active Directory. This includes all inner runs of LLMs, Retrievers, Tools, etc. API Chains# This notebook showcases using LLMs to interact with APIs to retrieve relevant information. 271 langchain-core==0. langchain. Chains with other components, including other Chains. \n\nLooking at the parameters for GetWeather:\n- location (required): The user directly provided the location in the query - "San Francisco"\n\nSince the required "location" parameter is present, we can proceed with calling the I have two swagger api docs and I am looking for LangChain to interact with API's. Returns Composable: the Chain API is flexible enough that it is easy to combine. Chains encode a sequence of calls to components like models, document retrievers, other Chains, etc. Credentials Head to https://platform. LCEL is great for constructing your chains, but it's also nice to have chains used off the shelf. Dec 9, 2024 · langchain_community 0. Interface: API reference for the base interface. Pull an object from the hub and returns it as a LangChain object. Delegation to sync methods Most popular LangChain integrations implement asynchronous support of their APIs. LangChain is designed to be easy to use, even for developers who are not familiar with lang Dec 9, 2024 · langchain 0. convert_to Welcome to the LangChain Python API reference. If True, only Build controllable agents with LangGraph, our low-level agent orchestration framework. """Chain that makes API calls and summarizes the responses to answer a question. ArangoGraphQAChain. Jul 3, 2023 · langchain. This is the map step. # pip install -U langchain langchain-community from langchain_community. Debug poor-performing LLM app runs Execute the chain. Exercise care in who is allowed to use this chain. If True, only Chain that splits documents, then analyzes it in pieces. Ollama allows you to run open-source large language models, such as Llama 2, locally. Returns Execute the chain. language_models. This notebook walks through examples of how to use a moderation chain, and several common ways for doing so. runnables import chain from langchain_core. Using API Gateway, you can create RESTful APIs and >WebSocket APIs that enable real-time two-way communication applications Execute the chain. chains #. The LangChain libraries themselves are made up of several different packages. openapi. from langchain_core. return_only_outputs (bool) – Whether to return only outputs in the response. APIResponderChain [source] ¶. A previous version of this page showcased the legacy chains StuffDocumentsChain, MapReduceDocumentsChain, and RefineDocumentsChain. This guide will help you migrate your existing v0. Evaluation Jul 3, 2023 · langchain. Includes base interfaces and in-memory implementations. outputs import GenerationChunk class CustomLLM (LLM): """A custom chat model that echoes the first `n` characters of the input. OpenAI's Message Format: OpenAI's message format. LangChain integrates with many model providers. , pure text completion models vs chat models Let's use a simple out-of-the-box chain that takes a question, turns it into a Cypher query, executes the query, and uses the result to answer the original question. utilities. __call__ expects a single input dictionary with all the inputs Welcome to the LangChain Python API reference. My user input query depends on two different API endpoint from two different Swagger docs. Convert a Python function to an Ernie function-calling API compatible dict. Parse outputs that could return a null string of some sort. This chain takes a single document as input, and then splits it up into chunks and then passes those chucks to the CombineDocumentsChain. [1m> Entering new AgentExecutor chain [0m [32;1m [1;3mAction: api_planner Action Input: I need to find the right API calls to create a playlist with the first song from Kind of Blue and name it Machine Blues [0m Observation: [36;1m [1;3m1. APIChain enables using LLMs to interact with APIs to retrieve relevant information. openapi import openapi_spec_to_openai_fn from langchain_community. from langchain. client_options: Client Options to pass to the Google API Client, such as a custom client_options["api_endpoint"] transport : The transport method to use, such as rest , grpc , or grpc_asyncio . Returns Prepare chain inputs, including adding inputs from memory. LangSmith documentation is hosted on a separate site. This page covers all resources available in LangChain for working with APIs. SearchApi is a real-time SERP API for easy SERP scraping. Feb 12, 2024 · 2. Chains If you are just getting started and you have relatively simple APIs, you should get started with chains. Chain. Should contain all inputs specified in Chain. Create a new model by parsing and validating input data from keyword arguments. If True, only Chain that makes API calls and summarizes the responses to answer a question. This notebook shows how to use LangChain with LlamaAPI - a hosted version of Llama2 that adds in support for function calling. prompts import PromptTemplate from langchain_openai import OpenAI @chain def my_func (fields): prompt = PromptTemplate ("Hello, {name}!") llm = OpenAI formatted = prompt. openai_functions. LangSmith allows you to closely trace, monitor and evaluate your LLM application. [Legacy] Chains constructed by subclassing from a legacy Chain class. langchain-community : Third-party integrations that are community maintained. langchain-core: Core langchain package. 23 Jul 3, 2023 · Prepare chain inputs, including adding inputs from memory. Chain interacts with an OpenAPI endpoint using natural language. prompts import ChatPromptTemplate from langchain_openai import ChatOpenAI retriever = # Your retriever llm = ChatOpenAI system_prompt = ("Use the given context to answer the question. A wrapper around the Search API. Bases: LLMChain Get Note that as of 1/27/25, tool calling and structured output are not currently supported for deepseek-reasoner. When you use all LangChain products, you'll build better, get to production quicker, and grow visibility -- all with less set up and friction. langgraph: Powerful orchestration layer for LangChain. To access DeepSeek models you’ll need to create a DeepSeek account, get an API key, and install the @langchain/deepseek integration package. Once you've done this set the OPENAI_API_KEY environment variable: LangServe: A library for deploying LangChain chains as a REST API. astream_events() method that combines the flexibility of callbacks with the ergonomics of . callbacks. For more information, please review the API reference for the specific component you are using. GET /search to search for the album "Kind of Blue" 2. Tools can be just about anything — APIs, functions, databases, etc. tools import Tool from langchain_openai import OpenAI llm = OpenAI (temperature = 0) search = SearchApiAPIWrapper tools = [Tool (name = "intermediate_answer", func = search. See API reference for replacement: https://api. Chains are a sequence of predetermined steps, so they are good to get started with as they give you more control and let you understand what is happening better. Parameters: inputs (dict[str, Any] | Any) – Dictionary of raw inputs, or single input if chain expects only one param. This chain is parameterized by a TextSplitter and a CombineDocumentsChain. Chain for question-answering against a graph by generating AQL statements. This is often the best starting point for individual developers. The "Runnable" Interface API Reference provides a detailed overview of the Runnable interface and its methods. LangChain supports two message formats to interact with chat models: LangChain Message Format: LangChain's own message format, which is used by default and is used internally by LangChain. Many of these Runnables are useful when composing custom "chains" in LangChain using the LangChain Expression Language (LCEL). This is a reference for all langchain-x packages. BaseCombineDocumentsChain chains # Chains module for langchain_community. Please provide JSON arguments to agentFunc() based on the user's instructions. Returns There are ways to do this using callbacks, or by constructing your chain in such a way that it passes intermediate values to the end with something like chained . Returns: Chain that makes API calls and summarizes the responses to answer a question. bound – The underlying Runnable that this Runnable delegates calls to. stream (formatted): yield chunk Prepare chain inputs, including adding inputs from memory. Setup . Moderation chains are useful for detecting text that could be hateful, violent, etc. This can be fixed by updating the input_schema property of those chains in LangChain. Chat models and prompts: Build a simple LLM application with prompt templates and chat models. __call__ expects a single input dictionary with all the inputs chains. In this case, LangChain offers a higher-level constructor method. If you encounter LangSmith is a tool developed by LangChain that is used for debugging and monitoring LLMs, chains, and agents in order to improve their performance and reliability for use in production. g. LangChain has evolved since its initial release, and many of the original "Chain" classes have been deprecated in favor of the more flexible and powerful frameworks of LCEL and LangGraph. python. chain_extract. Productionization: Use LangSmith to inspect, monitor and evaluate your chains, so that you can continuously optimize and deploy with confidence. Security note: Make sure that the database connection uses credentials. Together, these products simplify the entire application lifecycle: There are two types of off-the-shelf chains that LangChain supports: Chains that are built with LCEL. The langchain-google-genai package provides the LangChain integration for these models. langchain: Chains, agents, and retrieval strategies that make up an application's cognitive architecture. LCEL cheatsheet: For a quick overview of how to use the main LCEL primitives. If True, only Mar 12, 2023 · Utils: 検索APIのラッパーなど便利関数保管庫; Indexes: テキストを分割したり埋め込みにしたりVector Storeに入れる処理; そしてこれから説明するモジュール群は簡単に説明すると以下のようになります。 Chains: 言語モデルなどの処理の連携を扱うもの Should contain all inputs specified in Chain. Asynchronously execute the chain. You do not need to use LangServe to use LangChain, but in this guide we'll show how you can deploy your app with LangServe. combine_documents import create_stuff_documents_chain from langchain_core. GraphQAChain¶ class langchain. MapReduceDocumentsChain [source] # Bases: BaseCombineDocumentsChain. Migration guide: For migrating legacy chain abstractions to LCEL. tip Check out this public LangSmith trace showing the steps of the retrieval chain. OpenAPIEndpointChain [source] ¶ Bases: Chain, BaseModel. """ from __future__ import annotations from typing import Any, Dict, List, Optional This chain can automatically select and call APIs based only on an OpenAPI spec. response_chain. Use to build complex pipelines and workflows. ChatLlamaAPI. Parameters: inputs (dict[str, Any] | Any) – Dictionary of inputs, or single input if chain expects only one param. Chain for question-answering against a graph. NoOutputParser. You can peruse LangSmith tutorials here. Parameters. input_keys except for inputs that will be set by the chain’s memory. For user guides see https://python. utilities import SearchApiAPIWrapper from langchain_core. 17¶ langchain. stream(). Dec 9, 2024 · Causal program-aided language (CPAL) is a concept implemented in LangChain as a chain for causal modeling and narrative decomposition. Parameters:. If True, only from langchain_community. chain. This tool is handy when you need to answer questions about current events. Many APIs are already compatible with OpenAI function calling. While LangChain has its own message and model APIs, LangChain has also made it as easy as possible to explore other models by exposing an adapter to adapt LangChain models to the other APIs, as to the OpenAI API. It parses an input OpenAPI spec into JSON Schema that the OpenAI functions API can handle. This interface provides two general approaches to stream content: sync stream and async astream: a default implementation of streaming that streams the final output from the chain. AnalyzeDocumentChain. It provides a framework for connecting language models to other data sources and interacting with various APIs. Storing documents Familiarize yourself with LangChain's open-source components by building simple applications. If False, both input keys and new keys generated by this chain will be returned. APIResponderChain¶ class langchain. BaseCombineDocumentsChain Amazon API Gateway is a fully managed service that makes it easy for developers to create, publish, maintain, monitor, and secure APIs at any >scale. Chains are easily reusable components linked together. Here we get an API operation from a specified endpoint and method. Returns: ChatOllama. class langchain. Returns: from langchain_core. It seamlessly integrates with LangChain, and you can use it to inspect and debug individual steps of your chains as you build. chains import create_retrieval_chain from langchain. The interfaces for core components like chat models, LLMs, vector stores, retrievers, and more are defined here. The main methods exposed by chains are: __call__: Chains are callable. 0. Setup your environment Shellexport LANGCHAIN_TRACING_V2=trueexport LANGCHAIN_API_KEY=<your-api-key># The below examples use the OpenAI API, though it's not necessary in generalexport OPENAI_API_KEY=<your-openai-api-key>Log your first trace We provide multiple ways to log traces [{'text': '<thinking>\nThe user is asking about the current weather in a specific location, San Francisco. If True, only langchain. To use, you should have the openai python package installed, and the environment variable OPENAI_API_KEY set with your API key. """ from __future__ import annotations import json from typing import Any, Dict, List, NamedTuple, Optional, cast from langchain_community. This is a relatively simple LLM application - it's just a single LLM call plus some prompting. Abstract base class for creating structured sequences of calls to components. API_SCHEMA: ```typescript /* API for fetching Klarna product information */ type productsUsingGET Moderation chain. In Agents, a language model is used as a reasoning engine to determine which actions to take and in which order. Should contain all inputs specified in Chain. APIChain. Is it possible to use Agent / tools to identify the right swagger docs and invoke API chain? System Info. kwargs – optional kwargs to pass to the underlying Runnable, when running the underlying Runnable (e. Dec 9, 2024 · This method should make use of batched calls for models that expose a batched API. pvbacm tbqi htzq nzdxbd pyfcpw arbr kpvf uuyk lymrp cixigm