Langchain apichain python.

Langchain apichain python __call__ expects a single input dictionary with all the inputs In this quickstart we'll show you how to build a simple LLM application with LangChain. 1 and <4. Apr 25, 2023 · To follow along in this tutorial, you will need to have the langchain Python package installed and all relevant API keys ready to use. " Dec 9, 2024 · Check Cache and run the LLM on the given prompt and input. Debug poor-performing LLM app runs Sep 27, 2024 · Python REPL tool: LangChain has a PythonREPL tool that can execute Python code within a LangChain application. langchain. API key for an LLM provider: For instance, an API key from OpenAI. chains. runnables. 8. Chain that makes API calls and summarizes the responses to answer a question. stop (Optional[List[str]]) – Stop words to use when generating. Feb 28, 2024 · from langchain. ): Important integrations have been split into lightweight packages that are co-maintained by the LangChain team and the integration developers. 🖇️ Relationship with Python LangChain This is built to integrate as seamlessly as possible with the LangChain Python package . Learn how to create a fully local, privacy-friendly RAG-powered chat app using Reflex, LangChain, Huggingface, FAISS, and Ollama. stream (formatted): yield chunk Jul 3, 2023 · Asynchronously execute the chain. LLM [source] ¶. 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. llm (BaseLanguageModel) – The language model to use. In this guide, we will go over the basic ways to create Chains and Agents that call Tools. AnalyzeDocumentChain. Jan 27, 2024 · Chatbot’s response when asked about an ice-cream recipe Next Steps. Use to create flexible templated prompts for chat models. Jupyter Notebook integration: LangChain can be used within Jupyter Notebooks, where Python code can be executed. pydantic_v1 import BaseModel from langchain_core. This notebook walks through examples of how to use a moderation chain, and several common ways for doing so. runnables import Runnable from operator import itemgetter prompt = (SystemMessagePromptTemplate. base. To install the langchain Python package, you can pip install it. pydantic_v1 import BaseModel, Field class AnswerWithJustification (BaseModel): '''An answer to the user question along with justification for the answer. utilities import SearchApiAPIWrapper from langchain_core. combine_documents import create_stuff_documents_chain from langchain_core. prompts import SystemMessagePromptTemplate from langchain_core. 8+: Ensure you have the latest version installed. llms import 1st example: hierarchical planning agent . 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. Here, we explore LangChain - An open-source Python framework for building applications based on Large Language Models such as GPT. __call__ is that this method expects inputs to be passed directly in as positional arguments or keyword arguments, whereas Chain. 0. input_keys except for inputs that will be set by the chain’s memory. 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. to make GET, POST, PATCH, PUT, and DELETE requests to an API. Asynchronously execute the chain. In Python 3. Here is how you can use it: if "api_request_chain" in config: api_request_chain_config = config. The interfaces for core components like chat models, LLMs, vector stores, retrievers, and more are defined here. Feb 6, 2025 · LangChain is a Python module that allows you to develop applications powered by language models. Sep 18, 2024 · LangChain is available via the Python Package Index (PyPI) and can be easily installed using pip. The LangChain Expression Language (LCEL) offers a declarative method to build production-grade programs that harness the power of LLMs. Dec 6, 2023 · Currently, I want to build RAG chatbot for production. callbacks. tools import BaseTool from langchain. For the APIChain class, we need the external API’s documentation in string format to access endpoint details. , search, code execution, API calls). Quick Install. Dec 9, 2024 · # IMPORTANT: If you are using Python <=3. js. Runnable [source] ¶ A unit of work that can be invoked, batched, streamed, transformed and composed. It provides a framework for connecting language models to other data sources and interacting with various APIs. prompts import PromptTemplate from langchain_community. llms import Dec 9, 2024 · Check Cache and run the LLM on the given prompt and input. Dec 9, 2024 · Creates a chain that extracts information from a passage using pydantic schema. txt Script Execution # Run OpenAI, LangChain, and Multion scripts python3 src/my_openai. ChatPromptTemplate [source] ¶. invoke (** fields) for chunk in llm. 2. param id: Optional [str] = None ¶. 11 conda activate langchain_env # Install dependencies pip install -r requirements. agents. Use the client SDK to call a LangServe server as if it was a Runnable running locally (or call the HTTP API directly) Dec 9, 2024 · The benefits of this implementation are: - Uses LLM tool calling features to encourage properly-formatted API requests; - Support for both token-by-token and step-by-step streaming; - Support for checkpointing and memory of chat history; - Easier to modify or extend (e. from typing_extensions import Annotated, TypedDict from langchain_openai import ChatOpenAI class AnswerWithJustification (TypedDict): '''An answer to the user question along with justification for the answer. memory. combine_documents. llms import OpenAI # This controls how each document will be formatted. Install the needed libraries using pip. ''' answer: str justification: str dict_schema = convert_to_openai_tool (AnswerWithJustification) llm 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. pip install langchain or pip install langsmith && conda install langchain -c conda-forge Oct 13, 2023 · This LangChain Python Tutorial simplifies the integration of powerful language models into Python applications. APIChain. pip install langchain Oct 10, 2023 · LangChain is a Python library that facilitates the creation, experimentation, and analysis of language models and agents, offering a wide range of features for natural language processing. ''' answer: str Dec 9, 2024 · Create a BaseTool from a Runnable. Chains are easily reusable components linked together. runnables import chain from langchain_core. __call__ expects a single input dictionary with all the inputs Dec 9, 2024 · class langchain_community. 使用 LangChain CLI 快速引导 LangServe 项目。 要使用 langchain CLI，请确保您已安装最新版本的 langchain-cli。您可以使用 pip install -U langchain-cli 安装它。 设置 . Familiarize yourself with LangChain's open-source components by building simple applications. HTMLHeaderTextSplitter (headers_to_split_on). run, description = "useful for when you need to ask with search",)] In this quickstart we'll show you how to build a simple LLM application with LangChain. Apr 11, 2024 · Use of LangChain is not necessary - LangSmith works on its own!Install LangSmith We offer Python and Typescript SDKs for all your LangSmith needs. openapi. runnables import RunnablePassthrough from langchain_openai import ChatOpenAI prompt = ChatPromptTemplate. WikipediaQueryRun [source] ¶. llms import Bedrock from langchain_community. 11 or newer. Using API Gateway, you can create RESTful APIs and >WebSocket APIs that enable real-time two-way communication applications Asynchronously execute the chain. Base class for parsing agent output into agent action/finish. langgraph: Powerful orchestration layer for LangChain. Tool for app operations. output_parsers import StrOutputParser from langchain_core. Apr 9, 2025 · LangChain agents are LLM-driven entities that can autonomously choose and execute actions to solve user queries. Bases: _BaseYandexGPT, LLM Yandex large language models. For handling the second pattern, LangChain relies on Python's contextvars. Before we dive in, make sure you have: Python 3. \n\nOverall, the integration of structured planning, memory systems, and advanced tool use aims to enhance the capabilities Jul 3, 2023 · Asynchronously execute the chain. 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. Element type as typed dict. langchain-openai, langchain-anthropic, etc. The main difference between this method and Chain. __call__ expects a single input dictionary with all the inputs We can construct agents to consume arbitrary APIs, here APIs conformant to the OpenAPI/Swagger specification. For user guides see https://python. Use to build complex pipelines and workflows. html. buffer import ConversationBufferMemory from dotenv import load_dotenv load_dotenv() Step 2. Bases: BaseChatPromptTemplate Prompt template for chat models. As with the example of chaining questions together, we start Dec 9, 2024 · class langchain_core. com. runnables import RunnablePassthrough # ユーザー入力 user_input = " Bedrockで使用 Feb 13, 2024 · If you're captivated by the transformative powers of Generative AI and LLMs, this tutorial is perfect for you. ChatLlamaAPI. One of the most powerful applications enabled by LLMs is sophisticated question-answering (Q&A) chatbots. Aug 14, 2024 · Create a BaseTool from a Runnable. pop ("api_request_chain") api_request_chain = load_chain_from_config (api_request_chain_config) elif "api_request_chain_path" in config: May 7, 2025 · Python 3. Tools to perform actions (e. Bases: BaseTool Tool that searches the Wikipedia API. Dec 9, 2024 · LangChain Runnable and the LangChain Expression Language (LCEL). Jan 19, 2025 · Enter LangChain — a framework designed to simplify the development of applications powered by language models. Agent that is using tools. **Structured Software Development**: A systematic approach to creating Python software projects is emphasized, focusing on defining core components, managing dependencies, and adhering to best practices for documentation. AgentOutputParser. __call__ expects a single input dictionary with all the inputs LangChain provides a modular interface for working with LLM providers such as OpenAI, Cohere, HuggingFace, Anthropic, Together AI, and others. requests import Requests from langchain APIChain enables using LLMs to interact with APIs to retrieve relevant information. 注意：我们使用 poetry 进行依赖管理。请按照 poetry 文档 了解更多信息。 1. fake import FakeStreamingListLLM from langchain_core. runnables import RunnableLambda, RunnablePassthrough from langchain_openai import ChatOpenAI llm = ChatOpenAI Dec 9, 2024 · class langchain_community. Bases: BaseLLM Simple interface for implementing a custom LLM. chains import (StuffDocumentsChain, LLMChain, ReduceDocumentsChain, MapReduceDocumentsChain,) from langchain_core. Mar 18, 2024 · In this tutorial, learn how to build and deploy LLM-based applications with ease using LangChain, Python, and Heroku for streamlined development and deployment. Important LangChain primitives like LLMs, parsers, prompts, retrievers, and agents implement the LangChain Runnable Interface. You should subclass this class and implement the following: Aug 9, 2023 · 1 How To Use LangChain in 10 Minutes 2 How I Made an AI Agent in 10 Minutes with LangChain 3 How I Use Google's Gemini Pro with LangChain LangChain is a powerful library for Python and Javascript/Typescript that allows you to quickly prototype large language model applications. APIChain: Requests Wrapper: This chain uses an LLM to convert a query into an API request, then executes that request, gets back a response, and then passes that request to an LLM to respond: OpenAPIEndpointChain: OpenAPI Spec: Similar to APIChain, this chain is designed to interact with APIs. These are applications that can answer questions about specific source information. In most cases, all you need is an API key from the LLM provider to get started using the LLM with LangChain. Initialize the tool. globals import set_debug set_debug (False) # debug時はTrue from langchain_core. Following this step-by-step guide and exploring the various LangChain modules will give you valuable insights into generating texts, executing conversations, accessing external resources for more informed answers, and analyzing and Jul 3, 2023 · from operator import itemgetter from typing import Literal from typing_extensions import TypedDict from langchain_core. , some pre-built chains). ; A valid OpenAI API key. The universal invocation protocol (Runnables) along with a syntax for combining components (LangChain Expression Language) are also defined here. It seamlessly integrates with LangChain and LangGraph, and you can use it to inspect and debug individual steps of your chains and agents as you build. Partner packages (e. A basic agent works in the following manner: Given a prompt an agent uses an LLM to request an action to take (e. ): Some integrations have been further split into their own lightweight packages that only depend on langchain-core. Dec 9, 2024 · from langchain_core. """ from __future__ import annotations import json from typing import Any, Dict, List, NamedTuple, Optional, cast from langchain_community. prompts. chains #. utils. OpenAI has a tool calling (we use "tool calling" and "function calling" interchangeably here) API that lets you describe tools and their arguments, and have the model return a JSON object with a tool to invoke and the inputs to that tool. In this LangChain Crash Course you will learn how to build applications powered by large language models. chain. app. agents import initialize_agent, AgentType from langchain. In this example, we'll consider an approach called hierarchical planning, common in robotics and appearing in recent works for LLMs X robotics. Programs created using LCEL and LangChain Runnables inherently support synchronous, asynchronous, batch, and streaming operations. Custom tools: You can create custom tools in LangChain that execute Python code as part of your application logic. Ideally this should be unique across the document collection and formatted as a UUID, but this will not be enforced. LangChain integrates with many model providers. , and provide a simple interface to this sequence. chat. An optional identifier for the document. ElementType. LangChain also supports LLMs or other language models hosted on your own machine. The user is responsible for updating this table using the REST API or the Python SDK. Memory to retain context across interactions. batch/abatch: Efficiently transforms multiple inputs into outputs. It’s best practice to use a virtual environment to manage dependencies: Oct 10, 2023 · LangChain is a Python library that facilitates the creation, experimentation, and analysis of language models and agents, offering a wide range of features for natural language processing. py python3 src/llm_example. 8 or higher installed. I already had my LLM API and I want to create a custom LLM and then use this in RetrievalQA. language_models. The latest and most popular OpenAI models are chat completion models. let’s explore LangChain from the ground up, covering everything from basic Jan 23, 2024 · Yes, you can use APIChain as a custom tool in LangChain. Runnable¶ class langchain_core. AppOperationType (value). AINAppOps. Jan 7, 2025 · Prerequisites. Jul 10, 2023 · In this code, we use the Python syntax of async and await. The _load_api_chain function is used to load an APIChain. __call__ expects a single input dictionary with all the inputs agents. Feb 18, 2024 · import chainlit as cl from langchain_openai import OpenAI from langchain. from langchain . prompts import PromptTemplate from langchain_openai import OpenAI @chain def my_func (fields): prompt = PromptTemplate ("Hello, {name}!") llm = OpenAI formatted = prompt. We can also build our own interface to external APIs using the APIChain and provided API documentation. Exercise care in who is allowed to use this chain. get_input_schema. manager import CallbackManagerForToolRun, AsyncCallbackManagerForToolRun from typing import Optional, Type, Callable from pydantic import Field import requests import json # APIキーをセット (変数名はLangChain側で決められています) from langchain. Tools can be just about anything — APIs, functions, databases, etc. If your API requires authentication or other headers, you can pass the chain a headers property in the config object. from_chain_type function. as_tool will instantiate a BaseTool with a name, description, and args_schema from a Runnable. ainetwork. combine_documents LangChain will try to propagate RunnableConfig automatically for both of the patterns. langchain: A package for higher level components (e. param api_wrapper: WikipediaAPIWrapper [Required] ¶ Dec 9, 2024 · from langchain_core. __call__ expects a single input dictionary with all the inputs Integration packages (e. ''' answer: str # If we provide default values and/or descriptions for fields, these will be passed # to the Dec 9, 2024 · html. py python3 src/multion_integration. tools. Key Methods¶ invoke/ainvoke: Transforms a single input into an output. You can peruse LangSmith how-to guides here, but we'll highlight a few sections that are particularly relevant to LangChain below: Evaluation You are currently on a page documenting the use of OpenAI text completion models. Jul 3, 2023 · from langchain. We recommend only using this setting for demos or testing. May 1, 2024 · def load_tools (tool_names: List [str], llm: Optional [BaseLanguageModel] = None, callbacks: Callbacks = None, allow_dangerous_tools: bool = False, ** kwargs: Any Nov 17, 2023 · To get the libraries you need for this part of the tutorial, run pip install langchain openai milvus pymilvus python-dotenv tiktoken. inputs (Union[Dict[str, Any], Any]) – Dictionary of inputs, or single input if chain expects only one param. %pip install --upgrade --quiet llamaapi Get setup with LangChain, LangSmith and LangServe; Use the most basic and common components of LangChain: prompt templates, models, and output parsers; Use LangChain Expression Language, the protocol that LangChain is built on and which facilitates component chaining; Build a simple application with LangChain; Trace your application with LangSmith langchain-core defines the base abstractions for the LangChain ecosystem. , OpenAI or Groq, depending on the model you choose). Before proceeding, ensure that Python and pip are installed on your machine. Dec 9, 2024 · langchain_core. This application will translate text from English into another language. yandex. . ; Expected Output: The system answers questions about Python, such as “What is a Apr 9, 2023 · LangChain is a framework for developing applications powered by language models. Here’s a breakdown of its key features and benefits: May 7, 2025 · Python version 3. from langchain_core. HTMLSectionSplitter (headers_to_split_on) Apr 9, 2023 · LangChain is a framework for developing applications powered by language models. To help you ship LangChain apps to production faster, check out LangSmith. This guide will help you migrate your existing v0. tools import Tool from langchain_openai import OpenAI llm = OpenAI (temperature = 0) search = SearchApiAPIWrapper tools = [Tool (name = "intermediate_answer", func = search. 11 and above, this works out of the box, and you do not need to do anything special to propagate the RunnableConfig to the sub-calls. Set up a new virtual environment (optional) An API key (e. 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. LangSmith documentation is hosted on a separate site. utilities. langchain-core: Core langchain package. 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-community: Third party integrations. 5-turbo-instruct, you are probably looking for this page instead. chains. If exposing to end users, consider that users will be able to make arbitrary requests on behalf of the server hosting the code. Using API Gateway, you can create RESTful APIs and >WebSocket APIs that enable real-time two-way communication applications tools. Basic Python knowledge: Familiarity with Python’s syntax and concepts will be beneficial. Installing LangChain. In my previous articles on building a custom chatbot application, we’ve covered the basics of creating a chatbot with specific functionalities using LangChain and OpenAI, and how to build the web application for our chatbot using Chainlit. chains import APIChain from langchain . You can create a custom agent that uses the ReAct (Reason + Act) framework to pick the most suitable tool based on the input query. To improve your LLM application development, pair LangChain with: LangSmith - Helpful for agent evals and observability. api import open_meteo_docs Convenience method for executing chain. Chains encode a sequence of calls to components like models, document retrievers, other Chains, etc. Convenience method for executing chain. 0 chains to the new abstractions. This step-by-step guide walks you through building an interactive chat UI, embedding search, and local LLM integration—all without needing frontend skills or cloud dependencies. Feb 18, 2024 · In this tutorial, we will see how we can integrate an external API with a custom chatbot application. langchain: Chains, agents, and retrieval strategies that make up an application's cognitive architecture. , with additional tools, structured responses, etc. langchain-community: Community-driven components for LangChain. LangSmith is a unified developer platform for building, testing, and monitoring LLM applications. Construct the chain by providing a question relevant to the provided API documentation. Includes base interfaces and in-memory implementations. chains . g. Langchain also gives us the code to run the chain async, with the arun() function. They use: LLMs (like GPT-4) to reason and plan. LangChain is designed to be easy to use, even for developers who are not familiar with lang Dec 9, 2024 · from typing import Optional from langchain_groq import ChatGroq from langchain_core. Create a virtual environment. retrievers import AmazonKendraRetriever from langchain_core. To use, you should have the yandexcloud python package installed. If you are using a delta-sync index with Databricks-managed embeddings: LangChain CLI 🛠️ . tool. __call__ expects a single input dictionary with all the inputs First, you can use a LangChain agent to dynamically call LLMs based on user input and access a suite of tools, such as external APIs. llms. map_reduce. Should contain all inputs specified in Chain. To interact with external APIs, you can use the APIChain module in LangChain. This is a reference for all langchain-x packages. from_template ("You are a nice assistant. ''' answer: str # Create and activate a Conda environment conda create --name langchain_env python=3. All built with battle-tested open-source Python libraries like FastAPI, Pydantic, uvloop and asyncio. For detailed documentation of all ChatAnthropic features and configurations head to the API reference. Where possible, schemas are inferred from runnable. Dec 9, 2024 · class langchain_core. tool-calling is extremely useful for building tool-using chains and agents, and for getting structured outputs from models more generally. Tools allow us to extend the capabilities of a model beyond just outputting text/messages. YandexGPT [source] ¶. tools. Chain that makes API calls and summarizes the responses to answer a question. codes/diagnosis. ) Install LangGraph 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. Jul 3, 2023 · from langchain_community. 8, you need to import Annotated # from typing_extensions, not from typing. APIs act as the "front door" for applications to access data, business logic, or functionality from your backend services. api. wikipedia. function_calling import convert_to_openai_tool class AnswerWithJustification (BaseModel): '''An answer to the user question along with justification for the answer. MapReduceDocumentsChain. 使用LangChain通常需要与一个或多个模型提供者、数据存储、API等进行集成。 在本示例中，我们将使用OpenAI的模型API。 首先，我们需要安装他们的Python包： APIChain: Requests Wrapper: This chain uses an LLM to convert a query into an API request, then executes that request, gets back a response, and then passes that request to an LLM to respond: OpenAPIEndpointChain: OpenAPI Spec: Similar to APIChain, this chain is designed to interact with APIs. Jul 3, 2023 · Convenience method for executing chain. prompts import ChatPromptTemplate from langchain_core. adapters ¶. So in the beginning we first process each row sequentially (can be optimized) and create multiple "tasks" that will await the response from the API in parallel and then we process the response to the 👷 Review code better and faster with my 3-Factor Framework: https://arjan. 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. chains import LLMChain, APIChain from langchain. Welcome to the LangChain Python API reference. py Dec 9, 2024 · Pass page_content in as positional or named arg. Here's an example with the above two options turned on: Note: If you enable public trace links, the internals of your chain will be exposed. 19¶ langchain_community. chains import create_retrieval_chain from langchain. Also for delta-sync index, you can choose to use Databricks-managed embeddings or self-managed embeddings (via LangChain embeddings classes). Specific Python libraries: langchain-mcp-adapters, langgraph, and an LLM library (like langchain-openai or langchain-groq) of your choice. """Chain that makes API calls and summarizes the responses to answer a question. 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! chains. Splitting HTML files based on specified headers. from langchain. pydantic_schema (Any) – The pydantic schema of the entities to extract. api_models import APIOperation from langchain_community. Chat models and prompts: Build a simple LLM application with prompt templates and chat models. Nov 20, 2024 · Retrieval-Augmented Generation (RAG) combines the power of large language models (LLMs) with external knowledge retrieval, enabling AI systems to provide accurate, context-aware responses. This is a relatively simple LLM application - it's just a single LLM call plus some prompting. Specifically, this means all objects (prompts, LLMs, chains, etc) are designed in a way where they can be serialized and shared between languages. AppSchema langchain-core defines the base abstractions for the LangChain ecosystem. # IMPORTANT: If you are using Python <=3. Fill out this form to speak with our sales team. PythonTypeScriptpip install -U langsmithyarn add langchain langsmithCreate an API key To create an API key head to the setting pages. AgentExecutor. prompts import ChatPromptTemplate from langchain_openai import ChatOpenAI retriever = # Your retriever llm = ChatOpenAI system_prompt = ("Use the given context to answer the question. LangChain is a great Python library for creating applications that Oct 10, 2023 · LangChain is a Python library that facilitates the creation, experimentation, and analysis of language models and agents, offering a wide range of features for natural language processing. In the next tutorial, we will be focusing on integrating a history Apr 4, 2024 · But what is LangChain? LangChain is a powerful Python library that makes it easier to build applications powered by large language models (LLMs). Our simple use-case specific chatbot is now ready. Parameters. Before installing the langchain package, ensure you have a Python version of ≥ 3. Agents use language models to choose a sequence of actions to take. Tool calling . prompt (str) – The prompt to generate from. These applications use a technique known as Retrieval Augmented Generation, or RAG. Environment setup steps. , a tool to run). May 8, 2024 · Source code for langchain. Adapters are used to adapt LangChain models to other APIs. Dec 9, 2024 · langchain_community 0. This notebook shows how to use LangChain with LlamaAPI - a hosted version of Llama2 that adds in support for function calling. Type of app operation as enumerator. from_template ("""Answer the question based only on the context provided. This notebook provides a quick overview for getting started with Anthropic chat models. Unless you are specifically using gpt-3. What Are Tools in LangChain? Tools are callable Python functions that May 2, 2025 · Check out LangChain. from langchain_community. agent. gcxsus tzzi tbyaroi nqjwzgr jgxv kcywi iazoyhy wbhg ayrg jej