Langchain api example. Let’s see another example, which I copied and pasted from one of my older langchain agents (hence the weird instructions). env and paste your API key in. py. The base interface is defined as below: """Interface for selecting examples to include in prompts. language_models ¶. ) and exposes a standard interface to interact with all of these models. FAISS. Prerequisites. To see how this works, let's create a chain that takes a topic and generates a joke: %pip install --upgrade --quiet langchain-core langchain-community langchain-openai. In particular, you'll be able to create LLM agents that use custom tools to answer user queries. Wikipediabarackobama. May 16, 2023 · For example, by connecting OpenAI’s language models with Wikipedia, the AI assistant can provide real-time answers to user’s questions based on up-to-date information from Wikipedia. send ( "Tell me a story about a goldfish on the moon. It is commonly used for tasks like competitor analysis and rank tracking. In this case, LangChain offers a higher-level constructor method. Feb 7, 2024 · The first example demonstrates how to invoke an OCI Generative AI LLM. 1 day ago · langchain_community 0. py file. We can create this in a few lines of code. First, we'll need to install the main langchain package for the entrypoint to import the method: %pip install langchain. Value: 1 In this sample, I demonstrate how to quickly build chat applications using Python and leveraging powerful technologies such as OpenAI ChatGPT models, Embedding models, LangChain framework, ChromaDB vector database, and Chainlit, an open-source Python package that is specifically designed to create user interfaces (UIs) for AI applications. Then, set OPENAI_API_TYPE to azure_ad. We can connect practically any data source (including our own) to a LangChain agent and ask it questions about LangChain is a framework for developing applications powered by language models. LLM Create your . We'll work with the Spotify API as one of the examples of a somewhat complex API. llms import OpenAI llm_math = LLMMathChain. Custom parameters. This notebook takes you through how to use LangChain to augment an OpenAI model with access to external tools. 0. To work around this, the documentation suggests returning fewer search results, for example, by updating the question to "Show me episodes for money saving tips, return only 1 result". 1. LangChain agents aren’t limited to searching the Internet. Hit the ground running using third-party integrations and Templates. predict(input="Hi there!") 3 days ago · A prompt template consists of a string template. from_template("Question: {question}{answer}") . You'll have to set up an application in the Spotify developer console, documented here, to get credentials: CLIENT_ID, CLIENT_SECRET, and REDIRECT_URI. LangChain has integrations with many model providers (OpenAI, Cohere, Hugging Face, etc. In this section, we will show some of the basic functionalities of LangChain with examples so that beginners can understand it better. There are two types of off-the-shelf chains that LangChain supports: Chains that are built with LCEL. env file: # Create a new file named . OpenAI systems run on an Azure -based supercomputing platform from Microsoft. SearchApi wrapper can be customized to use different engines like Google News, Google Jobs, Google Scholar, or others which can be found in SearchApi documentation. Example. At its core, LangChain is a framework built around LLMs. For example, LLMs have to access large volumes of big data, so LangChain organizes these large quantities of Apr 11, 2024 · LangChain has a set_debug() method that will return more granular logs of the chain internals: Let’s see it with the above example. It enables applications that: Are context-aware: connect a language model to sources of context (prompt instructions, few shot examples, content to ground its response in, etc. env file. In agents, a language model is used as a reasoning engine to determine which actions to take and in which order. , example. chains import LLMMathChain from langchain_community. ) Reason: rely on a language model to reason (about how to answer based on provided The Hugging Face Model Hub hosts over 120k models, 20k datasets, and 50k demo apps (Spaces), all open source and publicly available, in an online platform where people can easily collaborate and build ML together. input_keys except for inputs that will be set by the chain’s memory. 2. Extraction Using OpenAI Functions: Extract information from text using OpenAI Function Calling. llms import OpenAI llm = OpenAI(temperature=0) For example, in OpenAI Chat Completion API, a chat message can be associated with an AI, human or system role. The main use cases for LangGraph are Feb 18, 2024 · Setting up the API Chain from LangChain Step 1. ChatGPT is the Artificial Intelligence (AI) chatbot developed by OpenAI. Used for debugging and tracing. 0¶ langchain_community. Agents. Start experimenting with your own variations. An examples code to make langchain agents without openai API key (Google Gemini), Completely free unlimited and open source, run it yourself on website. chat_models import ChatOpenAI from langchain. It can recover from errors by running a generated For example, you may wish to use an API to retrieve stock data or to interact with a cloud platform. LangChain's chain and agent features that allow you to connect these steps in sequence (and use additional business logic for branching pipelines) are ideal for this use case. The HuggingFaceEndpoint class requires the endpoint_url and task parameters during initialization. OpenAI. APIChain enables using LLMs to interact with APIs to retrieve relevant information. from langchain_core. ) Reason: rely on a language model to reason (about how to answer based on Oct 10, 2023 · Agent test example 2. As noted above, see the API reference for the full set of parameters. prompts. The only method it needs to define is a select_examples method. python -m venv venv. - Chat Models are a variation on language models. We can use it for chatbots, G enerative Q uestion- A nswering (GQA), summarization, and much more. It extends the LangChain Expression Language with the ability to coordinate multiple chains (or actors) across multiple steps of computation in a cyclic manner. API description Endpoint docs Import Example usage; Chat: Build chat bots: chat: from langchain_cohere import ChatCohere: cohere. example_keys: If It parses an input OpenAPI spec into JSON Schema that the OpenAI functions API can handle. Setting up key as an environment variable. Open in Github. Chain to have a conversation and load context from memory. Suppose we want to summarize a blog post. Throughout the examples. It supports inference for many LLMs models, which can be accessed on Hugging Face. Run this code only when you're finished. k: Number of examples to select input_keys: If provided, the search is based on the input variables instead of all variables. Natural Language API Toolkits (NLAToolkits) permit LangChain Agents to efficiently plan and combine calls across endpoints. This library is integrated with FastAPI and uses pydantic for data validation. streaming_stdout import StreamingStdOutCallbackHandler from langchain. " Jun 15, 2023 · Answer Questions from a Doc with LangChain via SMS. LangChain is a framework for developing applications powered by language models. Oct 17, 2023 · Setting up the environment. Setup You will need the langchain-core and langchain-mistralai package to use the API. 3 days ago · For example, {“openai_api_key”: “OPENAI_API_KEY”} Examples using Document¶ # Automatically restart kernel after installs so that your environment can access the new packages %pip install -qU langchain langchain-community langchain-openai youtube-transcript-api pytube langchain-chroma Bases: LLMChain. This notebook goes over how to run llama-cpp-python within LangChain. document_loaders import TextLoader. Users can access the service through REST APIs, Python SDK, or a web Feb 25, 2023 · Visualizing Sequential Chain Building a demo Web App with LangChain + OpenAI + Streamlit. LangChain provides tooling to create and work with prompt templates. LangChain is a powerful, open-source framework designed to help you develop applications powered by a language model, particularly a large language model (LLM). """Select which examples to use based on the inputs. It will include the selection of the LLM, definition of the prompt, and integration of the tools. OpenAIEmbeddings(). Aug 15, 2023 · Finally, python-dotenv will be used to load the OpenAI API keys into the environment. # Set env var OPENAI_API_KEY or load from a . First, create the instance of openai-embedding: import { OpenAIEmbeddings } from "langchain/embeddings/openai"; const embeddings = new OpenAIEmbeddings({ openAIApiKey: "YOUR-API-KEY," // Replace the key with your own open API key, Nov 29, 2023 · LangChain Examples. environ["OPENAI_API_KEY"] = OPEN_AI_API_KEY app = FastAPI() from langchain. cpp. Should contain all inputs specified in Chain. This notebook showcases using LLMs to interact with APIs to retrieve relevant information. In all the examples, SerpAPI is a real-time API that provides access to search results from various search engines. The template can be formatted using either f-strings (default) or jinja2 syntax. LangChain provides several prompt templates to make constructing and working with prompts easily. And that is a much better answer. 5-Turbo, and Embeddings model series. Feb 18, 2024 · Setting up the API Chain from LangChain Step 1. It empowers businesses to scrape, extract, and make sense of data from all search engines' result pages. It can be imported using the following syntax: 1. pip install langchain openai python-dotenv requests duckduckgo-search. Sep 29, 2023 · The syntax to create embeddings for OpenAI’s embedding generator is as follows. Welcome to LangChain — 🦜🔗 LangChain 0. LangChain. property output_schema: Type [BaseModel] ¶ The type of output this runnable produces specified as a pydantic model. command model, and the OCI Generative AI endpoint. Ready to support ollama. This notebook demonstrates a sample composition of the Speak, Klarna, and Spoonacluar APIs. This is a breaking change. Quick reference. Below is a minimal example of how to create a run using the REST API. stream import TextStream # Initialize a TextStream stream = TextStream () # Send a message and return an iterator of results for result in stream . This example goes over how to use the Zapier integration with a SimpleSequentialChain, then an Introduction. . Dec 21, 2023 · To use HuggingFace hosted API endpoints with LangChain, you can utilize the HuggingFaceEndpoint class. Apr 21, 2023 · This happens when the response returned by the API might be too big. What is Langchain? LangChain is a framework for developing applications powered by language models. LangChain simplifies every stage of the LLM application lifecycle: Development: Build your applications using LangChain's open-source building blocks and components. return_only_outputs ( bool) – Whether to return only outputs in the response. This allows ChatGPT to automatically select the correct method and populate the correct parameters for the a API call in the spec for a given user input. First we generate a user ID for ourselves. import { OpenAI } from "langchain/llms/openai"; The OpenAI API uses API keys for authentication. At the top of the file, add the following lines to import the required libraries. example_prompt = PromptTemplate. The indexing API lets you load and keep in sync documents from any source into a vector store. However, all that is being done under the hood is constructing a chain with LCEL. Here’s a look at my completed code and response. prompt import PromptTemplate from langchain. Overview. API Chains. # Open the . Your job is to plot an example chart using matplotlib. The most basic and common use case is chaining a prompt template and a model together. env file in a text editor and add the following line: OPENAI_API_KEY= "copy your key material here". The core idea of the library is that we can “chain” together different components to create more advanced use cases around LLMs. com'. callbacks. from langchain. Let’s first import LangChain’s APIChain module, alongwith the other required modules, in our chatbot. inputs ( Union[Dict[str, Any], Any]) – Dictionary of inputs, or single input if chain expects only one param. Copy the examples to a Python file and run them. Jul 3, 2023 · Bases: Chain. adapters ¶. Chain that interprets a prompt and executes python code to do math. S. The OpenAI API is powered by a diverse set of models with different capabilities and price points. He previously served as a U. cpp API reference docs, a few are worth commenting on: n_gpu_layers: number of layers to be loaded into GPU memory. We then make the actual API call, and return the result. Usage There are two ways to achieve this: 1. js . In this tutorial, you'll learn how to build an AI chatbot that leverages Wikipedia data using the LangChain framework with the OpenAI API wrapper. Adapters are used to adapt LangChain models to other APIs. prompts import PromptTemplate. chat_models import ChatOpenAI. # import os. env. There's a bit of auth-related setup to do if you want to replicate this. API keys and default language models for OpenAI & HuggingFace are set up in config. globals import set_debug. llama-cpp-python is a Python binding for llama. The Assistants API allows you to build AI assistants within your own applications. From the llama. we will work with two LLMs – OpenAI’s GPT model and Google’s Flan t5 model. api. Extraction Using Anthropic Functions: Extract information from text using a LangChain wrapper around the Anthropic endpoints intended to simulate function calling. It goes beyond standard API calls by being data-aware and agentic, enabling connections with various data sources for richer, personalized experiences. LangServe helps developers deploy LangChain runnables and chains as a REST API. from langchain import hub from langchain. Construct the chain by providing a question relevant to the provided API documentation. Language Model is a type of model that can generate text or complete text prompts. " He is the husband of Chloris, who is the youngest daughter of Amphion son of Iasus and king of Minyan Orchomenus. chains. Mar 12, 2024 · LangChain allows the use of OpenAI Functions agents, among others. LangChain has a SQL Agent which provides a more flexible way of interacting with SQL Databases than a chain. Jump to Example Using OAuth Access Token to see a short example how to set up Zapier for user-facing situations. agents import create_openai_functions_agent. Here, we will look at a basic indexing workflow using the LangChain indexing API. LangChain is a very large library so that may take a few minutes. Jan 6, 2024 · If an API call fails, LangChain will automatically retry the request up to 6 times. LangChain has two main classes to work with language models: - LLM classes provide access to the large language model ( LLM) APIs and services. A chat model is a language model that uses chat messages as inputs and returns chat messages as outputs (as opposed to using plain text). First set environment variables and install packages: %pip install --upgrade --quiet langchain-openai tiktoken chromadb langchain langchainhub. 190 Redirecting Set environment variables. The main advantages of using the SQL Agent are: It can answer questions based on the databases' schema as well as on the databases' content (like describing a specific table). Note2: While tinkering around with this tool, I noticed some inconsistencies. First, import dependencies and load the LLM Parameters. The core idea of agents is to use a language model to choose a sequence of actions to take. A prompt for a language model is a set of instructions or input provided by a user to guide the model's response, helping it understand the context and generate relevant and coherent language-based output, such as answering questions, completing sentences, or engaging in a conversation. Update your code to this: from langchain. May 2, 2023 · May 2, 2023. chains import APIChain from langchain. These models can be easily adapted to your specific task including but not limited to content generation, summarization, semantic search, and natural language to code translation. 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. To access the OpenAI key, make an account on the OpenAI platform. To work with OCI Generative AI, import the OCI LLM interface, called OCIGenAI, from the LangChain library. Directly set up the key in the relevant class. [Legacy] Chains constructed by subclassing from a legacy Chain class. OPENAI_API_KEY="" If you'd prefer not to set an environment variable, you can pass the key in directly via the openai_api_key named parameter when initiating the OpenAI LLM class: 2. This API can be used to interact with your StateGraph from any programming language that can make HTTP requests. LangChain is a framework that simplifies the process of creating generative AI application interfaces. Best Practices for Using LangChain Embeddings Jan 31, 2023 · 1️⃣ An example of using Langchain to interface to the HuggingFace inference API for a QnA chatbot. We’ll use OpenAI in this example: OPENAI_API_KEY=your-api-key. The Example Selector is the class responsible for doing so. chains import ConversationChain from langchain_community. import os. This feature makes the embedding process more robust and reliable. It accepts a set of parameters from the user that can be used to generate a prompt for a language model. Specifically, it helps: Avoid writing duplicated content into the vector store; Avoid re-writing unchanged content; Avoid re-computing embeddings over unchanged content APIChain enables using LLMs to interact with APIs to retrieve relevant information. llms import OpenAI conversation = ConversationChain(llm=OpenAI()) Create a new model by parsing and validating input data from keyword arguments. Faiss documentation. For example, in OpenAI Chat Completion API, a chat message can be associated with an AI, human or system role. This guide shows how to load web search results using the SerpAPILoader Jul 3, 2023 · For example, {“openai_api_key”: “OPENAI_API_KEY”} name: Optional [str] = None ¶ The name of the runnable. # Copy the example code to a Python file, e. LangGraph is a library for building stateful, multi-actor applications with LLMs, built on top of (and intended to be used with) LangChain. Mar 16, 2023 · Constants import OPEN_AI_API_KEY os. Now let’s see how to work with the Chat Model (the one that takes in a message instead of a simple string). It contains algorithms that search in sets of vectors of any size, up to ones that possibly do not fit in RAM. Attributes of LangChain (related to this blog post) As the name suggests, one of the most powerful attributes (among many Apr 9, 2023 · LangChain provides a standard interface for memory, a collection of memory implementations, and examples of chains/agents that use memory. Neleus is a character in Homer's epic poem "The Odyssey. This script will host all our application logic. Introduction. These only provide minimal examples of how to use the API, see the documentation for more information about the API and the extraction use-case documentation for more information about how to extract information using LangChain. This class was introduced in a pull request and allows for the integration of HuggingFace API endpoints. Finally, set the OPENAI_API_KEY environment variable to the token value. """. Head to the API reference for detailed documentation of all attributes and methods. These templates extract data in a structured format based upon a user-specified schema. schema import ( AIMessage A member of the Democratic Party, Obama was the first African-American president of the United States. Next, use the DefaultAzureCredential class to get a token from AAD by calling get_token as shown below. All parameters supported by SearchApi can be passed when executing the query. llm = ChatOpenAI(model="gpt-3. Security warning: Prefer using template_format=”f-string” instead of. IDG. A JavaScript client is available in LangChain. ipynb <-- Example of using LangChain to interact with CSV data via chat, containing a verbose switch to show the LLM thinking process. Then add this code: from langchain. LangChain is a framework for developing applications powered by large language models (LLMs). Azure OpenAI Service provides REST API access to OpenAI's powerful language models including the GPT-4, GPT-3. In chains, a sequence of actions is hardcoded (in code). js. touch . The Assistants API currently supports three types of tools: Code Interpreter, Retrieval, and Function calling. Note: new versions of llama-cpp-python use GGUF model files (see here ). An Assistant has instructions and can leverage models, tools, and knowledge to respond to user queries. Next, we need to define Neo4j credentials. #. While this is downloading, create a new file called . Task. Visit Google MakerSuite and create an API key for PaLM. In addition, it provides a client that can be used to call into runnables deployed on a server. Neleus has several children with Chloris, including Nestor, Chromius, Periclymenus, and Pero. g. run("AI Engineer Dec 1, 2023 · To use AAD in Python with LangChain, install the azure-identity package. The model is supposed to follow instruction from system chat message more closely. Create your own random data. This formatter should be a PromptTemplate object. Inside your lc-qa-sms directory, make a new file called app. Since each run represents the start and end of a function call (or other unit of work), we typically log the run in two calls: First create the run by submitting a POST request at the beginning of the function call; Then update the run via a PATCH request at the end. pull("hwchase17/openai OpenAI assistants. search = SearchApiAPIWrapper(engine="google_jobs") search. A template may include instructions, few-shot examples, and specific context and questions appropriate for a given task. Review full docs for full user-facing oauth developer support. Examples using SimpleSequentialChain¶!pip3 install rebuff openai -U. LangGraph is a library for building stateful, multi-actor applications with LLMs. senator from Illinois from 2005 to 2008 and as an Illinois state senator from 1997 to 2004, and previously worked as a civil rights lawyer before entering politics. These can be called from LangChain either through this local pipeline wrapper or by calling their hosted inference endpoints through OpenAI conducts AI research with the declared intention of promoting and developing a friendly AI. 5-turbo", temperature=0) prompt = hub. Prompt templates are predefined recipes for generating prompts for language models. # Optional, use LangSmith for best-in-class observability. Configure a formatter that will format the few-shot examples into a string. Below are two sample curl requests to demonstrate how to use the API. """Add new example to store. Llama. Faiss. Follow these installation steps to set up a Neo4j database. If your API requires authentication or other headers, you can pass the chain a headers property in the config object. Mar 6, 2024 · Run the code from the terminal: python my-langchain-app. Users can access the service through REST APIs, Python SDK, or a web Mar 25, 2023 · In this article, we are going to dwell on how to integrate Azure OpenAI models’ API into LangChain, including some examples in Python. LANGSMITH_API_KEY=your-api-key. chat_with_csv_verbose. In the terminal, create a Python virtual environment and activate it. It also contains supporting code for evaluation and parameter tuning. base import AsyncCallbackManager,CallbackManager from langchain. I leveraged a sample dataset of the Sales Performance DQLab Store from Kaggle to chat with data to figure out valuable insight. This project contains example usage and documentation around using the LangChain library to work with language models. ipynb: LLM: Generate text: generate May 18, 2023 · This helps guide the LLM into actually defining functions and defining the dependencies. from langchain import OpenAI, ConversationChain llm = OpenAI(temperature=0) conversation = ConversationChain(llm=llm, verbose=True) conversation. 2️⃣ Followed by a few practical examples illustrating how to introduce context into the conversation via a few-shot learning approach, using Langchain and HuggingFace. vectorstore_cls: A vector store DB interface class, e. LangChain strives to create model agnostic templates to 3 days ago · Args: examples: List of examples to use in the prompt. prompt import API_RESPONSE_PROMPT. Let's now try to implement this idea of LangChain in a real use-case and I'm certain that would help us to 1 day ago · langchain_core. Go to API keys and Generate API key with the option : Create new secret key. Nov 17, 2023 · This quick start focus mostly on the server-side use case for brevity. Create a formatter for the few-shot examples. source venv/bin Feb 25, 2023 · A general sketchy workflow while working with Large Language Models. Apr 29, 2024 · Here's a simplified example of using the LangChain Streaming API: from langchain_community . For example, below we run inference on llama2-13b with 4 bit quantization downloaded from HuggingFace. It is inspired by Pregel and Apache Beam . LANGCHAIN_TRACING_V2=true. from_llm(OpenAI()) Create a new model by parsing and validating input data from keyword arguments. Chat Models are a core component of LangChain. Facebook AI Similarity Search (Faiss) is a library for efficient similarity search and clustering of dense vectors. Basic example: prompt + model + output parser. In this example, we initialize the interface with the default authentication method (API key), the cohere. This is an example of how to use langgraph-api to stand up a REST API for your custom LangGraph StateGraph. embeddings: An initialized embedding API interface, e. Developers working on these types of interfaces use various tools to create advanced NLP apps; LangChain streamlines this process. LangChain integrates with many model providers. ir ru oy bm xz mt xf jm qe jg