Langchain prompt chain example github. The autoreload extension is already loaded.

We'll illustrate both methods using a two step sequence where the first step classifies an input question as being about LangChain, Anthropic, or Other, then routes to a corresponding prompt chain. import os from langchain. format(adjective="colorful", noun="flower") Based on your requirements, it seems you want to use two different prompts in a single RAG chain. The keys of this dictionary should match the names of the parameters that the next chain expects. 9) prompt = PromptTemplate ( input_variables = ["product"], template = "What is a good name for a company that makes {product}?", ) # Running the Chain # Import Using human prompt with Python as HTTP Get or Post input, calculates the completions using chains of human input and templates. 2. agents. When we use load_summarize_chain with chain_type="stuff", we will use the StuffDocumentsChain. py file: Nov 12, 2023 · It first determines which tables to use based on the query, and then calls the normal SQL database chain based on those tables. messages . Feb 8, 2024 · As for the load_qa_chain function in the LangChain codebase, it is used to load a question answering chain with sources. In this guide we'll go over prompting strategies to improve graph database query generation. chains import RefineDocumentsChain, LLMChain from langchain. example_prompt = PromptTemplate. For the purpose of this lesson, the idea is to create a chain that prompts the user for a sentence and then returns the sentence. Memory: State persistence between chain or agent calls, including a standard memory interface, memory implementations, and examples of chains and agents utilizing memory. chains. py contains tests for the chain. *Security warning*: Prefer using `template_format="f-string"` instead of `template_format="jinja2"`, or make LANGCHAIN TOOLS. extensions. Example Setup First, let's create a chain that will identify incoming questions as being about LangChain, Anthropic, or Other: Note: The example code here focused on securing OpenAI models, but the same principles apply to any LLM model provider or ChatLLM model provider that LangChain supports. Jun 8, 2023 · Pass the prompt to the pal_chain pal_chain. prompts import PromptTemplate. llms import OpenAI from langchain. \n\nRoses are red. You can edit this to add more endpoints or customise your server. py: More advanced usage of chats, including Chat Models, Chat Prompt Templates, and Chat Chains. messages import HumanMessage, SystemMessage from genai import Client, Credentials from genai. Issue 2 (possible, unverfied): This has me thinking that "\n AI:" is added to the prompt, which is in line with how my llm are reacting. The template can be formatted using either f-strings (default) or jinja2 syntax. schema import BasePromptTemplate # Initialize the database db I am trying to call below chain using use MultiPromptChain in LangChain in Python. prompts import PromptTemplate from langchain. You signed in with another tab or window. prompt import PromptTemplate _DEFAULT_ENTITY_EXTRACTION_TEMPLATE = """Extract all entities from the following text. How to compose prompts together. Nov 10, 2023 · Hi, @afedotov-align, I'm helping the LangChain team manage their backlog and am marking this issue as stale. - height (float): The height of the cylinder. Dec 9, 2023 · # LangChain-Example: TextSplitter from langchain. text_splitter import RecursiveCharacterTextSplitter text="The meaning of life is to love. js starter app. This repository contains source code for Lang Chain and Prompt Engineering, aimed at providing a user-friendly interface for non-technical users to interact with advanced language models. Option 1. Given an input question, first create a syntactically correct MS SQL query to run, then look at the results of the query and return the answer to the input question. If we take a look at the LangSmith trace, we can see all three components show up in the LangSmith trace. 339 Python version: 3. Here is an example: from langchain_experimental. 文档地址： https://python. langchain: Chains, agents, and retrieval strategies that make up an application's cognitive architecture. However, the way I format the dict doesn't seem to work? KeyError: "'revenue at ABB in 2019'" Is there a solution to this? System Info System Information. This process helps agents or models handle intricate tasks by dividing them into more manageable subtasks. js, an API for language models. Cannot retrieve latest commit at this time. Create the prompt value with as usual, with required variables along with history = memory. I want to use Parallel chain on 4 chains but in that way that for first three (general_info, first_product, limits) I want to use as input var combined_text which is str. prompts import ChatPromptTemplate, PromptTemplate, format_document from langchain_core. prompts. Different methods like Chain of Thought and Tree of Thoughts are employed to guide the decomposition process effectively. As a guideline, a proper noun is generally capitalized. Dec 1, 2023 · 🤖. Azure Functions LangChain with Azure OpenAI and ChatGPT (Python v2 Function) langchain-examples. py. format(adjective="colorful", noun="flower") Dec 2, 2023 · I added an example prompt to ensure that the llm is working properly. Experiment using elastic vector search and langchain. OS: Linux OS Version: #101-Ubuntu SMP Tue Nov 14 13:30:08 UTC 2023 LangChain is a framework for developing applications powered by language models. These include: How to use few-shot examples with LLMs. def create_full_chain (retriever, openai_api_key=None, chat_memory=ChatMessageHistory ()): model = get_model ("ChatGPT", openai_api_key=openai_api_key) system_prompt = """You are a helpful AI assistant for busy professionals trying to improve their health. chains import (. Oct 31, 2023 · In this example, next_chain_inputs is a dictionary that contains the parameters you want to pass to the next chain. Let's dive into the issue you've brought up. 10 Who can help? @hwchase17 Information The official example notebooks/scripts My own modified scripts Related Components LLMs/Chat Models Embedding Models Prompts / Prompt Templat You signed in with another tab or window. ) Reason: rely on a language model to reason (about how to answer based on provided # Import PromptTemplate and OpenAI from langchain. Those who remember the early days of Elasticsearch will remember that ES nodes were spawned with random superhero names that may or may not have come from a wiki scrape of super heros from a certain marvellous comic book universe. Jul 27, 2023 · chains= [ summary_llm_chain, guest_llm_chain, host_llm_chain ] ) # Run the chain results = chain. Choices include: add to add two numbers, subtract to subtract two numbers, multiply to multiply two numbers, and divide to divide them. Use the following context and the users' chat Sep 20, 2023 · Yes, it is possible to use multiple vector stores with the RetrievalQA chain in LangChain. For more details, you can refer to the ImagePromptTemplate class in the LangChain repository. When using a local path, the image is converted to a data URL. 16 LangChain Model I/Oとは？【Prompts・Language Models・Output Parsers】 17 LangChain Retrievalとは？【Document Loaders・Vector Stores・Indexing etc. Expected: No code is execued or just calculate the valid part 1+1. Hello @Boopalanoptisol,. operation (string): The operation. Suggestion: Add a sanitizer to check the sensitive code. prompts import PromptTemplate import mlflow # Ensure the OpenAI API key is set in the environment assert "OPENAI_API_KEY" in os. \n\nHack the planet!" Apr 29, 2024 · For example, we can create a template that prompts the user to write a sentence using both a noun and an adjective: template = PromptTemplate("Please write a {adjective} sentence using a {noun}. input_variables= [ "page_content" ], template="{page_content}" Add this topic to your repo. Mar 22, 2023 · Invalid prompt schema; check for mismatched or missing input parameters. For example, if I end the prompt with "\nSummary:\n" sometimes the AI would In this guide we'll go over prompting strategies to improve graph database query generation. Stuff. Inside the template, the sentence should be specified in the following way: Mar 3, 2024 · In this example, agent_one and agent_two could be instances of AgentExecutor or LLMChain, and input_one is the initial input to the sequence. Save the context in memory with user input query and result from chain. This memory can then be used to inject the summary of the conversation so far into a prompt/chain. Here's an example of how you can do this: fromlangchain Build resilient language agents as graphs. It can be used for chatbots, text summarisation, data generation, code understanding, question answering, evaluation langserve_launch_example/chain. js project using LangChain. This class allows you to run multiple tasks concurrently, which is useful when you want to process the same input in different ways simultaneously. To create a new LangChain project and install this as the only package, you can do: langchain app new my-app --package stepback-qa-prompting. createDocuments([t. tests/test_chain. It is build using FastAPI, LangChain and Postgresql. If you want to create a chatbot that remembers the conversation history, you should use the ConversationChain class instead. " GitHub is where people build software. load_memory_variable ( {}) ['history'] Pass prompt value to SQLDatabaseChain, get the results. memory. To use a custom prompt template with a 'persona' variable, you need to modify the prompt_template and PROMPT in the prompt. 181 or above) to interact with multiple CSV files data via chat. chains import LLMChain. py: ConversationChain used for memory retention in a bio generation example. The code simplifies the process of generating human-like responses and performing language-related tasks using OpenAI's GPT Aug 27, 2023 · Here is an example of how to use these parameters: from langchain. Below is a simple example of how to create and use Conversation Summary Memory in Langchain. Good to see you again! I hope you're doing well. environ, "Please set the OPENAI_API_KEY environment variable. I used the GitHub search to find a similar question and didn't find it. Contribute to langchain-ai/langchain development by creating an account on GitHub. Issue 1: Even when using custom prompt, "Human: " is added to all of my prompts, which have been messing up my outputs. 3. And add the following code to your server. LCEL was designed from day 1 to support putting prototypes in production, with no code changes , from the simplest “prompt + LLM” chain to the most complex chains (we’ve seen folks successfully run LCEL chains with 100s of steps in production). More than 100 million people use GitHub to discover, fork, and contribute to over 420 million projects. Apr 29, 2024 · For example, we can create a template that prompts the user to write a sentence using both a noun and an adjective: template = PromptTemplate("Please write a {adjective} sentence using a {noun}. This repository contains a collection of apps powered by LangChain. This template scaffolds a LangChain. Configure a formatter that will format the few-shot examples into a string. sql import SQLDatabaseSequentialChain from langchain. \n\nThe meaning of vacation is to relax. 1-Ubuntu SMP Fri Jun 2 21:38:08 Models: Various model types and model integrations supported by LangChain. Prompts: Prompt management, optimization, and serialization. Create a formatter for the few-shot examples. basics. Many Git commands accept both tag and branch names, so creating this branch may cause unexpected behavior. world , date & title only) and NASDAQ data (from Yahoo Finance) to chat with both datasets to figure out valuable insight. stuff import StuffDocumentsChain. %load_ext autoreload %autoreload 2. langchain-extract is a simple web server that allows you to extract information from text and files using LLMs. As an open-source project in a rapidly developing field, we are extremely open to contributions, whether it be in the form of updating Apr 22, 2024 · I searched the LangChain documentation with the integrated search. Sep 25, 2023 · I understand you're trying to use a custom prompt template with a 'persona' variable in the RetrievalQA chain in LangChain and you're also curious about how the RetrievalQA chain handles custom input variables. chats. 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. This function takes in a language model ( llm ), a chain_type which specifies the type of document combining chain to use, and a verbose flag to indicate whether the chains should be run in verbose mode or not. It showcases how to use and combine LangChain modules for several use cases. Cheat Sheet: Creating custom tools with the tool decorator: Import tool from langchain. You can edit this to add more tests. The backend closely follows the extraction use-case documentation and provides a reference implementation of an app that helps to do extraction over data using LLMs. js + Next. You signed out in another tab or window. OS: Linux OS Version: #47~20. langchain We have many how-to guides for working with prompts. Although the code is generated by llm, from my perspective, we'd better not execute it directly without any checking. runnables import RunnablePassthrough , RunnableLambda from langchain_core . Returning structured output from an LLM call. " > Entering new AgentExecutor chain Thought: To write a prompt that implements the ReAct agent within LCEL using the OpenAI tools agent as described in the provided GitHub link, I first need to understand the structure and requirements of the ReAct agent and how it integrates with the OpenAI tools agent according to the LangChain documentation. js Slack app framework, Langchain, openAI and a Pinecone vectorstore to provide LLM generated answers to user questions based on a custom data set. How to use few-shot examples with chat models. LLM Agent with Tools: Extend the agent with access to multiple tools and test that it uses them to answer questions. text]); const chain = loadSummarizationChain(model, { type: "map_reduce" }); const res = await chain. Retrieval augmented generation (RAG) with a chain and a vector store. prompt import PromptTemplate. 】 18 LangChain Chainsとは？【Simple・Sequential・Custom】 19 LangChain Memoryとは？【Chat Message History・Conversation Buffer Memory】 20 LangChain Agents LangChain Examples. 4. The chain will take a list of documents, insert them all into a prompt, and pass that prompt to an LLM: from langchain. '"title"' (type=value_error) In my opinion, is needed to introduce some kind of parameter, like an escape parameter that can control if have sense to parse the string or modify the variables into the string from {variable} to {% variable %} May 14, 2023 · You would do something like this: from langchain. Description. Calculate the volume of a cylinder. base import BaseMessage Dec 15, 2023 · There are 2 different parameter passing strategies: inputs and configs: 1 - If I want to use an input parameter in the arbitrary components of the chain, then whole chain components should be wrapped by RunnablePassthrough, to pass parameter all the way down from the start of the chain to end. langchain. This includes prompt management, prompt optimization, generic interface for all LLMs, and common utilities for working with LLMs. Replace OpenAI GPT with another LLM in your app by changing a single line of code. It accepts a set of parameters from the user that can be used to generate a prompt for a language model. It showcases how two large language models can be seamlessly connected using SimpleSequentialChain. const output = await splitter. Apr 10, 2024 · I am trying to use add some examples to the few-shot prompt. LangChain is a framework for developing applications powered by language models. This memory is most useful for longer conversations, where keeping the past message history in the prompt verbatim would take up too many tokens. However, there are a few points to consider: Oct 18, 2023 · This function is used to create a chain that generates SQL queries, and it doesn't interact with the memory system of LangChain. ) Reason: rely on a language model to reason (about how to answer based on provided That is a simple example of how to create a chain using Langchain. In this example, a single sequential chain is created, allowing for a single input that generates a single output. LangGraph: A library for building robust and stateful multi-actor applications with LLMs by modeling steps as edges and nodes in a graph. Below is an example: from langchain_community. It appears that even when passing in a confirmed subclass of BaseModel, which is pydantic_schema, create_tagging_chain_pydantic(Tags, llm) is triggering validation errors. 所以，我们来介绍一个非常强大的第三方开源库： LangChain 。. Langfuse Prompt Management helps to version control and manage prompts collaboratively in one place. This parameter should be an instance of a chain that combines documents, such as the StuffDocumentsChain. chat_llm import LangChainChatInterface Mar 14, 2024 · For example, when Cypher query returns 5 records, the qa_chain says only 3 are returned. In addition, we use Langfuse Tracing via the native Langchain integration to inspect and debug the Langchain application. A simple starter for a Slack app / chatbot that uses the Bolt. LangChain Expression Language, or LCEL, is a declarative way to chain LangChain components. How to use example selectors. prompts import ChatPromptTemplate from langchain_core . These examples contain dict items as seen from the codes above. Jul 19, 2023 · To pass context to the ConversationalRetrievalChain, you can use the combine_docs_chain parameter when initializing the chain. . format(adjective="colorful", noun="flower") simple_chain. LangChain is an open-source framework created to aid the development of applications leveraging the power of large language models (LLMs). You can achieve this by using the RunnableParallel class in LangChain. I believe that the summarization quality will increase when you can pass a title to your summarization. from_llm function. To remedy this I want to grab the output of the Cypher chain, calculate the number of records and pass it explicitly in the prompt to the qa_chain. System Info System Information. The autoreload extension is already loaded. llms import OpenAI document_prompt = PromptTemplate (. call({ input_documents: output, }); 1. How to partial prompts. Apr 11, 2024 · Description. Here's an example of how you can do this: Dec 13, 2023 · This class is designed to handle few-shot learning scenarios by formatting the examples using the example_prompt attribute, which is a PromptTemplate used to format an individual example. Answering complex, multi-step questions with agents. This repository provides implementations of various tutorials found online. llms import OpenAI, SQLDatabase from langchain. I would like to pass the title of summarization. Prerequisites Nov 21, 2023 · System Info LangChain version: 0. Based on the context provided and the issues found in the LangChain repository, you can add system and human prompts to the RetrievalQA chain by creating a ChatPromptTemplate and passing it to the ConversationalRetrievalChain. chains import LLMChain from langchain. combine_documents. ipynb <-- Example of LangChain (0. We'll largely focus on methods for getting relevant database-specific information in your prompt. py contains a FastAPI app that serves that chain using langserve. Xinference gives you the freedom to use any LLM you need. run(prompt) Influence: Expected behavior. I commit to help with one of those options 👆; Example Code Feb 22, 2024 · Checked other resources I added a very descriptive title to this issue. I searched the LangChain documentation with the integrated search. Please refer to the acknowledgments section for the source tutorials where most of the code examples originated and were inspired from. A tag already exists with the provided branch name. Reload to refresh your session. From what I understand, Dosubot has provided a comprehensive response with code snippets and references, outlining the steps to create the chain in LangChain and wrap it in a Flask server for storing chat history. Here's an example of how you can do this: from langchain. This formatter should be a PromptTemplate object. This code demonstrates the chaining aspect of the Langchain framework. runnables import RunnableMap, RunnablePassthrough from langchain_openai import ChatOpenAI, OpenAIEmbeddings Langchain Decorators: a layer on the top of LangChain that provides syntactic sugar 🍭 for writing custom langchain prompts and chains ; FastAPI + Chroma: An Example Plugin for ChatGPT, Utilizing FastAPI, LangChain and Chroma; AilingBot: Quickly integrate applications built on Langchain into IM such as Slack, WeChat Work, Feishu, DingTalk. 众所周知 OpenAI 的 API 无法联网的，所以如果只使用自己的功能实现联网搜索并给出回答、总结 PDF 文档、基于某个 Youtube 视频进行问答等等的功能肯定是无法实现的。. from langchain. chat_with_multiple_csv. To associate your repository with the langchain topic, visit your repo's landing page and select "manage topics. The prompt is also slightly modified from the original. 🔗 Chains: Chains go beyond just a single LLM call, and are sequences of calls (whether to an LLM or a different utility). py: Agents with access to web search & calculator tools. llms import OpenAI # Initialize OpenAI and PromptTemplate llm = OpenAI (temperature = 0. Examples include langchain_openai and langchain_anthropic. This code snippet shows how to create an image prompt using ImagePromptTemplate by specifying an image through a template URL, a direct URL, or a local path. - radius (float): The radius of the base of the cylinder. I leveraged CNBC news data ( from data. This example demostrates how to use prompts managed in Langchain applications. 1. ") formatted_prompt = template. \n Examples include langchain_openai and langchain_anthropic. Quickstart The easiest way to secure your LangChain LLM agents is to use the get_guarded_llm() method of LakeraChainGuard to create a guarded LLM subclass that you can May 2, 2023 · Knowledge Base: Create a knowledge base of "Stuff You Should Know" podcast episodes, to be accessed through a tool. agents. py: Prompt Templates and LLM Chains used in an event planning example. This repository contains containerized code from this tutorial modified to use the ChatGPT language model, trained by OpenAI, in a node. This class allows you to route an input to one of multiple retrieval QA chains. human, {input} Create a memory object. _DEFAULT_TEMPLATE = """Given an input question, first create a syntactically correct {dialect} query to run, then look at the results of the query and return the answer. py file They accept a config with a key ( "session_id" by default) that specifies what conversation history to fetch and prepend to the input, and append the output to the same conversation history. You can achieve this by using the MultiRetrievalQAChain class. Create a custom LangChain agent dubbed "Agent AWS" that queries the AWS Well-Architected Framework and deploys Lambda functions, all backed by Amazon Bedrock and housed in a Streamlit chatbot. from langchain_core. LangChain provides a standard interface for chains, lots of integrations with other tools from langchain_core. The chains parameter is a list of the chains to be executed in sequence. langserve_launch_example/server. Commit to Help. from rag_chain import make_rag_chain. 😉. 0. To run at small scale, check out this google colab . Getting started To use this code, you will need to have a OpenAI API key. The decorator uses the function name as the tool name by default, but it can be overridden by passing a string as the first argument. Lang Chain and Prompt Engineering. Specifically: Simple chat. If you want to add this to an existing project, you can just run: langchain app add stepback-qa-prompting. The output of the first chain is automatically passed as the 🦜🔗 Build context-aware reasoning applications. run ( docs ) # Print the results print ( results) In this code, we're using SequentialDocumentsChain to chain the three prompts. Contribute to langchain-ai/langgraph development by creating an account on GitHub. web chain - It accepts one input parameter and retruns result; rag_chain - It accepts 2 input parameters, one is context that is retriever object and another is input question and return result. prompts. This would allow you to manually control the flow of data between different agents or language models. With Xinference, you're empowered to run inference with any open-source language models, speech recognition models, and multimodal models, whether in the cloud, on-premises, or even on your laptop You signed in with another tab or window. from_template("Question: {question}\n{answer}") Mar 4, 2024 · Task decomposition is a technique used to break down complex tasks into smaller and simpler steps. chat_message_histories import ChatMessageHistory. This is a simple example of using LangChain Expression Language (LCEL) to chain together LangChain modules. You switched accounts on another tab or window. A prompt template consists of a string template. Mar 31, 2024 · You signed in with another tab or window. There are several benefits to this approach, including optimized streaming and tracing support. Unless the user specifies in the question a specific number of examples to obtain, query for at most {top_k} results using the TOP clause as per MS SQL. 04. We have many how-to guides for working with prompts. Use the @tool decorator before defining your custom function. LangChain Examples. py contains an example chain, which you can edit to suit your needs. A collection of working code examples using LangChain for natural language processing tasks. to ug fq jb rs ii px yt tj kt