Langchain action agent github. 《LangChain 实战》配套实验示例代码.
- Langchain action agent github. However, when I run the code, the action tool is applied properly, but does not generate a final answer. js - langchain-ai/agent-inbox-langgraphjs-example Apr 16, 2024 · Checked other resources I added a very descriptive title to this question. agents import AgentExecutor, create_openai_tools_agent from langchain. A Python library for creating hierarchical multi-agent systems using LangGraph. The schemas for the agents themselves are defined in langchain. E. Mar 6, 2024 · Hey @FraRici90, great to see you back! Hope you've been doing well since our last chat. Create a new model by parsing and validating input data from keyword arguments. args: The arguments for the action. csv. Agents select and use Tools and Toolkits for actions. 4 I create a custom llm just like in the tutorial but when i use it on a mkrl agent it does not return to the agent the custom response. prompts import PromptTemplate template = '''Answer the following questions as best you can. Use LangGraph to build stateful agents with first-class streaming and human-in-the-loop support Nov 9, 2023 · I tried to create a custom prompt template for a langchain agent. language_models import OpenAI # or your specific model import # Initialize your language model model = OpenAI (api_key="your-api-key") # Replace with your model initialization # Create the CSV agent csv_agent = create_csv_agent ( Sep 7, 2023 · 🤖 Hello, Thank you for your question. Hierarchical systems are a type of multi-agent architecture where specialized agents are coordinated by a central supervisor agent. """ # noqa: E501 from __future__ import annotations import json from typing import Any, List, Literal, Sequence, Union from langchain_core. The agent then returns action. Contribute to TheAILearner/Langchain-Agents development by creating an account on GitHub. It is easy to write custom tools, and you can easily pass these to the model. Apr 2, 2024 · I am using MacOS, and installed Ollama locally. agents. But when I ask follow up questions like "How to delete it?, can we use this for X?," Its paraphrasing questions incorrectly from chat history. 276 Windows Python 3. langgraph-bigtool is a Python library for creating LangGraph agents that can access large numbers of tools. From what I understand, the issue is about the Agent Executor in the Custom Agent with Tool Retrieval example sometimes returning the answer itself as the Action Input, leading to inconsistent and nonsensical In Agents, a language model is used as a reasoning engine to determine which actions to take and in which order. py: An agent that replicates the MRKL demo (View the app) minimal_agent. agent. py" script. May 27, 2024 · LangChain-MultiAgent. name equals FINISH_NAME. py: Simple app using StreamlitChatMessageHistory for LLM conversation memory (View the app) mrkl_demo. tools import DuckDuckGoSearchRun from langchain_openai import ChatOpenAI from langchain. 😊 Based on the context provided, it seems like you're facing two main issues: The ReAct agent in LangChain is passing the "Action Input" as a single string instead of a dictionary of parameter-value pairs. It also includes a simple web interface for interacting with the agent. Same issue even if I base the class off BaseCallbackHandler Learning to Build and Orchestrate action agents for different tasks using Langchain Contribute to langchain-ai/agent-protocol development by creating an account on GitHub. I used the GitHub search to find a similar question and Dec 19, 2024 · Checked other resources I added a very descriptive title to this issue. I used the GitHub search to find a similar question and Agents involve an LLM making decisions about which Actions to take, taking that Action, seeing an Observation, and repeating that until done. Create the SQL query chain: Use LangChain to create a Oct 28, 2024 · from langchain_experimental. conversation. The AgentExecutor class has parameters like max_iterations and max_execution_time that control these limits. Dec 9, 2024 · langchain. My goal is to support the LangChain community by giving these fantastic 🦜🔗 Build context-aware reasoning applications. invoke (data) return {"agent_outcome 🦜🔗 Build context-aware reasoning applications. I used the GitHub search to find a similar question and Jan 30, 2024 · Checked other resources I added a very descriptive title to this question. I printed Additionally, ensure that none of the tools used by the multi-action agent have the returnDirect property set to true, as this is not supported for multi-action agents [1] [2]. name equals "ERROR". I used the GitHub search to find a similar question and Oct 1, 2023 · How to build a LangChain agents that can interact with data from a postgresql database of an Human Resources Systems. The agent operates by maintaining an internal state and iteratively performing actions based on the input and the results of previous actions. Langchain Agents. memory import ConversationBufferMemory from langchain import OpenAI from langchain. The action. These patterns demonstrate different approaches to agent architecture, from simple tool usage to complex autonomous systems. action_request: The action and arguments for the interrupt action: The name, or title of the action. It goes well so far. 0. tool_input – The A Langchain Action driven agent demo of a weather conversational chatbot Raw action_driven_chatbot. Using the AsyncCallbackManager on a custom class based off AsyncCallbackHandler. . You need an OpenAI API key for this project. To improve your LLM application development, pair LangChain with: LangSmith - Helpful for agent evals and observability. Sep 24, 2024 · To implement a Human-In-The-Loop logic where the agent requests confirmation from a human to process a specific tool in a cloud-hosted Agents/Tools application with the front-end being WhatsApp or a WebChat, you can follow these steps: Set up the environment: Ensure you have the necessary packages installed and environment variables set up. They both use a language model chain (LLMChain) to decide what action to take and have methods to parse the output of the language model chain into an agent action or finish. This JSON object should contain the tool input. I used the GitHub search to find a similar question and Jun 2, 2023 · System Info The MRKL and chat output parsers currently will allow an LLM response to generate a valid action, as well as hallucinate a "final answer" based on that response. I used the GitHub search to find a similar question and May 29, 2024 · To resolve the infinite loop problem in your LangChain CSV agent with Streamlit, you need to ensure that the agent is correctly configured to stop after a certain number of iterations or a time limit. - kanad13/Agentic-AI Jan 30, 2024 · Checked other resources I added a very descriptive title to this question. Create the agent: Use the defined tools and a language model to create an agent. agents import AgentFinish from langgraph. serializable import Serializable from langchain_core. Dec 4, 2024 · To generate JSON output using an agent in LangChain, you can use the create_json_chat_agent function. This AgentAction # class langchain_core. These patterns are based on the Anthropic blog post "Building Effective AI Agents" 🦜🎤 Voice ReAct Agent This is an implementation of a ReAct -style agent that uses OpenAI's new Realtime API. An Agentic AI chatbot that transforms user questions into actionable tasks using LangChain, enabling intelligent and dynamic interactions. The log is used to pass along extra information about the action. Jupyter Notebooks to help you get hands-on with Pinecone vector databases - pinecone-io/examples This repository contains sample code to demonstrate how to create a ReAct agent using Langchain. I used the GitHub search to find a similar question and The ReAct agent: Takes a user query as input Reasons about the query and decides on an action Executes the chosen action using available tools Observes the result of the action Repeats steps 2-4 until it can provide a final answer By default, it's set up with a basic set of tools, but can be easily extended with custom tools to suit various use cases. ReAct Agents Overview ReAct agents in LangChain are designed to handle natural language inputs, process them, and determine the appropriate actions to take using a set of integrated tools. Dec 9, 2024 · The schemas for the agents themselves are defined in langchain. Specifically, check the equality operator (==) used for llm and correct it to a single =. About 极客时间：LangChain实战课 - 这是LangChain框架早期设计的一系列重点模块的直接而清晰的示例和讲解。随着LangChain的快速演进，有些代码需要安装新的版本进行迭代。希望大家在快速浏览课程概念（仍有价值）的同时，自行学习LangChain最新的代码和进展。 Build resilient language agents as graphs. param log: str [Required] ¶ Additional information to log about the action 🦜🔗 Build context-aware reasoning applications. I searched the LangChain documentation with the integrated search. When I am using langgraph create_react_agent, the agent is most of the time saying "I am sorry, I cannot fulfill this request. , email drafts, tool parameters). Contribute to langchain-ai/langgraph development by creating an account on GitHub. Open Agent Platform provides a modern, web-based interface for creating, managing, and interacting with LangGraph agents. agent_toolkits. [docs] class AgentActionMessageLog(AgentAction): """Representation of an action to be executed by an agent. The action consists of the name of the tool to execute and the input to pass to the tool. Parameters: tool – The name of the tool to execute. The agent returns the observation to the LLM, which can then be used to generate the next action. The expected behavior is for the agent to return 25. LangChain provides a standard interface for agents, a selection of agents to choose from, and examples of end to end agents. Please let me know how to fix this issue. GitHub Gist: instantly share code, notes, and snippets. Insert your OpenAI API key in the "ai-langchain-react-agent. This is when the agent has completed its task and no longer needs to interact with the user. Logic This is because t Aug 2, 2024 · from langchain_core. The project provides detailed instructions for setting up the environment and loading travel data, aiming to empower developers to integrate similar agents into their Collection of Langchain agents. Welcome to "Awesome LagnChain Agents" repository! This repository is dedicated to showcasing the most amazing, innovative, and intriguing LangChain Agents from all over the world. This is similar to AgentAction, but includes a message log consisting of chat messages. This repository contains reference implementations of various LangChain agents as Streamlit apps including: basic_streaming. Contribute to antoinewg/langchain-agent-collection development by creating an account on GitHub. Once the transcription is received the AgentExecutor chain is started and it will try to process the user input. py: A The repository contains a bare minimum code example to get started with the Agent Inbox with LangGraph. chains. Mar 5, 2024 · Checked other resources I added a very descriptive title to this question. Get your OpenAI API key here. It uses statistical methods to identify unusual patterns such as spend spikes, performance drops, and ratio anomalies in marketing campaigns. py: Simple streaming app with langchain. base import create_csv_agent from langchain_core. It uses a human-in-the-loop (HITL) flow to handle authentication with different social media platforms, and to allow the user to make changes, or accept/reject the Aug 1, 2024 · Checked other resources I added a very descriptive title to this question. I used the GitHub search to find a similar question and Overview The Anomaly Detection Agent is an advanced AI-powered tool designed to detect anomalies in marketing metrics data. , modify an email draft before sending). prebuilt. py from langchain. Agents give decision-making powers to Large Language Models (LLMs) and decide which action (s) to take to get the best answer. The assistant is easily extensible with new tools and features, allowing Apply LLMs to your data, build personal assistants, and expand your use of LLMs with agents, chains, and memories. Create an AgentAction. LangChain Agent Guide. 11. May 18, 2023 · I'm Dosu, and I'm helping the LangChain team manage their backlog. Feb 25, 2024 · Langchain AgentExecutor doesn't complete actions sometimes, ### Description **What happens?** I have a tool that transcribed user input and inserts that into the langchain agent for processing. I provide the agent a get_date function as a tool，but when I ask the agent what is today's date， the agent provide the action and action input, but instead of executing i 《LangChain 实战》配套实验示例代码. Packages: langgraph, langchain-openai. It allows language models to structure their problem-solving process into explicit, potentially revisable thought steps. The agent then runs the tool and adds the result to the memory. Ignore/Reject the action. Engineered an autonomous multi-agent system by integrating Code Interpreter, ReAct, and LangChain frameworks, which streamlined dynamic code execution and reasoning, resulting in a 35% boost in operational efficiency. Built with data science best practices and integrated with LangChain for natural language processing, this agent helps marketing The agent executes the action (e. The OpenAI Tools Agent is not accepting the tool parameter "return_direct=True" without causing an Jul 12, 2024 · Let's work together to solve this problem! To resolve the issues with creating an SQL agent using LangChain, you can follow these steps: Correct the create_sql_agent Function Call: Ensure that the parameters passed to the create_sql_agent function are correct. The supervisor controls all communication flow and task delegation, making decisions about which agent to invoke based on the current context and task requirements. I used the GitHub search to find a similar question and Apr 13, 2024 · from langchain_core. Jun 17, 2025 · Build an Agent LangChain supports the creation of agents, or systems that use LLMs as reasoning engines to determine which actions to take and the inputs necessary to perform the action. Edit data (e. Designed a robust LangGraph Bedrock LangChain JS Stream Agent Project OpenAI Project OpenAI LangChain Agent Currently the OpenAI stack includes a simple conversational Langchain agent running on AWS Lambda and using DynamoDB for memory that can be customized with tools and prompts. You will learn everything from the fundamentals of chat models to advanced concepts like Retrieval-Augmented Generation (RAG), agents, and custom tools. 2 makes much sense and it works well. Feb 14, 2024 · Checked other resources I added a very descriptive title to this question. This is useful when working with ChatModels, and is used to reconstruct conversation history from the agent's perspective. I have given the initialization code for you An example repository for getting started with the Agent Inbox and LangGraph. Provide feedback to guide the agent's next step. Dec 8, 2023 · According to the LangChain source code, the StructuredChatAgent expects the action input to be provided as a JSON object, not as plain text. , runs the tool), and receives an observation. Run the agent: Execute the agent to review git commits. Here's an example code snippet demonstrating how to set up and use this function: Feb 26, 2024 · Langchain Agent rephrasing questions incorrectlyDescription I am using langchain agent with a tool for RAG application. - ksm26/LangChain-for-LLM-Application-Development Nov 1, 2023 · Issue you'd like to raise. Dec 9, 2024 · langchain_core. agents. load. g tool call arguments. Jan 23, 2024 · Each agent can have its own prompt, LLM, tools, and other custom code to best collaborate with the other agents. Contribute to webup/langchain-in-action development by creating an account on GitHub. An Agent can use one or multiple specific "tools". It's designed to be simple yet informative, guiding you through the essentials of integrating custom tools with Langchain. args["response"]. Mar 16, 2023 · I'm also encountering this issue. config: The configuration for the interrupt allow_ignore: Whether the user can ignore the interrupt Mar 31, 2024 · Checked other resources I added a very descriptive title to this issue. Raises ValidationError if the input data cannot be parsed to form a valid model. I used the GitHub search to find a similar question and LangChain is a framework for developing applications powered by large language models (LLMs). 🦜🔗 Build context-aware reasoning applications. For these applications, LangChain simplifies the entire application lifecycle: Open-source libraries: Build your applications using LangChain's open-source components and third-party integrations. Human Review: Users can: Review proposed actions (e. In Aug 31, 2023 · System Info Langchain 0. agents import Tool from langchain. This is often achieved via tool-calling. exceptions. Oct 1, 2024 · Checked other resources I added a very descriptive title to this question. Contribute to lloydchang/langchain-ai-langgraph development by creating an account on GitHub. I wanted to let you know that we are marking this issue as stale. An agent is a custom Feb 6, 2024 · Checked other resources I added a very descriptive title to this question. To address these issues and facilitate communication with external applications, we introduce the concept of an Agent as a processor. Contribute to langchain-ai/langchain development by creating an account on GitHub. g. The main difference between these two classes lies in Sep 5, 2024 · Hello, @SAIL-Fang! To create a custom Agent that reviews git commits and checks their names using LangChain, you can follow these steps: Define the tools: Create a tool that can interact with the git repository to fetch commit names. Aug 29, 2024 · Checked other resources I added a very descriptive title to this question. Here's a step-by-step This package provides a LangChain BaseTool implementation based on the sequential thinking pattern, inspired by the Model Context Protocol (MCP) server implementation. param log: str [Required] # Additional information to log about the action. Classes Build resilient language agents as graphs. That means there are two main considerations when thinking about different multi-agent workflows: What are the multiple independent agents? How are those agents connected? This thinking lends itself incredibly well to a graph representation, such as that provided by langgraph. This log can be used in This YouTube tutorial goes over the architecture and concepts used for easily spinning up agents with using LangChain using OpenAI's API - edrickdch/langchain-agents Feb 27, 2025 · This project combines two functionalities: a Code Interpreter using LLM Agent Orchestration and Tool Utilization, and a ReAct LangChain Agent example. Apr 20, 2024 · langchain_core. I used the GitHub search to find a similar question and di Before executing certain tool calls within the response_agent (interrupt_handler node). It's designed with simplicity in mind, making it accessible to users without technical expertise, while still offering advanced capabilities for developers. tool_executor import ToolExecutor # This a helper class we have that is useful for running tools # It takes in an agent action and calls that tool and returns the result tool_executor = ToolExecutor (tools) # Define the agent def run_agent (data): agent_outcome = agent_runnable. When I ask specific questions it works well. name is in the list of tools (tools). It leverages LangGraph's long-term memory store to allow an agent to search for and retrieve relevant tools for a given problem. Feb 23, 2024 · Checked other resources I added a very descriptive title to this question. Specifically, we enable this model to call tools by providing it a list of LangChain tools. In the agent execution the tutorial use the tools name to tell the agent what tools it must us Contribute to n-mhatre/ReAct-Agent-Implementation-from-Scratch-with-LangChain development by creating an account on GitHub. AgentAction [source] # Bases: Serializable Represents a request to execute an action by an agent. This is rendered in the Agent Inbox as the main header for the interrupt event. OutputParserException: Parsing LLM output produced both a final answer and a parse-able action:: Thought: Do I need to use a tool? Yes Jul 15, 2024 · Checked other resources I added a very descriptive title to this question. When the agent reaches a stopping condition, it returns a final return value. Accept the agent's proposed action. I used the GitHub search to find a similar question and di Feb 13, 2024 · from langchain_community. Some of the time the Agent realised it needs to do an action and Build resilient language agents as graphs. May 25, 2023 · Based on my understanding, the issue is about a pandas dataframe agent in the Langchain library returning incorrect results even though the action input is correct. I used the GitHub search to find a similar question and Nov 6, 2023 · The loop breaks when: The action. AgentAction [source] ¶ Bases: Serializable Represents a request to execute an action by an agent. utilities import SerpAPIWrapper from langchain. Aug 30, 2023 · Explores the implementation of a LangChain Agent using Azure Cosmos DB for MongoDB vCore to handle traveler inquiries and bookings. Mar 1, 2024 · Checked other resources I added a very descriptive title to this issue. The Github toolkit contains tools that enable an LLM agent to interact with a github repository. The LangChain agents will be queried for use cases like employee password reque This repository contains a comprehensive, project-based tutorial that guides you through building sophisticated chatbots and AI applications using LangChain. """ message_log: Sequence[BaseMessage] """Similar to log, this can be used to Feb 28, 2025 · Familiarity with agent architectures, chat models, and tools. My objective is to develop an Agent using Langchain, that can take actions on inputs from LLM conversations, and execute various scripts or one-off s This repository contains an 'agent' which can take in a URL, and generate a Twitter & LinkedIn post based on the content of the URL. ChatOpenAI (View the app) basic_memory. In LangChain for LLM Application Development, you will gain essential skills in expanding the use cases and capabilities of language models in application development using the LangChain framework. agents import initialize_agent import os The role of Agent in LangChain is to help solve feature problems, which include tasks such as numerical operations, web search, and terminal invocation that cannot be handled internally by the language model. Both LLMSingleActionAgent and Agent classes in LangChain are concrete implementations of the BaseSingleActionAgent class. To continue talking to Dosu, mention @dosu. BaseMultiActionAgent ¶ class langchain. You have access to the following tools: {tools} Use the following format: Question: the input question you must answer Thought: you should always think about what to do Action: the action to take, should be one of [{tool_names}] Action Input: the input to the action, should be in A collection of proven patterns for building effective AI agents using LangChain and LangGraph. AgentAction ¶ class langchain_core. In this tutorial we LangChain’s ecosystem 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. I followed this langchain tutorial . BaseMultiActionAgent [source] ¶ Bases: BaseModel Base Multi Action Agent class. I used the GitHub search to find a similar question and di Sep 8, 2024 · The create_react_agent of langchain 0. messages import ( AIMessage, BaseMessage, FunctionMessage, HumanMessage, ) Jan 14, 2024 · I tries to make custom LLM with LangChain and want to use a ReAct agent. Jun 15, 2025 · This project uses: LangChain tools and agents to modularize tasks OpenAI’s GPT-4o-mini to keep responses fast and insightful A composite GitHub Action to encapsulate everything cleanly github-script to post comments from the output Here’s a small excerpt from the agent code: agent = initialize_agent( tools=[code_review_tool, security_scan AgentAction # class langchain_core. You mentioned that you believe the issue lies with the observation rather than the LLM. This project is a Python-based implementation that utilizes OpenAI's GPT model to create a helpful assistant capable of answering various questions, extracting information from web pages, and performing several other tasks. chat_models. After executing actions, the results can be fed back into the LLM to determine whether more actions are needed, or whether it is okay to finish. Curated list of agents built on LangChain. prompts import PromptTemplate search_tool = DuckDuckGoSearchRun () tools = [search_tool] react_openai_tools = """ Answer the following questions as best you can. nqemi erzw mavl qmn yeamzu wncm pfhroy myljs zxha umxugi