Langchain pandas agent

9 to work with pandas agent because of the following invocation: Google colab and many other easy-to-use platforms for developers however support python3. temperature=0, model="gpt-3. I’ve managed to work around by patching langchain. schema. Expectation Nov 19, 2023 · Creating the agent is a simple process since we are going to use the create_pandas_dataframe_agent provided by Langchain! For those who might not be familiar with it, an agent is a component that can help to tap into a collection of tools, making decisions on which to use based on the users’ input. read_csv ('csv path') pd_agent = create_pandas_dataframe_agent (OpenAI (temperature = 0), df, verbose = True) # pd_agent. Mar 8, 2024 · Based on the context provided, the create_csv_agent and create_pandas_dataframe_agent functions in the LangChain framework serve different purposes and their usage depends on the specific requirements of your data analytics tasks. 0: Use Use new agent constructor methods like create_react_agent, create_json_agent, create_structured_chat_agent, etc. I changed it a bit as I am using Azure OpenAI account referring this. agents This is a Jupyter Notebook which explains how to use LangChain and the Open AI API to create a PandasDataFrame Agent. It's easy to get the agent going, I followed the examples in the Langchain Docs. However, when the model can't find the answers from the data frame, I want the model to google the question and try to get the answers from the website. m Apr 29, 2024 · It simplifies data analysis by letting you talk to your data using natural language. Sep 29, 2023 · dosubot [bot] bot on Sep 29, 2023. So far I'm able to integrate Mistral 7B Instruct model with langchain , but I 'm not able to get final answer. 5. In Agents, a language model is used as a reasoning engine to determine which actions to take and in which order. Next, we will use the high level constructor for this type of agent. See examples of advanced querying operations, comparison with traditional query languages, and future applications. This article provides a concise step-by-step guide to creating a Langchain agent using the pre-built pandas agent Mar 6, 2024 · Here's an example of how you can do this: from langchain_openai import ChatOpenAI from langchain_experimental. In layers deep, its architecture wove, A neural network, ever-growing, in love. Dec 2, 2023 · Based on the information you've provided and the context from the LangChain repository, it seems like you're trying to conditionally create or update a Pandas DataFrame agent using create_pandas_dataframe_agent in the LangChain framework, especially when dealing with dynamically created DataFrames from functions that agents may or may not call. 5. It’s based on the popular Python library pandas. base import BaseCallbackManager from langchain. A Pandas DataFrame is a popular data structure in the Python programming language, commonly used for data manipulation and analysis. The name of the dataframe is `df` You are an Dec 22, 2023 · I am using the CSV agent which is essentially a wrapper for the Pandas Dataframe agent, both of which are included in langchain-experimental. Also I have tried to add memory into the agent via this pieace of code: pd_agent. It imports necessary libraries, handles API key loading, displays a user-friendly interface for file upload and data preview, creates a Pandas DF agent with OpenAI, and executes user queries. This agent takes df, the ChatOpenAI model, and the user's question as arguments to generate a response. Nov 21, 2023 · from langchain. Jul 30, 2023 · I would like to make two Langchain agents cooperate, the first one performs a search on a vector database that contains information about operating procedures (PDF file), the second one is pandas dataframe agent and performs queries on the data. 8 What is LangChain. read_csv ( "your_data. llm_chain. Firstly, you would need to create a CSV agent using the create_csv_agent function from the LangChain agent toolkits. You mentioned that you believe the issue lies with the observation rather than the LLM. May 17, 2023 · Setting up the agent is fairly straightforward as we're going to be using the create_pandas_dataframe_agent that comes with langchain. instead. I am developing a chatbot/question-answer agent using GPT-4 on pandas dataframe in langchain. read_csv, "xls CSV. 89 lines (71 loc) · 2. This notebook is accompanied a more detailed Medium article https://zhijingeu. Jun 28, 2024 · langchain. CSV Agent of LangChain uses CSV (Comma-Separated Values) format, which is a simple file format for storing tabular data. PandasAI is a Python library that extends pandas, the well-known data analysis and manipulation tool, with Generative AI features. Agents are a method of using a language model as a reasoning engine to determine how to interact with the outside world based on the user's input. Apr 21, 2023 · Pandas Dataframe Agent. Customizable agents. I have integrated LangChain's create_pandas_dataframe_agent to set up a pandas agent that interacts with df and the OpenAI API through the LLM model. llms. I would like depending on the user’s query to invoke the correct agent, someone can help me? thanks a lot! Handle parsing errors. - Assembling these modular components for specific use cases. base. Mar 12, 2023 · Dataframes (df) are generic containers to store different data-structures and pandas (or CSV) agent help manipulate dfs effectively. create_pandas_dataframe_agent from langchain_experimental. It provides a set of functions to generate Apr 26, 2024 · Agents in LangChain are components that allow you to interact with third-party tools via natural language. 281 does not use the SystemMessage in its implementation and suggested workarounds. One of LangChain's distinct features is agents (not to be confused with the sentient eradication programs of The Matrix). from langchain import hub. Jul 14, 2023 · import boto3 import json import os import sys from langchain. agent. Jun 15, 2023 · To handle the token size issue when using the create_pandas_dataframe_agent with GPT-3. tools. AgentType. Reload to refresh your session. ¶. This agent is more focused on working with CSV files specifically. Aug 7, 2023 · Pandas: The well-known library for working with tabular data. Then, I installed langchain-experimental and changed the import statement to 'from langchain_experimental. Agents are systems that use LLMs as reasoning engines to determine which actions to take and the inputs to pass them. Oct 23, 2023 · Let him answer. But you can easily control this functionality with handle_parsing_errors! Aug 31, 2023 · 2. Agents select and use Tools and Toolkits for This notebook goes over how to load data from a pandas DataFrame. Jul 5, 2023 · By leveraging Langchain, you can build your own agent and automate data analysis. Sep 26, 2023 · Hi, @RaviChanduUmmadisetti, I'm helping the LangChain team manage their backlog and am marking this issue as stale. This toolkit is used to interact with the browser. 2 is out! Leave feedback on the v0. The create_pandas_dataframe_agent function is a pivotal component for integrating pandas DataFrame operations within a LangChain agent. agents import load_tools from langchain. This notebook shows how to use agents to interact with a pandas dataframe. After uploading a CSV file formatted to be read as a Dataframe by Pandas, I asked the same budget-related questions. 1 docs here. %pip install --upgrade --quiet langchain langchain-community langchainhub langchain I am trying to use the Pandas Agent create_pandas_dataframe_agent, but instead of using OpenAI I am replacing the LLM with LlamaCpp. Load the data and create the Agent. But current langchain implementation requires python3. You signed in with another tab or window. We will use the LangChain wrap Oct 5, 2023 · Hi guys, after successfully trying out langchain pandas' agents with Open AI, my next aim is to use open source LLM to query database. In this video, you will discover how you can harness the power of LangChain, Pan Python Streamlit web app allowing users to interact with their data from a CSV or XLSX file, utilizing OpenAI API and LangChain. Occasionally the LLM cannot determine what step to take because its outputs are not correctly formatted to be handled by the output parser. The expected behavior is for the agent to return 25. agent_types. FORMAT_INSTRUCTIONS = f"""Use the following format: Question: the input question you must answer. Here's a sample code snippet to illustrate this: from langchain. The name of the dataframe is `df`. 4. In your code, you're correctly creating an instance of ChatOpenAI (which is a subclass of BaseLanguageModel) and passing it as the 'llm' argument to create_pandas_dataframe_agent. Jul 1, 2023 · Implementation of CSV Agent s. Security Notice: This agent relies on access to a python repl tool which can execute arbitrary code. However, there is no SQL Agent in the current version of LangChain. I want to save the output from verbose into a variable, but all I can access from the agent. session_state['chat_history'] methods. agent. llm import LLMChain from langchain. 📄️ PlayWright Browser. Apr 18, 2023 · """Agent for working with pandas objects. Specifically, we'll use the pandas DataFrame Agent, which allows us to work with pandas DataFrame by simply asking questions. This notebook shows how to use agents to interact with data in CSV format. The core idea of agents is to use a language model to choose a sequence of actions to take. memory = memory. 🤖. This can be dangerous and requires a specially sandboxed environment to be safely used. chat_models import AzureChatOpenAI from langchain. configurable_alternatives (ConfigurableField (id = "llm"), default_key = "anthropic", openai = ChatOpenAI ()) # uses the default model Langchain pandas agents (create_pandas_dataframe_agent ) is hard to work with llama models. pip uninstall langchain pip install langchain pip install langchain_experimental Then in code: Jul 4, 2023 · 3. 0. This function reads CSV data from the provided path(s), converts it into a pandas DataFrame, and then uses this DataFrame to create a pandas DataFrame agent. agents import ZeroShotAgent from langchain. How can I save the verbose output to a variable so that I can use later? My code: Aug 25, 2023 · I am trying to make an LLM model that answers questions from the panda's data frame by using Langchain agent. . LangChain 0. In this case, by default the agent errors. tools import Tool question = 'Which itemnumber has the most sales and what is the product description of the itemnumber?' search = SerpAPIWrapper(serpapi_api_key Jun 5, 2023 · If I only use Retrieval QA Chain, and enables streaming, it can start typing the output in less than 5 seconds. Jun 28, 2024 · An AgentExecutor with the specified agent_type agent and access to a PythonAstREPLTool with the loaded DataFrame (s) and any user-provided extra_tools. May 3, 2023 · Langchain Agent Errors and Recommendations for chatbot (Error: json. agents import create_pandas_dataframe_agent from langchain. It excels in tasks such as grouping and aggregating data as well as statistical analysis. pandas as pd: A library for data manipulation. agents: A function to create an agent that interacts with pandas DataFrames. agents import AgentExecutor, create_openai_functions_agent from langchain_core. From minds of brilliance, a tapestry formed, A model to learn, to comprehend, to transform. messages import AIMessage, HumanMessage from langchain_core. run('some question on dataframe') # you can print below print (pd_agent. Hello everyone, this article is a written form of a tutorial I conducted two weeks ago with Neurons Lab. To load the data, I’ve prepared a function that allows you to upload an Excel file from your local disk. Jan 10, 2024 · This function expects an instance of BaseLanguageModel as the 'llm' argument. I am trying to use Langchain for structured data using these steps from the official document. It looks like you opened this issue as a feature request to add memory support to the create_pandas_dataframe_agent in Langchain for post-processing a trained model. The results of those actions can then be fed back into the agent and it determines whether more actions are needed, or whether it is okay to finish. Agents are systems that use an LLM as a reasoning engine to determine which actions to take and what the inputs to those actions should be. chat_models: A custom module for integrating OpenAI with Azure's chat services. I'm using the create_pandas_dataframe_agent to create an agent that does the analysis with OpenAI's GPT-3. Sep 22, 2023 · Langchain is a great tool for building applications powered by LLMs. For example, you can use LangChain agents to access information on the web, to interact with CSV files, Pandas DataFrames, SQL databases, and so on. pandas. Before we proceed, we would like to confirm if this issue is still relevant to the latest version of the LangChain repository. Framework for building context-aware reasoning applications Core, modular building blocks. from langchain_openai import ChatOpenAI from langchain_experimental. langchain-pandas-agent-example LangChain is a library that utilizes natural language processing and machine learning algorithms to create agents to answer questions from CSV data. chains. Cap the max number of iterations. You signed out in another tab or window. decoder. callbacks. This approach is recommended when Natural Language API Toolkits (NLAToolkits) permit LangChain Agents to efficiently plan and combine calls across endpoints. Sure, I can guide you on how to create a LangChain conversational agent with the requirements you've mentioned. render import format_tool_to_openai_function from langchain_core. If it is, please let us know by commenting on the issue. Sep 5, 2023 · From what I understand, you raised an issue regarding problems with the SystemMessage feature in the create_pandas_dataframe_agent function. If I use the complete agent, with a few custom tools, it starts to type the answer / output within 10-20 seconds. It can read and write data from CSV files and perform primary operations on the data. It provides a series of agents that lets users interact with the LLMs on their specific Jun 29, 2023 · from langchain. language_model import BaseLanguageModel import Sep 26, 2023 · To add a custom tool to your pandas dataframe agent in the LangChain framework, you can follow these steps: Define your custom tool function. Mar 31, 2023 · The other part is the description of PythonAstREPLTool, which does not sanitize backticks by default. Apr 21, 2023 · agent_name. After initializing the the LLM and the agent (the csv agent is initialized with a csv file containing data from an online retailer), I run the agent with agent. Apr 3, 2024 · LangChain features 1. A tale unfolds of LangChain, grand and bold, A ballad sung in bits and bytes untold. We'll build the pandas DataFrame Agent app for answering questions on a pandas DataFrame created from a user-uploaded CSV file in four steps: Jun 14, 2023 · Hi @ALL, Hope all of you are doing great. llm_chain. agents import create_pandas_dataframe_agent. These variables are used to construct the prompt that will be passed to the language model. In chains, a sequence of actions is hardcoded (in code). agents. Agents are responsible for taking user input, processing it, and generating a response. (the same scripts work well with gpt3. read_csv (file_path) # Create a pandas dataframe agent with the GPT-3. agent_types import AgentType from langchain. agents. A key distinction between chains and agents, both core components of LangChain, is their Aug 6, 2023 · from langchain. For those who might not be familiar, an agent is is a software program that can access and use a large language model (LLM). You can then use this information to adjust the agent's response accordingly. A big use case for LangChain is creating agents . I am able to make it work with following code: gpt4_agent = c Jun 15, 2023 · Make natural language queries to a Pandas DataFrame using LangChain & LLM's. import openai import pandas as pd from dotenv import load_dotenv from langchain. llms import AzureOpenAI. template) # and just update your prompt along with May 1, 2024 · from langchain. csv" ) # Initialize the ChatOpenAI model llm = ChatOpenAI ( model="gpt-3. You should use the tools below to answer the question posed of you: python_repl_ast: A Python shell. May 12, 2023 · Learn how to use Langchain's Pandas Agent and CSV Agent to query large datasets using OpenAI language models. Input should be a valid python command. Mar 31, 2023 · If you are comfortable using a very powerful library called Langchain, then it's pretty much possible. chat_models import ChatOpenAI import streamlit as st import pandas as pd import os file_formats = { "csv": pd. Amidst the codes and circuits' hum, A spark ignited, a vision would come. [ Deprecated] An enum for agent types. I am running this in Python 3. prompts Feb 29, 2024 · Ensure a cohesive flow in the agent's response: To ensure a cohesive flow in the agent's response, you can modify the extract_graph_code function to return the modified code snippets along with a flag indicating whether a graph was generated. 5 (LLaMa2 based) to create a local Question&Answer system. It provides a unified interface to create agents based on different language models such as OpenAI. We pass the initialized Bedrock model, the path to the CSV file containing the data we want to analyze Apr 6, 2024 · Today, I'll show you how to use pandas dataframe agent for data analysis and monitor an LLM app in LangSmith. runnables. I have worked with Bing Chat, Bard, and Claude with no success. If it is incomplete then tell him complete answer. Then take out the relevant information from the get_next_content tool. Example. If your function requires multiple arguments, you can use the StructuredTool class or subclass the BaseTool class. llms import LlamaCpp from langchain. Jun 29, 2023 · from langchain. A zero shot agent that does a reasoning step before acting. You switched accounts on another tab or window. """. May 18, 2023 · LangChain has a specific library for Pandas called the pandas_dataframe_agent. llms import OpenAI from langchain. AgentExecutor. From what I understand, you raised an issue regarding the create_pandas_dataframe_agent function causing an OutputParserException when used with open source models. Pandas AI works by turning your questions into code for data analysis. Feb 23, 2024 · AzureChatOpenAI from langchain. agents ¶ Agent is a class that uses an LLM to choose a sequence of actions to take. agents import create_pandas_dataframe_agent import Pandas. 62¶ langchain_experimental. xlarge instance size. This can be useful to ensure that they do not go haywire and take too many steps. But it is not too hard to work around it if you're looking for a solution in the short term. from langchain. I provided a detailed response explaining that the create_pandas_dataframe_agent function in LangChain version 0. Deprecated since version 0. prompt import PREFIX, SUFFIX from langchain. csv') agent = create_pandas_dataframe_agent(OpenAI(temperature=0), df, verbose=True) agent. It provides a comprehensive set of tools for working with structured data, making it a versatile option for tasks such as data cleaning, transformation, and analysis. Oct 1, 2023 · Does Langchain's create_csv_agent and create_pandas_dataframe_agent functions work with non-OpenAl LLM models too like Llama 2 and Vicuna? The only example I have seen in the documentation (in the links below) are only using OpenAI API. _get_single_prompt to initialize PythonAstREPLTool with custom description like “A Python shell. agents import AgentExecutor, create_react_agent. agent_toolkits. ) I am trying to use local model Vicuna 13b v1. I have tried adding the memory via construcor: create_pandas_dataframe_agent(llm, df, verbose=True, memory=memory) which didn't break the code but didn't resulted in the agent to remember my previous questions. read_csv('titanic. Apr 16, 2023 · Additionally, there was a question about the expected answer from the agent executor and a comment questioning the use of gpt4all or llamaCpp models with agents. LangChain and OpenAI as an LLM engine. The create_csv_agent() function in the LangChain codebase is used to create a CSV agent by loading data into a pandas DataFrame and using a pandas agent. 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. agents import create_csv_agent llm = ChatOpenAI(model="gpt-3. This is a powerful tool to handle large datasets efficiently and allows for advanced queries and transformations. Here is a simple hack: from langchain. 5-turbo-0613 model. Return type. it works well dealing with doc QAs. agents import create_pandas_dataframe_agent from langchain. To start, we will set up the retriever we want to use, and then turn it into a retriever tool. This notebook shows how to use agents to interact with a Pandas DataFrame. agent_types import AgentType import pandas as pd # Create a pandas dataframe df = pd. 9 on a SageMaker notebook, with a ml. A zero shot agent that does a reasoning 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. 📄️ Pandas Dataframe. import os. utils import ConfigurableField from langchain_openai import ChatOpenAI model = ChatAnthropic (model_name = "claude-3-sonnet-20240229"). Sep 5, 2023 · In the LangChain codebase, we have two types of agents you mentioned: the Pandas Dataframe agent and the CSV agent. NOTE: this agent calls the Python agent under the hood, which executes LLM generated Python code - this can be bad if the LLM generated Python code is harmful. 5-turbo-0613", openai_api_key=openapi_key , streaming=True Blame. agents import create_pandas_dataframe_agent import pandas as pd # Load your DataFrame df = pd. agents import create_pandas_dataframe_agent'. template = """ You are working with a pandas dataframe in Python. This function should take a single string input and return a string output. You can use the get_num_tokens_from_messages function provided in the context to calculate the number of tokens in your input and adjust accordingly. manager import CallbackManager from langchain. #. prompts import ChatPromptTemplate, MessagesPlaceholder from langchain_openai import ChatOpenAI from typing_extensions import TypedDict # This defines the object that is passed between each node # in Aug 23, 2023 · However, upon reviewing the source code, I believe this could also be applied to the CSV agent. Agents. Use cautiously. 1. The Pandas Dataframe agent is designed to facilitate the interaction between language models and pandas dataframes. This notebook walks through how to cap an agent at taking a certain number of steps. run(user_message). llms import OpenAI from langchain import SerpAPIWrapper from langchain. 350. Thought: you should always think about what to do. streaming_stdout import StreamingStdOutCallbackHandler callback_manager = CallbackManager([StreamingStdOutCallbackHandler Jul 18, 2023 · Here's how you can achieve this: First, you'll need to import the model and use it when creating the agent. 5-turbo", temperature=0 ) # Create the pandas Dec 11, 2023 · The create_csv_agent function in LangChain returns an instance of AgentExecutor. agent_types import AgentType from langchain. This function enables the agent to perform complex data manipulation and analysis tasks by leveraging the powerful pandas library. agents import AgentType from langchain_experimental. It is mostly optimized for question answering. agents import create_openai_functions_agent from langchain. May 5, 2024 · In this section, we create the LangChain CSV Agent using the create_csv_agent() function. Sep 27, 2023 · The create_csv_agent() function will return an AgentExecutor instance that you can use in your chain. This function loads data into a pandas DataFrame and uses a pandas agent. In this video, we are going to explore the Pandas data frame agent to try to understand what the future of data analysis holds. agents import create_pandas_dataframe_agent df = pd. JSONDecodeError: Unterminated string starting) 3 Langchain pandas agent - Azure OpenAI account Mar 15, 2024 · Apologies, but something went wrong on our end. 5-turbo-0613", openai_api_key=openapi_key , streaming=True Jun 24, 2023 · Hi, @matt7salomon I'm helping the LangChain team manage their backlog and am marking this issue as stale. 00:01 Introduction00:54 Setup01:23 Install libra Jul 21, 2023 · This tutorial explores the use of the fourth LangChain module, Agents. base import BaseLLM from Feb 14, 2024 · So create_pandas_dataframe_agent could stand to be more flexible. Below is the snippet of my code -. If you prefer a narrative walkthrough, you can find the YouTube video here: Let’s begin the…. g4dn. Jun 20, 2023 · I'm experimenting with Langchain to analyze csv documents. I know this is to be expected, since the agent needs to think about which tools to use. Apr 24, 2024 · A big use case for LangChain is creating agents. Sep 16, 2023 · I have been trying for 6 hours straight to add any memory to the pandas_dataframe_agent in my Streamlit app. If the handle_parsing_errors=True argument is passed, the function should handle any parsing errors that Jun 5, 2023 · I tried executing a langchain agent. The function first checks if the pandas package is installed. Refresh the page, check Medium ’s site status, or find something interesting to read. run is only the final answer. Finally, we will walk through how to construct a conversational retrieval agent from components. In agents, a language model is used as a reasoning engine to determine which actions to take and in which order. TEMPLATE = """ You are working with a pandas dataframe in Python. run("how many Jun 28, 2024 · def create_pandas_dataframe_agent (llm: LanguageModelLike, df: Any, agent_type: Union [AgentType, Literal ["openai-tools", "tool-calling"]] = AgentType. Oct 2, 2023 · If you want to apply the Tree-Of-Thought (ToT) change the format prompt to:. chat_models import ChatOpenAI from langchain. Oct 4, 2023 · This issue generally is one of the biggest obstacles to langchain agents -- it should truncate by default or expose a hook where we can pass a runnable to truncate the text, much like the trim_intermediate_steps runnable hook in AgentExecutor. - Integrations with LLMs, vector stores, embedding models. It is mostly Feb 29, 2024 · Ensure a cohesive flow in the agent's response: To ensure a cohesive flow in the agent's response, you can modify the extract_graph_code function to return the modified code snippets along with a flag indicating whether a graph was generated. tools import Tool question = 'Which itemnumber has the most sales and what is the product description of the itemnumber?' search = SerpAPIWrapper(serpapi_api_key Pydantic parser. 2 docs here. numpy as np: A library for numerical computations. agents import Tool from langchain_experimental. prompt. prompt. In Chains, a sequence of actions is hardcoded. 5-turbo API model agent = create_pandas_dataframe_agent Jun 28, 2024 · from langchain_anthropic import ChatAnthropic from langchain_core. The create_csv_agent function is implied to be used in a SQL database approach. 5-turbo", temperature=0 Aug 27, 2023 · GPT-4 with Langchain Pandas Dataframe Agent. May 31, 2023 · 📊 Multi-dataframe Agents | 🦜🔗 LangChain UseCasesIn this video, I will walk you through how to use agents to interact with a pandas dataframe. """ from typing import Any, List, Optional from langchain. Initialize LLM Jun 28, 2024 · langchain_experimental 0. NOTE: this agent calls the Pandas DataFrame agent under the hood, which in turn calls the Python agent, which executes LLM generated Python code - this can be bad if the LLM generated Python code is harmful. callbacks import StreamlitCallbackHandler from langchain. - Implementations of prompt templates, text splitters, agents, tools, memory, etc End-to-end chains. llms import OpenAI import pandas as pd df = pd. Jun 28, 2024 · Construct a Pandas agent from an LLM and dataframe(s). agent import AgentExecutor # from langchain. Dec 8, 2023 · What helped me was uninstalling langchain and installing the latest version, 0. 68 KB. Use this to execute python commands. I have tried conversational_memory and st. 5 Turbo, you can try the following approaches: Truncate or shorten the input text to fit within the token limit. agent_toolkits import create_pandas_dataframe_agent from langchain Oct 2, 2023 · The input_variables parameter in the create_pandas_dataframe_agent function is used to specify the variables that will be included in the prompt created by the ZeroShotAgent or OpenAIFunctionsAgent. You can view the v0. qy cc jv bs po gc gx xs oq xq