Langchain csv analysis github. llms import OpenAI from langchain.

Langchain csv analysis github. Acknowledgment to the creators of the Titanic, CarDekho, and Swiggy datasets for enabling rich conversational data analysis. The app leverages LangChain agents in the background to enable seamless analysis and provides the flexibility to choose from a range of Large Language Models (LLMs) such as Gemini, Claude, or GPT. 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. - ademarc/langchain-ask-csv-data Contribute to humzawaqar66/Chatbot-CSV-Analysis-OpenAI-LangChain-Streamlit-Integration development by creating an account on GitHub. This tutorial covers how to create an agent that performs analysis on the Pandas DataFrame loaded from CSV or Excel files. Each row of the CSV file is translated to one document. Have you ever wished you could communicate with your data effortlessly, just like talking to a colleague? With LangChain CSV Agents, that’s exactly what you can do Powerful web application that combines Streamlit, LangChain, and Pinecone to simplify document analysis. I used the GitHub search to find a similar question and LangChain & Prompt Engineering tutorials on Large Language Models (LLMs) such as ChatGPT with custom data. I used the GitHub search to find a similar question and The CSV analysis agent can query and analyze CSV data using Pandas. LangChain is used to create a seamless We would like to show you a description here but the site won’t allow us. This repository contains a Python-based web application, "Ask Your CSV", which allows users to upload CSV files and ask questions about the data within them. The chatbot accepts voice commands through a microphone, processes queries using Langchain and Hugging Face embeddings, and leverages the LAMA3 model via the GROQ API for powerful language understanding. Content Embedding: Creates embeddings using Hugging Face models for precise retrieval. michaelmburu / csv-data-analysis-tool-using-streamlit-and-langchain-pandas-dataframe-agent Public Notifications You must be signed in to change notification settings Fork 0 Star 0 Sep 25, 2024 · Checked other resources I added a very descriptive title to this question. That limits use in production or real-time CSV analysis. It enables the construction of cyclical graphs, often needed for agent runtimes, and extends the LangChain Expression Language to coordinate multiple chains or actors across multiple steps. This project leverages the power of large language models (LLMs) to analyze CSV datasets, generate summary reports, perform data analysis, and create visualizations (bar and line charts). llms import OpenAI def query_agent (data, query): #Parse teh CSV file and create a Pandas Dataframe from it's contents. File upload system for CSV Github Toolkit The Github toolkit contains tools that enable an LLM agent to interact with a github repository. The proposal is to separate these two files, say a smaller This project showcases a voice-activated chatbot designed to analyze CSV data using Retrieval-Augmented Generation (RAG) architecture. Azure OpenAI Sentiment Analysis with LangChain A Python-based sentiment analysis tool that processes comments from Excel/CSV files using Azure OpenAI and LangChain. js + Next. Appreciation for LangChain for their conversational AI toolkits. Synthesize Answers: Provide final answers in plain English, not just raw data tables. csv_agent import CSVAgent # Assuming CSVAgent is a BaseTool prompt = hub. Checked other resources I added a very descriptive title to this question. Text Loader: Processes plain text files and extracts content for analysis. Data_Analysis Automated Data Analysis using LangChain is a tool that lets users ask questions about their data in plain English. SQL use case: Many of the challenges of working with SQL db's and CSV's are generic to any structured data type, so it's useful to read the SQL techniques even if you're using Pandas for CSV data analysis. Nov 5, 2024 · I like to create a prompt template and attach to create_pandas_dataframe_agent. In this guide we'll go over the basic ways to create a Q&A system over tabular data An AI-powered agent that automates data analysis tasks using Groq, Langchain, and Gradio. Specifically: Simple chat Returning structured output from an LLM call Answering complex, multi-step questions with agents Retrieval augmented generation (RAG) with a chain and a vector store Retrieval augmented generation (RAG) with an agent and a vector 1. Sep 11, 2023 · Analyzing CSV data in Human Conversational format In today’s data-driven world, businesses and individuals rely on analyzing large datasets to extract valuable insights. The tool is a wrapper for the PyGitHub library. Projects for using a private LLM (Llama 2) for chat with PDF files, tweets sentiment analysis. It provides a unified interface to create agents based on different language models such as OpenAI. It uses AI to understand the questions and find answers from CSV or Excel files, making data analysis easy for everyone without writing any code. - Nicolepcx/AI-Data-Analysis-MultiAgent This template scaffolds a LangChain. Nov 6, 2024 · In LangChain, a CSV Agent is a tool designed to help us interact with CSV files using natural language. The application employs Streamlit to create the graphical user interface (GUI) and utilizes Langchain to interact with Data Analyzer with LLM Agents is an intelligent application designed to analyze CSV files using advanced language models. The application facilitates various data analysis techniques and visualizations, providing insights into the underlying patterns and statistics of the data. - GitHub - easonlai/azure_o Upload a CSV file and ask questions about the data. The project showcases two main approaches: a baseline model using RandomForest for initial sentiment classification and an enhanced analysis leveraging LangChain to utilize Large Language Models (LLMs) for more in-depth sentiment analysis. The CSV agent then uses tools to find solutions to your questions and generates an appropriate response with the help of a LLM. OpenAI and Gemini API Utilization: Use cutting-edge AI models for intelligent data interpretation and response generation. Utilizing OpenAI's language model, the application intelligently generates responses, providing a user-friendly interface for data exploration and analysis. The proposal is to separate these two files, say a smaller Apr 8, 2023 · Hi, @bleso-a I'm helping the LangChain team manage their backlog and am marking this issue as stale. The tool analyzes the sentiment and emotion of comments and provides human-like responses based on the analysis. lenaar / financial-ai-agent Public Notifications You must be signed in to change 🦜🔗 Build context-aware reasoning applications. Contribute to langchain-ai/langchain development by creating an account on GitHub. Feb 7, 2024 · Here's an example of how you might do this: from langchain import hub from langchain_community. This repository contains various examples of how to use LangChain, a way to use natural language to interact with LLM, a large language model from Azure OpenAI Service. QnA bot on a CSV. Integrated with LangChain & Ollama: Enhances AI response generation and reasoning capabilities. The Github toolkit contains tools that enable an LLM agent to interact with a github repository. Jun 26, 2025 · Python code analysis with Langchain, Azure OpenAI and Azure Cognitive Search: A demo about Python notebooks analysis with Azure OpenAI and Azure Cognitive Search and its vector store Practical course about Large Language Models. It dynamically selects between a Python agent for code tasks and a CSV agent for data queries, enabling intelligent responses to diverse requests like generating QR codes or analyzing CSV files. The application reads the CSV file and processes the data. It showcases how to use and combine LangChain modules for several use cases. Natural language queries replace complex SQL/Excel. Jun 17, 2024 · How to add local Pandas datframe in Agentic workflow for Analysis? #686 Unanswered mraguth asked this question in Q&A mraguth CSV Processing: Loads and processes CSV files using LangChain CSVLoader. This project provides a comprehensive data analysis tool leveraging LangChain, OpenAI, and various Python libraries. Disclaimer: This project was made before OpenAI released Code Interpreter on ChatGPT Plus. Whether you're looking to build chatbots, Q&A systems, data analysis tools, or more, LangChain provides the tools you need Support for CSV and Excel Files: Easily upload your data from common file formats. Is that possible? sample code is below from langchain_openai import ChatOpenAI from langchain_experimental. AI-Powered CSV Analyzer automates data cleaning, EDA, forecasting, and visualization using CrewAI, LangChain, and Streamlit. Contribute to google-gemini/cookbook development by creating an account on GitHub. Chat with your CSV data using Langchain Pandas Agent for instant, interactive analysis and insights. Powerful Data Analysis: Get answers to questions about trends, statistics, distributions, and relationships within your data. llms import OpenAI from langchain. About LangChain & Prompt Engineering tutorials on Large Language Models (LLMs) such as ChatGPT with custom data. LangChain-Masterclass---Build-15-OpenAI-and-LLAMA-2-LLM-Apps-Using-Python- LangChain Masterclass - Build 15 OpenAI and LLAMA 2 LLM Apps Using Python, published by Packt This project demonstrates the integration of Google's Gemini AI model with LangChain framework, specifically focusing on CSV data analysis using agents. from langchain_experimental. - gonzajim/rag-streamlit-langchain. - Nicolepcx/AI-Data-Analysis-MultiAgent Document loaders in LangChain are tools that help you read and extract text from various file formats or sources, such as text files, CSVs, PDFs, web pages, or entire folders. Tutorial for langchain LLM library. It connects a language model to sources of context (prompt instructions, content to ground its response in, etc. A "grand" agent acts as a router, directing user queries to the appropriate agent based on the query's nature. Contribute to rrumark/langchain-csv-wikipedia-analysis development by creating an account on GitHub. Contribute to codebasics/langchain development by creating an account on GitHub. The tool enables users to load data, clean it, and perform various analysis techniques based on user input Auto-Save to CSV: Clicking the Flag button automatically saves the generated data into a CSV file for further analysis. Follow the instructions in the CSV Loader Documentation for usage details and examples. The agent processes financial data from CSV files, performs competitor analysis, and generates detailed reports with interactive feedback loops. LangChain and Pandas Integration: Leverage the CSV and DataFrame agents for seamless data handling. Powered by LangChain, Groq's LLMs, and Pandas. pull ("hwchase17/react") model = OpenAI () By integrating the strengths of Langchain and OpenAI, ChatBot-CSV employs large language models to provide users with seamless, context-aware natural language interactions for a better understanding of their CSV data. Chat with Pandas DataFrame via 🦜LangChain using multiple models and data formats. This repository contains an 'agent' which can take in a URL, and generate a Twitter & LinkedIn post based on the content of the URL. Multiple AI Model Testing: The project incorporates implementations from ChatGPT, DeepSeek, Claude, and Grok for comparative analysis. Perfect for researchers and data scientists seeking to enhance their workflow and productivity. It allows users to upload CSVs or import Google Sheets and ask natural language queries, with intelligent responses and automated data visualizations. Setup At a high-level, we will: Install the pygithub library Create a Github app Set your environmental variables Pass the tools to Univariate analysis in exploratory data analysis focuses on analyzing a single variable at a time. This repository contains a project that implements an interactive agent using Streamlit and LangChain to execute Python code and answer queries based on data from CSV files. This GitHub repository hosts a comprehensive Jupyter Notebook focused on performing advanced sentiment analysis. May 5, 2024 · LangChain and Bedrock. Contribute to bhanu-pratap-rana/Azure-OpenAI-Sentiment-Analysis-with-LangChain development by creating an account on Click on open in Google colab from the file Data analysis with Langchain and run all the steps one by one Make sure to setup the openai key in create_csv_agent function Jul 9, 2025 · Current options in LangChain, such as CSVLoader and PandasAgent, either convert CSVs to documents or require them to be preloaded into memory. Data Scientist with ML and Deep Learning experience - krishnaik06 LangChain CSV Query Engine is an AI-powered tool designed to interact with CSV files using natural language. Upload a CSV, and AI agents will clean, analyze, and generate interactive charts & PDF reports. The app uses Streamlit to create the graphical user interface (GUI) and uses Langchain to interact with the LLM. This agent uses an LLM to generate Python code snippets based on user prompts and questions which are used to analyze the data using pandas - GitHub - hblink/langchain-PandaBot: PandaBot incorporates the Langchain Pandas This tool integrates with OpenAI's Langchain platform to provide insights from CSV data. - sprider/servicenow-incident-analysis-qnabot About AI-Driven Research Assistant: An advanced multi-agent system for automating complex research processes. The idea behind this tool is to simplify the process of querying information within PDF documents. Specifically: Simple chat Returning structured output from an LLM call Answering complex, multi-step questions with agents Retrieval augmented generation (RAG) with a chain and a vector store Retrieval augmented generation (RAG) with an agent and a vector LangChain & Prompt Engineering tutorials on Large Language Models (LLMs) such as ChatGPT with custom data. Github Toolkit The Github toolkit contains tools that enable an LLM agent to interact with a github repository. The application allows users to upload their datasets and interactively explore the data using various language Sep 7, 2024 · Checked other resources I added a very descriptive title to this question. Custom Prompting: Designed prompts to enhance content retrieval accuracy. ) an Overview This Streamlit-based web application uses LangChain and OpenAI's GPT-3. May 17, 2023 · Langchain provides a standard interface for accessing LLMs, and it supports a variety of LLMs, including GPT-3, LLama, and GPT4All. df = pd. - talalmuzaffar/CSVChat About This LLM-based web application harnesses LangChain and OpenAI's GPT-3. Load CSV into Chroma vector db using OpenAIEmbeddings from LangChain Generate queries and answers from LLM using LangChain RetrieveQA and ChatOpenAI Evaluate the answers with expected answers from ChatOpenAI using LangChain's QAEvalChain Record time taken, query info, and estimated tokens (using LangChain's get_openai_callback ()) GitHub - lenaar/financial-ai-agent: This repository contains a sophisticated AI agent built with LangGraph and LangChain that automates financial analysis workflows. It leverages Langchain, a powerful language model, to extract keywords, phrases, and sentences from PDFs, making it an efficient digital assistant for tasks like research and data analysis. With similar functions. agents Data Scientist with ML and Deep Learning experience - krishnaik06 Tutorial for langchain LLM library. This project enables intuitive data analysis by translating natural language into Pandas commands, ideal for stakeholders and analysts. read_csv (data) llm = OpenAI () #create a pandas data frame agent agent = create_pandas_dataframe_agent (llm, df, verbose=True) # Run PYTHON_REPL: A python shell Apr 8, 2023 · Hi, @bleso-a I'm helping the LangChain team manage their backlog and am marking this issue as stale. py) that demonstrates how to use LangChain for processing Excel files, splitting text documents, and creating a FAISS (Facebook AI Similarity Search) vector store. It eliminates the need for manual data extraction and transforms seemingly complex PDFs into valuable 📊 GenAI Data Analysis Agent in Langchain This project is an interactive, generative AI-powered data analysis and visualization tool built with Streamlit, LangChain, and Google Gemini. Query and Response: Interacts with the LLM model to generate responses based on CSV content. Sep 12, 2024 · Hosted Application Let's explore an exciting project that leverages LangGraph Cloud's streaming API to create a data visualization agent. Built with Streamlit and powered by the advanced Google Gemini 2. It looks like the CSV agent is encountering a ValueError: Could not parse LLM output when analyzing transaction data, and users have tried different models like gpt-3. Today, we’ll zero in on pivotal use cases: Offline Document Analysis for Q&A from local Each line of the file is a data record. This LangChain app uses a routing agent to handle CSV data analysis or Python code execution based on user prompts. The create_csv_agent function is implied to be used in a SQL database approach. . Whether you're looking to build chatbots, Q&A systems, data analysis tools, or more, LangChain provides the tools you need This is a code that uses the LangChain library and OpenAI's ChatGPT API to perform data analysis on a dataset. It's powered by LangChain and OpenAI's GPT-4. AI Integration: Utilizes LangChain's integration with Google Gemini, OpenAI, and other AI models for Explore natural language querying of JIRA CSV data using LangChain and Pandas. Contribute to ncodepro/chatwithCSV development by creating an account on GitHub. Retrieval Augmented Generation Examples - Original, GPT based, Semantic Search based. Built with Streamlit: Provides a simple and interactive web interface. About CSVChat: AI-powered CSV explorer using LangChain, FAISS, and Groq LLM. LangChain is a framework for developing applications powered by language models. A Flask-based web application that allows users to perform exploratory data analysis (EDA) on uploaded datasets. agents import create_pandas_dataframe_agent import pandas as pd from langchain. Powered by OpenAI's GPT-3, RAG enables dynamic, interactive document conversations, making it ideal for efficient document retrieval and summarization. Azure OpenAI Sentiment Analysis with LangChain. This tool takes a CSV dataset as input, performs comprehensive data analysis, and generates a detailed report with insights. Built with Pandas, Matplotlib, Gradio, and LangChain (Ollama LLM). Whereas in the latter it is common to generate text that can be searched against a vector database, the approach for structured data is often for the LLM to write and execute queries in a DSL, such as SQL. With this tool, you can generate descriptive statistics for any uploaded LangChain & Prompt Engineering tutorials on Large Language Models (LLMs) such as ChatGPT with custom data. 🦜🔗 Build context-aware reasoning applications. - curiousily/Get-Things-Done-with-Prompt Dataset Upload: Users can upload CSV files for analysis. It utilizes OpenAI LLMs alongside with Langchain Agents in order to answer your questions. Source. CSV Loader Repository The CSV loader allows you to effortlessly load data from Comma-Separated Values (CSV) files into your FAISSVector database. tools. attempt to read csv with langchain. You can upload documents in txt, pdf, CSV, or docx formats and chat with your data. The application employs Streamlit to create the graphical user interface (GUI) and utilizes Langchain to interact with LangChain is a powerful framework for developing applications powered by language models. 5-turbo to analyze CSV and Excel datasets. Transforms CSVs to searchable knowledge via vector embeddings. Auto-Save to CSV: Clicking the Flag button automatically saves the generated data into a CSV file for further analysis. I searched the LangChain documentation with the integrated search. Enabling a LLM system to query structured data can be qualitatively different from unstructured text data. Features Upload Excel 📊 CSV Data Analysis Tool A user-friendly Streamlit web app for exploring and analyzing CSV files using natural language queries and interactive visualizations. The app reads the CSV file and processes the data. This project leverages the power of large language models (LLMs) to analyze CSV datasets, generate summary reports, perform data analysis, and create visualizations (bar and line charts). ipynb at main · reichenbch/RAG-examples About LangChain & Prompt Engineering tutorials on Large Language Models (LLMs) such as ChatGPT with custom data. js starter app. - codeloki15/LLM-fine-tuning-and-RAG About CSV-AI is the ultimate app powered by LangChain, OpenAI, and Streamlit that allows you to unlock hidden insights in your CSV files. 5-turbo, gpt-4, and davinci-003, but the issue persists. In this article, I will show how to use Langchain to analyze CSV files. This project is a user-friendly web application that empowers anyone to explore and analyze CSV datasets through natural language queries. The script leverages the LangChain library for embeddings and vector stores and utilizes multithreading for parallel processing. It can: Translate Natural Language: Convert plain English questions into precise SQL queries. PandaBot incorporates the Langchain Pandas DataFrame Agent to facilitate advanced analysis of user-uploaded CSV files. Contribute to loftwah/langchain-csv development by creating an account on GitHub. Contribute to peremartra/Large-Language-Model-Notebooks-Course development by creating an account on GitHub. Each loader is designed to handle a specific type of This template scaffolds a LangChain. It simplifies the process of building complex LLM workflows, enabling you to chain together different components, integrate with external data sources, and create intelligent agents. This blog is a brief dive into the agent’s workflow and key features. The implementation allows for interactive chat-based analysis of CSV data using Gemini's advanced language capabilities. Contribute to hereandnowai/langchain-tuto-2025 development by creating an account on GitHub. Sep 22, 2023 · In our previous Langchain series, we’ve delved from the fundamentals to intricate NLP and Mathematics. Leveraging Langchain agents and Google Gemini LLMs, this tool provides a natural language interface for querying spreadsheet data. You can upload an SQLite database or CSV file, ask questions about your data, and the agent will generate appropriate visualizations. . Leveraging LangChain, OpenAI GPT, and LangGraph, this tool streamlines hypothesis generation, data analysis, visualization, and report writing. It leverages language models to interpret and execute queries directly on the CSV data. 5 for seamless, interactive exploratory data analysis (EDA). Intuitive data analysis through conversation. - RAG-examples/LangChain LLamaIndex RAG. It provides intelligent data analysis and general question answering capabilities. An integrated Python Flask App for extracting ServiceNow incident data, exporting it to CSV, and utilizing Langchain with Amazon Bedrock's models for an AI-powered Q&A bot. Seamless Integration: Leverages LangChain to connect Ollama with data analysis tools like Pandas. Jupyter notebooks on loading and indexing data, creating prompt templates, CSV agents, and using retrieval QA chains to query the custom data. CSV Loader: Loads and processes CSV files for structured data analysis. Generates graphs (bar, line, scatter) based on AI responses. Users can upload CSV files and explore their datasets through natural language queries to gain insights, create visualizations, and perform statistical analysis without coding. Jan 23, 2024 · Feature request CSVAgent currently uses the same CSV file for schema to generate the query and data for executing it to generate results. Automatically detects file encoding for robust CSV parsing. Each record consists of one or more fields, separated by commas. 4 LangGraph LangGraph is a library built on top of LangChain, designed for creating stateful, multi-agent applications with LLMs (large language models). Features: HuggingFace embeddings, FAISS store, contextual QA. agents import AgentExecutor, create_react_agent from langchain. These loaders convert the content into a format (like text or structured data) that can be used for tasks like natural language processing, chatbots, or text analysis. Query CSV Data: Use the DuckDB engine to execute these SQL queries directly on a local CSV file. WebBase Loader: Scrapes and processes content from web pages. 0 model via LangChain, this tool transforms how you interact with your data. It eliminates the need for manual data extraction and transforms seemingly complex PDFs into valuable About LangChain & Prompt Engineering tutorials on Large Language Models (LLMs) such as ChatGPT with custom data. This Data Analysis and EDA Report Generator uses Generative AI to help data analysts and business professionals quickly generate insightful EDA and data analysis reports from csv files, streamlining the process of extracting valuable insights from raw data. PDF Loader: Reads and processes PDF files, either individually or from a directory. 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 Examples and guides for using the Gemini API. AI-Powered Data Insights: The application utilizes the LangChain framework with Gemini AI to answer queries and generate statistical summaries. The aim of this project is to build a RAG chatbot in Langchain powered by OpenAI, Google Generative AI and Hugging Face APIs. LangChain & Prompt Engineering tutorials on Large Language Models (LLMs) such as ChatGPT with custom data. This repository contains an application built with Streamlit that utilizes language models to perform Exploratory Data Analysis (EDA) on datasets. This repository contains a Python script (excel_data_loader. The agent generates Pandas queries to analyze the dataset. With CSV-AI, you can effortlessly interact with, summarize, and analyze your CSV files in one convenient place. Langchain leverages cutting-edge natural language processing (NLP) models to extract valuable information and generate insights from textual data. This dual approach allows for a comparison Market Intelligence LLM Application A comprehensive market intelligence application that combines Tavily AI for real-time data retrieval and OpenAI GPT-4o-mini for intelligent analysis and insight generation. 🧠 About LangChain & Prompt Engineering tutorials on Large Language Models (LLMs) such as ChatGPT with custom data. For detailed documentation of all GithubToolkit features and configurations head to the API reference. LangChain implements a CSV Loader that will load CSV files into a sequence of Document objects. ChatWithExcel is an advanced AI-powered application designed to interact seamlessly with Excel and CSV files. Mar 7, 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. It involves examining the distribution, central tendency, dispersion, and other statistical properties of a single variable without considering its relationship with other variables. This is a code that uses the LangChain library and OpenAI's ChatGPT API to perform data analysis on a dataset. xmtbih hegzbd dphqwu xmj fwti kwpzg tcogg nzig rxizjv ttxtoit