Langchain pandas example

This could mean films where Ben Affleck is the star or films that have been directed by Ben Affleck. Refresh the page, check Medium ’s site status, or find something interesting to read. This notebook shows how to get started using Hugging Face LLM's as chat models. This notebook shows how to use agents to interact with a pandas dataframe. %pip install --upgrade --quiet python-gitlab langchain-community. It will be converted to a Pandas DataFrame and then serialized to json using the Pandas split-oriented format, or a numpy array where the example will be serialized to json by converting it to a list. 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. 5 Turbo model and returns the AI response. First, load the titanic data into a dataframe, then create a constructor for our agent. Sep 14, 2023 · In this video, we will see how to chat or interact with structured data using LangChain agents - create_sql_agent & create_pandas_dataframe_agent. Add the following code to create a CSV agent and pass it the OpenAI model, and our CSV file of activities. The UnstructuredExcelLoader is used to load Microsoft Excel files. The two main ways to do this are to either: See a typical basic example of using Ollama chat model in your LangChain application. Agents select and use Tools and Toolkits for actions. At a high level, text splitters work as following: Split the text up into small, semantically meaningful chunks (often sentences). agents import create_pandas_dataframe_agent import pandas as pd # Setting up the api key import environ env = environ. You can ask questions to your data in natural language, generate graphs and charts to visualize your data, and cleanse datasets by addressing missing values. Its key features include the ability to group and aggregate data, filter data based on complex conditions, and join multiple data frames. pubmed. Example. agents import create_pandas_dataframe_agent import pandas as pd df = pd. After this configuration, you can run queries that refer to 'df', and the tool will recognize it as your dataframe. 8 and langchain==0. Let's start by asking a simple question that we can get an answer to from the Llama2 model using Ollama. May 2, 2023 · Knowledge Base: Create a knowledge base of "Stuff You Should Know" podcast episodes, to be accessed through a tool. we will work with two LLMs – OpenAI’s GPT model and Google’s Flan t5 model. LLMを使いやすくwrapしてくれるLangChainにはいくつかAgentというLLMとToolと呼ばれるものを組み合わせて実行する仕組みが用意されています。. llms import OpenAI from langchain. 5-turbo", temperature=0 Dec 1, 2023 · To use AAD in Python with LangChain, install the azure-identity package. xls files. 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. agents import AgentType from langchain_community. Args Setup. py from langchain import OpenAI from langchain. Follow the instructions here to create a Gitlab personal access token. Hello everyone, this article is a written form of a tutorial I conducted two weeks ago with Neurons Lab. LLM Agent with Tools: Extend the agent with access to multiple tools and test that it uses them to answer questions. from langchain_openai import ChatOpenAI from langchain_experimental. 306 Who can help? @agola11 @hwchase17 Information The official example notebooks/scripts My own modified scripts Related Components LLMs/Chat Models Embeddin Apr 21, 2023 · There are some FAISS specific methods. The prefix and suffix are used to construct the prompt that is sent to the language model. For example, here is a guide to RAG with local LLMs. LangChain Document Loaders also contribute to the fine-tuning process of language models. Asking the LLM to summarize the spreadsheet using these vectors Jun 1, 2023 · In short, LangChain just composes large amounts of data that can easily be referenced by a LLM with as little computation power as possible. We can also create our own reasoning agents using LangChain. Then, set OPENAI_API_TYPE to azure_ad. agent_types import AgentType Display the app title Code documentation Q&A bot example with LangChain. It works by taking a big source of data, take for example a 50-page PDF, and breaking it down into "chunks" which are then embedded into a Vector Store. 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. Ok, let’s start writing some code. Facebook AI Similarity Search (Faiss) is a library for efficient similarity search and clustering of dense vectors. langchain app new my-app. This is ideal for building tools such as code interpreters, or Advanced Data Analysis like in ChatGPT. LangChain is an open-source framework created to aid the development of applications leveraging the power of large language models (LLMs). csv") llm = ChatOpenAI(model="gpt-3. xlsx and . Use cautiously. Geopandas is an open-source project to make working with geospatial data in python easier. Apr 27, 2023 · LangChainのPandas Dataframe Agentとは. it works well dealing with doc QAs. Hugging Face. For example: df has columns department, salary, manager_name, emp_name. 2. To get started see the guide and the list of datasets. 5-turbo", temperature=0) agent_executor = create_pandas_dataframe_agent(llm, df, agent_type="tool-calling", verbose=True Dec 15, 2023 · To add a custom template to the create_pandas_dataframe_agent in LangChain, you can provide your custom template as the prefix and suffix parameters when calling the function. Nov 17, 2023 · It also allows integration with external tools e. This Q&A bot will allow you to query your own documentation easily using questions. Simple Diagram of creating a Vector Store Next, go to the and create a new index with dimension=1536 called "langchain-test-index". Env. In this example we'll use Pandas 2. We hope to continue developing different toolkits that can enable agents to do amazing feats. read_env API_KEY = env ("apikey") def create_agent (filename: str): """ Create an agent that can access and use a large language model (LLM). ) # assuming you have Ollama installed and have llama3 model pulled with `ollama pull llama3 `. split_text(some_text) Output: 1. LangChain is a framework for including AI from large language models inside data pipelines and applications. llm_chain. Jul 1, 2023 · Now you know how to query structured data using CSV Agents of LangChain and Pandas. 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. The vectors are usually compared using cosine similarity. For example, here is a prompt for RAG with LLaMA-specific tokens. 2) AIMessage: contains the extracted information from the model. In this section, we will show some of the basic functionalities of LangChain with examples so that beginners can understand it better. exceptions import OutputParserException from langchain_core. from_template("Question: {question}\n{answer}") In this video, we are going to explore the Pandas data frame agent to try to understand what the future of data analysis holds. Query Strava Data with a CSV Agent. Then add this code: from langchain. Nov 29, 2023 · LangChain Examples. chat_models import AzureChatOpenAI from langchain. You are a pandas agent. We will use the LangChain wrap input_example – one or several instances of valid model input. read_csv ( "your_data. Make sure your app has the following repository permissions: read_api. code-block:: python from langchain_openai import ChatOpenAI from langchain_experimental. # Initialize the embeddings model. Today, we're announcing agent toolkits, a new abstraction that allows developers to create agents designed for a particular use-case (for example, interacting with a relational database or interacting with an OpenAPI spec). agent_toolkits import create_pandas_dataframe_agent from langchain. You can preview the code before executing, or set yolo=True to execute the code straight from the LLM. Suppose CSV is not what Jun 16, 2024 · 1. Now I'd like to combine the two (training context loading and conversation memory) into one - so I can load previously trained data and also have conversation history in my chat bot. agents Mar 13, 2024 · Setup: LangSmith. We'll use the off-the-shelf pandas dataframe agent from LangChain for this tutorial. We need to install huggingface-hub python package. In [40]: !pip LangChain cookbook. agents import create_pandas_dataframe_agent from langchain. Use poetry to add 3rd party packages (e. You may even notice that the prompt templates of both agents are identical when you check them. In particular, we will: Utilize the HuggingFaceEndpoint integrations to instantiate an LLM. Apr 19, 2024 · I have a Datarame and want to query it using langchain create_pandas_dataframe_agent. Warning: YOLOPandas will execute arbitrary Python code on the machine it Geopandas is an open-source project to make working with geospatial data in python easier. Feb 29, 2024 · @dosu-bot, the approach to remove/filter out the code before it is displayed is a smart approach. If you prefer a narrative walkthrough, you can find the YouTube video here: Let’s begin the…. docs_and_scores = db. 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. It contains algorithms that search in sets of vectors of any size, up to ones that possibly do not fit in RAM. prompt. TEI enables high-performance extraction for the most popular models, including FlagEmbedding, Ember, GTE and E5. This tutorial provides an overview of what you can do with LangChain, including the problems that LangChain solves and examples of data use cases. With below prefix and same invoke query, i got the output as expected. This characteristic is what provides LangChain with its Aug 6, 2023 · In this example, 'df' is the pandas DataFrame that you want the tool to recognize. configurable_alternatives (ConfigurableField (id = "llm"), default_key = "anthropic", openai = ChatOpenAI ()) # uses the default model Pandas DataFrame. Let’s see what output we get for each case: 1. Go to server. May 18, 2023 · LangChain has a specific library for Pandas called the pandas_dataframe_agent. agents import create_pandas_dataframe_agent import Pandas. Once you reach that size, make that chunk its Introduction to LangChain for Data Engineering & Data Applications. Apr 27, 2024 · 1. import streamlit as st import pandas as pd from langchain. invoke("Tell me a joke") API Reference: Ollama. Aug 25, 2023 · I currently have a dataset in csv file, and I converted it into the pandas dataframe. agents import Tool from langchain_experimental. LLMs are great for building question-answering systems over various types of data sources. For example the query “Ben Affleck films” could be problematic. Define the runnable in add_routes. id, ) 2. Use FAISS to create and populate a vector database with embeddings of your documents: Python. chat_models import ChatOpenAI from langchain. Create a Gitlab personal access token. output_parsers. Return type. 5 Turbo model. Faiss documentation. Scripts -. The first step is the setting up of LangSmith, an in-built tool within LangChain that guarantees observability and debuggability of the agents that you build. embeddings = OpenAIEmbeddings() # Create a FAISS vector store and add documents. Automatic Embeddings with TEI through Inference Endpoints Migrating from OpenAI to Open LLMs Using TGI's Messages API Advanced RAG on HuggingFace documentation using LangChain Suggestions for Data Annotation with SetFit in Zero-shot Text Classification Fine-tuning a Code LLM on Custom Code on a single GPU Prompt tuning with PEFT RAG Evaluation Using LLM-as-a-judge for an automated and Tool calling . Initialize LLM Jul 21, 2023 · LangChain. tools. 2. May 17, 2023 · # agent. This walkthrough uses the FAISS vector database, which makes use of the Facebook AI Similarity Search (FAISS) library. What is Gradio ? Gradio is an open-source Python library that allows developers and researchers to quickly create customizable UIs for their machine-learning models, without requiring any web development experience. agents Jun 20, 2023 · I'm using the create_pandas_dataframe_agent to create an agent that does the analysis with OpenAI's GPT-3. Hugging Face Text Embeddings Inference (TEI) is a toolkit for deploying and serving open-source text embeddings and sequence classification models. 5 (LLaMa2 based) to create a local Question&Answer system. Class hierarchy: Mar 1, 2023 · Agent Toolkits. agents import create_csv_agent llm = ChatOpenAI(model="gpt-3. This formatter should be a PromptTemplate object. By setting specific environment variables, developers will be able to trace all the steps in LangSmith automatically, making the debugging process a lesser burden. Pandas: The well-known library for working with tabular data. Apr 21, 2023 · Pandas Dataframe Agent. temperature (float): The temperature parameter controls Langchain pandas agents (create_pandas_dataframe_agent ) is hard to work with llama models. After that, I have created the agent as shown below. Geopandas further depends on fiona for file access and matplotlib for plotting. Configure a formatter that will format the few-shot examples into a string. An LLM framework that coordinates the use of an LLM model to generate a response based on the user-provided prompt. This notebooks shows how you can load issues and pull requests (PRs) for a given repository on GitHub. In this section we'll go over how to build Q&A systems over data stored in a CSV file(s). Nov 8, 2023 · The create_pandas_dataframe_agent function in Langchain is designed to enable interaction with a Pandas DataFrame for question-answering tasks. 5. py and edit. 240. Hope you're ready for another round of fun with language models! 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. getenv("OPENAI_API_KEY") from langchain_openai import ChatOpenAI. LangChain includes integration with a variety of vector databases. We also un Jul 5, 2023 · You signed in with another tab or window. In Chains, a sequence of actions is hardcoded. TensorFlow Datasets is a collection of datasets ready to use, with TensorFlow or other Python ML frameworks, such as Jax. Datasets, enabling easy-to-use and high-performance input pipelines. It provides a unified interface to create agents based on different language models such as OpenAI. ) I am trying to use local model Vicuna 13b v1. First, we'll need to install the main langchain package for the entrypoint to import the method: %pip install langchain. Also shows how you can load github files for a given repository on GitHub. OpenAI has a tool calling (we use "tool calling" and "function calling" interchangeably here) API that lets you describe tools and their arguments, and have the model return a JSON object with a tool to invoke and the inputs to that tool. agents. Jul 24, 2023 · LangChain is a robust library designed to streamline interaction with several large language models (LLMs) providers like OpenAI, Cohere, Bloom, Huggingface, and more. You switched accounts on another tab or window. 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. NotImplemented) 3. The list of messages per example corresponds to: 1) HumanMessage: contains the content from which content should be extracted. run(user_message) . g. Mar 6, 2024 · Here's an example of how you can do this: from langchain_openai import ChatOpenAI from langchain_experimental. format_instructions Feb 13, 2024 · When splitting text, it follows this sequence: first attempting to split by double newlines, then by single newlines if necessary, followed by space, and finally, if needed, it splits character by character. runnables. It's easy to get the agent going, I followed the examples in the Langchain Docs. . Example of how to use LangChain and Vertex AI Generative AI to ask plain English questions about Pandas dataframes. You must work with the DataFrame df containing information about the company's employees. This notebook shows how to use agents to interact with data in CSV format. Aug 7, 2023 · create_pandas_dataframe_agent: As the name suggests, this library is used to create our specialized agent, capable of handling data stored in a Pandas DataFrame. agents import create_pandas_dataframe_agent, create_csv_agent. However I want to pass one dynamic variable with the prompt. It uses FastAPI as the backend and NextJS as the frontend. So far I'm able to integrate Mistral 7B Instruct model with langchain , but I 'm not able to get final answer. It also contains supporting code for evaluation and parameter tuning. Apr 2023 · 11 min read. 6¶ langchain. E2B's cloud environments are great runtime sandboxes for LLMs. Pandas examples dataset_id=dataset. GeoPandas extends the datatypes used by pandas to allow spatial operations on geometric types. May 5, 2023 · YOLOPandas. Reload to refresh your session. The page content will be the raw text of the Excel file. This is a powerful tool to handle large datasets efficiently and allows for advanced queries and transformations. data. However, I haven't found a way to actually filter a dataframe and save (or access) the result. OPENAI_API_KEY = os. add_routes(app. #. Aug 23, 2023 · import openai import pandas as pd from dotenv import load_dotenv from langchain. Parameters: prompt (str): The input prompt to send to the GPT-3. If you use the loader in "elements" mode, an HTML representation of the Excel file will be available in the document metadata under the textashtml key. com May 12, 2023 · LangChain's Pandas Agent is a tool used to process large datasets by loading data from Pandas data frames and performing advanced querying operations. We want to use OpenAIEmbeddings so we have to get the OpenAI API Key. 3) ToolMessage: contains confirmation to the model that the model requested a tool correctly. The whole idea behind vector databases is the ability to store vectors and provide fast similarity searches. Env environ. We'll also demonstrate the use of LangChain and LanceDB using the OpenAI API. model="llama3". It can be used for chatbots, text summarisation, data generation, code understanding, question answering, evaluation Jun 28, 2024 · Source code for langchain. %load_ext autoreload %autoreload 2. This repository contains a collection of apps powered by LangChain. You can use the PandasDataFrameLoader to load the data into LangChain: Aug 24, 2023 · Instead of passing entire sheets to LangChain, eparse will find and pass sub-tables, which appears to produce better segmentation in LangChain. prompts import PromptTemplate. Oct 12, 2023 · System Info Platform: Windows Server 2022 Python: 3. from langchain_community. Pandas Dataframe Agent. We will use the LangChain Python repository as an example. See full list on analyzingalpha. Create new app using langchain cli command. It effectively creates an agent that uses OpenAI's Jun 29, 2023 · Example 4: Fine-tuning with LangChain Document Loaders. Apr 3, 2023 · Let’s install the latest versions of openai and langchain via pip: pip install openai --upgrade pip install langchain --upgrade In this post, we’re using openai==0. Any help or support would be appreciated! Jun 28, 2024 · Example:. Here is an example of how you can do this: The PandasAI platform provides a web-based interface for interacting with your data in a more visual way. tool-calling is extremely useful for building tool-using chains and agents, and for getting structured outputs from models more generally. agents ¶ Agent is a class that uses an LLM to choose a sequence of actions to take. This notebook showcases several ways to do that. This notebook goes over how to load data from a pandas DataFrame. First, we need to install the LangChain package: pip install langchain_community This notebook shows how to use agents to interact with Xorbits Pandas dataframe and Xorbits Numpy ndarray. chat_models import ChatOpenAI from langchain. Datasets are mainly used to save results of Apify Actors—serverless cloud programs for various web scraping, crawling, and data extraction use cases. Apr 11, 2024 · LangChain has a set_debug() method that will return more granular logs of the chain internals: Let’s see it with the above example. import re from typing import Any, Dict, List, Tuple, Union from langchain_core. You can use the PandasDataFrameLoader to load the data into LangChain: May 1, 2023 · I'm attempting to modify an existing Colab example to combine langchain memory and also context document loading. All datasets are exposed as tf. 6 Langchain version: 0. E2B Data Analysis sandbox allows you to: We'll create a simple OpenAI agent that will use E2B 1. LangChain's unique proposition is its ability to create Chains, which are logical links between one or more LLMs. Apr 19, 2023 · In this example, we will use the ada-002 model provided by OpenAI to embed documents. def ask_gpt(prompt, temperature, max_tokens): """. For example, suppose you have a Pandas DataFrame named dataframe containing structured data. agents Jun 28, 2024 · from langchain_anthropic import ChatAnthropic from langchain_core. from langchain. Defaults to “pandas”. Then, copy the API key and index name. template” to check it out. agent = create_pandas_dataframe_agent(OpenAI(temperature=1), df, verbose=True) I am a beginner who just tried to use LLM model. Next, use the DefaultAzureCredential class to get a token from AAD by calling get_token as shown below. , langchain-openai, langchain-anthropic, langchain-mistral etc). The input example is used as a hint of what data to feed the model. So I need to pass the department name as variable in the prompt langchain-pandas-agent-example \n LangChain is a library that utilizes natural language processing and machine learning algorithms to create agents to answer questions from CSV data. YOLOPandas lets you specify commands with natural language and execute them directly on Pandas objects. import pandas as pd. import os. You can see another example here. These are mainly transformation chains that preprocess the prompt, such as removing extra spaces, before inputting it into the LLM. May 7, 2023 · Applications of LangChain include documentation, creating agents, and Chatbots. 11. globals import set_debug. CSV. Faiss. %pip install --upgrade --quiet pandas. Mar 15, 2024 · Apologies, but something went wrong on our end. It is mostly optimized for question answering. In general, use cases for local LLMs can be driven by at least two factors: TensorFlow Datasets. In two separate tests, each instance works perfectly. This can be dangerous and requires a specially sandboxed environment to be safely used. I want to find top 3 manager names for the department "CSE". Interact with Pandas objects via LLMs and LangChain. agents import create_pandas_dataframe_agent import pandas as pd # Load your DataFrame df = pd. 1. An agent can carry out limited tasks using tools at its disposal. AgentExecutor. similarity_search_with_score(query) docs_and_scores[0] (Document(page_content='In state after state, new laws have been passed, not only to . Here's an example: Create a formatter for the few-shot examples. Define Q&A system. However, if you want to create an agent that can interact with a pandas dataframe, you can use the create_pandas_dataframe_agent function from the Sep 26, 2023 · from langchain. Finally, set the OPENAI_API_KEY environment variable to the token value. Start combining these small chunks into a larger chunk until you reach a certain size (as measured by some function). Example code for building applications with LangChain, with an emphasis on more applied and end-to-end examples than contained in the main documentation. It excels in tasks such as grouping and aggregating data as well as statistical analysis. pandas_dataframe. First, let’s initialize our Azure OpenAI Service connection and create the LangChain objects: Python Streamlit web app allowing users to interact with their data from a CSV or XLSX file, utilizing OpenAI API and LangChain. agents import AgentType, initialize_agent from langchain. read_csv("titanic. 0. E2B's Data Analysis sandbox allows for safe code execution in a sandboxed environment. tool import PubmedQueryRun from 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. (the same scripts work well with gpt3. Utilize the ChatHuggingFace class to enable any of these LLMs to interface with LangChain's Chat Messages abstraction. To load all rows from your dataframe, you need to set number_of_head_rows to a value that equals or exceeds the total langchain-examples. pydantic_v1 import validator from langchain. Build a chat application that interacts with a SQL database using an open source llm (llama2), specifically demonstrated on an SQLite database containing rosters. この中でもPandas Dataframe Agentは名前の通りpandasのDataframeに対する操作をLLMにやらせるため Jul 11, 2023 · 2. Mar 6, 2024 · This behavior is due to the number_of_head_rows parameter in the create_pandas_dataframe_agent function. Sometimes, when the agent responds with the code, it mentions how the code needs to be run in an interactive environment or in a notebook, for example. llms import Ollama. c_splitter. You signed out in another tab or window. One of them is similarity_search_with_score, which allows you to return not only the documents but also the similarity score of the query to them. agent. Then run it and ask it questions about the data contained in the CSV file: Python. In Agents, a language model is used as a reasoning engine to determine which actions to take and in which order. base import BaseOutputParser from langchain_core. This is an example where clarification of the query would be helpful. from langchain_core. llm = Ollama(. Apify Dataset is a scalable append-only storage with sequential access built for storing structured web scraping results, such as a list of products or Google SERPs, and then export them to various formats like JSON, CSV, or Excel. allow_dangerous_code (bool) – bool, default False This agent relies on access to a python repl tool which can execute arbitrary code. With the dataset created, it's time to define our question answering system. Apr 25, 2024 · Bad metadata filtering by the self-querying retrieval. Apr 21, 2023 · Even though PalChain requires an LLM (and a corresponding prompt) to parse the user’s question written in natural language, there are some chains in LangChain that don’t need one. Sends a prompt to the GPT-3. Geometric operations are performed by shapely. The loader works with both . 0 documentation, but, this could be replaced for your own docs as well. The autoreload extension is already loaded. csv" ) # Initialize the ChatOpenAI model llm = ChatOpenAI ( model="gpt-3. !pip install langchain-community. 27. Actually, to get best result you need to give proper prefix, suffix, invoke query and at last a best llm model. By default, this parameter is set to 5, which means only the first 5 rows of the dataframe are included in the prompt. llm. Throughout the examples. 5-turbo", temperature=0 ) # Create the pandas Jun 28, 2024 · engine (Literal['pandas', 'modin']) – One of “modin” or “pandas”. example_prompt = PromptTemplate. Like working with SQL databases, the key to working with CSV files is to give an LLM access to tools for querying and interacting with the data. 5-turbo-0613 model. I do have a follow up question. Using eparse, LangChain returns 9 document chunks, with the 2nd piece (“2 – Document”) containing the entire first sub-table. Run “pd_agent. Jun 30, 2023 · Example 4: Fine-tuning with LangChain Document Loaders. Jun 23, 2024 · Step 4: Create and Populate the Vector Database. Use cases Given an llm created from one of the models above, you can use it for many use cases. So let's figure out how we can use LangChain with Ollama to ask our question to the actual document, the Odyssey by Homer, using Python. Jun 28, 2024 · langchain 0. tools import Tool from pydantic import BaseModel, Field # Define your custom tool function def custom_tool_func (query: str) -> str: # Your custom logic here return "custom tool result" # Define the input schema for your Mar 8, 2024 · Hey @Raghulkannan14!Great to see you back diving into more adventures with LangChain. , Pandas and python_repl_ast as we saw in the example above. utils import ConfigurableField from langchain_openai import ChatOpenAI model = ChatAnthropic (model_name = "claude-3-sonnet-20240229"). Install the python-gitlab library. 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. that can be fed into a chat model. qa ih vc nd td rm nm ur do vw