Langchain interact with api python github API designed to interact with models like GPT-4o, Claude 3 LLM and Langchain powered chatbot to handle Google Calendar tasks - jgordley/GoogleCalendarAssistant This project introduces tools to easily integrate Anthropic Model Context Protocol(MCP) with langchain. The agent is created using a CSV agent and an OpenAI language model, which allows the user to interact with the data using natural language queries. Interact with LLM. The project includes three main functionalities - Dec 2, 2023 · This is a very basic example and the actual implementation would depend on the specifics of the Cloudflare Vectorize API. In the future when the TS package is on par with the Python package we will migrate to only using Javascript. datasets: Provides a vast array of datasets for machine learning. This notebooks shows how you can load issues and pull requests (PRs) for a given repository on GitHub. The chatbot utilizes the LangChain library and the Groq API for language model processing and retrieval - aadhil96/Chat-with-Doc-LangChain-LLM This Streamlit application allows users to interact with a chatbot that can answer questions based on the content of a PDF document. Deprecated since version 0. It showcases the development of AI agents that can interact with various tools, perform web searches, fetch real-time information, and take notes autonomously based on voice commands or text queries. Installation % pip install --upgrade langchain-xai Apr 20, 2023 · I'm trying to use the LLM and planner modules to interact with the Google Calendar API, but I'm facing issues in creating a compatible requests wrapper. It is mostly optimized for question answering. We'll use it to chain together different language models and components for our chatbot. It uses the 'Agents' feature in LangChain to create flexible conversation chains based on user input. Sep 9, 2023 · Feature request Currently llama-cpp-python provides server package which acts like a drop-in replacement for the OpenAI API. With LangChain at its core, the This repository demonstrates how to integrate the open-source OLLAMA Large Language Model (LLM) with Python and LangChain. Playwright is an open-source automation tool developed by Microsoft that allows you to programmatically control and automate web browsers. By leveraging the power of LangChain, SQL Agents, and OpenAI’s Large Language Models (LLMs) like Chat with PDF locally: An advanced chatbot using Ollama/Openrouter LLMs to interactively extract information from PDFs, Using Streamlit & Ollama/Openrouter API and langchain chatbot rag streamlit streamlit-application llm langchain chromadb retrieval-augmented-generation chat-with-pdf openrouter ollama chat-with-your-data openrouter-api deepseek-r1 Create a Python AI chatbot using the Llama 3 model, running entirely on your local machine for privacy and control. langchain==0. Gemini API Integration: Run python gemini. Oct 1, 2023 · Use the OpenAI API key for responses. - Sweee2012/SIMPLE-CHATBOT-USING-LANGCHAIN-AND-GEMINI-API The language model-driven project utilizes the LangChain framework, an in-memory database, and Streamlit for serving the app. The chatbot leverages these technologies to provide intelligent responses to user queries. It is designed to provide a seamless chat interface for querying information from multiple PDF documents. client. - GitHub - ausboss/DiscordLangAgent: DiscordLangAgent: This is a Discord chatbot built with LangChain. Unfortunately, I'm unable to provide a more detailed answer or a specific plan for implementing this feature, as I don't have enough information about how the LangChain Python framework interacts with vector stores or how the Cloudflare Vectorize API works. This project is a Streamlit-based web application that allows users to interact with SQL databases (SQLite or MySQL) using the LangChain framework and Groq's LLM. LangChain is a comprehensive framework designed for developing applications powered by language models. We will use the LangChain Python repository as an example. It leverages the LangChain library and OpenAI's language model to convert plain English questions into SQL queries and execute them on the provided database. env with your valid OpenAI API key in your local env following the example . toolkit import ExtendLangChainToolkit from extend_ai_toolkit. Feel free to explore this project and enhance it further to suit your needs. It provides a standard interface for working with various LLMs while offering additional tools for building complex applications. With this chat interface, you can easily send and receive messages in real-time. Python Streamlit web app with an SQLite user login/authentication system. This would involve making HTTP requests to your Django endpoints within the methods of your LangChain agent. Powered by Langchain, Chainlit, Chroma, and OpenAI, our application offers advanced natural language processing and retrieval augmented generation (RAG) capabilities. xAI offers an API to interact with Grok models. Prerequisites This example defaults to using Pinecone for its memory database, and nomic-ai/nomic-embed-text-v1. Jan 19, 2025 · LangChain is a framework that enables developers to create applications by chaining together different components, primarily focusing on applications that interact with language models. It provides a simple way to connect to MCP servers and access tools that can be made available to LangChain. First, let's initialize Tavily and an OpenAI chat model capable of tool calling: LangchainGo is the Go Programming Language port/fork of LangChain. SQLite3: For local database operations. This project allows you to interact with a locally downloaded Large Language Model (LLM) using the Ollama platform and LangChain Python library. g. pem file, or the full text of that file as a string. Initialize the tool. Environment setup steps. Feb 18, 2024 · In this tutorial, we will see how we can integrate an external API with a custom chatbot application. - shiv-rna/Webchat-RAG-Langchain Contribute to ollama/ollama-python development by creating an account on GitHub. It showcases how to combine a React-style agent with a modern web UI, all hosted within a single LangGraph deployment. Oct 1, 2023 · How to build a LangChain agents that can interact with data from a postgresql database of an HR systems. Jul 3, 2023 · embeddings = OpenAIEmbeddings(openai_api_key=API_KEY) """## Loading Vectors into VectorDB (FAISS) As created by OpenAIEmbeddings vectors can now be stored in the database. py; API keys are maintained over databutton secret management; Indexed are stored over session state Apr 4, 2023 · More than 150 million people use GitHub to discover, fork, and contribute to over 420 million projects. Basic Python knowledge: Familiarity with Python’s syntax and concepts will be beneficial. Spark Dataframe. py: This has all the langchain code; requirements. config) and branch I have two swagger api docs and I am looking for LangChain to interact with API's. It utilizes the Streamlit framework to create an interactive user interface and implements conversation buffer memories to store chat histories. It uses prompt chaining to interact with the Gemini LLM and demonstrates basic conversational AI setup in Python. The agents leverage a language model to interpret user queries, translate them into SQL statements, execute these statements against a database, and present the results. Oct 1, 2023 · Integrate the Django REST Framework with your LangChain Agent: You would need to write the logic for your agent to interact with your Django REST Framework. Lambda Service: An API Gateway + Lambda based REST More than 150 million people use GitHub to discover, fork, and contribute to over 420 million projects. 5 model for generating conversational responses. This would involve creating a new tool that uses the OpenAI API to generate responses. Is it possible to use Agent / tools to identify the right swagger docs and invoke API chain? System Info. This will launch the chat UI, allowing you to interact with the Falcon LLM model using LangChain. prebuilt import create_react_agent from langchain_core. agents. ai retriever export KAY_API_KEY= # for tracing export LANGCHAIN_TRACING_V2=true export Full LangChain Course for Python. Agentic: allow a language model to interact with its environment; The main value props of LangChain are: Components: abstractions for working with language models, along with a collection of implementations for each abstraction. com retriever export YDC_API_KEY= # if you'd like to use the Google retriever export GOOGLE_CSE_ID= export GOOGLE_API_KEY= # if you'd like to use the Kay. single-long Aug 3, 2024 · Handling KeyError: 400 in reduce_openapi_spec. The CSV agent then uses tools to find solutions to your questions and generates an appropriate response with the help of a LLM. This project demonstrates the power of AI-driven agents using the LangChain framework. The application employs Streamlit to create the graphical user interface (GUI) and utilizes Langchain to interact with the LLM. Follow step-by-step instructions to set up, customize, and interact with your AI. 11 or newer. py: Python script implementing a LangChain server using FastAPI. The reduce_openapi_spec function simplifies an OpenAPI specification by focusing on specific HTTP methods (GET, POST) and reducing the documentation to essential elements. The Langtrain library forms the This project demonstrates how to integrate LangChain with Google Generative AI (Gemini) to build applications that process text, images, and PDFs. The Github toolkit contains tools that enable an LLM agent to interact with a github repository. ai-agents huggingface openai-api langchain langchain Cheat Sheet:. - M-A-S1/Local-LLM-Chatbot-using-Ollama-and-LangChain You may either enter your own sample FHIR server (unauthenticated access needed) You may create a temporary sample server in Intersystems IRIS FHIR platform Due to the limitations imposed by OpenAI's token usage, if the reference data + prompt being sent to the OpenAI API exceeds the specified limit Python 3. Most importantly, langchain-mcp-connect allows developers to easily integrate their LLMs with a rich ecosystem of pre-built MCP servers. A Langchain pandas agent utilizing GPT-4 and customized stock-market/financial prompts is then initiated allowing the user to intelligently interact with their specified data. py. This README will guide you through the process of setting up the project on your local machine. It uses Git software, providing the distributed version control of Git plus access control, bug tracking, software feature requests, task management, continuous integration, and wikis for every project. This project covers: Implementing a RAG system using LangChain to combine document retrieval and response generation. 271 langchain-core==0. The app uses Streamlit to create the graphical user interface (GUI) and uses Langchain to interact with the LLM. You will also need your OpenAI key set as OPENAI_API_KEY and your Tavily API key set as TAVILY_API_KEY. With LangChain at its core, the This repository provides a set of tools and scripts designed to interact with Microsoft SharePoint to manage and process documents. Chat with PDF locally: An advanced chatbot using Ollama/Openrouter LLMs to interactively extract information from PDFs, Using Streamlit & Ollama/Openrouter API and langchain chatbot rag streamlit streamlit-application llm langchain chromadb retrieval-augmented-generation chat-with-pdf openrouter ollama chat-with-your-data openrouter-api deepseek-r1 Create a Python AI chatbot using the Llama 3 model, running entirely on your local machine for privacy and control. ) xAI. Groq Language Model: For language understanding and response generation. LangChain: 🔗GitHub, 📚Documentation This repository contains a Streamlit application that allows users to interact with a conversational chatbot powered by the LangChain API. py to use the extended functionality. Contribute to Ashwand5/Langchain development by creating an account on GitHub. Without a valid token, the chat UI will not function properly. At present, the following templates are included. With Ollama for managing the model locally and LangChain for prompt templates, this chatbot engages in contextual, memory-based conversations. You can seamlessly integrate this backend into your existing streamlit streamlit-webapp streamlit-cloud langchain pdf-chat-bot langchain-chains faiss-vector-database groq-api llama3 huggingface-embeddings langchain-community Updated Feb 2, 2025 Python It utilizes OpenAI LLMs alongside with Langchain Agents in order to answer your questions. Streamlit Application: Launch the Streamlit app with streamlit run sql_app. Install Docker Desktop: Windows: Double-click the downloaded installer and follow the on-screen instructions. 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. May 7, 2025 · Python 3. It simplifies querying databases by leveraging the power of large language models and makes database management more accessible to non-technical users. It is designed for end-to-end testing, scraping, and automating tasks across various web browsers such as Chromium, Firefox, and WebKit. In my previous articles on building a custom chatbot application, we’ve covered the basics of creating a chatbot with specific functionalities using LangChain and OpenAI, and how to build the web application for our chatbot using Chainlit. Python web app built on Streamlit, utilizing LangChain and the OpenAI API to automate YouTube title and script generation. Application allows users to select multiple stocks, metrics, and visualizations. 23 It utilizes OpenAI LLMs alongside with Langchain Agents in order to answer your questions. The idea is simple: to get coherent agent behavior over long sequences behavior & to save on tokens, we'll separate concerns: a "planner" will be responsible for what endpoints to call and a Custom Python Script: Execute python custom_tool. This innovative project harnesses the power of LangChain, a transformative framework for developing applications powered by language models. This example goes over how to use LangChain to interact with xAI models. MySQL Connector/Python: For connecting to MySQL databases. txt: A list of required Python packages for the project. This project is a simple chat interface built using Python, the NiceGUI package, and the LangChain API. This Python project, developed for language understanding and question-answering tasks, combines the power of the Langtrain library, OpenAI GPT, and PDF search capabilities. The Ollama Python library's API is designed around the Ollama REST API. BaseModel. May 5, 2025 · A simple chatbot built using LangChain and Google Gemini API, implemented in Google Colab. 0. Processing and storing documents for efficient retrieval in the RAG system. API key for an LLM provider: For instance, an API key from OpenAI. - GitHub - easonlai/azure_o We have migrated all agent functionality from LangChain Typescript to LangChain Python. This repository contains two Python scripts, app. The project features a Gradio chat interface, providing a seamless user experience for querying and receiving information in natural language. It goes beyond merely calling an LLM via an API, as the most advanced and differentiated applications are also data-aware and agentic, enabling language models to connect with other data sources and interact with their environment. In this example, there is an API in Python, that accepts POST query with text, connects to Big Query and returns the result, processed by GhatGPT model you have specified. You can leave the defaults for the config file (langgraph. - ruslanmv/Medical-Chatbot-with-Langchain-with-a-Custom-LLM This Streamlit app, "LangChain ChatBot," invites users to input queries, utilizing the LangChain library and OpenAI's text-davinci-003 model to generate responses with controlled randomness. This tool should also inherit from the BaseTool class and use the OpenAI Python library to interact with the OpenAI API. shared import Configuration, Scope, Product, Actions‍ # Load environment An LLM GUI application; enables you to interact with your files, offering dynamic parameters that can modify response behavior during runtime. You can read the full article This project allows you to plug in a GitHub repository URL, generate vectors for a LLM and use ChatGPT models to interact. Fill out the required information, including: Your GitHub username (or organization) and the name of the repo you just forked. 7: Use callbacks instead. 5-Turbo and GPT-4) to interact with users via Telegram, WhatsApp and Facebook Messenger. LangSmith: A developer platform that lets you debug, test, evaluate, and monitor chains built on any LLM framework and seamlessly integrates with LangChain. Dec 9, 2024 · Tool for interacting with the GitHub API. - ravirch/Query-Databases-with-AI Multi-Agent Chatbot is a sophisticated chatbot application that leverages multiple agents to handle different types of queries. Create a virtual environment. In order to construct such a chain, we will pass in: operation, llm, requests=Requests(), verbose=True, return_intermediate_steps=True, # Return request and response text. py; PDF parsing and indexing : brain. ipynb with Jupyter Notebook to follow the step-by-step guide. 7+ Streamlit: For building the web application interface. API chains. This package contains code templates to deploy LLM applications built with LangChain to AWS. LangChain: To create agents that interpret and execute natural language queries. The templates contain both the infrastructure (CDK code) and the application code to run these services. Set up a new virtual environment (optional) An API key (e. A Streamlit app that allows users to query SQLite or MySQL databases using LangChain agents powered by Groq's LLM for natural language processing. This notebook shows how to use agents to interact with a Spark DataFrame and Spark Connect. The main framework used is Langchain. The application uses the Groq API to generate responses and maintains a history of the conversation to provide context for the chatbot's responses. The chatbot utilizes the capabilities of language models and embeddings to perform conversational This repository contains a Streamlit application that allows users to interact with a conversational chatbot powered by the LangChain API. Set up environment variables: Create a . Creating custom tools with the tool decorator:. The chatbot leverages both OpenAI's GPT-3. It integrates with LangChain, OpenAI, and various tools to deliver accurate and helpful responses. In just a click, users can explore the intriguing world of conversation through this compact and user-friendly interface. Mar 6, 2023 · Kuberentes LangChain Agent - Interact with Kubernetes Clusters using LLMs - jjoneson/k8s-langchain apps, batch, networking, and rbac API groups Specifically Interactive chatbot: to talk with a webpage using the power of OpenAI's API, Langchain for language processing, and RAG (Retrieval-Augmented Generation) for enhanced responses. In this project, we used Langchain to create a ChatGPT for your PDF using Streamlit. Provided here are a few python scripts to help get started with building your own multi document reader and chatbot. api_request_chain: Generate an API URL based on the input question and the api_docs; api_answer_chain: generate a final answer based on the API response; We can look at the LangSmith trace to inspect this: The api_request_chain produces the API url from our question and the API documentation: Here we make the API request with the API url. LangChain SQL Chatbot enables users to interact with SQLite, PostgreSQL, and MySQL databases using natural language. Wikipedia API: For retrieving information from Wikipedia as part of the agent's toolset. I used the GitHub search to find a similar question and didn't find it. The LangChain agents will interact with data from the database when queried. May 1, 2025 · import os import asyncio from dotenv import load_dotenv‍ from langchain_openai import ChatOpenAI from langgraph. The app offers a prompt-based interaction system, leveraging conversational memory and Wikipedia research. This open-source project leverages cutting-edge tools and methods to enable seamless interaction with PDF documents. v1. Thus you will need to run the Langchain UI API in order to interact with the chatbot. Sends the entire document content to the LLM prompt. LangServe: A library for deploying LangChain chains as a REST API. Support for PDF, DOCX, and plain text export OPENAI_API_KEY= export TAVILY_API_KEY= # for Anthropic # remove models from code if unused ANTHROPIC_API_KEY= # if you'd like to use the You. Full-Stack Python Chatbot with LangGraph This template demonstrates how to build a full-stack chatbot application using LangGraph's HTTP configuration capabilities. Jupyter Notebook Guide: Open mysql. In the APIChain class, there are two instances of LLMChain: api_request_chain and api_answer_chain Jun 10, 2024 · ChatOpenAI is a class from the langchain_openai module used to interact with OpenAI's language models. ; Use the @tool decorator before defining your custom function. A simple chatbot that can interact with just one document and finish up with a more advanced chatbot that can interact with multiple different documents and document types, as well as maintain a record of the chat history, so you can ask it things in the context of recent conversations. In this code I am using GPT-4, but you can change it to any other model. - safakan/TalkWithYourFiles GitHub. Feature Description; 🔄 Ease of use: Create your first MCP capable agent you need only 6 lines of code: 🤖 LLM Flexibility: Works with any langchain supported LLM that supports tool calling (OpenAI, Anthropic, Groq, LLama etc. 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. This application is built using Streamlit and is deployed on Google LangChain: LangChain is the library used for communication and interaction with OpenAI's API. BaseModel if accessing v1 namespace in pydantic 2. env file, as mentioned in step 3. This repository contains three Python scripts that demonstrate how to interact with various AI models using the LangChain library. 5-turbo model. 5 as the text encoder (hosted on Fireworks). We built an application that allows you to ask questions about a PDF document and get answers directly from an LLM (Large Language Model), like OpenAI's ChatGPT. This template provides a one-click dev environment for building "LLM apps" with LangChain, Codespaces, and GPT-3. The scripts increase in complexity and features, as follows: single-doc. OpenAI API: To leverage the ChatOpenAI model for natural language understanding and generation. In this Python notebook, I will show you how to use SQLDatabaseChain to interact with a MySQL database in natural language. I will be using django rest framework for Post and get requests when a user query a search and the LangChain agents will retrieve knowledge from the database. We believe that the most powerful and differentiated applications will not only call out to a language model via an API, but will also: Be data-aware: connect a language model to other sources of data A simple python library to interact with Microsoft Graph and Office 365 API Topics microsoft python oauth planner graph calendar email excel onedrive mailbox outlook sharepoint calendars oauth-authentication microsoft-api microsoft-teams microsoft-graph-api addressbook office-365-rest-api Building a Medical Chatbot with Langchain and custom LLM via API. The project is mainly built on top of two Python libraries: langchain, which provides a convenient and flexible interface for working with LLMs, and rich which provides a user-friendly interface for the REPL. The script uses OpenAI's GPT-3. There is also a script for interacting with your cloud hosted LLM's using Cerebrium and Langchain The scripts increase in complexity and features, as follows: local-llm. This chatbot retrieve relevant information from a medical conversation dataset and leverage a large language model (LLM) service to generate informative responses to user queries. py: Python script demonstrating how to interact with a LangChain server using the langserve library. The main functionality of the chatbot is implemented in main. langchain-java is a Java-based library designed to interact with large language models (LLMs) like OpenAI's GPT-4. langchain. py Interact with a local GPT4All model. py, which use the Langchain library to create a chatbot application. py and client. py for tasks involving the Gemini model. GITHUB_REPOSITORY- The name of the Github repository you want your bot to act upon. Contribute to srhill12/Open-Library-API-Integration-with-LangChain development by creating an account on GitHub. It utilizes OpenAI LLMs alongside with Langchain Agents in order to answer your questions. GitHub is a developer platform that allows developers to create, store, manage and share their code. This is a project that enables users to interact with their documents (PDF, DOCX, or plain text files) using natural language. The chat interface is hosted on a Streamlit web application, providing an intuitive and user-friendly experience. May 7, 2025 · Python version 3. gpt-4 generative-ai chatgpt langchain chatgpt-api This project demonstrates how to use LangChain to build agents that can process natural language queries and interact with SQL databases. More than 150 million people use GitHub to discover, fork, and contribute to over 420 million projects. serve. \n The input to this tool is a JQL query string, and will be passed into atlassian-python-api\'s Jira `jql` function,\n For example, to find all the issues in project "Test" assigned to the me, you would pass in the following string:\n project = Test AND Provided here are a few python scripts for interacting with your own locally hosted GPT4All LLM model using Langchain. Also shows how you can load github files for a given repository on GitHub. env: Configuration file for storing your Google API key. messages import SystemMessage, AIMessage, HumanMessage‍ from extend_ai_toolkit. The server hosts a LangChain agent that can process input requests and Website Interaction: The chatbot uses the latest version of LangChain to interact with and extract information from various websites. With it, you'll get free access to a VS Code-based web editor, complete with a fully-configured Python playground, that includes the neccessary SDKs, libraries, and IDE extensions 🐱 The system utilizes LangChain for the RAG (Retrieval-Augmented Generation) component, FastAPI for the backend API, and Streamlit for the frontend interface. The chatbot retains conversation context, making it an interactive and user-friendly experience. If your API requires authentication or other headers, you can pass the chain a headers property in the config object. It also integrates with the Pinecone index and SentenceTransformers for sentence similarity and embeddings. Aug 16, 2023 · To replace the OpenAI API with another language model API in the LangChain framework, you would need to modify the instances of LLMChain in the APIChain class. , OpenAI or Groq, depending on the model you choose). #1 SMP Thu Jan 11 04:09 Contribute to srhill12/LangChain-with-OpenAI-API-Integration development by creating an account on GitHub. 🦜🔗 Build context-aware reasoning applications. Contribute to RGGH/LangChain-Course development by creating an account on GitHub. LangChain: For building and integrating the ReAct agent framework. Users can interact with the web-based interface, providing an OpenAI API key, uploading a PDF document, and querying questions related to the PDF content. Large Language Model Integration: Compatibility with models like GPT-4, Mistral, Llama2, and ollama. Install the needed libraries using pip. This project demonstrates how to effectively integrate Langchain and LLMs with SQL databases, allowing users to interact with structured data using natural language. Replace {username} with the desired username. This project demonstrates the creation of a Conversational Q&A Chatbot using LangChain for context management and deployment on Hugging Face Spaces. Is there any specific langchain LLM class which supports the above server or do we need to alter the existing Op The bot can interact with different language models and tools, and supports multiple API endpoints. This walkthrough provides step-by-step instructions for building a solution that enables chatting with Google's BigQuery service "Build your own ChatGPT on Telegram, WhatsApp and Facebook Messenger!" LangChain Assistant is a versatile chatbot that leverages state-of-the-art Language Models (currently GPT-3, GPT-3. The scripts utilize different models, including Gemini, Hugging Face, and Mistral AI, to generate responses to user queries. Utilizing Python, this project simplifies tasks such as retrieving, managing, and processing documents stored in SharePoint. 1. At least one LLM API key or configuration is required. By integrating Langchain's advanced PALChain (Program-Aided Language) prompting technology, this project offers an intuitive way to interact with Spotify's vast music database. - Saba-Gul/Text-to-SQL This project provides a Gradio-based web application that allows users to interact with an SQLite database using natural language queries. Note: Ensure that you have provided a valid Hugging Face API token in the . 🌟 Features Contextual Memory: The chatbot retains Feb 15, 2024 · I searched the LangChain documentation with the integrated search. This action ensures that the chatbot will only retrieve data from the Redis database specific to that user. This chatbot leverages Langchain, Python, ChatGPT, ChromaDB, and OpenAI technologies to provide a seamless conversational experience. This knowledge will allow you to create custom chatbots that can retrieve and generate contextually relevant responses based on both structured and unstructured data. Components are modular and easy-to-use, whether you are using the rest of the LangChain framework or not This repository contains a Python application built with Streamlit that utilizes lanhchain and openai API for answering questions based on uploaded PDF files. For detailed documentation of all GithubToolkit features and configurations head to the API reference . This app utilizes a language model to generate JSON ingest chatbot using Python, Langchain and OpenAI GPT models ai python3 chatbot-application streamlit gpt-3 openai-api gpt-4 langchain langchain-python Updated Jul 28, 2023 GITHUB_APP_ID- A six digit number found in your app's general settings; GITHUB_APP_PRIVATE_KEY- The location of your app's private key . langchain_helper. langchain: A library for GenAI. Chat. output = chain("whats the most expensive shirt?") Python Streamlit web app allowing users to interact with their data from a CSV or XLSX file, utilizing OpenAI API and LangChain. Langchain Chatbot is a conversational chatbot powered by OpenAI and Hugging Face models. It’s best practice to use a virtual environment to manage dependencies: In this quiz, you'll test your understanding of building a retrieval-augmented generation (RAG) chatbot using LangChain and Neo4j. Python: The core language used for scripting and logic. Pydantic model class to validate and parse the tool’s input arguments. ; The decorator uses the function name as the tool name by default, but it can be overridden by passing a string as the first argument. LangChain: LangChain is a transformative framework that empowers the language model capabilities, allowing for the development of applications driven by language models. Langchain with OpenAI API is a Python project that integrates the OpenAI API with the Langchain framework to generate information about celebrities based on user queries. Specific Python libraries: langchain-mcp-adapters, langgraph, and an LLM library (like langchain-openai or langchain-groq) of your choice. I want to create a Google Calendar agent and schedule appointments using the agent. You’ll need to follow that flow to connect LangGraph Cloud to GitHub. Chat with your docs in PDF/PPTX/DOCX format, using LangChain and GPT4/ChatGPT from both Azure OpenAI Service and OpenAI - linjungz/chat-with-your-doc We'll see it's a viable approach to start working with a massive API spec AND to assist with user queries that require multiple steps against the API. LangChain Templates: A collection of easily deployable reference architectures for a wide variety of tasks. 5-turbo and the open-source model LLaMA2 through the Ollama API to generate essays and poems based on user input. Chroma DB: Chroma DB is a vector database used to store and query high-dimensional vectors efficiently. 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. It includes various examples, such as simple chat functionality, live token streaming, context-preserving conversations, and API usage. py: Contains few shot prompts. example file for a full list of available environment variables, including a variety of model provider API keys, header-based authentication, LangSmith tracing, testing and development modes, and OpenWeatherMap API key. 📚 Welcome to the "LangChain: Chat with Your Data" course! Learn directly from the LangChain creator, Harrison Chase, and discover the power of LangChain in building chatbots that interact with information from your own documents and data. Creating an agent Our end goal is to create an agent that can respond conversationally to user questions while looking up information as needed. OpenAI : OpenAI provides state-of-the-art language models that power the chat interface, enabling natural and meaningful conversations with text files. [('JQL Query', '\n This tool is a wrapper around atlassian-python-api\'s Jira jql API, useful when you need to search for Jira issues. Args schema should be either: A subclass of pydantic. Download Docker Desktop: Go to the Docker website and download the appropriate version for your operating system (Windows, macOS, or Linux). few_shots. - soos3d/chat-with-repo-langchain-openai This repository contains Python scripts showcasing various functionalities and utilities built using the LangChain framework. Built with Streamlit, LangChain, and Groq Llama3, this open-source project simplifies SQL query generation and execution. For the front-end : app. py Can handle interacting with a single pdf. This script invokes a LangChain chain remotely by sending an HTTP request to a LangChain server. example . The MultiPDF Chat App is a Python application that allows you to chat with multiple PDF documents. APIChain enables using LLMs to interact with APIs to retrieve relevant information. PlayWright Browser Toolkit. The tools and examples provided demonstrate how to leverage LangChain for conversational AI, retrieval-augmented generation (RAG), memory management, output parsing, and prompt templates. This endpoint provides comprehensive guidance on utilizing the APIs effectively. Contribute to langchain-ai/langchain development by creating an account on GitHub. Load these tools into your LangChain agent using the load_tools function. In this project, it is used to create a chatbot using the GPT-3. Here we get an API operation from a specified endpoint and method. Import tool from langchain. LangChain is a framework for developing applications powered by language models. We'll use it to interact with the OpenAI API and generate responses for our chatbot. You can ask questions about the PDFs using natural language, and the application will provide relevant responses based on the content of the documents. The goal of this project is to create a simple, interactive REPL (Read-Eval-Print-Loop) that allows users to interact with a variety of Large Language Models (LLMs). How to use Configure . Construct the chain by providing a question relevant to the provided API documentation. Enjoy chatting with your PDFs and extracting valuable insights! RAG enabled Chatbots using LangChain and Databutton. or - A subclass of pydantic. The LLMChain class is responsible for making predictions using the language model. Once you have set up your GitHub connection, select +New Deployment. Once created, you can interact with it from any API. The language model-driven project utilizes the LangChain framework, an in-memory database, and Streamlit for serving the app. - praj2408/Realtime-Document-Chat-System This project is using the LangChain library and OpenAI to create an agent that can answer questions about a dataset (in this case, the iris dataset). Natural language querying allows users to interact with databases more intuitively and efficiently. Must follow the format {username}/{repo-name}. We can now construct a chain to interact with it. env file in the root directory. 8+: Ensure you have the latest version installed. . See the . This library allows you to build and execute chains of operations on LLMs, such as processing input data, applying templates, and generating responses. The tool is a wrapper for the PyGitHub library. openai: The official OpenAI Python client. env. My user input query depends on two different API endpoint from two different Swagger docs. qdeh ctfbv punznfm lnpdmz qrux frjl hwan rjjvxn clftg nfiad