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Docgpt Langchain

Docgpt Langchain is a Python web application built with LangChain and Streamlit that lets users ask questions about PDF, DOCX, CSV and TXT documents, including requests such as summarizing an article. It supports local file uploads and document URLs, and describes gpt4free and OpenAI model options.

Explore the practical guide ↓

Independent OpenViST project profile, based on linked sources.

Docgpt Langchain — OpenViST project profile in RAG & Knowledge Systems.
OpenViST project illustration. See the linked sources for product details.
Understand the project

Practical overview

When it fits

Use it when you want conversational questions or summaries grounded in a supported document, or when you want to explore a Streamlit-based document-chat implementation.

Who it is for

  • Readers who want to query or summarize supported document files.
  • Developers exploring a Python, LangChain and Streamlit document-chat application.

Documented uses

  • Ask questions about a PDF, DOCX, CSV or TXT document.
  • Request a summary of an article in a document.
  • Provide a document URL for parsing instead of uploading a local file.
  • Add Google search results to responses by supplying a SerpAPI key.
Before you choose

Requirements & limits

The README describes a gpt4free option that does not require an API key and an OpenAI option that requires an OpenAI API key. A SerpAPI key is needed for responses that include Google search results. The README also warns that the free Streamlit Cloud deployment may be slow or crash with concurrent use.

  • Choose gpt4free or provide an OpenAI API key, depending on the model option used.
  • Google search results require a SerpAPI key; document question answering is described separately.
  • Inputs can be uploaded files or document URLs.
  • The README documents a public repository under the MIT license.
  • The README warns of latency and possible crashes in the free Streamlit Cloud version under simultaneous use.

Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.

Source-based practical guide

Run Docgpt Langchain locally without Docker

Start the Streamlit application locally using the repository's documented Python dependency setup.

Before you start

  • Python 3.10.11 is listed among the project's main development packages.
  • The repository and its requirements.txt file.

Steps

  1. Clone the repository, as directed in the README.

  2. Install the project packages with pip install -r requirements.txt.

  3. From the project root, run streamlit run ./app.py.

  4. Open the local service at http://localhost:8501.

Expected outcome

The README says the local Streamlit service will run at http://localhost:8501.

Guide limitations

  • The README's local-development instructions name a separate docGPT-streamlit repository in the clone command; confirm the intended repository before following that command.
  • The README documents setup steps but does not establish that they were independently executed.
Documentation 1 ↗
Evidence and transparency

Sources & review

Official repository ↗
Source record details
Source availability
Active
Sources checked
15 October 2026
Original website title
Lin-jun-xiang/docGPT-langchain · Official homepage title · retained in its source language
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