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NaviLaw

NaviLaw is a legal research system that uses ReAct-style agent reasoning, retrieval-augmented generation and the Llama 3 70B model to research legal materials and user-uploaded PDFs. It supports legal advisory responses, precedent retrieval and summaries, report generation, and case-outcome prediction.

Explore the practical guide ↓

Independent OpenViST project profile, based on linked sources.

NaviLaw — OpenViST project profile in Research Agents.
OpenViST project illustration. See the linked sources for product details.
Understand the project

Practical overview

When it fits

Use NaviLaw when a legal research task should combine a question with uploaded PDF materials and produce an advisory response, precedent summary, report, or case-outcome prediction.

Who it is for

  • Legal professionals and researchers working with case documents
  • Developers exploring agentic retrieval-augmented generation for legal workflows

Documented uses

  • Ask a legal question in the context of multiple uploaded PDF documents.
  • Retrieve and summarize relevant legal precedents.
  • Generate a concise legal report with findings, analysis and recommendations.
  • Request an advisory response or a predicted case outcome based on case details.
Before you choose

Requirements & limits

The source repository is public and identifies an MIT license. The repository links to a Streamlit web application and documents a self-hosted setup.

  • The system is described as using Llama 3 70B, ReAct agent reasoning and retrieval-augmented generation.
  • Supplementary legal research uses the Tavily Search tool.
  • A local setup requires Python 3.7 or higher and GROQ_API_KEY, TAVILY_API_KEY and HF_TOKEN environment values.
  • The documented stack includes FastAPI, LangChain, PyPDF2 and Streamlit.

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

Prepare a local NaviLaw setup

Install the documented project dependencies and configure the API credentials required by the repository instructions.

Before you start

  • Python 3.7 or higher
  • The NaviLaw GitHub repository
  • API keys or tokens for GROQ_API_KEY, TAVILY_API_KEY and HF_TOKEN

Steps

  1. Clone the repository and change into the navilaw-ai directory.

  2. Create and activate a Python virtual environment.

  3. Install dependencies with pip install -r requirements.txt.

  4. Create a root-level .env file and add GROQ_API_KEY, TAVILY_API_KEY and HF_TOKEN.

Expected outcome

The repository's documented dependency installation and environment-variable setup are complete.

Guide limitations

  • These steps cover setup only; they do not document starting the application or completing a legal research request.
  • The repository lists requirements files in backend and frontend directories, while its installation instructions use a requirements.txt path without a directory.
Documentation 1 ↗
COMPARE OPTIONS

Compare options for Retrieval-augmented applications

These projects document a common task and share a project role. This is a source-based comparison, not an execution benchmark or a guarantee of interchangeability.

ProjectDocumented purposePlatformAccess and requirements
NaviLawAsk a legal question in the context of multiple uploaded PDF documents.WebThe source repository is public and identifies an MIT license. The repository links to a Streamlit web application and documents a self-hosted setup.
Local RAG Researcher with DeepSeek R1 & LangGraphTurn a user instruction into research questions and retrieve relevant local documents.Self-hostedThe documented application is run from the Python repository on a self-hosted setup. The README lists Python 3.9 or later and Ollama as prerequisites; it describes a Tavily API key as optional for web search.
Evidence and transparency

Sources & review

Official repository ↗
Source record details
Source availability
Active
Sources checked
17 October 2026
Original website title
devroopsaha744/navilaw-ai · Official homepage title · retained in its source language
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