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What is meridian-wealth-deployment?

prashant9501/meridian-wealth-deployment — explained in plain English

Analysis updated 2026-05-18

20PythonAudience · developerComplexity · 4/5Setup · moderate

In one sentence

A FastAPI service wrapping an AI financial analyst agent that can query portfolio data, calculate returns, search policy documents, and check live market news.

Mindmap

mindmap
  root((Meridian Wealth))
    What it does
      Answers financial questions
      Calls tools to reason
      Tracks conversation context
    Tech stack
      FastAPI
      LangGraph
      FAISS
      SQLite
    Use cases
      Portfolio lookups
      Financial calculations
      Policy document search
    Audience
      Developers
      Fintech builders

Code map

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filefunction / class

What do people build with it?

USE CASE 1

Ask a chat endpoint questions about client portfolios and market data.

USE CASE 2

Run financial calculations like returns and percentages through an AI agent.

USE CASE 3

Search investment policy documents using semantic similarity instead of keywords.

USE CASE 4

Pull live market news through a web search tool during a conversation.

What is it built with?

PythonFastAPILangGraphFAISSSQLite

How does it compare?

prashant9501/meridian-wealth-deploymentalex72-py/aria-termuxanime0t4ku/gentleman
Stars202020
LanguagePythonPythonPython
Setup difficultymoderatemoderatemoderate
Complexity4/52/52/5
Audiencedeveloperdevelopergeneral

Figures from each repo's GitHub metadata at analysis time.

How do you get it running?

Difficulty · moderate Time to first run · 30min

Requires an OpenAI API key, a Tavily API key, and a separately provided SQLite database.

So what is it?

Meridian Wealth is a FastAPI web service that wraps an AI agent, specifically a LangGraph ReAct agent, designed to act as a financial analyst assistant for a fictional firm called Meridian Wealth Partners. FastAPI is a Python framework for building web APIs, LangGraph is a library for building AI agents that can use tools in a loop to reason through complex questions (the ReAct pattern: Reason, then Act, then observe the result). The agent has five tools it can call to answer questions: it can look up client portfolio data and market data from a SQLite database (a simple local database file), run Python calculations for financial metrics like returns and percentages, search over investment policy documents using a vector search index called FAISS (which lets you find relevant passages from PDF files using semantic similarity rather than keyword matching), and run live web searches via the Tavily API for current news and market updates. The policy PDFs are included in the repository, the database is not and must be provided separately. You send questions to the /chat endpoint, optionally with a conversation ID to maintain context across multiple messages. The agent figures out which combination of tools to call, calls them, uses the results to form a follow-up reasoning step if needed, and eventually returns a final answer. Optionally you can request the tool-call trace showing exactly what steps the agent took. Setup requires creating a Python virtual environment, installing dependencies, copying the example environment file and filling in an OpenAI API key and a Tavily API key, and then running the server with uvicorn. The first startup embeds the policy PDFs into the FAISS index, which takes about a minute, subsequent starts load the saved index.

Copy-paste prompts

Prompt 1
Help me set up Meridian Wealth with an OpenAI API key and a Tavily API key.
Prompt 2
Explain how the ReAct agent decides which of its five tools to call.
Prompt 3
Walk me through what happens on the first startup when the FAISS index is built.
Prompt 4
Show me how to call the /chat endpoint and get back the tool-call trace.

Frequently asked questions

What is meridian-wealth-deployment?

A FastAPI service wrapping an AI financial analyst agent that can query portfolio data, calculate returns, search policy documents, and check live market news.

What language is meridian-wealth-deployment written in?

Mainly Python. The stack also includes Python, FastAPI, LangGraph.

How hard is meridian-wealth-deployment to set up?

Setup difficulty is rated moderate, with roughly 30min to a first successful run.

Who is meridian-wealth-deployment for?

Mainly developer.

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