AI-Query

LangChain Flask SerpAPI MongoDB Ollama Integration

• An Ollama AI model server
• SerpAPI for web search
• MongoDB for persistent chat memory

Setup

1. Clone the repo:

   git clone https://github.com/drewesk/AIQueryApp.git
   cd langchain_flask_serpapi_mongo
   

2. Create and activate a virtual environment:

   python3 -m venv venv
   source venv/bin/activate
   

3. Install dependencies:

   pip install -r requirements.txt
   

4. Set up environment variables:

   Create a .env file with:

   SERPAPI_API_KEY=your_serpapi_api_key
   MONGODB_URI=your_mongodb_connection_string
   

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SerpAPI setup

1. Go to serpapi.com, sign up.
2. Copy your API key.
3. Add to .env

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MongoDB setup

1. Go to mongodb.com/cloud/atlas and sign up.
2. Create a free shared cluster.
3. In Database Access, create a user with a username and password.
4. In Network Access, add IP 0.0.0.0/0 to allow all connections.
5. Click Connect → Connect your application.
6. Choose:
   • Driver: Python
   • Version: Latest (e.g. 3.12 or later)
7. Copy the connection auto-genearated string, then add to your .env file

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5. Run Ollama model server:

   ollama serve

6. Pull model:

   ollama pull WhiteRabbitNeo/WhiteRabbitNeo-2.5-Qwen-2.5-Coder-7B

   or use the of your choice and then modify app.py to reflect new new Model Name in GET request.

7. Run the Flask app:

   python app.py

8. Send POST requests to the Flask app /chat endpoint with JSON body:

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To activate real-time web search (instead of using the local LLM), prefix your prompt with the word search.

This bypasses the local language model and uses your SerpAPI key to fetch live results directly from Google Search.

Example Using search Keyword:

curl -X POST http://127.0.0.1:5000/chat \
  -H "Content-Type: application/json" \
  -d '{"prompt":"search the weather in NYC"}'

Or to prompt the AI without using SerpAI, omit using Search as the first word of the prompt.

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MIT License | Open Source |

Copyright (c) 2025 Andrew Eskenazi

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