Agent Cortex v1

Agent Cortex is a local, multi-tool AI assistant built with LangChain, Fast retrieval, and a reasoning-capable language model (Mistral 7B). It can answer questions using a mix of:

• 🔍 Document retrieval (RAG)
• 🧮 Math calculations
• 🌐 Web search (DuckDuckGo)

All running locally with no paid APIs.

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Working Cortex CLI

In this terminal session, Agent Cortex handles three different types of queries using different tools. The LLM decides which tool will be optimal to get the best answer:

1. Retrieval (RAG) — Where are the fireworks on July 3rd?
   → Retrieved from local documents indexed about Bristol, RI events.

2. Web Search — What is the weather in Bristol, RI tomorrow?
   → Uses DuckDuckGo to search live internet results and summarizes forecast.

3. Calculator Tool — What is 5 * 7 + 15?
   → Routes through a custom calculator tool to evaluate the expression.

Each query is interpreted by the ReAct-based agent and routed to the appropriate tool — all executed locally with no API calls or internet billing of an LLM. The websearch is real though but not using outside LLMs for reasoning.

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Features

• Retrieval-Augmented Generation from .txt documents
• Tool-based reasoning using LangChain’s ReAct agent
• DuckDuckGo web search integration
• Calculator for numeric inputs
• Mistral 7B via Ollama (runs locally as CLI)
• Fallback + context injection for vague queries
• CLI chat interface

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Tech Stack

• LangChain
• Ollama (local LLM hosting)
• Mistral 7B
• ChromaDB (vector store)
• HuggingFace Embeddings (all-MiniLM-L6-v2)
• Python 3.10
• Poetry for dependency management

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Ollama + Mistral Setup

This project uses Ollama to run the mistral model locally.

1. Install Ollama (macOS)

brew install ollama

Or download from ollama.com/download and install the desktop app.

2. Download the Mistral Model

ollama run mistral

This will download and launch the Mistral model. Leave it running.

Make sure curl http://localhost:11434 returns {"status":"ok"}

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Getting Started

Clone the Repo

git clone https://github.com/YOUR_USERNAME/agent_cortex_v1.git
cd agent_cortex_v1

Install Poetry & Dependencies

poetry install

Index Your Documents

Place .txt files under data/documents, then run:

PYTHONPATH=. poetry run python scripts/index_documents.py

Start the Agent

poetry run python main.py

You'll be prompted with:

You:

Try asking:

• "What time is the Fourth of July parade?"
• "Who is todays date and the weather look like in Boston?"
• "What is 25 * 4 + 3?"

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Limitations

While Agent Cortex v1 is functional, it's an early prototype with several known limitations:

Agent Behavior

• No long-term memory: The agent has no history of previous interactions or user context beyond a single input.
• No conversational flow: It cannot maintain back-and-forth dialogue or refer to prior questions.
• No agent reflection or self-correction: It does not retry intelligently or summarize thoughts beyond what the base model provides.
• Inconsistent ReAct formatting: The LLM may sometimes fail to produce valid Thought / Action / Action Input format, causing parsing errors or retries.
• Fallbacks are basic and do not yet include streaming or error correction

Retrieval System

• Only supports .txt files: No PDF, HTML, or Markdown parsing.
• No document metadata or filtering: The retriever does not rank sources by type, date, or confidence.
• No chunking or advanced preprocessing: Raw text is split into single documents without semantic boundaries.
• No multi-vector fusion: Only single-query similarity search; no query rewriting or reranking logic.
• Static index: You must manually re-index documents after any updates.

Performance & Deployment

• No streaming output: The full response is printed only after the agent completes.
• Latency: Mistral via Ollama is slower than hosted APIs, especially on lower-spec machines.
• Ollama dependency: Requires installing and running the Ollama server separately, which some users may find nontrivial.

Model Limitations

• No fine-tuning: The Mistral model is used out-of-the-box with no task-specific customization.
• No prompt injection prevention: User input is not sanitized or structured securely for prompt-based attacks.
• No multi-turn tool use: Tools are single-action only — no recursive or multi-step reasoning chains.

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What's Next (v2 Preview)

Agent Cortex v2 will include:

• Streaming FastAPI endpoint + web UI
• Tool-aware chain-of-thought reasoning
• Memory + clarification for ambiguous questions
• More tools (e.g. file summarization, search filtering)

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License

MIT