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QWED + Ollama Integration Guide

Use QWED for FREE with Local LLMs!

QWED supports ANY OpenAI-compatible API, including Ollama for running models locally.

Why Ollama + QWED?​

✅ $0 Cost - No API fees, just electricity
✅ 100% Private - Data never leaves your machine
✅ Full Control - Choose any model (Llama 3, Mistral, Phi, etc.)
✅ Fast - Local inference, no network latency
✅ Perfect for: Students, hobbyists, privacy-focused developers

Quick Start (5 Minutes)​

Step 1: Install Ollama​

macOS/Linux:

curl -fsSL https://ollama.com/install.sh | sh

Windows: Download from https://ollama.com/download

Step 2: Pull a Model​

# Recommended: Llama 3 (8B)
ollama pull llama3

# Or other models:
ollama pull mistral
ollama pull phi3
ollama pull codellama

Step 3: Start Ollama Server​

ollama serve
# Server runs on http://localhost:11434

Step 4: Install QWED​

pip install qwed

Step 5: Use QWED with Ollama!​

Option A: Backend Server (Recommended)

# terminal 1: Configure backend to use Ollama
cp .env.example .env

# Edit .env:
echo "ACTIVE_PROVIDER=openai" >> .env
echo "OPENAI_BASE_URL=http://localhost:11434/v1" >> .env
echo "OPENAI_API_KEY=ollama" >> .env
echo "OPENAI_MODEL=llama3" >> .env

# Start backend
python -m qwed_api
# terminal 2: Use QWED SDK
from qwed import QWEDClient

client = QWEDClient(
    api_key="qwed_local",
    base_url="http://localhost:8000"
)

result = client.verify("What is 2+2?")
print(result.verified)  # True
print(result.value)  # 4

Option B: QWEDLocal (Coming in v2.1.0)

from qwed import QWEDLocal

client = QWEDLocal(
    base_url="http://localhost:11434/v1",
    model="llama3",
    api_key="ollama"  # Dummy key
)

result = client.verify("Calculate factorial of 5")
print(result.verified)  # True
print(result.value)  # 120

Supported Models​

QWED works with any Ollama model! Tested with:

ModelSizeBest ForSpeed
llama38BGeneral use, best accuracy⚡⚡⚡
mistral7BFast, good quality⚡⚡⚡⚡
phi33.8BLow memory, decent accuracy⚡⚡⚡⚡⚡
codellama7BCode verification⚡⚡⚡
gemma7BGoogle's model⚡⚡⚡

Complete Example​

from qwed import QWEDClient

client = QWEDClient(
    api_key="qwed_local",
    base_url="http://localhost:8000"  # Your QWED backend
)

# Math verification
result = client.verify_math(
    query="What is the derivative of x^2?",
    llm_output="2x"
)
print(f"✅ Verified: {result.verified}")
print(f"📊 Evidence: {result.evidence}")

# Logic verification
result = client.verify_logic(
    query="If A implies B, and B implies C, does A imply C?",
    llm_output="Yes"
)
print(f"✅ Valid: {result.verified}")

# Code security
result = client.verify_code(
    code='user_input = request.GET["q"]; eval(user_input)',
    language="python"
)
print(f"🚨 Blocked: {result.blocked}")
print(f"⚠️ Vulnerabilities: {result.vulnerabilities}")

Cost Comparison​

SetupMonthly CostBest For
Ollama (Local)$0 💚Students, hobbyists, privacy
OpenAI GPT-4o-mini~$5-10Startups, quick prototypes
Anthropic Claude~$20-50Production, best accuracy
OpenAI GPT-4~$50-100Enterprises, critical systems

With Ollama: 1 million verifications = $0 (just electricity!)

Hardware Requirements​

Minimum (Phi3, small models):

  • 8GB RAM
  • No GPU required (CPU only)
  • Works on: M1 Mac, modern laptops

Recommended (Llama 3, Mistral):

  • 16GB RAM
  • GPU with 6GB+ VRAM (optional, speeds up inference)
  • Works on: M1/M2 Mac, NVIDIA RTX 3060+

Ideal (Large models):

  • 32GB+ RAM
  • NVIDIA RTX 4090 / Apple M2 Ultra
  • Can run: Llama 3 70B, CodeLlama 34B

Troubleshooting​

Ollama not responding​

# Check Ollama is running
ollama list

# Restart Ollama
ollama serve

Connection refused​

# Verify Ollama endpoint
curl http://localhost:11434/api/tags

# Should return list of models

Slow inference​

# Use smaller model
ollama pull phi3

# Or enable GPU acceleration (if available)
ollama run llama3 --gpu

Alternative Local LLM Tools​

QWED also works with:

  • LM Studio - GUI for local models
  • LocalAI - Drop-in OpenAI replacement
  • text-generation-webui - Advanced UI
  • vLLM - High-performance inference

All use OpenAI-compatible APIs → work with QWED!

Privacy Benefits​

Data that NEVER leaves your machine:

  • ✅ Prompts & queries
  • ✅ LLM responses
  • ✅ Verification results
  • ✅ User information

Perfect for:

  • 🏥 Healthcare (HIPAA compliance)
  • 🏦 Finance (sensitive data)
  • 🏛️ Government (classified info)
  • 🔬 Research (confidential experiments)

Next Steps​

Expand your setup:

  • Try different models: ollama pull <model>
  • Fine-tune for your domain
  • Deploy to production (Docker + Ollama)

Upgrade when needed:

  • Start free with Ollama
  • Switch to cloud APIs for scale
  • QWED works with both seamlessly!

Community​

Questions?

Show your setup!

  • Tweet with #QWED #Ollama
  • Share your use case
  • Help others get started

Remember: QWED is model agnostic. Start free with Ollama, scale to cloud when ready! 🚀