Documentation

export VEROQ_API_KEY=vq_live_xxx

veroq ask "What's happening with NVDA?"
veroq screen "oversold semiconductors"
veroq signal MSFT
veroq compare AAPL MSFT GOOGL
veroq earnings TSLA
veroq market --human

from veroq import shield
from veroq.middleware import openai_shield

# Middleware — auto-shield every LLM call
client = openai_shield(openai.OpenAI())
response = client.chat.completions.create(...)
print(response.veroq_shield.trust_score)

# Or shield any text directly
result = shield("NVIDIA reported $22B in Q4")
print(result.trust_score, result.corrections)

# Multi-agent verified analysis
from veroq import VeroqClient
swarm = VeroqClient().create_verified_swarm(
    "Analyze NVDA",
    roles=["planner","researcher","verifier",
           "critic","synthesizer"],
)
print(swarm["synthesis"]["summary"])

from veroq import AsyncVeroqClient

async with AsyncVeroqClient() as client:  # reads ~/.veroq/credentials
    # All methods are async
    feed = await client.feed(category="ai_ml")
    results = await client.search(
        "quantum computing",
        depth="deep",
        exclude_sources="foxnews.com"
    )

    # Extract articles
    extracted = await client.extract([
        "https://reuters.com/article/..."
    ])

    # Stream briefs in real-time
    async for brief in client.stream(category="ai_ml"):
        print(brief.headline)

import { shield, shieldOpenAI } from "@veroq/sdk";
import OpenAI from "openai";

// Middleware — auto-shield every LLM call
const client = shieldOpenAI(new OpenAI());
const response = await client.chat.completions.create({...});
console.log(response.veroqShield.trustScore);

// Or shield any text directly
const result = await shield("NVIDIA reported $22B");
console.log(result.trustScore, result.corrections);

// Express middleware — one line
import { shieldMiddleware } from "@veroq/sdk";
app.use("/api/ai", shieldMiddleware({ threshold: 0.7 }));

from langchain_veroq import (
    VeroqSearchTool,
    VeroqExtractTool,
    VeroqTrendingTool,
    VeroqRetriever,
)

# 40 tools for LangChain agents
tools = [
    VeroqSearchTool(api_key="vq_live_xxx"),
    VeroqExtractTool(api_key="vq_live_xxx"),
    VeroqTrendingTool(api_key="vq_live_xxx"),
]

# RAG retriever for chains
retriever = VeroqRetriever(
    api_key="vq_live_xxx",
    category="ai_ml",
    min_confidence=0.7,
    include_sources="reuters.com",
)
docs = retriever.invoke("AI regulation")

import { generateText } from "ai";
import { openai } from "@ai-sdk/openai";
import { veroqSearch, veroqFeed } from "@veroq/ai";

const result = await generateText({
  model: openai("gpt-4o"),
  tools: {
    searchNews: veroqSearch({ apiKey: "vq_live_xxx" }),
    getLatest: veroqFeed({ apiKey: "vq_live_xxx" }),
  },
  prompt: "What's happening in AI today?",
});

from crewai import Agent, Task, Crew
from crewai_veroq import VeroqSearchTool, VeroqFeedTool

researcher = Agent(
    role="News Analyst",
    goal="Find and analyze the latest news",
    tools=[
        VeroqSearchTool(api_key="vq_live_xxx"),
        VeroqFeedTool(api_key="vq_live_xxx"),
    ],
)

task = Task(
    description="What are the top AI developments today?",
    agent=researcher,
    expected_output="A summary of today's top AI news",
)

crew = Crew(agents=[researcher], tasks=[task])
result = crew.kickoff()