pip install cerevox

# Using conda
conda install -c conda-forge cerevox

# Using poetry
poetry add cerevox

# Using pipenv
pipenv install cerevox

from cerevox import Hippo

# Initialize Hippo (uses CEREVOX_API_KEY from environment)
hippo = Hippo()

# 1. Create a folder for your knowledge base
folder = hippo.create_folder(
    name="Product Documentation",
    description="User guides and API docs"
)
print(f"✅ Created folder: {folder.name} (ID: {folder.id})")

# 2. Upload documents to the folder
print("📤 Uploading documents...")

# Upload from local file
file1 = hippo.upload_file(
    folder_id=folder.id,
    file_path="user-guide.pdf"
)

# Upload from URL
file2 = hippo.upload_file_from_url(
    folder_id=folder.id,
    file_url="https://example.com/api-docs.pdf",
    file_name="api-docs.pdf"
)

print(f"✅ Uploaded {file1.name} and {file2.name}")

# 3. Create a chat session
chat = hippo.create_chat(
    folder_id=folder.id,
    chat_name="Technical Support Q&A"
)
print(f"✅ Created chat session: {chat.name}")

# 4. Ask questions and get AI-powered answers!
questions = [
    "How do I authenticate users?",
    "What are the API rate limits?",
    "How do I handle errors?"
]

for question in questions:
    print(f"\n❓ Question: {question}")

    answer = hippo.submit_ask(
        chat_id=chat.id,
        question=question
    )

    print(f"💡 Answer: {answer.response}")
    print(f"📚 Sources: {len(answer.sources)} citations")

    # Show source details
    for source in answer.sources[:2]:  # First 2 sources
        print(f"  → {source.file_name} (Page {source.page_number})")

print("\n🎉 Your RAG Q&A system is working!")

import asyncio
from cerevox import AsyncHippo

async def main():
    async with AsyncHippo() as hippo:
        # 1. Create folder
        folder = await hippo.create_folder("Product Docs")

        # 2. Upload multiple files concurrently
        files = await asyncio.gather(
            hippo.upload_file(folder.id, "guide.pdf"),
            hippo.upload_file(folder.id, "docs.pdf")
        )
        print(f"✅ Uploaded {len(files)} documents")

        # 3. Create chat
        chat = await hippo.create_chat(folder.id, "Support Q&A")

        # 4. Ask questions
        answer = await hippo.submit_ask(
            chat.id,
            "How do I get started?"
        )

        print(f"💡 {answer.response}")
        print(f"📚 {len(answer.sources)} sources")

asyncio.run(main())

from cerevox import Hippo

hippo = Hippo()

# Quick setup: Create folder, upload, create chat
folder = hippo.create_folder("My Docs")
hippo.upload_file(folder.id, "document.pdf")
chat = hippo.create_chat(folder.id, "Q&A")

# Ask your first question
answer = hippo.submit_ask(
    chat_id=chat.id,
    question="What is the main topic of this document?"
)

print(f"Answer: {answer.response}")
print(f"Confidence: {answer.confidence_score}")

# That's it! 80% cost reduction, flagship accuracy