web_plus_knowledge.py
"""
Web + Knowledge - Live Search Meets Your Own Documents
======================================================
Real agents need two kinds of information: what is in your own documents, and
what is happening on the web right now. This example gives one agent both:
- Agno Knowledge (a local Chroma vector store) for internal or static docs
- Parallel Search for fresh, live information from the web
The agent decides which to use: it searches its knowledge base for grounded
facts and reaches for Parallel when the question needs current data.
Prerequisites:
- pip install parallel-web chromadb
- export PARALLEL_API_KEY=<your-api-key>
- export OPENAI_API_KEY=<your-api-key> (model + embeddings)
"""
from agno.agent import Agent
from agno.knowledge.embedder.openai import OpenAIEmbedder
from agno.knowledge.knowledge import Knowledge
from agno.models.openai import OpenAIResponses
from agno.tools.parallel import ParallelTools
from agno.vectordb.chroma import ChromaDb
from agno.vectordb.search import SearchType
# ---------------------------------------------------------------------------
# Setup - local knowledge base (embedded, no server needed)
# ---------------------------------------------------------------------------
knowledge = Knowledge(
vector_db=ChromaDb(
collection="company_knowledge",
path="tmp/chromadb",
persistent_client=True,
search_type=SearchType.hybrid,
embedder=OpenAIEmbedder(id="text-embedding-3-small"),
),
)
# ---------------------------------------------------------------------------
# Create the Agent
# ---------------------------------------------------------------------------
# search_knowledge=True gives the agent a knowledge-search tool; ParallelTools
# gives it live web search. It chooses per question.
agent = Agent(
model=OpenAIResponses(id="gpt-5.4"),
knowledge=knowledge,
search_knowledge=True,
tools=[ParallelTools()],
markdown=True,
instructions=[
"Answer from your knowledge base when the facts are internal or static.",
"Use Parallel web search when the question needs current information.",
"Tell the user which source you used: knowledge base or live web.",
],
)
# ---------------------------------------------------------------------------
# Run the Agent
# ---------------------------------------------------------------------------
if __name__ == "__main__":
# Load a document into the knowledge base (stands in for internal docs).
knowledge.insert(url="https://agno-public.s3.amazonaws.com/recipes/ThaiRecipes.pdf")
# Internal question -> knowledge base.
agent.print_response(
"From our documents, how do I make Tom Kha Gai?",
stream=True,
)
# Live question -> Parallel web search.
agent.print_response(
"What is the latest news on AI agent frameworks this week?",
stream=True,
)
Run the Example
1
Set up your virtual environment
uv venv --python 3.12
source .venv/bin/activate
uv venv --python 3.12
.venv\Scripts\activate
2
Install dependencies
uv pip install -U agno chromadb openai parallel-web pypdf
3
Export your API keys
export OPENAI_API_KEY="your_openai_api_key_here"
export PARALLEL_API_KEY="your_parallel_api_key_here"
$Env:OPENAI_API_KEY="your_openai_api_key_here"
$Env:PARALLEL_API_KEY="your_parallel_api_key_here"
4
Run the example
Save the code above as
web_plus_knowledge.py, then run:python web_plus_knowledge.py