repo stringlengths 7 90 | file_url stringlengths 81 315 | file_path stringlengths 4 228 | content stringlengths 0 32.8k | language stringclasses 1
value | license stringclasses 7
values | commit_sha stringlengths 40 40 | retrieved_at stringdate 2026-01-04 14:38:15 2026-01-05 02:33:18 | truncated bool 2
classes |
|---|---|---|---|---|---|---|---|---|
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/requesty/structured_output.py | cookbook/11_models/requesty/structured_output.py | from typing import List
from agno.agent import Agent
from agno.models.requesty import Requesty
from pydantic import BaseModel, Field
class MovieScript(BaseModel):
setting: str = Field(
..., description="Provide a nice setting for a blockbuster movie."
)
ending: str = Field(
...,
d... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/requesty/async_basic.py | cookbook/11_models/requesty/async_basic.py | import asyncio
from agno.agent import Agent, RunOutput # noqa
from agno.models.requesty import Requesty
agent = Agent(model=Requesty(id="openai/gpt-4o"), markdown=True)
# Get the response in a variable
# run: RunOutput = agent.run("Share a 2 sentence horror story")
# print(run.content)
# Print the response in the ... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/ibm/retry.py | cookbook/11_models/ibm/retry.py | """Example demonstrating how to set up retries with IBM WatsonX."""
from agno.agent import Agent
from agno.models.ibm import WatsonX
# We will use a deliberately wrong model ID, to trigger retries.
wrong_model_id = "watsonx-wrong-id"
agent = Agent(
model=WatsonX(
id=wrong_model_id,
retries=3, # ... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/ibm/__init__.py | cookbook/11_models/ibm/__init__.py | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false | |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/ibm/watsonx/image_agent_bytes.py | cookbook/11_models/ibm/watsonx/image_agent_bytes.py | from pathlib import Path
from agno.agent import Agent
from agno.media import Image
from agno.models.ibm import WatsonX
agent = Agent(
model=WatsonX(id="meta-llama/llama-3-2-11b-vision-instruct"),
markdown=True,
)
image_path = Path(__file__).parent.joinpath("sample.jpg")
# Read the image file content as byte... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/ibm/watsonx/db.py | cookbook/11_models/ibm/watsonx/db.py | """Run `pip install ddgs sqlalchemy ibm-watsonx-ai` to install dependencies."""
from agno.agent import Agent
from agno.db.postgres import PostgresDb
from agno.models.ibm import WatsonX
from agno.tools.duckduckgo import DuckDuckGoTools
# Setup the database
db_url = "postgresql+psycopg://ai:ai@localhost:5532/ai"
db = P... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/ibm/watsonx/async_tool_use.py | cookbook/11_models/ibm/watsonx/async_tool_use.py | """
Async example using Claude with tool calls.
"""
import asyncio
from agno.agent import Agent
from agno.models.ibm import WatsonX
from agno.tools.duckduckgo import DuckDuckGoTools
agent = Agent(
model=WatsonX(id="mistralai/mistral-small-3-1-24b-instruct-2503"),
tools=[DuckDuckGoTools()],
markdown=True,... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/ibm/watsonx/basic_stream.py | cookbook/11_models/ibm/watsonx/basic_stream.py | from typing import Iterator # noqa
from agno.agent import Agent, RunOutputEvent # noqa
from agno.models.ibm import WatsonX
agent = Agent(
model=WatsonX(id="mistralai/mistral-small-3-1-24b-instruct-2503"), markdown=True
)
# Get the response in a variable
# run_response: Iterator[RunOutputEvent] = agent.run("Shar... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/ibm/watsonx/knowledge.py | cookbook/11_models/ibm/watsonx/knowledge.py | """Run `pip install ddgs sqlalchemy pgvector pypdf openai ibm-watsonx-ai` to install dependencies."""
from agno.agent import Agent
from agno.knowledge.knowledge import Knowledge
from agno.models.ibm import WatsonX
from agno.vectordb.pgvector import PgVector
db_url = "postgresql+psycopg://ai:ai@localhost:5532/ai"
kno... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/ibm/watsonx/tool_use.py | cookbook/11_models/ibm/watsonx/tool_use.py | """Run `pip install ddgs` to install dependencies."""
from agno.agent import Agent
from agno.models.ibm import WatsonX
from agno.tools.duckduckgo import DuckDuckGoTools
agent = Agent(
model=WatsonX(id="mistralai/mistral-small-3-1-24b-instruct-2503"),
tools=[DuckDuckGoTools()],
markdown=True,
)
agent.print... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/ibm/watsonx/basic.py | cookbook/11_models/ibm/watsonx/basic.py | from agno.agent import Agent, RunOutput # noqa
from agno.models.ibm import WatsonX
agent = Agent(
model=WatsonX(id="mistralai/mistral-small-3-1-24b-instruct-2503"), markdown=True
)
# Get the response in a variable
# run: RunOutput = agent.run("Share a 2 sentence horror story")
# print(run.content)
# Print the r... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/ibm/watsonx/async_basic_stream.py | cookbook/11_models/ibm/watsonx/async_basic_stream.py | import asyncio
from agno.agent import Agent, RunOutputEvent # noqa
from agno.models.ibm import WatsonX
agent = Agent(
model=WatsonX(id="mistralai/mistral-small-3-1-24b-instruct-2503"),
debug_mode=True,
markdown=True,
)
# Get the response in a variable
# run_response: Iterator[RunOutputEvent] = agent.run... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/ibm/watsonx/__init__.py | cookbook/11_models/ibm/watsonx/__init__.py | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false | |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/ibm/watsonx/structured_output.py | cookbook/11_models/ibm/watsonx/structured_output.py | from typing import List
from agno.agent import Agent, RunOutput # noqa
from agno.models.ibm import WatsonX
from pydantic import BaseModel, Field
from rich.pretty import pprint # noqa
class MovieScript(BaseModel):
setting: str = Field(
..., description="Provide a nice setting for a blockbuster movie."
... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/ibm/watsonx/async_basic.py | cookbook/11_models/ibm/watsonx/async_basic.py | import asyncio
from agno.agent import Agent, RunOutput # noqa
from agno.models.ibm import WatsonX
agent = Agent(
model=WatsonX(id="mistralai/mistral-small-3-1-24b-instruct-2503"), markdown=True
)
# Get the response in a variable
# run: RunOutput = agent.run("Share a 2 sentence horror story")
# print(run.content... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/together/image_agent.py | cookbook/11_models/together/image_agent.py | from agno.agent import Agent
from agno.media import Image
from agno.models.together import Together
agent = Agent(
model=Together(id="meta-llama/Llama-Vision-Free"),
markdown=True,
)
agent.print_response(
"Tell me about this image",
images=[
Image(
url="https://upload.wikimedia.org... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/together/image_agent_bytes.py | cookbook/11_models/together/image_agent_bytes.py | from pathlib import Path
from agno.agent import Agent
from agno.media import Image
from agno.models.together import Together
agent = Agent(
model=Together(id="meta-llama/Llama-Vision-Free"),
markdown=True,
)
image_path = Path(__file__).parent.joinpath("sample.jpg")
# Read the image file content as bytes
ima... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/together/tool_use_stream.py | cookbook/11_models/together/tool_use_stream.py | """Run `pip install ddgs` to install dependencies."""
from agno.agent import Agent
from agno.models.together import Together
from agno.tools.duckduckgo import DuckDuckGoTools
agent = Agent(
model=Together(id="meta-llama/Meta-Llama-3.1-8B-Instruct-Turbo"),
tools=[DuckDuckGoTools()],
markdown=True,
)
agent.... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/together/async_tool_use.py | cookbook/11_models/together/async_tool_use.py | """Run `pip install ddgs` to install dependencies."""
import asyncio
from agno.agent import Agent
from agno.models.together import Together
from agno.tools.duckduckgo import DuckDuckGoTools
agent = Agent(
model=Together(id="meta-llama/Meta-Llama-3.1-8B-Instruct-Turbo"),
tools=[DuckDuckGoTools()],
markdow... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/together/basic_stream.py | cookbook/11_models/together/basic_stream.py | from typing import Iterator # noqa
from agno.agent import Agent, RunOutputEvent # noqa
from agno.models.together import Together
agent = Agent(
model=Together(id="meta-llama/Meta-Llama-3.1-8B-Instruct-Turbo"), markdown=True
)
# Get the response in a variable
# run_response: Iterator[RunOutputEvent] = agent.run(... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/together/image_agent_with_memory.py | cookbook/11_models/together/image_agent_with_memory.py | from agno.agent import Agent
from agno.media import Image
from agno.models.together import Together
agent = Agent(
model=Together(id="meta-llama/Llama-Vision-Free"),
markdown=True,
add_history_to_context=True,
num_history_runs=3,
)
agent.print_response(
"Tell me about this image",
images=[
... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/together/reasoning_agent.py | cookbook/11_models/together/reasoning_agent.py | from agno.agent import Agent
from agno.models.together import Together
agent = Agent(
model=Together(
id="Qwen/Qwen3-235B-A22B-Thinking-2507",
),
reasoning=True,
)
agent.print_response("How many r are in the word 'strawberry'?", show_reasoning=True)
| python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/together/tool_use.py | cookbook/11_models/together/tool_use.py | """Run `pip install ddgs` to install dependencies."""
from agno.agent import Agent
from agno.models.together import Together
from agno.tools.duckduckgo import DuckDuckGoTools
agent = Agent(
model=Together(id="meta-llama/Meta-Llama-3.1-8B-Instruct-Turbo"),
tools=[DuckDuckGoTools()],
markdown=True,
)
agent.... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/together/basic.py | cookbook/11_models/together/basic.py | from agno.agent import Agent, RunOutput # noqa
from agno.models.together import Together
agent = Agent(
model=Together(id="meta-llama/Meta-Llama-3.1-8B-Instruct-Turbo"), markdown=True
)
# Get the response in a variable
# run: RunOutput = agent.run("Share a 2 sentence horror story")
# print(run.content)
# Print ... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/together/async_basic_stream.py | cookbook/11_models/together/async_basic_stream.py | import asyncio
from typing import Iterator # noqa
from agno.agent import Agent, RunOutputEvent # noqa
from agno.models.together import Together
agent = Agent(
model=Together(id="meta-llama/Meta-Llama-3.1-8B-Instruct-Turbo"), markdown=True
)
# Get the response in a variable
# run_response: Iterator[RunOutputEve... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/together/retry.py | cookbook/11_models/together/retry.py | """Example demonstrating how to set up retries with Together."""
from agno.agent import Agent
from agno.models.together import Together
# We will use a deliberately wrong model ID, to trigger retries.
wrong_model_id = "together-wrong-id"
agent = Agent(
model=Together(
id=wrong_model_id,
retries=3... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/together/__init__.py | cookbook/11_models/together/__init__.py | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false | |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/together/structured_output.py | cookbook/11_models/together/structured_output.py | from typing import List
from agno.agent import Agent, RunOutput # noqa
from agno.models.together import Together
from pydantic import BaseModel, Field
from rich.pretty import pprint # noqa
class MovieScript(BaseModel):
setting: str = Field(
..., description="Provide a nice setting for a blockbuster mov... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/together/async_basic.py | cookbook/11_models/together/async_basic.py | import asyncio
from agno.agent import Agent, RunOutput # noqa
from agno.models.together import Together
agent = Agent(
model=Together(id="meta-llama/Meta-Llama-3.1-8B-Instruct-Turbo"), markdown=True
)
# Get the response in a variable
# run: RunOutput = agent.run("Share a 2 sentence horror story")
# print(run.co... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/groq/image_agent.py | cookbook/11_models/groq/image_agent.py | from agno.agent import Agent
from agno.media import Image
from agno.models.groq import Groq
agent = Agent(model=Groq(id="meta-llama/llama-4-scout-17b-16e-instruct"))
agent.print_response(
"Tell me about this image",
images=[
Image(url="https://upload.wikimedia.org/wikipedia/commons/f/f2/LPU-v1-die.jpg... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/groq/metrics.py | cookbook/11_models/groq/metrics.py | from agno.agent import Agent, RunOutput
from agno.models.groq import Groq
from agno.tools.yfinance import YFinanceTools
from agno.utils.pprint import pprint_run_response
from rich.pretty import pprint
agent = Agent(
model=Groq(id="llama-3.3-70b-versatile"),
tools=[YFinanceTools()],
markdown=True,
)
run_ou... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/groq/db.py | cookbook/11_models/groq/db.py | """Run `pip install ddgs sqlalchemy groq` to install dependencies."""
from agno.agent import Agent
from agno.db.postgres import PostgresDb
from agno.models.groq import Groq
from agno.tools.duckduckgo import DuckDuckGoTools
# Setup the database
db_url = "postgresql+psycopg://ai:ai@localhost:5532/ai"
db = PostgresDb(db... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/groq/async_tool_use.py | cookbook/11_models/groq/async_tool_use.py | """Please install dependencies using:
pip install openai ddgs newspaper4k lxml_html_clean agno
"""
import asyncio
from agno.agent import Agent
from agno.models.groq import Groq
from agno.tools.duckduckgo import DuckDuckGoTools
from agno.tools.newspaper4k import Newspaper4kTools
agent = Agent(
model=Groq(id="llam... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/groq/browser_search.py | cookbook/11_models/groq/browser_search.py | from agno.agent import Agent
from agno.models.groq import Groq
agent = Agent(
model=Groq(id="openai/gpt-oss-20b"),
tools=[{"type": "browser_search"}],
)
agent.print_response("Is the Going-to-the-sun road open for public?")
| python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/groq/basic_stream.py | cookbook/11_models/groq/basic_stream.py | from typing import Iterator # noqa
from agno.agent import Agent, RunOutputEvent # noqa
from agno.models.groq import Groq
agent = Agent(model=Groq(id="llama-3.3-70b-versatile"), markdown=True)
# Get the response in a variable
# run_response: Iterator[RunOutputEvent] = agent.run("Share a 2 sentence horror story", str... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/groq/knowledge.py | cookbook/11_models/groq/knowledge.py | """Run `pip install ddgs sqlalchemy pgvector pypdf openai groq` to install dependencies."""
from agno.agent import Agent
from agno.knowledge.knowledge import Knowledge
from agno.models.groq import Groq
from agno.vectordb.pgvector import PgVector
db_url = "postgresql+psycopg://ai:ai@localhost:5532/ai"
knowledge = Kno... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/groq/reasoning_agent.py | cookbook/11_models/groq/reasoning_agent.py | from agno.agent import Agent
from agno.models.groq import Groq
# Create a reasoning agent that uses:
# - `deepseek-r1-distill-llama-70b` as the reasoning model
# - `llama-3.3-70b-versatile` to generate the final response
reasoning_agent = Agent(
model=Groq(id="llama-3.3-70b-versatile"),
reasoning_model=Groq(
... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/groq/tool_use.py | cookbook/11_models/groq/tool_use.py | """Please install dependencies using:
pip install openai ddgs newspaper4k lxml_html_clean agno
"""
from agno.agent import Agent
from agno.models.groq import Groq
from agno.tools.duckduckgo import DuckDuckGoTools
from agno.tools.newspaper4k import Newspaper4kTools
agent = Agent(
model=Groq(id="llama-3.3-70b-versat... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/groq/basic.py | cookbook/11_models/groq/basic.py | from agno.agent import Agent, RunOutput # noqa
from agno.models.groq import Groq
agent = Agent(model=Groq(id="llama-3.3-70b-versatile"), markdown=True)
# Get the response in a variable
# run: RunOutput = agent.run("Share a 2 sentence horror story")
# print(run.content)
# Print the response on the terminal
agent.pri... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/groq/deep_knowledge.py | cookbook/11_models/groq/deep_knowledge.py | """🤔 DeepKnowledge - An AI Agent that iteratively searches a knowledge base to answer questions
This agent performs iterative searches through its knowledge base, breaking down complex
queries into sub-questions, and synthesizing comprehensive answers. It's designed to explore
topics deeply and thoroughly by followin... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/groq/async_basic_stream.py | cookbook/11_models/groq/async_basic_stream.py | import asyncio
from agno.agent import Agent
from agno.models.groq import Groq
agent = Agent(
model=Groq(id="llama-3.3-70b-versatile"),
description="You help people with their health and fitness goals.",
instructions=["Recipes should be under 5 ingredients"],
)
# -*- Print a response to the terminal
asynci... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/groq/retry.py | cookbook/11_models/groq/retry.py | """Example demonstrating how to set up retries with Groq."""
from agno.agent import Agent
from agno.models.groq import Groq
# We will use a deliberately wrong model ID, to trigger retries.
wrong_model_id = "groq-wrong-id"
agent = Agent(
model=Groq(
id=wrong_model_id,
retries=3, # Number of times... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/groq/__init__.py | cookbook/11_models/groq/__init__.py | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false | |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/groq/transcription_agent.py | cookbook/11_models/groq/transcription_agent.py | """Run `pip install groq` to install dependencies."""
from agno.agent import Agent
from agno.models.openai import OpenAIChat
from agno.tools.models.groq import GroqTools
url = "https://agno-public.s3.amazonaws.com/demo_data/sample_conversation.wav"
agent = Agent(
name="Groq Transcription Agent",
model=OpenAI... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/groq/structured_output.py | cookbook/11_models/groq/structured_output.py | from typing import List
from agno.agent import Agent, RunOutput # noqa
from agno.models.groq import Groq
from pydantic import BaseModel, Field
from rich.pretty import pprint # noqa
class MovieScript(BaseModel):
setting: str = Field(
..., description="Provide a nice setting for a blockbuster movie."
... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/groq/translation_agent.py | cookbook/11_models/groq/translation_agent.py | import base64
from pathlib import Path
from agno.agent import Agent
from agno.models.openai import OpenAIChat
from agno.tools.models.groq import GroqTools
from agno.utils.media import save_base64_data
path = "tmp/sample-fr.mp3"
agent = Agent(
name="Groq Translation Agent",
model=OpenAIChat(id="gpt-4o-mini"),... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/groq/agent_team.py | cookbook/11_models/groq/agent_team.py | from agno.agent import Agent
from agno.models.groq import Groq
from agno.team.team import Team
from agno.tools.duckduckgo import DuckDuckGoTools
from agno.tools.yfinance import YFinanceTools
web_agent = Agent(
name="Web Agent",
role="Search the web for information",
model=Groq(id="llama-3.3-70b-versatile")... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/groq/async_basic.py | cookbook/11_models/groq/async_basic.py | import asyncio
from agno.agent import Agent
from agno.models.groq import Groq
agent = Agent(
model=Groq(id="llama-3.3-70b-versatile"),
description="You help people with their health and fitness goals.",
instructions=["Recipes should be under 5 ingredients"],
)
# -*- Print a response to the cli
asyncio.run... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/groq/research_agent_exa.py | cookbook/11_models/groq/research_agent_exa.py | """Run `pip install groq exa-py` to install dependencies."""
from datetime import datetime
from pathlib import Path
from textwrap import dedent
from agno.agent import Agent
from agno.models.groq import Groq
from agno.tools.exa import ExaTools
cwd = Path(__file__).parent.resolve()
tmp = cwd.joinpath("tmp")
if not tmp... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/groq/reasoning/demo_qwen_2_5_32B.py | cookbook/11_models/groq/reasoning/demo_qwen_2_5_32B.py | """Run `pip install ddgs sqlalchemy pgvector pypdf openai groq` to install dependencies."""
from agno.agent import Agent
from agno.knowledge.knowledge import Knowledge
from agno.models.groq import Groq
from agno.vectordb.pgvector import PgVector
db_url = "postgresql+psycopg://ai:ai@localhost:5532/ai"
knowledge = Kno... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/groq/reasoning/finance_agent.py | cookbook/11_models/groq/reasoning/finance_agent.py | from agno.agent import Agent
from agno.models.groq import Groq
from agno.tools.yfinance import YFinanceTools
# Create an Agent with Groq and YFinanceTools
finance_agent = Agent(
model=Groq(id="deepseek-r1-distill-llama-70b-specdec"),
tools=[YFinanceTools()],
description="You are an investment analyst with ... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/groq/reasoning/basic_stream.py | cookbook/11_models/groq/reasoning/basic_stream.py | from agno.agent import Agent
from agno.models.groq import Groq
agent = Agent(model=Groq(id="deepseek-r1-distill-llama-70b-specdec"), markdown=True)
# Print the response on the terminal
agent.print_response("Share a 2 sentence horror story", stream=True)
| python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/groq/reasoning/basic.py | cookbook/11_models/groq/reasoning/basic.py | from agno.agent import Agent
from agno.models.groq import Groq
agent = Agent(model=Groq(id="deepseek-r1-distill-llama-70b-specdec"), markdown=True)
# Print the response on the terminal
agent.print_response("Share a 2 sentence horror story")
| python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/groq/reasoning/__init__.py | cookbook/11_models/groq/reasoning/__init__.py | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false | |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/groq/reasoning/demo_deepseek_qwen.py | cookbook/11_models/groq/reasoning/demo_deepseek_qwen.py | """Run `pip install ddgs sqlalchemy pgvector pypdf openai groq` to install dependencies."""
from agno.agent import Agent
from agno.models.groq import Groq
agent_with_reasoning = Agent(
model=Groq(id="Qwen-2.5-32b"),
reasoning=True,
reasoning_model=Groq(
id="Deepseek-r1-distill-qwen-32b", temperatu... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/ollama/image_agent.py | cookbook/11_models/ollama/image_agent.py | from pathlib import Path
from agno.agent import Agent
from agno.media import Image
from agno.models.ollama import Ollama
agent = Agent(
model=Ollama(id="llama3.2-vision"),
markdown=True,
)
image_path = Path(__file__).parent.joinpath("super-agents.png")
agent.print_response(
"Write a 3 sentence fiction st... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/ollama/tool_use_stream.py | cookbook/11_models/ollama/tool_use_stream.py | """Run `pip install ddgs` to install dependencies."""
from agno.agent import Agent
from agno.models.ollama import Ollama
from agno.tools.duckduckgo import DuckDuckGoTools
agent = Agent(
model=Ollama(id="llama3.2:latest"),
tools=[DuckDuckGoTools()],
markdown=True,
)
agent.print_response("Whats happening in... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/ollama/demo_qwen.py | cookbook/11_models/ollama/demo_qwen.py | from agno.agent import Agent
from agno.models.ollama import Ollama
from agno.tools.yfinance import YFinanceTools
agent = Agent(
model=Ollama(id="qwen3:8b"),
tools=[
YFinanceTools(),
],
instructions="Use tables to display data.",
)
agent.print_response("Write a report on NVDA", stream=True, mar... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/ollama/demo_gemma.py | cookbook/11_models/ollama/demo_gemma.py | from pathlib import Path
from agno.agent import Agent
from agno.media import Image
from agno.models.ollama import Ollama
agent = Agent(model=Ollama(id="gemma3:12b"), markdown=True)
image_path = Path(__file__).parent.joinpath("super-agents.png")
agent.print_response(
"Write a 3 sentence fiction story about the im... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/ollama/memory.py | cookbook/11_models/ollama/memory.py | """
This recipe shows how to use personalized memories and summaries in an agent.
Steps:
1. Run: `./cookbook/scripts/run_pgvector.sh` to start a postgres container with pgvector
2. Run: `pip install ollama sqlalchemy 'psycopg[binary]' pgvector` to install the dependencies
3. Run: `python cookbook/models/ollama/memory.p... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/ollama/db.py | cookbook/11_models/ollama/db.py | """Run `pip install ddgs sqlalchemy ollama` to install dependencies."""
from agno.agent import Agent
from agno.db.postgres import PostgresDb
from agno.models.ollama import Ollama
from agno.tools.duckduckgo import DuckDuckGoTools
# Setup the database
db_url = "postgresql+psycopg://ai:ai@localhost:5532/ai"
db = Postgre... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/ollama/basic_stream.py | cookbook/11_models/ollama/basic_stream.py | from typing import Iterator # noqa
from agno.agent import Agent, RunOutputEvent # noqa
from agno.models.ollama import Ollama
agent = Agent(model=Ollama(id="llama3.1:8b"), markdown=True)
# Get the response in a variable
# run_response: Iterator[RunOutputEvent] = agent.run("Share a 2 sentence horror story", stream=Tr... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/ollama/knowledge.py | cookbook/11_models/ollama/knowledge.py | """Run `pip install ddgs sqlalchemy pgvector pypdf openai ollama` to install dependencies."""
from agno.agent import Agent
from agno.knowledge.embedder.ollama import OllamaEmbedder
from agno.knowledge.knowledge import Knowledge
from agno.models.ollama import Ollama
from agno.vectordb.pgvector import PgVector
db_url =... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/ollama/demo_phi4.py | cookbook/11_models/ollama/demo_phi4.py | from agno.agent import Agent, RunOutput # noqa
from agno.models.ollama import Ollama
agent = Agent(model=Ollama(id="phi4"), markdown=True)
# Print the response in the terminal
agent.print_response("Tell me a scary story in exactly 10 words.")
| python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/ollama/reasoning_agent.py | cookbook/11_models/ollama/reasoning_agent.py | from agno.agent import Agent
from agno.models.ollama import Ollama
reasoning_agent = Agent(
model=Ollama(id="gpt-oss:120b"),
reasoning=True,
debug_mode=True,
)
reasoning_agent.print_response(
"How many r are in the word 'strawberry'?", show_reasoning=True
)
| python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/ollama/tool_use.py | cookbook/11_models/ollama/tool_use.py | """Run `pip install ddgs` to install dependencies."""
from agno.agent import Agent
from agno.models.ollama import Ollama
from agno.tools.duckduckgo import DuckDuckGoTools
agent = Agent(
model=Ollama(id="llama3.2:latest"),
tools=[DuckDuckGoTools()],
markdown=True,
)
agent.print_response("Whats happening in... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/ollama/basic.py | cookbook/11_models/ollama/basic.py | from agno.agent import Agent, RunOutput # noqa
from agno.models.ollama import Ollama
agent = Agent(model=Ollama(id="llama3.1:8b"), markdown=True)
# Get the response in a variable
# run: RunOutput = agent.run("Share a 2 sentence horror story")
# print(run.content)
# Print the response in the terminal
agent.print_res... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/ollama/async_basic_stream.py | cookbook/11_models/ollama/async_basic_stream.py | import asyncio
from typing import Iterator # noqa
from agno.agent import Agent, RunOutput # noqa
from agno.models.ollama import Ollama
agent = Agent(model=Ollama(id="llama3.1:8b"), markdown=True)
# Get the response in a variable
# run_response: Iterator[RunOutputEvent] = agent.run("Share a 2 sentence horror story"... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/ollama/set_temperature.py | cookbook/11_models/ollama/set_temperature.py | from agno.agent import Agent, RunOutput # noqa
from agno.models.ollama import Ollama
agent = Agent(model=Ollama(id="llama3.2", options={"temperature": 0.5}), markdown=True)
# Get the response in a variable
# run: RunOutput = agent.run("Share a 2 sentence horror story")
# print(run.content)
# Print the response in t... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/ollama/set_client.py | cookbook/11_models/ollama/set_client.py | """Run `pip install yfinance` to install dependencies."""
from agno.agent import Agent, RunOutput # noqa
from agno.models.ollama import Ollama
from ollama import Client as OllamaClient
agent = Agent(
model=Ollama(id="llama3.1:8b", client=OllamaClient()),
markdown=True,
)
# Print the response in the terminal... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/ollama/retry.py | cookbook/11_models/ollama/retry.py | """Example demonstrating how to set up retries with Ollama."""
from agno.agent import Agent
from agno.models.ollama import Ollama
# We will use a deliberately wrong model ID, to trigger retries.
wrong_model_id = "ollama-wrong-id"
agent = Agent(
model=Ollama(
id=wrong_model_id,
retries=3, # Numbe... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/ollama/__init__.py | cookbook/11_models/ollama/__init__.py | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false | |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/ollama/demo_deepseek_r1.py | cookbook/11_models/ollama/demo_deepseek_r1.py | from agno.agent import Agent, RunOutput # noqa
from agno.models.ollama import Ollama
agent = Agent(model=Ollama(id="deepseek-r1:14b"), markdown=True)
# Print the response in the terminal
agent.print_response(
"Write me python code to solve quadratic equations. Explain your reasoning."
)
| python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/ollama/structured_output.py | cookbook/11_models/ollama/structured_output.py | from typing import List
from agno.agent import Agent, RunOutput # noqa
from agno.models.ollama import Ollama
from pydantic import BaseModel, Field
from rich.pretty import pprint # noqa
class MovieScript(BaseModel):
name: str = Field(..., description="Give a name to this movie")
setting: str = Field(
... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/ollama/ollama_cloud.py | cookbook/11_models/ollama/ollama_cloud.py | """To use Ollama Cloud, you need to set the OLLAMA_API_KEY environment variable. Host is set to https://ollama.com by default."""
from agno.agent import Agent
from agno.models.ollama import Ollama
agent = Agent(
model=Ollama(id="gpt-oss:120b-cloud"),
)
agent.print_response("What is the capital of France?", strea... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/ollama/async_basic.py | cookbook/11_models/ollama/async_basic.py | import asyncio
from agno.agent import Agent
from agno.models.ollama import Ollama
agent = Agent(
model=Ollama(id="llama3.1:8b"),
description="You help people with their health and fitness goals.",
instructions=["Recipes should be under 5 ingredients"],
)
# -*- Print a response to the cli
asyncio.run(agent... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/litellm_openai/basic_stream.py | cookbook/11_models/litellm_openai/basic_stream.py | from agno.agent import Agent, RunOutput # noqa
from agno.models.litellm import LiteLLMOpenAI
agent = Agent(model=LiteLLMOpenAI(id="gpt-4o"), markdown=True)
# Get the response in a variable
# run: RunOutput = agent.run("Share a 2 sentence horror story")
# print(run.content)
# Print the response in the terminal
agent... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/litellm_openai/audio_input_agent.py | cookbook/11_models/litellm_openai/audio_input_agent.py | """
Please first install litellm[proxy] by running: pip install 'litellm[proxy]'
Before running this script, you need to start the LiteLLM server:
litellm --model gpt-4o-audio-preview --host 127.0.0.1 --port 4000
"""
import requests
from agno.agent import Agent, RunResponse # noqa
from agno.media import Audio
from ... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/litellm_openai/tool_use.py | cookbook/11_models/litellm_openai/tool_use.py | """Run `pip install ddgs` to install dependencies."""
from agno.agent import Agent
from agno.models.litellm import LiteLLMOpenAI
from agno.tools.duckduckgo import DuckDuckGoTools
agent = Agent(
model=LiteLLMOpenAI(id="gpt-4o"),
tools=[DuckDuckGoTools()],
markdown=True,
)
agent.print_response("Whats happen... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/litellm_openai/basic.py | cookbook/11_models/litellm_openai/basic.py | from agno.agent import Agent, RunOutput # noqa
from agno.models.litellm import LiteLLMOpenAI
agent = Agent(model=LiteLLMOpenAI(id="gpt-4o"), markdown=True)
# Get the response in a variable
# run: RunOutput = agent.run("Share a 2 sentence horror story")
# print(run.content)
# Print the response in the terminal
agent... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/litellm_openai/__init__.py | cookbook/11_models/litellm_openai/__init__.py | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false | |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/vllm/tool_use_stream.py | cookbook/11_models/vllm/tool_use_stream.py | """Build a Web Search Agent using xAI."""
from agno.agent import Agent
from agno.models.vllm import VLLM
from agno.tools.duckduckgo import DuckDuckGoTools
agent = Agent(
model=VLLM(
id="NousResearch/Nous-Hermes-2-Mistral-7B-DPO", top_k=20, enable_thinking=False
),
tools=[DuckDuckGoTools()],
ma... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/vllm/memory.py | cookbook/11_models/vllm/memory.py | """
Personalized memory and session summaries with vLLM.
Prerequisites:
1. Start a Postgres + pgvector container (helper script is provided):
./cookbook/scripts/run_pgvector.sh
2. Install dependencies:
pip install sqlalchemy 'psycopg[binary]' pgvector
3. Run a vLLM server (any open model). Example with P... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/vllm/db.py | cookbook/11_models/vllm/db.py | """Run `pip install sqlalchemy` and ensure Postgres is running (`./cookbook/scripts/run_pgvector.sh`)."""
from agno.agent import Agent
from agno.db.postgres import PostgresDb
from agno.models.vllm import VLLM
from agno.tools.duckduckgo import DuckDuckGoTools
# Setup the database
db_url = "postgresql+psycopg://ai:ai@l... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/vllm/async_tool_use.py | cookbook/11_models/vllm/async_tool_use.py | """Run `pip install ddgs` to install dependencies."""
import asyncio
from agno.agent import Agent
from agno.models.vllm import VLLM
from agno.tools.duckduckgo import DuckDuckGoTools
agent = Agent(
model=VLLM(id="Qwen/Qwen2.5-7B-Instruct", top_k=20, enable_thinking=False),
tools=[DuckDuckGoTools()],
markd... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/vllm/basic_stream.py | cookbook/11_models/vllm/basic_stream.py | from agno.agent import Agent
from agno.models.vllm import VLLM
agent = Agent(
model=VLLM(id="Qwen/Qwen2.5-7B-Instruct", top_k=20, enable_thinking=False),
markdown=True,
)
agent.print_response("Share a 2 sentence horror story", stream=True)
| python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/vllm/code_generation.py | cookbook/11_models/vllm/code_generation.py | """Code generation example with DeepSeek-Coder.
Run vLLM model: vllm serve deepseek-ai/deepseek-coder-6.7b-instruct \
--dtype float32 \
--tool-call-parser pythonic
"""
from agno.agent import Agent
from agno.models.vllm import VLLM
agent = Agent(
model=VLLM(id="deepseek-ai/deepseek-coder-6.7b-instr... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/vllm/tool_use.py | cookbook/11_models/vllm/tool_use.py | """Build a Web Search Agent using xAI."""
from agno.agent import Agent
from agno.models.vllm import VLLM
from agno.tools.duckduckgo import DuckDuckGoTools
agent = Agent(
model=VLLM(
id="NousResearch/Nous-Hermes-2-Mistral-7B-DPO", top_k=20, enable_thinking=False
),
tools=[DuckDuckGoTools()],
ma... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/vllm/basic.py | cookbook/11_models/vllm/basic.py | from agno.agent import Agent
from agno.models.vllm import VLLM
agent = Agent(
model=VLLM(id="Qwen/Qwen2.5-7B-Instruct", top_k=20, enable_thinking=False),
markdown=True,
)
agent.print_response("Share a 2 sentence horror story")
| python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/vllm/async_basic_stream.py | cookbook/11_models/vllm/async_basic_stream.py | import asyncio
from agno.agent import Agent
from agno.models.vllm import VLLM
agent = Agent(model=VLLM(id="Qwen/Qwen2.5-7B-Instruct"), markdown=True)
asyncio.run(agent.aprint_response("Share a 2 sentence horror story", stream=True))
| python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/vllm/retry.py | cookbook/11_models/vllm/retry.py | """Example demonstrating how to set up retries with vLLM."""
from agno.agent import Agent
from agno.models.vllm import vLLM
# We will use a deliberately wrong model ID, to trigger retries.
wrong_model_id = "vllm-wrong-id"
agent = Agent(
model=vLLM(
id=wrong_model_id,
retries=3, # Number of times... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/vllm/__init__.py | cookbook/11_models/vllm/__init__.py | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false | |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/vllm/structured_output.py | cookbook/11_models/vllm/structured_output.py | from typing import List
from agno.agent import Agent
from agno.models.vllm import VLLM
from pydantic import BaseModel, Field
class MovieScript(BaseModel):
name: str = Field(..., description="Give a name to this movie")
setting: str = Field(
..., description="Provide a nice setting for a blockbuster m... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/vllm/async_basic.py | cookbook/11_models/vllm/async_basic.py | import asyncio
from agno.agent import Agent
from agno.models.vllm import VLLM
agent = Agent(model=VLLM(id="Qwen/Qwen2.5-7B-Instruct"), markdown=True)
asyncio.run(agent.aprint_response("Share a 2 sentence horror story"))
| python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/nexus/tool_use_stream.py | cookbook/11_models/nexus/tool_use_stream.py | """Run `pip install ddgs` to install dependencies."""
from agno.agent import Agent
from agno.models.nexus import Nexus
from agno.tools.duckduckgo import DuckDuckGoTools
agent = Agent(
model=Nexus(id="anthropic/claude-sonnet-4-20250514"),
tools=[DuckDuckGoTools()],
markdown=True,
)
agent.print_response("W... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/nexus/async_tool_use.py | cookbook/11_models/nexus/async_tool_use.py | """
Async example using Nexus with tool calls
"""
import asyncio
from agno.agent import Agent
from agno.models.nexus import Nexus
from agno.tools.duckduckgo import DuckDuckGoTools
agent = Agent(
model=Nexus(id="anthropic/claude-sonnet-4-20250514"),
tools=[DuckDuckGoTools()],
markdown=True,
)
asyncio.run... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/nexus/basic_stream.py | cookbook/11_models/nexus/basic_stream.py | from agno.agent import Agent, RunOutputEvent # noqa
from agno.models.nvidia import Nvidia
agent = Agent(model=Nvidia(id="meta/llama-3.3-70b-instruct"), markdown=True)
# Get the response in a variable
# run_response: Iterator[RunOutputEvent] = agent.run("Share a 2 sentence horror story", stream=True)
# for chunk in r... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/nexus/async_tool_use_stream.py | cookbook/11_models/nexus/async_tool_use_stream.py | """
Async example using Nexus with tool call streaming.
"""
import asyncio
from agno.agent import Agent
from agno.models.nexus import Nexus
from agno.tools.duckduckgo import DuckDuckGoTools
agent = Agent(
model=Nexus(id="anthropic/claude-sonnet-4-20250514"),
tools=[DuckDuckGoTools()],
markdown=True,
)
a... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/nexus/tool_use.py | cookbook/11_models/nexus/tool_use.py | """Run `pip install ddgs` to install dependencies."""
from agno.agent import Agent
from agno.models.nexus import Nexus
from agno.tools.duckduckgo import DuckDuckGoTools
agent = Agent(
model=Nexus(id="anthropic/claude-sonnet-4-20250514"),
tools=[DuckDuckGoTools()],
markdown=True,
)
agent.print_response("W... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/11_models/nexus/basic.py | cookbook/11_models/nexus/basic.py | from agno.agent import Agent, RunOutput # noqa
from agno.models.nexus import Nexus
agent = Agent(model=Nexus(id="anthropic/claude-sonnet-4-20250514"), markdown=True)
# Get the response in a variable
# run: RunOutput = agent.run("Share a 2 sentence horror story")
# print(run.content)
# Print the response in the term... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
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