repo stringlengths 7 90 | file_url stringlengths 81 315 | file_path stringlengths 4 228 | content stringlengths 0 32.8k | language stringclasses 1
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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/10_reasoning/models/azure_ai_foundry/reasoning_model_stream_deepseek.py | cookbook/10_reasoning/models/azure_ai_foundry/reasoning_model_stream_deepseek.py | import asyncio
import os
from agno.agent import Agent
from agno.models.azure import AzureAIFoundry
from agno.run.agent import RunEvent # noqa
async def streaming_reasoning():
"""Test streaming reasoning with a Azure AI Foundry DeepSeek model."""
# Create an agent with reasoning enabled
agent = 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/10_reasoning/models/azure_ai_foundry/__init__.py | cookbook/10_reasoning/models/azure_ai_foundry/__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/10_reasoning/models/azure_ai_foundry/reasoning_model_deepseek.py | cookbook/10_reasoning/models/azure_ai_foundry/reasoning_model_deepseek.py | import os
from agno.agent import Agent
from agno.models.azure import AzureAIFoundry
agent = Agent(
model=AzureAIFoundry(id="gpt-4o"),
reasoning=True,
reasoning_model=AzureAIFoundry(
id="DeepSeek-R1",
azure_endpoint=os.getenv("AZURE_ENDPOINT"),
api_key=os.getenv("AZURE_API_KEY"),
... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/10_reasoning/models/xai/reasoning_effort.py | cookbook/10_reasoning/models/xai/reasoning_effort.py | from agno.agent import Agent
from agno.models.xai import xAI
from agno.tools.yfinance import YFinanceTools
agent = Agent(
model=xAI(id="grok-3-mini-fast", reasoning_effort="high"),
tools=[YFinanceTools()],
instructions="Use tables to display data.",
markdown=True,
)
agent.print_response("Write a report... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/10_reasoning/models/xai/__init__.py | cookbook/10_reasoning/models/xai/__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/10_reasoning/models/groq/9_11_or_9_9.py | cookbook/10_reasoning/models/groq/9_11_or_9_9.py | from agno.agent import Agent
from agno.models.groq import Groq
agent = Agent(
model=Groq(
id="deepseek-r1-distill-llama-70b", temperature=0.6, max_tokens=1024, top_p=0.95
),
markdown=True,
)
agent.print_response("9.11 and 9.9 -- which is bigger?", 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/10_reasoning/models/groq/fast_reasoning.py | cookbook/10_reasoning/models/groq/fast_reasoning.py | """Fast Reasoning with Groq.
This example demonstrates Groq's ultra-fast reasoning capabilities with
DeepSeek-R1 and other reasoning models.
Requirements:
pip install agno groq
Environment:
export GROQ_API_KEY="gsk_..."
Usage:
python cookbook/reasoning/models/groq/fast_reasoning.py
What to expect:
... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/10_reasoning/models/groq/__init__.py | cookbook/10_reasoning/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/10_reasoning/models/groq/deepseek_plus_claude.py | cookbook/10_reasoning/models/groq/deepseek_plus_claude.py | from agno.agent import Agent
from agno.models.anthropic import Claude
from agno.models.groq import Groq
deepseek_plus_claude = Agent(
model=Claude(id="claude-3-7-sonnet-20250219"),
reasoning_model=Groq(
id="deepseek-r1-distill-llama-70b", temperature=0.6, max_tokens=1024, top_p=0.95
),
)
deepseek_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/10_reasoning/models/ollama/local_reasoning.py | cookbook/10_reasoning/models/ollama/local_reasoning.py | """Local Reasoning with Ollama.
This example demonstrates privacy-first reasoning using locally-run models
with Ollama. No data leaves your machine.
Requirements:
pip install agno ollama
# Install Ollama: https://ollama.ai
ollama pull qwq:32b
ollama pull deepseek-r1:8b
Usage:
python cookbook/reas... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/10_reasoning/models/ollama/__init__.py | cookbook/10_reasoning/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/10_reasoning/models/ollama/reasoning_model_deepseek.py | cookbook/10_reasoning/models/ollama/reasoning_model_deepseek.py | from agno.agent import Agent
from agno.models.ollama.chat import Ollama
agent = Agent(
model=Ollama(id="llama3.2:latest"),
reasoning_model=Ollama(id="deepseek-r1:14b", max_tokens=4096),
)
agent.print_response(
"Solve the trolley problem. Evaluate multiple ethical frameworks. "
"Include an ASCII diagram... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/10_reasoning/models/azure_openai/basic_reasoning_stream.py | cookbook/10_reasoning/models/azure_openai/basic_reasoning_stream.py | import asyncio
from agno.agent import Agent
from agno.models.azure.openai_chat import AzureOpenAI
from agno.run.agent import RunEvent # noqa
async def streaming_reasoning():
"""Test streaming reasoning with a Azure OpenAI model."""
# Create an agent with reasoning enabled
agent = Agent(
reasonin... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/10_reasoning/models/azure_openai/o1.py | cookbook/10_reasoning/models/azure_openai/o1.py | from agno.agent import Agent
from agno.models.azure.openai_chat import AzureOpenAI
agent = Agent(model=AzureOpenAI(id="o1"))
agent.print_response(
"Solve the trolley problem. Evaluate multiple ethical frameworks. "
"Include an ASCII diagram of your solution.",
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/10_reasoning/models/azure_openai/o3_mini_with_tools.py | cookbook/10_reasoning/models/azure_openai/o3_mini_with_tools.py | from agno.agent import Agent
from agno.models.azure.openai_chat import AzureOpenAI
from agno.tools.yfinance import YFinanceTools
agent = Agent(
model=AzureOpenAI(id="o3-mini"),
tools=[YFinanceTools()],
instructions="Use tables to display data.",
markdown=True,
)
agent.print_response("Write a report com... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/10_reasoning/models/azure_openai/reasoning_model_gpt_4_1.py | cookbook/10_reasoning/models/azure_openai/reasoning_model_gpt_4_1.py | from agno.agent import Agent
from agno.models.azure.openai_chat import AzureOpenAI
agent = Agent(
model=AzureOpenAI(id="gpt-4o-mini"), reasoning_model=AzureOpenAI(id="gpt-4.1")
)
agent.print_response(
"Solve the trolley problem. Evaluate multiple ethical frameworks. "
"Include an ASCII diagram of your solu... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/10_reasoning/models/azure_openai/o4_mini.py | cookbook/10_reasoning/models/azure_openai/o4_mini.py | from agno.agent import Agent
from agno.models.azure.openai_chat import AzureOpenAI
agent = Agent(model=AzureOpenAI(id="o4-mini"))
agent.print_response(
"Solve the trolley problem. Evaluate multiple ethical frameworks. "
"Include an ASCII diagram of your solution.",
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/10_reasoning/models/azure_openai/__init__.py | cookbook/10_reasoning/models/azure_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/10_reasoning/models/anthropic/basic_reasoning_stream.py | cookbook/10_reasoning/models/anthropic/basic_reasoning_stream.py | """
Test script for streaming reasoning content.
This demonstrates the new streaming reasoning feature where reasoning content
is streamed as it arrives instead of all at once.
"""
from agno.agent import Agent
from agno.models.anthropic import Claude
from agno.run.agent import RunEvent # noqa
# Create an agent 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/10_reasoning/models/anthropic/async_reasoning_stream.py | cookbook/10_reasoning/models/anthropic/async_reasoning_stream.py | """
Test script for streaming reasoning content.
This demonstrates the new streaming reasoning feature where reasoning content
is streamed as it arrives instead of all at once.
"""
import asyncio
from agno.agent import Agent
from agno.models.anthropic import Claude
from agno.run.agent import RunEvent # noqa
async... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/10_reasoning/models/anthropic/__init__.py | cookbook/10_reasoning/models/anthropic/__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/10_reasoning/models/anthropic/basic_reasoning.py | cookbook/10_reasoning/models/anthropic/basic_reasoning.py | """Basic Anthropic Claude Reasoning Example.
This cookbook demonstrates how to use Anthropic Claude with extended thinking support.
Requirements:
pip install agno anthropic
Environment:
export ANTHROPIC_API_KEY="sk-ant-..."
What to expect:
- Claude will use extended thinking to solve the problem
- ... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/10_reasoning/models/deepseek/finance_agent.py | cookbook/10_reasoning/models/deepseek/finance_agent.py | from agno.agent import Agent
from agno.models.deepseek import DeepSeek
from agno.models.openai import OpenAIChat
from agno.tools.yfinance import YFinanceTools
reasoning_agent = Agent(
model=OpenAIChat(id="gpt-4o"),
tools=[YFinanceTools()],
instructions=["Use tables where possible"],
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/10_reasoning/models/deepseek/ethical_dilemma.py | cookbook/10_reasoning/models/deepseek/ethical_dilemma.py | from agno.agent import Agent
from agno.models.deepseek import DeepSeek
from agno.models.openai import OpenAIChat
task = (
"You are a train conductor faced with an emergency: the brakes have failed, and the train is heading towards "
"five people tied on the track. You can divert the train onto another track, b... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/10_reasoning/models/deepseek/fibonacci.py | cookbook/10_reasoning/models/deepseek/fibonacci.py | from agno.agent import Agent
from agno.models.deepseek import DeepSeek
from agno.models.openai import OpenAIChat
task = "Give me steps to write a python script for fibonacci series"
reasoning_agent = Agent(
model=OpenAIChat(id="gpt-4o"),
reasoning_model=DeepSeek(id="deepseek-reasoner"),
markdown=True,
)
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/10_reasoning/models/deepseek/analyse_treaty_of_versailles.py | cookbook/10_reasoning/models/deepseek/analyse_treaty_of_versailles.py | from agno.agent import Agent
from agno.models.deepseek import DeepSeek
from agno.models.openai import OpenAIChat
task = (
"Analyze the key factors that led to the signing of the Treaty of Versailles in 1919. "
"Discuss the political, economic, and social impacts of the treaty on Germany and how it "
"contr... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/10_reasoning/models/deepseek/9_11_or_9_9.py | cookbook/10_reasoning/models/deepseek/9_11_or_9_9.py | from agno.agent import Agent
from agno.cli.console import console
from agno.models.anthropic import Claude
from agno.models.deepseek import DeepSeek
from agno.models.openai import OpenAIChat
task = "9.11 and 9.9 -- which is bigger?"
regular_agent_claude = Agent(model=Claude("claude-3-5-sonnet-20241022"))
reasoning_ag... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/10_reasoning/models/deepseek/ship_of_theseus.py | cookbook/10_reasoning/models/deepseek/ship_of_theseus.py | from agno.agent import Agent
from agno.models.deepseek import DeepSeek
from agno.models.openai import OpenAIChat
task = (
"Discuss the concept of 'The Ship of Theseus' and its implications on the notions of identity and change. "
"Present arguments for and against the idea that an object that has had all of it... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/10_reasoning/models/deepseek/python_101_curriculum.py | cookbook/10_reasoning/models/deepseek/python_101_curriculum.py | from agno.agent import Agent
from agno.models.deepseek import DeepSeek
from agno.models.openai import OpenAIChat
task = "Craft a curriculum for Python 101"
reasoning_agent = Agent(
model=OpenAIChat(id="gpt-4o"),
reasoning_model=DeepSeek(id="deepseek-reasoner"),
markdown=True,
)
reasoning_agent.print_respo... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/10_reasoning/models/deepseek/strawberry.py | cookbook/10_reasoning/models/deepseek/strawberry.py | import asyncio
from agno.agent import Agent
from agno.cli.console import console
from agno.models.deepseek import DeepSeek
from agno.models.openai import OpenAIChat
task = "How many 'r' are in the word 'strawberry'?"
regular_agent = Agent(model=OpenAIChat(id="gpt-4o"), markdown=True)
reasoning_agent = Agent(
mod... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/10_reasoning/models/deepseek/trolley_problem.py | cookbook/10_reasoning/models/deepseek/trolley_problem.py | from agno.agent import Agent
from agno.models.deepseek import DeepSeek
from agno.models.openai import OpenAIChat
task = (
"You are a philosopher tasked with analyzing the classic 'Trolley Problem'. In this scenario, a runaway trolley "
"is barreling down the tracks towards five people who are tied up and unabl... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/10_reasoning/models/deepseek/logical_puzzle.py | cookbook/10_reasoning/models/deepseek/logical_puzzle.py | from agno.agent import Agent
from agno.models.deepseek import DeepSeek
from agno.models.openai import OpenAIChat
task = (
"Three missionaries and three cannibals need to cross a river. "
"They have a boat that can carry up to two people at a time. "
"If, at any time, the cannibals outnumber the missionarie... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/10_reasoning/models/deepseek/scientific_research.py | cookbook/10_reasoning/models/deepseek/scientific_research.py | from agno.agent import Agent
from agno.models.deepseek import DeepSeek
from agno.models.openai import OpenAIChat
task = (
"Read the following abstract of a scientific paper and provide a critical evaluation of its methodology,"
"results, conclusions, and any potential biases or flaws:\n\n"
"Abstract: This ... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/10_reasoning/models/deepseek/life_in_500000_years.py | cookbook/10_reasoning/models/deepseek/life_in_500000_years.py | from agno.agent import Agent
from agno.models.deepseek import DeepSeek
from agno.models.openai import OpenAIChat
task = "Write a short story about life in 500000 years"
reasoning_agent = Agent(
model=OpenAIChat(id="gpt-4o"),
reasoning_model=DeepSeek(id="deepseek-reasoner"),
markdown=True,
)
reasoning_agen... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/10_reasoning/models/deepseek/__init__.py | cookbook/10_reasoning/models/deepseek/__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/10_reasoning/models/deepseek/mathematical_proof.py | cookbook/10_reasoning/models/deepseek/mathematical_proof.py | from agno.agent import Agent
from agno.models.deepseek import DeepSeek
from agno.models.openai import OpenAIChat
task = "Prove that for any positive integer n, the sum of the first n odd numbers is equal to n squared. Provide a detailed proof."
reasoning_agent = Agent(
model=OpenAIChat(id="gpt-4o"),
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/10_reasoning/models/deepseek/plan_itenerary.py | cookbook/10_reasoning/models/deepseek/plan_itenerary.py | from agno.agent import Agent
from agno.models.deepseek import DeepSeek
from agno.models.openai import OpenAIChat
task = "Plan an itinerary from Los Angeles to Las Vegas"
reasoning_agent = Agent(
model=OpenAIChat(id="gpt-4o"),
reasoning_model=DeepSeek(id="deepseek-reasoner"),
markdown=True,
)
reasoning_age... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/10_reasoning/models/gemini/basic_reasoning_stream.py | cookbook/10_reasoning/models/gemini/basic_reasoning_stream.py | from agno.agent import Agent
from agno.models.google import Gemini
from agno.run.agent import RunEvent # noqa
# Create an agent with reasoning enabled
# Note: For Gemini, you MUST set thinking_budget to enable thinking mode
agent = Agent(
reasoning_model=Gemini(
id="gemini-2.5-flash",
thinking_bud... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/10_reasoning/models/gemini/async_reasoning_stream.py | cookbook/10_reasoning/models/gemini/async_reasoning_stream.py | import asyncio
from agno.agent import Agent
from agno.models.google import Gemini
from agno.run.agent import RunEvent # noqa
async def streaming_reasoning():
"""Test streaming reasoning with a Gemini model."""
# Create an agent with reasoning enabled
# Note: For Gemini, you MUST set thinking_budget to e... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/10_reasoning/models/gemini/__init__.py | cookbook/10_reasoning/models/gemini/__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/10_reasoning/models/gemini/basic_reasoning.py | cookbook/10_reasoning/models/gemini/basic_reasoning.py | """Basic Google Gemini 2.5+ Reasoning Example.
This cookbook demonstrates how to use Google Gemini 2.5+ with thinking support.
Gemini 2.5+ models support reasoning through the thinking_budget parameter.
Requirements:
pip install agno google-generativeai
Environment:
export GOOGLE_API_KEY="AIza..."
Usage:
... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/13_integrations/__init__.py | cookbook/13_integrations/__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/13_integrations/discord/agent_with_media.py | cookbook/13_integrations/discord/agent_with_media.py | from agno.agent import Agent
from agno.integrations.discord import DiscordClient
from agno.models.google import Gemini
media_agent = Agent(
name="Media Agent",
model=Gemini(id="gemini-2.0-flash"),
description="A Media processing agent",
instructions="Analyze images, audios and videos sent by the user",... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/13_integrations/discord/agent_with_user_memory.py | cookbook/13_integrations/discord/agent_with_user_memory.py | from textwrap import dedent
from agno.agent import Agent
from agno.db.sqlite import SqliteDb
from agno.integrations.discord import DiscordClient
from agno.models.google import Gemini
from agno.tools.duckduckgo import DuckDuckGoTools
db = SqliteDb(db_file="tmp/discord_client_cookbook.db")
personal_agent = 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/13_integrations/discord/basic.py | cookbook/13_integrations/discord/basic.py | from agno.agent import Agent
from agno.integrations.discord import DiscordClient
from agno.models.openai import OpenAIChat
basic_agent = Agent(
name="Basic Agent",
model=OpenAIChat(id="gpt-4o"),
add_history_to_context=True,
num_history_runs=3,
add_datetime_to_context=True,
)
discord_agent = Discor... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/13_integrations/discord/__init__.py | cookbook/13_integrations/discord/__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/13_integrations/memory/memori_integration.py | cookbook/13_integrations/memory/memori_integration.py | import os
from agno.agent import Agent
from agno.models.openai import OpenAIChat
from dotenv import load_dotenv
from memori import Memori
from sqlalchemy import create_engine
from sqlalchemy.orm import sessionmaker
load_dotenv()
db_path = os.getenv("DATABASE_PATH", "memori_agno.db")
engine = create_engine(f"sqlite:/... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/13_integrations/memory/zep_integration.py | cookbook/13_integrations/memory/zep_integration.py | import time
from agno.agent import Agent
from agno.models.openai import OpenAIChat
from agno.tools.zep import ZepTools
# Initialize the ZepTools
zep_tools = ZepTools(user_id="agno", session_id="agno-session")
zep_tools.add_zep_message(role="user", content="My name is John Billings")
zep_tools.add_zep_message(role="u... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/13_integrations/memory/__init__.py | cookbook/13_integrations/memory/__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/13_integrations/memory/mem0_integration.py | cookbook/13_integrations/memory/mem0_integration.py | from agno.agent import Agent, RunOutput
from agno.models.openai import OpenAIChat
from agno.utils.pprint import pprint_run_response
try:
from mem0 import MemoryClient
except ImportError:
raise ImportError(
"mem0 is not installed. Please install it using `pip install mem0ai`."
)
client = MemoryClie... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/13_integrations/observability/traceloop_op.py | cookbook/13_integrations/observability/traceloop_op.py | """
Integrate Agno with Traceloop to send traces and gain insights into your agent's performance.
Prerequisites:
- Traceloop account
- Traceloop API key
Steps:
1. `pip install agno openai traceloop-sdk`
2. Set the Traceloop API key as an environment variable: `export TRACELOOP_API_KEY=<your-api-key>`
"""
from agno.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/13_integrations/observability/langfuse_via_openinference_response_model.py | cookbook/13_integrations/observability/langfuse_via_openinference_response_model.py | """
This example shows how to instrument your agno agent with OpenInference and send traces to Langfuse,
using an Agent with a response model.
1. Install dependencies: pip install openai langfuse opentelemetry-sdk opentelemetry-exporter-otlp openinference-instrumentation-agno
2. Either self-host or sign up for an acco... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/13_integrations/observability/arize_phoenix_via_openinference_local.py | cookbook/13_integrations/observability/arize_phoenix_via_openinference_local.py | """
This example shows how to instrument your agno agent with OpenInference and send traces to Arize Phoenix.
1. Install dependencies: pip install arize-phoenix openai openinference-instrumentation-agno opentelemetry-sdk opentelemetry-exporter-otlp
2. Run `phoenix serve` to start the local collector.
"""
import os
f... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/13_integrations/observability/logfire_via_openinference.py | cookbook/13_integrations/observability/logfire_via_openinference.py | """
This example shows how to instrument your agno agent with OpenInference and send traces to Logfire.
Sign up to Logfire at https://logfire.dev
1. Install dependencies: pip install openai langfuse opentelemetry-sdk opentelemetry-exporter-otlp openinference-instrumentation-agno
2. Either self-host or sign up for an ... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/13_integrations/observability/atla_op.py | cookbook/13_integrations/observability/atla_op.py | """
This example shows how to add observability to your agno agent with Atla.
1. Install dependencies: pip install "atla-insights"
2. Sign up for an account at https://app.atla-ai.com
3. Set your Atla Insights API key as an environment variable:
- export ATLA_API_KEY=<your-key>
"""
from os import getenv
from agno.... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/13_integrations/observability/weave_op.py | cookbook/13_integrations/observability/weave_op.py | """
This example shows how to use weave to log model calls.
Steps to get started with weave:
1. Install weave: pip install weave
2. Add weave.init('project-name') and weave.op() decorators to your functions
3. Authentication:
- Go to https://wandb.ai and copy your API key from https://wandb.ai/authorize
- Enter your... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/13_integrations/observability/langfuse_via_openinference.py | cookbook/13_integrations/observability/langfuse_via_openinference.py | """
This example shows how to instrument your agno agent with OpenInference and send traces to Langfuse.
1. Install dependencies: pip install openai langfuse opentelemetry-sdk opentelemetry-exporter-otlp openinference-instrumentation-agno
2. Either self-host or sign up for an account at https://us.cloud.langfuse.com
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/13_integrations/observability/langfuse_via_openlit.py | cookbook/13_integrations/observability/langfuse_via_openlit.py | """
This example shows how to use langfuse via OpenLIT to trace model calls.
1. Install dependencies: pip install openai langfuse openlit opentelemetry-sdk opentelemetry-exporter-otlp
2. Set your Langfuse API key as an environment variables:
- export LANGFUSE_PUBLIC_KEY=<your-key>
- export LANGFUSE_SECRET_KEY=<you... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/13_integrations/observability/arize_phoenix_moving_traces_to_different_projects.py | cookbook/13_integrations/observability/arize_phoenix_moving_traces_to_different_projects.py | """
Send traces from different agents to different Arize Phoenix projects.
1. Install dependencies: pip install arize-phoenix openai openinference-instrumentation-agno opentelemetry-sdk opentelemetry-exporter-otlp
2. Setup your Arize Phoenix account and get your API key: https://phoenix.arize.com/
3. Set your Arize Ph... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/13_integrations/observability/arize_phoenix_via_openinference.py | cookbook/13_integrations/observability/arize_phoenix_via_openinference.py | """
This example shows how to instrument your agno agent with OpenInference and send traces to Arize Phoenix.
1. Install dependencies: pip install arize-phoenix openai openinference-instrumentation-agno opentelemetry-sdk opentelemetry-exporter-otlp
2. Setup your Arize Phoenix account and get your API key: https://phoe... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/13_integrations/observability/langsmith_via_openinference.py | cookbook/13_integrations/observability/langsmith_via_openinference.py | """
This example shows how to instrument your agno agent with OpenInference and send traces to LangSmith.
1. Create a LangSmith account and get your API key: https://smith.langchain.com/
2. Set your LangSmith API key as an environment variable:
- export LANGSMITH_API_KEY=<your-key>
- export LANGSMITH_TRACING=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/13_integrations/observability/agent_ops.py | cookbook/13_integrations/observability/agent_ops.py | """
This example shows how to use agentops to log model calls.
Steps to get started with agentops:
1. Install agentops: pip install agentops
2. Obtain an API key from https://app.agentops.ai/
3. Export environment variables like AGENTOPS_API_KEY and OPENAI_API_KEY.
4. Run the script.
You can view the logs in the Agen... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/13_integrations/observability/trace_to_database.py | cookbook/13_integrations/observability/trace_to_database.py | """
Example demonstrating the two-table trace design with Agno.
This example shows:
1. How traces and spans are stored in separate tables
2. How to query traces (high-level view)
3. How to drill down to spans for a specific trace
4. The hierarchical relationship between traces and spans
Requirements:
pip install ... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/13_integrations/observability/opik_via_openinference.py | cookbook/13_integrations/observability/opik_via_openinference.py | """
Instrument your Agno agents with OpenTelemetry and stream traces to Opik for rich debugging, cost tracking, and production monitoring.
1. Install dependencies:
pip install -U opik agno openai opentelemetry-sdk opentelemetry-exporter-otlp openinference-instrumentation-agno
2. Point the OTLP exporter at the Opik ... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/13_integrations/observability/__init__.py | cookbook/13_integrations/observability/__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/13_integrations/observability/langwatch_op.py | cookbook/13_integrations/observability/langwatch_op.py | """
This example shows how to instrument your agno agent and send traces to LangWatch.
1. Install dependencies: pip install openai langwatch openinference-instrumentation-agno
2. Sign up for an account at https://app.langwatch.ai/
3. Set your LangWatch API key as an environment variables:
- export LANGWATCH_API_KEY=... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/13_integrations/observability/langtrace_op.py | cookbook/13_integrations/observability/langtrace_op.py | """
This example shows how to instrument your agno agent with Langtrace.
1. Install dependencies: pip install langtrace-python-sdk
2. Sign up for an account at https://app.langtrace.ai/
3. Set your Langtrace API key as an environment variables:
- export LANGTRACE_API_KEY=<your-key>
"""
# Must precede other imports
... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/13_integrations/observability/maxim_ops.py | cookbook/13_integrations/observability/maxim_ops.py | """
This example shows how to use Maxim to log agent calls and traces.
Steps to get started with Maxim:
1. Install Maxim: pip install maxim-py
2. Add instrument_agno(Maxim().logger()) to initialize tracing
3. Authentication:
- Go to https://getmaxim.ai and create an account
- Generate your API key from the settings
... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/13_integrations/observability/workflows/arize_phoenix_via_openinference_workflow.py | cookbook/13_integrations/observability/workflows/arize_phoenix_via_openinference_workflow.py | """
This example shows how to instrument your agno agent with OpenInference
and send traces to Arize Phoenix
Install dependencies:
pip install openai opentelemetry-sdk opentelemetry-exporter-otlp
pip install -U openinference-instrumentation-agno arize-phoenix
"""
import os
from agno.agent.agent import Agent
from agn... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/13_integrations/observability/workflows/langfuse_via_openinference_workfows.py | cookbook/13_integrations/observability/workflows/langfuse_via_openinference_workfows.py | """
This example shows how to instrument your agno agent with OpenInference and send traces to Langfuse.
1. Install dependencies: pip install openai langfuse opentelemetry-sdk opentelemetry-exporter-otlp openinference-instrumentation-agno
2. Either self-host or sign up for an account at https://us.cloud.langfuse.com
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/13_integrations/observability/teams/langfuse_via_openinference_team.py | cookbook/13_integrations/observability/teams/langfuse_via_openinference_team.py | import base64
import os
from uuid import uuid4
from agno.agent import Agent
from agno.models.openai import OpenAIChat
from agno.team import Team
from agno.tools.duckduckgo import DuckDuckGoTools
from agno.tools.yfinance import YFinanceTools
from openinference.instrumentation.agno import AgnoInstrumentor
from opentelem... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/13_integrations/observability/teams/langfuse_via_openinference_async_team.py | cookbook/13_integrations/observability/teams/langfuse_via_openinference_async_team.py | import asyncio
import base64
import os
from uuid import uuid4
from agno.agent import Agent
from agno.models.openai import OpenAIChat
from agno.team import Team
from agno.tools.duckduckgo import DuckDuckGoTools
from agno.tools.yfinance import YFinanceTools
from openinference.instrumentation.agno import AgnoInstrumentor... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/13_integrations/observability/teams/__init__.py | cookbook/13_integrations/observability/teams/__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/13_integrations/a2a/__init__.py | cookbook/13_integrations/a2a/__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/13_integrations/a2a/basic_agent/client.py | cookbook/13_integrations/a2a/basic_agent/client.py | from typing import Any
from uuid import uuid4
import httpx
from a2a.client import A2AClient
from a2a.types import (
MessageSendParams,
SendMessageRequest,
SendStreamingMessageRequest, # noqa: F401
)
async def main() -> None:
async with httpx.AsyncClient() as httpx_client:
client = await A2AC... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/13_integrations/a2a/basic_agent/__main__.py | cookbook/13_integrations/a2a/basic_agent/__main__.py | from a2a.server.apps import A2AStarletteApplication
from a2a.server.request_handlers import DefaultRequestHandler
from a2a.server.tasks import InMemoryTaskStore
from a2a.types import (
AgentAuthentication,
AgentCapabilities,
AgentCard,
AgentSkill,
)
from basic_agent import BasicAgentExecutor
if __name_... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/13_integrations/a2a/basic_agent/basic_agent.py | cookbook/13_integrations/a2a/basic_agent/basic_agent.py | from a2a.server.agent_execution import AgentExecutor, RequestContext
from a2a.server.events import EventQueue
from a2a.types import Part, TextPart
from a2a.utils import new_agent_text_message
from agno.agent import Agent, Message, RunOutput
from agno.models.openai import OpenAIChat
from typing_extensions import overrid... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/13_integrations/a2a/basic_agent/__init__.py | cookbook/13_integrations/a2a/basic_agent/__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/02_examples/__init__.py | cookbook/02_examples/__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/02_examples/04_gemini/run.py | cookbook/02_examples/04_gemini/run.py | from pathlib import Path
from agents.creative_studio_agent import creative_studio_agent
from agents.pal_agent import pal_agent
from agents.product_comparison_agent import product_comparison_agent
from agents.self_learning_agent import self_learning_agent
from agents.self_learning_research_agent import self_learning_re... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/02_examples/04_gemini/db.py | cookbook/02_examples/04_gemini/db.py | # ============================================================================
# Configure database for storing agent sessions, memories, metrics, evals and knowledge
# ============================================================================
from agno.db.postgres import PostgresDb
db_url = "postgresql+psycopg://ai... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/02_examples/04_gemini/__init__.py | cookbook/02_examples/04_gemini/__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/02_examples/04_gemini/agents/pal_agent.py | cookbook/02_examples/04_gemini/agents/pal_agent.py | """
PaL — Plan and Learn Agent
===========================
A disciplined planning and execution agent that:
- Creates structured plans with success criteria
- Executes steps sequentially with verification
- Learns from successful executions
- Persists state across sessions
> Plan. Execute. Learn. Repeat.
"""
import j... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/02_examples/04_gemini/agents/simple_research_agent.py | cookbook/02_examples/04_gemini/agents/simple_research_agent.py | from textwrap import dedent
from agno.agent import Agent
from agno.models.google import Gemini
from db import gemini_agents_db
simple_research_agent = Agent(
name="Simple Research Agent",
model=Gemini(
id="gemini-3-flash-preview",
search=True,
),
instructions=dedent("""\
You are 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/02_examples/04_gemini/agents/db.py | cookbook/02_examples/04_gemini/agents/db.py | # ============================================================================
# Configure database for storing agent sessions, memories, metrics, evals and knowledge
# ============================================================================
from agno.db.postgres import PostgresDb
db_url = "postgresql+psycopg://ai... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/02_examples/04_gemini/agents/self_learning_agent.py | cookbook/02_examples/04_gemini/agents/self_learning_agent.py | """
Self-Learning Agent
====================
GPU Poor Continuous Learning: System-level learning without fine-tuning.
The loop:
1. Search knowledge base for relevant learnings
2. Gather fresh information (search, APIs)
3. Synthesize answer using both
4. Identify reusable insight
5. Save with user approval
Built 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/02_examples/04_gemini/agents/creative_studio_agent.py | cookbook/02_examples/04_gemini/agents/creative_studio_agent.py | from pathlib import Path
from textwrap import dedent
from agno.agent import Agent, RunOutput
from agno.models.google import Gemini
from agno.tools.nano_banana import NanoBananaTools
from db import gemini_agents_db
creative_studio_agent = Agent(
name="Creative Studio Agent",
model=Gemini(id="gemini-3-flash-pre... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/02_examples/04_gemini/agents/product_comparison_agent.py | cookbook/02_examples/04_gemini/agents/product_comparison_agent.py | from textwrap import dedent
from agno.agent import Agent
from agno.models.google import Gemini
from db import gemini_agents_db
product_comparison_agent = Agent(
name="Product Comparison Agent",
model=Gemini(
id="gemini-3-flash-preview",
url_context=True,
search=True,
),
instruc... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/02_examples/04_gemini/agents/__init__.py | cookbook/02_examples/04_gemini/agents/__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/02_examples/04_gemini/agents/self_learning_research_agent.py | cookbook/02_examples/04_gemini/agents/self_learning_research_agent.py | import json
from datetime import datetime
from typing import Any, Dict, List, Optional
from agno.agent import Agent
from agno.knowledge.embedder.google import GeminiEmbedder
from agno.knowledge.knowledge import Knowledge
from agno.knowledge.reader.text_reader import TextReader
from agno.models.google import Gemini
fro... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/02_examples/01_agents/agent_with_instructions.py | cookbook/02_examples/01_agents/agent_with_instructions.py | from agno.agent import Agent
from agno.models.anthropic import Claude
from agno.tools.yfinance import YFinanceTools
agent = Agent(
model=Claude(id="claude-3-7-sonnet-latest"),
tools=[YFinanceTools()],
instructions=[
"Use tables to display data.",
"Only include the table in your response. No... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/02_examples/01_agents/shopping_partner.py | cookbook/02_examples/01_agents/shopping_partner.py | from agno.agent import Agent
from agno.models.openai import OpenAIChat
from agno.tools.exa import ExaTools
agent = Agent(
name="shopping partner",
model=OpenAIChat(id="gpt-4o"),
instructions=[
"You are a product recommender agent specializing in finding products that match user preferences.",
... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/02_examples/01_agents/study_partner.py | cookbook/02_examples/01_agents/study_partner.py | from agno.agent import Agent
from agno.models.openai import OpenAIChat
from agno.tools.exa import ExaTools
from agno.tools.youtube import YouTubeTools
study_partner = Agent(
name="StudyScout", # Fixed typo in name
model=OpenAIChat(id="gpt-4o"),
tools=[ExaTools(), YouTubeTools()],
markdown=True,
de... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/02_examples/01_agents/fibonacci_agent.py | cookbook/02_examples/01_agents/fibonacci_agent.py | import json
from agno.agent import Agent
from agno.models.openai import OpenAIChat
from agno.tools.calculator import CalculatorTools
def get_fibonacci_series(count: int = 5) -> str:
"""Generate a Fibonacci series up to the specified count."""
if count <= 0:
return "Count must be a positive integer."
... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/02_examples/01_agents/agent_with_knowledge.py | cookbook/02_examples/01_agents/agent_with_knowledge.py | from agno.agent import Agent
from agno.db.postgres import PostgresDb
from agno.knowledge.embedder.openai import OpenAIEmbedder
from agno.knowledge.knowledge import Knowledge
from agno.models.anthropic import Claude
from agno.vectordb.pgvector import PgVector, SearchType
db_url = "postgresql+psycopg://ai:ai@localhost:5... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/02_examples/01_agents/finance_agent.py | cookbook/02_examples/01_agents/finance_agent.py | """🗞️ Finance Agent - Your Personal Market Analyst!
This example shows how to create a sophisticated financial analyst that provides
comprehensive market insights using real-time data. The agent combines stock market data,
analyst recommendations, company information, and latest news to deliver professional-grade
fin... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/02_examples/01_agents/media_trend_analysis_agent.py | cookbook/02_examples/01_agents/media_trend_analysis_agent.py | """Please install dependencies using:
pip install openai exa-py agno firecrawl
"""
from datetime import datetime, timedelta
from textwrap import dedent
from agno.agent import Agent
from agno.models.openai import OpenAIChat
from agno.tools.exa import ExaTools
from agno.tools.firecrawl import FirecrawlTools
def calcu... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/02_examples/01_agents/meeting_summarizer_agent.py | cookbook/02_examples/01_agents/meeting_summarizer_agent.py | """Example: Meeting Summarizer & Visualizer Agent
This script uses OpenAITools (transcribe_audio, generate_image, generate_speech)
to process a meeting recording, summarize it, visualize it, and create an audio summary.
Requires: pip install openai agno
"""
import base64
from pathlib import Path
from textwrap import... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/02_examples/01_agents/readme_generator.py | cookbook/02_examples/01_agents/readme_generator.py | from agno.agent import Agent
from agno.models.openai import OpenAIChat
from agno.tools.github import GithubTools
from agno.tools.local_file_system import LocalFileSystemTools
readme_gen_agent = Agent(
model=OpenAIChat(id="gpt-4o"),
name="Readme Generator Agent",
tools=[GithubTools(), LocalFileSystemTools()... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
agno-agi/agno | https://github.com/agno-agi/agno/blob/26b9daa0fb760c3ad8384e1ba9218b1bce854535/cookbook/02_examples/01_agents/reasoning_finance_agent.py | cookbook/02_examples/01_agents/reasoning_finance_agent.py | from agno.agent import Agent
from agno.models.anthropic import Claude
from agno.tools.reasoning import ReasoningTools
from agno.tools.yfinance import YFinanceTools
agent = Agent(
model=Claude(id="claude-3-7-sonnet-latest"),
tools=[
ReasoningTools(add_instructions=True),
YFinanceTools(),
],
... | python | Apache-2.0 | 26b9daa0fb760c3ad8384e1ba9218b1bce854535 | 2026-01-04T14:41:49.609528Z | false |
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