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https://github.com/agno-agi/agno.git
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Ashpreet
c7c5adcc60
## Summary Overhauls `cookbook/00_quickstart` into a coherent capability ladder: build one useful agent, add context and learning, introduce safety and human approval, then scale to teams, workflows, and AgentOS. - Upgrades every active quickstart model to the stable `gemini-3.6-flash` ID. - Repositions the README around **Build an Agent That Can Act, Remember, and Improve**, with a minimal first success and clear Core → Context → Trust → Scale → Ship progression. - Replaces the hand-built self-learning demo with the canonical `LearningMachine` and shared learned knowledge. - Fixes misleading guardrail status handling, structured-output truth claims, optional-value handling, and cross-session memory behavior. - Gives each stateful example isolated SQLite/Chroma storage and stable session IDs. - Makes knowledge deterministic with a versioned local fixture. - Reworks human approval to verify both approve and reject paths. - Narrows tool exposure, refreshes AgentOS prompts/registration, and regenerates a lean Agno 2.8 dependency lock. - Adds a repeatable live test plan and preserves the historical Gemini 3.5 verification record. This makes the folder useful as both a newcomer journey and a set of standalone, copyable agent patterns. ## Type of change - [x] Bug fix - [ ] New feature - [ ] Breaking change - [x] Improvement - [x] Model update - [ ] Other: --- ## Checklist - [x] Code complies with style guidelines - [x] Ran format/validation scripts (`./scripts/format.sh` and `./scripts/validate.sh`) - [x] Self-review completed - [x] Documentation updated (comments, docstrings) - [x] Examples and guides: Relevant cookbook examples have been included or updated (if applicable) - [x] Tested in clean environment - [x] Tests added/updated (if applicable) ### Duplicate and AI-Generated PR Check - [x] I have searched existing [open pull requests](../../pulls) and confirmed that no other PR already addresses this issue - [x] If a similar PR exists, I have explained below why this PR is a better approach - [x] Check if this PR was entirely AI-generated (by Copilot, Claude Code, Cursor, etc.) --- ## Additional Notes Validation completed against Agno `2.8.0`, `google-genai==2.14.0`, and Gemini 3.6 Flash: - 12/12 quickstart cookbooks passed live behavioral checks. - AgentOS passed with 10 agents, 1 team, and 1 workflow; `/health` and `/config` returned successfully. - Approval/rejection, guardrail failure paths, cross-session memory, and process-restart persistence passed. - Focused unit suite: 82 passed, 1 skipped. - `./scripts/format.sh`, `./scripts/validate.sh`, `compileall`, cookbook pattern checks, and `git diff --check` passed. - An independent final diff review found no remaining correctness issues. The global Gemini framework default is intentionally unchanged; this PR only updates the quickstart folder. Historical Gemini 3.5 results remain in `TEST_LOG.md` under a clearly labeled historical section. Prepared with Codex under user direction and validated with live model calls plus repository gates.
69 lines
2.2 KiB
Python
69 lines
2.2 KiB
Python
"""
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Agent with Tools - Your First Useful Agent
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===========================================
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Start here. This example combines the three pieces of an Agno agent:
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1. A model that reasons about the request
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2. Instructions that define good work
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3. Tools that let the agent act on live data
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The agent uses Yahoo Finance to turn a plain-English question into tool calls
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and a current market brief.
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Example prompts to try:
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- "What's the current price of AAPL?"
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- "Compare NVDA and AMD"
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- "Give me a quick market brief on Microsoft"
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"""
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from agno.agent import Agent
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from agno.models.google import Gemini
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from agno.tools.yfinance import YFinanceTools
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# ---------------------------------------------------------------------------
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# Create the Agent
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# ---------------------------------------------------------------------------
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agent_with_tools = Agent(
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name="Agent with Tools",
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model=Gemini(id="gemini-3.6-flash"),
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instructions=[
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"Use Yahoo Finance for facts that can change.",
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"Lead with the answer, then show the evidence.",
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"Use a table when comparing companies.",
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"Say when data is unavailable; never invent a value.",
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"Keep the response concise and do not give personalized financial advice.",
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],
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tools=[
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YFinanceTools(
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enable_company_info=True,
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enable_stock_fundamentals=True,
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enable_company_news=True,
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)
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],
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add_datetime_to_context=True,
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markdown=True,
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)
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# ---------------------------------------------------------------------------
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# Run the Agent
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# ---------------------------------------------------------------------------
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if __name__ == "__main__":
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agent_with_tools.print_response(
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"Give me a quick market brief on NVIDIA",
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stream=True,
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)
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# ---------------------------------------------------------------------------
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# More Examples
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# ---------------------------------------------------------------------------
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"""
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Swap the prompt and run the file again:
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- Single company: "What is Apple's current valuation?"
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- Comparison: "Compare Google and Microsoft"
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- Sector: "Show key metrics for NVDA, AMD, GOOGL, and MSFT"
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The same Agent object can be reused for every request. Do not create agents
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inside a loop.
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"""
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