تشغيل أي مهارة في Manus بنقرة واحدة

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pydantic-ai

النجوم٢

التفرعات١

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Expert guidance on building agents and tools with Pydantic AI.

التثبيت

التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.

تشغيل في Manus

المصدر

FullFran

FullFran/Hybrid-RAG-example

فتح مستودع GitHub عرض مستودعات المنشئ

تنزيل

تشغيل في Manus

المهن ذات الصلةSOC

استنادا إلى تصنيف SOC المهني

مطوّرو البرمجياتمهن الحاسوب والرياضيات·SOC 15-1252

مستكشف الملفات

2 ملفات

SKILL.md

readonly

name	pydantic-ai
description	Expert guidance on building agents and tools with Pydantic AI.

Pydantic AI Expert Skill

This skill provides patterns for defining agents, dependencies, and tools using Pydantic AI.

🤖 Agent Definition

State Management: Use StateDeps[T] to pass dependencies (DB clients, settings) to agents.
System Prompts: Define complex prompts in src/prompts.py. Use @agent.instructions for dynamic context.
Model Choice: Use OpenAIModel as a base for OpenAI-compatible providers (OpenRouter, Ollama) via OpenAIProvider.

🛠️ Tool Patterns

Return Strings: Agents work best with text. Tools should return formatted strings, not Pydantic objects.
Resource Management: Initialize and cleanup DB connections properly within the tool or via injected deps.
Error Handling: Tools should catch exceptions and return helpful error messages to the agent rather than crashing.

📺 CLI & Streaming

Rich Integration: Use Rich to display real-time streaming of agent output and tool call details.
Node Handling: Implement logic for user_prompt, model_request, call_tools, and end nodes in the CLI.
Transparency: Always show the user which tool is being called and with what parameters.

المزيد من هذا المستودع

نفس المستودع

architecture-decision-record

FullFran/Hybrid-RAG-example

Help the team document and maintain Architecture Decision Records (ADRs).

2026-02-022

docling

FullFran/Hybrid-RAG-example

Expert guidance on document processing with Docling and audio transcription with Whisper.

2026-02-022

docs-standard

FullFran/Hybrid-RAG-example

Standard for creating technical documentation in this repository. Use this when writing new documentation in docs/ to ensure consistent hierarchy and formatting.

2026-02-022

mermaid-diagrams

FullFran/Hybrid-RAG-example

Expert guidance on creating accurate, visually polished Mermaid diagrams for architecture documentation.

2026-02-022

mongodb

FullFran/Hybrid-RAG-example

Expert guidance on MongoDB implementation for RAG, including aggregation pipelines and search patterns.

2026-02-022

python-async-patterns

FullFran/Hybrid-RAG-example

Best practices for async Python code, avoiding common pitfalls like await precedence bugs and sync-in-async anti-patterns.

2026-02-022

name	pydantic-ai
description	Expert guidance on building agents and tools with Pydantic AI.

Pydantic AI Expert Skill

This skill provides patterns for defining agents, dependencies, and tools using Pydantic AI.

🤖 Agent Definition

State Management: Use StateDeps[T] to pass dependencies (DB clients, settings) to agents.
System Prompts: Define complex prompts in src/prompts.py. Use @agent.instructions for dynamic context.
Model Choice: Use OpenAIModel as a base for OpenAI-compatible providers (OpenRouter, Ollama) via OpenAIProvider.

🛠️ Tool Patterns

Return Strings: Agents work best with text. Tools should return formatted strings, not Pydantic objects.
Resource Management: Initialize and cleanup DB connections properly within the tool or via injected deps.
Error Handling: Tools should catch exceptions and return helpful error messages to the agent rather than crashing.

📺 CLI & Streaming

Rich Integration: Use Rich to display real-time streaming of agent output and tool call details.
Node Handling: Implement logic for user_prompt, model_request, call_tools, and end nodes in the CLI.
Transparency: Always show the user which tool is being called and with what parameters.