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- Implemented a brand validation script to check content against brand guidelines including colors, fonts, tone, and messaging. - Created a comprehensive financial modeling suite with DCF analysis, sensitivity testing, Monte Carlo simulations, and scenario planning. - Added scripts for DCF modeling and sensitivity analysis, including detailed documentation for usage and input requirements. - Included example usage for both brand validation and financial modeling to demonstrate functionality.
31 lines
824 B
TOML
31 lines
824 B
TOML
[project]
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name = "pydantic-ai"
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version = "0.1.0"
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description = "Add your description here"
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readme = "README.md"
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requires-python = ">=3.12"
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dependencies = [
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"ipykernel>=6.29.5",
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"ipywidgets>=8.1.7",
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"pip>=25.1.1",
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"pydantic-ai-slim[duckduckgo,mcp,openai]>=0.2.18",
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"asyncpg>=0.30.0",
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"fastapi>=0.115.4",
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"logfire[asyncpg,fastapi,sqlite3,httpx]>=2.6",
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"python-multipart>=0.0.17",
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"rich>=13.9.2",
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"uvicorn>=0.32.0",
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"devtools>=0.12.2",
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"gradio>=5.9.0; python_version>'3.9'",
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"mcp[cli]>=1.4.1; python_version >= '3.10'",
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"groq>=0.28.0",
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"pydantic-ai-backend>=0.2.11",
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"pydantic-ai-harness[code-mode]",
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"pydantic-ai-shields",
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"pydantic-ai-skills",
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"pydantic-ai-todo",
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"pydantic-deep",
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"subagents-pydantic-ai",
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"summarization-pydantic-ai",
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]
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