Merge branch 'main' into release/v1.10

Author: William Bakst

docs/learn/agents.md

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 # Agents
 
 > __Definition__: a person who acts on behalf of another person or group

docs/learn/async.md

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 # Async
 
 Asynchronous programming is a crucial concept when building applications with LLMs (Large Language Models) using Mirascope. This feature allows for efficient handling of I/O-bound operations (e.g., API calls), improving application responsiveness and scalability. Mirascope utilizes the [asyncio](https://docs.python.org/3/library/asyncio.html) library to implement asynchronous processing.

docs/learn/calls.md

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 # Calls
 
 !!! mira ""

docs/learn/chaining.md

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 # Chaining
 
 !!! mira ""

docs/learn/evals.md

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 # Evals: Evaluating LLM Outputs
 
 !!! mira ""

docs/learn/json_mode.md

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 # JSON Mode
 
 !!! mira ""

docs/learn/output_parsers.md

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 # Output Parsers
 
 !!! mira ""

docs/learn/prompts.md

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 # Prompts
 
 When working with Large Language Model (LLM) APIs, the "prompt" is generally a list of messages where each message has a particular role. These prompts are the foundation of effectively working with LLMs, so Mirascope provides powerful tools to help you create, manage, and optimize your prompts for various LLM interactions.

docs/learn/response_models.md

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 # Response Models
 
 !!! mira ""

docs/learn/retries.md

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 # Retries
 
 Making an API call to a provider can fail due to various reasons, such as rate limits, internal server errors, validation errors, and more. This makes retrying calls extremely important when building robust systems.

docs/learn/streams.md

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 # Streams
 
 !!! mira ""

docs/learn/tools.md

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 # Tools
 
 {% set tool_methods = [["base_tool", "BaseTool"], ["function", "Function"]] %}