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docs: `output_parsers` page fix (#19623)

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Issue with this
[page](https://python.langchain.com/docs/modules/model_io/output_parsers/):
Table: "Input Type" columns: strings `str \| Message` (the escape char
"\" doesn't work inside backticked text).
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Leonid Ganeline 3 months ago committed by GitHub
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docs/docs/modules/model_io/output_parsers/index.mdx
Unescape Escape View File

@ -32,16 +32,16 @@ LangChain has lots of different types of output parsers. This is a list of outpu
| Name | Supports Streaming | Has Format Instructions | Calls LLM | Input Type | Output Type | Description |
|-----------------|--------------------|-------------------------------|-----------|----------------------------------|----------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| [OpenAITools](./types/openai_tools) | | (Passes `tools` to model) | | `Message` (with `tool_choice`) | JSON object | Uses latest OpenAI function calling args `tools` and `tool_choice` to structure the return output. If you are using a model that supports function calling, this is generally the most reliable method. |
| [OpenAITools](./types/openai_tools) | | (Passes `tools` to model) | | `Message` (with `tool_choice`) | JSON object | Uses latest OpenAI function calling args `tools` and `tool_choice` to structure the return output. If you are using a model that supports function calling, this is generally the most reliable method. |
| [OpenAIFunctions](./types/openai_functions) | ✅ | (Passes `functions` to model) | | `Message` (with `function_call`) | JSON object | Uses legacy OpenAI function calling args `functions` and `function_call` to structure the return output. |
| [JSON](./types/json) | ✅ | ✅ | | `str \| Message` | JSON object | Returns a JSON object as specified. You can specify a Pydantic model and it will return JSON for that model. Probably the most reliable output parser for getting structured data that does NOT use function calling. |
| [XML](./types/xml) | ✅ | ✅ | | `str \| Message` | `dict` | Returns a dictionary of tags. Use when XML output is needed. Use with models that are good at writing XML (like Anthropic's). |
| [CSV](./types/csv) | ✅ | ✅ | | `str \| Message` | `List[str]` | Returns a list of comma separated values. |
| [OutputFixing](./types/output_fixing) | | | ✅ | `str \| Message` | | Wraps another output parser. If that output parser errors, then this will pass the error message and the bad output to an LLM and ask it to fix the output. |
| [RetryWithError](./types/retry) | | | ✅ | `str \| Message` | | Wraps another output parser. If that output parser errors, then this will pass the original inputs, the bad output, and the error message to an LLM and ask it to fix it. Compared to OutputFixingParser, this one also sends the original instructions. |
| [Pydantic](./types/pydantic) | | ✅ | | `str \| Message` | `pydantic.BaseModel` | Takes a user defined Pydantic model and returns data in that format. |
| [YAML](./types/yaml) | | ✅ | | `str \| Message` | `pydantic.BaseModel` | Takes a user defined Pydantic model and returns data in that format. Uses YAML to encode it. |
| [PandasDataFrame](./types/pandas_dataframe) | | ✅ | | `str \| Message` | `dict` | Useful for doing operations with pandas DataFrames. |
| [Enum](./types/enum) | | ✅ | | `str \| Message` | `Enum` | Parses response into one of the provided enum values. |
| [Datetime](./types/datetime) | | ✅ | | `str \| Message` | `datetime.datetime` | Parses response into a datetime string. |
| [Structured](./types/structured) | | ✅ | | `str \| Message` | `Dict[str, str]` | An output parser that returns structured information. It is less powerful than other output parsers since it only allows for fields to be strings. This can be useful when you are working with smaller LLMs. |
| [JSON](./types/json) | ✅ | ✅ | | `str` \| `Message` | JSON object | Returns a JSON object as specified. You can specify a Pydantic model and it will return JSON for that model. Probably the most reliable output parser for getting structured data that does NOT use function calling. |
| [XML](./types/xml) | ✅ | ✅ | | `str` \| `Message` | `dict` | Returns a dictionary of tags. Use when XML output is needed. Use with models that are good at writing XML (like Anthropic's). |
| [CSV](./types/csv) | ✅ | ✅ | | `str` \| `Message` | `List[str]` | Returns a list of comma separated values. |
| [OutputFixing](./types/output_fixing) | | | ✅ | `str` \| `Message` | | Wraps another output parser. If that output parser errors, then this will pass the error message and the bad output to an LLM and ask it to fix the output. |
| [RetryWithError](./types/retry) | | | ✅ | `str` \| `Message` | | Wraps another output parser. If that output parser errors, then this will pass the original inputs, the bad output, and the error message to an LLM and ask it to fix it. Compared to OutputFixingParser, this one also sends the original instructions. |
| [Pydantic](./types/pydantic) | | ✅ | | `str` \| `Message` | `pydantic.BaseModel` | Takes a user defined Pydantic model and returns data in that format. |
| [YAML](./types/yaml) | | ✅ | | `str` \| `Message` | `pydantic.BaseModel` | Takes a user defined Pydantic model and returns data in that format. Uses YAML to encode it. |
| [PandasDataFrame](./types/pandas_dataframe) | | ✅ | | `str` \| `Message` | `dict` | Useful for doing operations with pandas DataFrames. |
| [Enum](./types/enum) | | ✅ | | `str` \| `Message` | `Enum` | Parses response into one of the provided enum values. |
| [Datetime](./types/datetime) | | ✅ | | `str` \| `Message` | `datetime.datetime` | Parses response into a datetime string. |
| [Structured](./types/structured) | | ✅ | | `str` \| `Message` | `Dict[str, str]` | An output parser that returns structured information. It is less powerful than other output parsers since it only allows for fields to be strings. This can be useful when you are working with smaller LLMs. |

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