# 🔀Output Parsers

#### 1)CSV Output Parser

Parse the output of an LLM call as a comma-separated list of values. 

#### Key Features:

• CSV Formatting: Converts responses into comma-separated values\
• Structured Output: Ensures consistent tabular data format\
• Autofix Option: Automatically fixes minor formatting issues

#### Setup Requirements:

1. Add CSV Output Parser node to the canvas
2. Enable Autofix if required
3. Connect the parser to a chat model output

#### Use Cases:

• Exporting data in CSV format\
• Tabular data generation

<figure><img src="/files/VobTIDJaxZtPGaoiesGu" alt=""><figcaption></figcaption></figure>

#### **2)Custom List Output Parser**

Parse the output of an LLM call as a list of values.&#x20;

#### Key Features:

• Custom Formatting: Define list length and separator\
• Flexible Output: Supports different list structures\
• Autofix Option: Handles formatting inconsistencies

#### Setup Requirements:

1. Add Custom List Output Parser node to the canvas
2. Set Length (number of items)
3. Define Separator (example: comma, newline)
4. Enable Autofix if required
5. Connect to model output

#### Use Cases:

• Generating lists from responses\
• Structured text formatting

<figure><img src="/files/7hjIbkbqCOkGzPhZmYdd" alt=""><figcaption></figcaption></figure>

#### 3)Structured Output Parser

Parse the output of an LLM call into a given (JSON) structure.

#### Key Features:

• Structured Data: Converts output into defined schema\
• Autofix Support: Fixes minor formatting issues\
• Consistent Responses: Ensures predictable output

#### Setup Requirements:

1. Add Structured Output Parser node to the canvas
2. Enable Autofix if required
3. Connect parser with model output

#### Use Cases:

• Structured response generation\
• API-ready outputs

<figure><img src="/files/eSADSEQzbGTW2vVw1FQp" alt=""><figcaption></figcaption></figure>

#### 4)Advanced Structured Output Parser

Parse the output of an LLM call into a given structure by providing a Zod schema.

#### Key Features:

• JSON Schema Support: Uses schema for structured output\
• High Accuracy: Ensures correct format strictly\
• Autofix Option: Handles minor formatting errors

#### Setup Requirements:

1. Add Advanced Structured Output Parser node to the canvas
2. Enable Autofix if required
3. Provide Example JSON schema
4. Connect parser to model output

#### Use Cases:

• JSON-based applications\
• Data validation and structured responses

<figure><img src="/files/rGbD7BY38QuxsGVxjO8v" alt=""><figcaption></figcaption></figure>


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