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docs: use details tabs in component pages (langflow-ai#7809)
* * Added collapsible sections for Inputs and Outputs to improve readability and organization. * Removed deprecated components and clarified legacy status for certain tools. * icosa-url * details-tab-styling * models * helpers * data * embedding-models * inputs-and-outputs * loaders * logic * memories-and-prompts * processing * vector-stores * legacy-agents * agents * hcd * revert-vector-stores * vector-stores * bundles-agents * update-legacy-wording * complete-sentences-and-punctionaion * vector-stores * google-components-are-legacy * commas * plural-s * remove-future-tense * code-review * code-review * fix-hcd-db * periods
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‎docs/docs/Components/components-agents.md‎

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‎docs/docs/Components/components-data.md‎

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‎docs/docs/Components/components-embedding-models.md‎

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‎docs/docs/Components/components-helpers.md‎

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@@ -52,53 +52,68 @@ record_number: {batch_index}, name: {text_input}, summary: {model_response}
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8. To view your created DataFrame, in the **Parser** component, click <Icon name="TextSearch" aria-label="Inspect icon" />.
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9. Optionally, connect a **Chat Output** component, and open the **Playground** to see the output.
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### Inputs
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<details>
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<summary>Parameters</summary>
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| Name | Display Name | Type | Info |
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|------|--------------|------|------|
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| model | Language Model | HandleInput | Connect the 'Language Model' output from your LLM component here. Required. |
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| system_message | System Message | MultilineInput | Multi-line system instruction for all rows in the DataFrame. |
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| df | DataFrame | DataFrameInput | The DataFrame whose column is treated as text messages, as specified by 'column_name'. Required. |
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| column_name | Column Name | MessageTextInput | The name of the DataFrame column to treat as text messages. Default='text'. Required. |
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| enable_metadata | Enable Metadata | BoolInput | If True, add metadata to the output DataFrame. |
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**Inputs**
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### Outputs
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| Name | Type | Description |
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|------|------|-------------|
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| model | HandleInput | Connect the 'Language Model' output from your LLM component here. Required. |
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| system_message | MultilineInput | A multi-line system instruction for all rows in the DataFrame. |
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| df | DataFrameInput | The DataFrame whose column is treated as text messages, as specified by 'column_name'. Required. |
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| column_name | MessageTextInput | The name of the DataFrame column to treat as text messages. Default='text'. Required. |
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| enable_metadata | BoolInput | If True, add metadata to the output DataFrame. |
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| Name | Display Name | Method | Info |
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|------|--------------|--------|------|
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| batch_results | Batch Results | run_batch | A DataFrame with columns: 'text_input', 'model_response', 'batch_index', and optional 'metadata' containing processing information. |
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**Outputs**
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| Name | Type | Description |
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|------|------|-------------|
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| batch_results | DataFrame | A DataFrame with columns: 'text_input', 'model_response', 'batch_index', and optional 'metadata' containing processing information. |
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</details>
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## Current date
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The Current Date component returns the current date and time in a selected timezone. This component provides a flexible way to obtain timezone-specific date and time information within a Langflow pipeline.
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### Inputs
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<details>
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<summary>Parameters</summary>
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**Inputs**
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| Name | Type | Description |
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|------|------|-------------|
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| timezone | String | The timezone for the current date and time. |
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| Name | Display Name | Info |
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|------|--------------|------|
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|timezone|Timezone|Select the timezone for the current date and time.
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**Outputs**
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### Outputs
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| Name | Type | Description |
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|------|------|-------------|
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| current_date | String | The resulting current date and time in the selected timezone. |
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| Name | Display Name | Info |
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|------|--------------|------|
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|current_date|Current Date|The resulting current date and time in the selected timezone.
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</details>
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## ID Generator
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This component generates a unique ID.
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### Inputs
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<details>
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<summary>Parameters</summary>
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| Name | Display Name | Info |
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|------|--------------|------|
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| unique_id| Value | The generated unique ID. |
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**Inputs**
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### Outputs
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| Name | Type | Description |
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|------|------|-------------|
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| unique_id | String | The generated unique ID. |
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| Name | Display Name | Info |
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|------|--------------|------|
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| id | ID | The generated unique ID. |
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**Outputs**
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| Name | Type | Description |
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|------|------|-------------|
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| id | String | The generated unique ID. |
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</details>
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## Message history
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For more information on configuring memory in Langflow, see [Memory](/memory).
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### Inputs
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<details>
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<summary>Parameters</summary>
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**Inputs**
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| Name | Type | Description |
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|------|------|-------------|
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| memory | Memory | Retrieve messages from an external memory. If empty, the Langflow tables are used. |
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| sender | String | Filter by sender type. |
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| sender_name | String | Filter by sender name. |
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| n_messages | Integer | The number of messages to retrieve. |
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| session_id | String | The session ID of the chat. If empty, the current session ID parameter is used. |
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| order | String | The order of the messages. |
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| template | String | The template to use for formatting the data. It can contain the keys `{text}`, `{sender}` or any other key in the message data. |
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| Name | Display Name | Info |
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|------|--------------|------|
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| memory | External Memory | Retrieve messages from an external memory. If empty, it will use the Langflow tables. |
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| sender | Sender Type | Filter by sender type. |
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| sender_name | Sender Name | Filter by sender name. |
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| n_messages | Number of Messages | Number of messages to retrieve. |
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| session_id | Session ID | The session ID of the chat. If empty, the current session ID parameter will be used. |
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| order | Order | Order of the messages. |
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| template | Template | The template to use for formatting the data. It can contain the keys `{text}`, `{sender}` or any other key in the message data. |
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**Outputs**
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### Outputs
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| Name | Type | Description |
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|------|------|-------------|
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| messages | Data | The retrieved messages as Data objects. |
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| messages_text | String | The retrieved messages formatted as text. |
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| lc_memory | Memory | A constructed Langchain [ConversationBufferMemory](https://api.python.langchain.com/en/latest/memory/langchain.memory.buffer.ConversationBufferMemory.html) object. |
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| Name | Display Name | Info |
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|------|--------------|------|
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| messages | Messages (Data) | Retrieved messages as Data objects. |
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| messages_text | Messages (Text) | Retrieved messages formatted as text. |
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| lc_memory | Memory | A constructed Langchain [ConversationBufferMemory](https://api.python.langchain.com/en/latest/memory/langchain.memory.buffer.ConversationBufferMemory.html) object |
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</details>
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## Message store
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For more information on configuring memory in Langflow, see [Memory](/memory).
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### Inputs
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<details>
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<summary>Parameters</summary>
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| Name | Display Name | Info |
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|------|--------------|------|
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| message | Message | The chat message to be stored. (Required) |
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| memory | External Memory | The external memory to store the message. If empty, it will use the Langflow tables. |
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| sender | Sender | The sender of the message. Can be Machine or User. If empty, the current sender parameter will be used. |
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| sender_name | Sender Name | The name of the sender. Can be AI or User. If empty, the current sender parameter will be used. |
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| session_id | Session ID | The session ID of the chat. If empty, the current session ID parameter will be used. |
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**Inputs**
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### Outputs
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| Name | Type | Description |
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|------|------|-------------|
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| message | String | The chat message to be stored. (Required) |
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| memory | Memory | The external memory to store the message. If empty, the Langflow tables are used. |
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| sender | String | The sender of the message. Can be Machine or User. If empty, the current sender parameter is used. |
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| sender_name | String | The name of the sender. Can be AI or User. If empty, the current sender parameter is used. |
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| session_id | String | The session ID of the chat. If empty, the current session ID parameter is used. |
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| Name | Display Name | Info |
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|------|--------------|------|
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| stored_messages | Stored Messages | The list of stored messages after the current message has been added. |
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**Outputs**
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| Name | Type | Description |
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|------|------|-------------|
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| stored_messages | List[Data] | The list of stored messages after the current message has been added. |
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</details>
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## Structured output
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For example, the template `EBITDA: {EBITDA} , Net Income: {NET_INCOME} , GROSS_PROFIT: {GROSS_PROFIT}` presents the extracted values in the **Playground** as `EBITDA: 900 million , Net Income: 500 million , GROSS_PROFIT: 1.2 billion`.
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### Inputs
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<details>
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<summary>Parameters</summary>
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**Inputs**
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| Name | Type | Description |
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|------|------|-------------|
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| llm | LanguageModel | The language model to use to generate the structured output. |
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| input_value | String | The input message to the language model. |
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| system_prompt | String | The instructions to the language model for formatting the output. |
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| schema_name | String | The name for the output data schema. |
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| output_schema | Table | The structure and data types for the model's output. |
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| multiple | Boolean | [Deprecated] Always set to `True`. |
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| Name | Display Name | Info |
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|------|--------------|------|
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| llm | Language Model | The language model to use to generate the structured output. |
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| input_value | Input Message | The input message to the language model. |
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| system_prompt | Format Instructions | Instructions to the language model for formatting the output. |
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| schema_name | Schema Name | The name for the output data schema. |
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| output_schema | Output Schema | Defines the structure and data types for the model's output.|
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| multiple | Generate Multiple | [Deprecated] Always set to `True`. |
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**Outputs**
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### Outputs
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| Name | Type | Description |
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|------|------|-------------|
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| structured_output | Data | The structured output is a Data object based on the defined schema. |
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| Name | Display Name | Info |
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|------|--------------|------|
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| structured_output | Structured Output | The structured output is a Data object based on the defined schema. |
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| structured_output_dataframe | DataFrame | The structured output converted to a [DataFrame](/concepts-objects#dataframe-object) format. |
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</details>
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## Legacy components
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This component dynamically creates a record with a specified number of fields.
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#### Inputs
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<details>
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<summary>Parameters</summary>
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| Name | Display Name | Info |
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|------|--------------|------|
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| n_fields | Number of Fields | Number of fields to be added to the record. |
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| text_key | Text Key | Key used as text. |
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**Inputs**
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#### Outputs
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| Name | Type | Description |
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|------|------|-------------|
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| n_fields | Integer | The number of fields to be added to the record. |
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| text_key | String | The key used as text. |
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**Outputs**
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| Name | Type | Description |
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|------|------|-------------|
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| list | List | The dynamically created list with the specified number of fields. |
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</details>
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### Output Parser
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This component transforms the output of a language model into a specified format. It supports CSV format parsing, which converts LLM responses into comma-separated lists using Langchain's `CommaSeparatedListOutputParser`.
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4. The output parser converts this into a Python list: `["apple", "banana", "orange"]`.
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#### Inputs
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<details>
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<summary>Parameters</summary>
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**Inputs**
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| Name | Type | Description |
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| parser_type | String | The parser type. Currently supports "CSV". |
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| Name | Display Name | Info |
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| parser_type | Parser | Select the parser type. Currently supports "CSV". |
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**Outputs**
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| Name | Type | Description |
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| format_instructions | String | Pass to a prompt template to include formatting instructions for LLM responses. |
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| output_parser | Parser | The constructed output parser that can be used to parse LLM responses. |
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| format_instructions | Format Instructions | Pass to a prompt template to include formatting instructions for LLM responses. |
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| output_parser | Output Parser | The constructed output parser that can be used to parse LLM responses. |
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</details>

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