Parloa Documentation

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### Example: JSON GET API Call

Source: https://docs.parloa.com/rule-based-automation/dialog-interface/services/public-services-provided-by-parloa/api-adapter

Demonstrates configuring a GET request to a JSON API and selecting a specific data entry from the response. This example shows how to specify the URL, method, and a body selector for extracting data.

```json
{
    "input": {
        "url": "https://reqres.in/api/users",
        "method": "get",
        "bodySelector": "data.0",
        "format": "json"
    }
}
```

--------------------------------

### Start Conversation Block Configuration

Source: https://docs.parloa.com/~gitbook/pdf

Details the configuration options for the Start Conversation block, which serves as the entry point for dialogs. Includes responses and intent handling for initial user interactions.

```APIDOC
StartConversationConfiguration:
  Responses: Predefined messages for greetings or initial queries.
  Intents: User intents recognized at the start to direct dialog flow.

  DetailedConfiguration:
    StandardGreetings: e.g., "Welcome"
    DTMFResponses: Handles touch-tone navigation.
    ErrorHandling: Responses for misunderstood intents, e.g., "Excuse me?"
    AffirmativeNegativeResponses: Recognizes "Yes" or "No".
    ComplexRequests: Routes nuanced requests like "ChangeAddress" or "ReportDamage".
```

--------------------------------

### Configuration Variable Example

Source: https://docs.parloa.com/general/release-greater-than-3.0.0/full-feature-base-template

An example of a configuration setting or variable default value change mentioned in the release notes.

```APIDOC
Configuration Setting:
  Set `_INCLUDE_OBJECTS` default to `false`.
```

--------------------------------

### Unified Naming Conventions Examples

Source: https://docs.parloa.com/general/release-greater-than-3.0.0/full-feature-base-template

Examples illustrating the standardized naming conventions adopted across different project elements like blocks, subdialogues, intents, and slots, emphasizing English language and specific casing rules.

```APIDOC
Block Name Convention:
  English language, each word starts with a capital letter, spaces as separators.
  Example: "Phone Start Conversation"

Subdialogue Name Convention:
  English language, each word starts with a capital letter, spaces as separators.
  Example: "Unclear Treatment"

Intent Name Convention (German):
  PascalCase, including umlauts.
  Example: "RückfrageLeistungskürzung"

Intent Name Convention (English):
  camelCase.
  Example: "reportBreakdown"

Slot Name Convention:
  English language, camelCase.
  Example: "houseNumber"

Text Snippet Name Convention:
  English language, camelCase.
  Example: "newNumber"
```

--------------------------------

### Example Intent Data Structure

Source: https://docs.parloa.com/~gitbook/pdf

An example JSON structure representing details of a recognized intent, including entity, start/end positions, and confidence.

```json
{
  "entity":"product",
  "start":40,
  "end":50,
  "confidence_entity":0.9971703886985779,
  "value":"strawberries"
}
```

--------------------------------

### Example: JSON POST API Call

Source: https://docs.parloa.com/rule-based-automation/dialog-interface/services/public-services-provided-by-parloa/api-adapter

Shows how to configure a POST request to a JSON API, including the request body and method. This example demonstrates sending data to an external service and specifying the format.

```json
{
    "input": {
        "url": "https://reqres.in/api/users",
        "method": "post",
        "bodySelector": "",
        "format": "json",
        "body": "{\"name\": \"morpheus\",\"job\": \"leader\"}"
    }
}
```

--------------------------------

### Example Dialog Input/Output Structure

Source: https://docs.parloa.com/~gitbook/pdf

Illustrates the structure for input parameters and context within a dialog, as well as the output format for results.

```json
{
    "input": {
        "input_name_1": "value from dialog",
        "input_name_2": "another value from the dialog"
    },
    "context": {
        "// Additional context information"
    }
}

{
    "choice": "success",
    "output": {
        "result_var_1": "data content",
        "result_var_2": "further information",
        "result_object": { "..." }
    }
}
```

--------------------------------

### RegEx Template Example

Source: https://docs.parloa.com/general/release-greater-than-3.0.0/full-feature-base-template

An example of a specific template provided for regular expressions, such as for zip codes in the DACH region.

```APIDOC
RegEx Template:
  Zip code RegEx template for the DACH region.
```

--------------------------------

### Basic Output Example

Source: https://docs.parloa.com/rule-based-automation/dialog-interface/services/technical-configuration

This JSON snippet demonstrates a basic successful response from an external service, including a formatted address.

```json
{
  "choice": "success",
  "output": {
    "formattedAddress": "Münzstraße 5, 10178 Berlin"
  }
}
```

--------------------------------

### FuzzyMatchNames API Input/Output Examples

Source: https://docs.parloa.com/rule-based-automation/dialog-interface/services/public-services-provided-by-parloa/fuzzy-match-names

Illustrative JSON examples for the FuzzyMatchNames API, showcasing different scenarios including exact matches, fuzzy matches with and without STT candidates, and the corresponding API responses.

```json
# Single string, no stt_candidates, exact match:
{
    "input": {
        "originalString": "Nicolas",
        "stt": "Nicolas",
        "lang": "EN"
    }
}

{
    "choice": "success",
    "output": {
        "MatchStatus": "exact",
        "operations": {
            "originalString": "Nicolas",
            "Stt": "Nicolas",
            "Ops": {}
        },
        "stt_candidates": []
    }
}
```

```json
# Single string, no stt_candidates, fuzzy match:
{
    "input": {
        "originalString": "Nicolas",
        "stt": "Nicholas",
        "lang": "EN"
    }
}

{
    "choice": "success",
    "output": {
        "MatchStatus": "fuzzy",
        "operations": {
            "originalString": "Nicolas",
            "Stt": "Nicholas",
            "Ops": [
                "Spurious 'h' between nicXolas and nicholas;"
            ]
        },
        "stt_candidates": []
    }
}
```

```json
# Single string, stt_candidates, exact match:
{
    "input": {
        "originalString": "Nicolas",
        "stt": [{"text":"Nikolas","confidence":0.5439518},{"text":"nikolas","confidence":0.48069397},{"text":"nicola","confidence":0.3820934},{"text":"Nicolas","confidence":0.47726634}],
        "lang": "EN"
    }
}

{
    "choice": "success",
    "output": {
        "MatchStatus": "exact",
        "operations": {
            "firstName": "Nicolas",
            "firstNameStt": "Nicolas",
            "MatchStatus": "exact"
        },
        "stt_candidates": []
    }
}
```

--------------------------------

### Select Starting Language for Project

Source: https://docs.parloa.com/rule-based-automation/overview/basic-concepts/multi-lingual-bots

Instructions for setting the primary language of a Parloa project. This involves opening an existing project, locating the 'Starting Language' dropdown, selecting the desired language, and confirming by clicking 'Add Language'.

```APIDOC
Project Configuration:
  Starting Language:
    - Action: Select a language from the dropdown menu.
    - Purpose: Defines the primary language for the project.
    - Step: Open an existing project.
    - Step: Click the 'Starting Language' dropdown.
    - Step: Choose the desired language.
    - Step: Click the 'Add Language' button to confirm.
```

--------------------------------

### Variable Types and Examples

Source: https://docs.parloa.com/rule-based-automation/dialog-interface/variables

Details the different types of variables used in rule-based automation, including Storage, Platform, and System variables, with illustrative examples of their typical use cases.

```APIDOC
Variable Types:

  Storage Variables:
    Purpose: Capture user input-related data.
    Example: `customerName`

  Platform Variables:
    Purpose: Hold platform-related data.
    Example: `PhoneV2`

  System Variables:
    Purpose: Contain system-retrieved data.
    Example: `callerNumber`
```

--------------------------------

### Parloa API POST Request Body Examples

Source: https://docs.parloa.com/rule-based-automation/parloa-apis/calldata-service-+-api

Illustrative examples of request bodies for the Parloa API's POST method, showcasing both a basic and a more complex structure with various input fields.

```json
{
  "input": {
    "callerid": "+4112345678",
    "callid": "12345",
    "content": "The user spoke to the bot",
    "destination": "someServiceQueue",
    "intent": "doSomeCoolThing",
    "sessionid": "d69130c6fe02bf8110a25d191c5ec6de"
  }
}
```

--------------------------------

### Opening Hours Config (Specific Date with Reason)

Source: https://docs.parloa.com/rule-based-automation/dialog-interface/services/public-services-provided-by-parloa/opening-hours

Example of a single configuration entry for a specific date, including a reason for closure or special hours.

```json
{
    "Date": "12/23/2024",
    "Department": "Kundenbetreuung",
    "Start": "-",
    "End": "-",
    "Reason": "Kurz vor Weinachten"
}
```

--------------------------------

### phoneV2 Request Body Example

Source: https://docs.parloa.com/~gitbook/pdf

This snippet shows an example JSON request body for the phoneV2 platform. It includes details about the input, context, and request, such as intent and slots, demonstrating how data is structured for this platform.

```json
{
    "input": {
        "addressInput": "Münz straße 5 in Berlin"
    },
    "context": {
        "releaseId": "60f6dab0adb66dce7fac1d7a",
        "userContextId": "60f6e59699712c59611f39df",
        "conversationId": "5e68aa33-e0a3-4d3a-b263-10540ef03d21",
        "dialogId": "60f6dab0adb66dce7fac1d7a",
        "dialogVersion": "1",
        "fovConversationId": "+4917612345678-60f6dab0adb66dce7fac1d7a--default",
        "platform": "phoneV2",
        "request": {
            "callMeta": {
                "callId": "54cb5639-6e40-123a-4ba8-d094667acbd8",
                "callerId": "+4917612345678",
                "instanceId": "60f6dab0adb66dce7fac1d7a"
            },
            "intent": {
                "id": -6487798570032697000,
                "name": "TellAddress",
                "confidence": 0.9999997615814209
            },
            "intentRanking": [
                {
                    "id": -6487798570032697000,
                    "name": "TellAddress",
                    "confidence": 0.9999997615814209
                },
                {
                    "id": 4374073288754445300,
                    "name": "CancelIntent",
                    "confidence": 2.335296192534919e-11
                }
            ],
            "slots": [
                {
                    "extractor": "DIETClassifier",
                    "entity": "Address",
                    "confidenceEntity": 0.7132492661476135,
                    "value": "Münz straße 5 in Berlin",
                    "start": 0,
                    "end": 23,
                    "processors": [],
                    "text": ""
                },
                {
                    "extractor": "DucklingEntityExtractor",
                    "value": 5,
                    "confidence": 1,
                    "entity": "number",
                    "additionalInfo": {
                        "value": 5,
                        "type": "value"
                    },
                    "start": 12,
                    "end": 13,
                    "processors": [],
                    "text": "86"
                }
            ],
            "text": "Münz straße 5 in Berlin"
        }
    }
}
```

--------------------------------

### AmountOfMoney Slot Example

Source: https://docs.parloa.com/~gitbook/pdf

This snippet demonstrates the structure of a pre-built slot, specifically `amountOfMoney`, as it appears in a response. It shows the extracted value, unit, confidence, and other relevant details.

```json
{
	"slots": [
		{
			"extractor": "DucklingEntityExtractor",
			"value": {
				"value": 60,
				"unit": "EUR"
			},
			"confidence": 1,
			"entity": "amountOfMoney",
			"additionalInfo": {
				"value": 60,
				"type": "value",
				"unit": "EUR"
			},
			"start": 0,
			"end": 3,
			"processors": [],
			"text": "60€"
		}
	]
}
```

--------------------------------

### Comprehensive JavaScript Regex Example

Source: https://docs.parloa.com/rule-based-automation/reference/javascript-cheat-sheet/using-regular-expressions-regex

This is a consolidated example of the step-by-step process for regex pattern matching in JavaScript. It includes initializing a variable, fetching text from storage, cleaning the text by removing non-alphanumeric characters, defining a flight number regex pattern, testing the text against the pattern, and returning the first match found.

```javascript
// Initialize a variable to hold the match
let match = "";

// Retrieve the text to be checked
let textCheck = storage.utterance;

// Optional: Remove non-alphanumeric characters for simplicity
textCheck = textCheck.replaceAll(/[^wd]/g, '');

// Define the regex pattern
const flightNum_pattern = /([A-z]\s?){2}([\d]\s?){2,4}/;

// Check if the text contains a pattern match
if (flightNum_pattern.test(textCheck)) {
    match = flightNum_pattern.exec(textCheck)[0];
}

// Return the match
match;
```

--------------------------------

### Basic JSON Response Example

Source: https://docs.parloa.com/~gitbook/pdf

A standard JSON structure representing a successful response, including a choice indicator and output data.

```json
{
  "choice": "success",
  "output": {
    "formattedAddress": "Münzstraße 5, 10178 Berlin"
  }
}
```

--------------------------------

### Alexa Request Body Example

Source: https://docs.parloa.com/~gitbook/pdf

This snippet provides an example JSON request body for the Alexa platform. It details the session, user, device, and system context, illustrating the structure of data received from an Alexa skill.

```json
{
  "context": {
    "releaseId": "5d4ab7ec5e8a29004109cee4",
    "userContextId": "e8a29004109cee5d4ab7ec54",
    "platform": "alexa",
    "request": {
      "version": "1.0",
      "session": {
        "new": true,
        "sessionId": "amzn1.echo-api.session.7f30f70a-c669-4cd4-9da0-85e1b3bd80cf",
        "application": {
          "applicationId": "amzn1.ask.skill.1004db3c-48e8-4ed3-8204-0fb4512176ec"
        },
        "user": {
          "userId": "amzn1.ask.account.XXQ4QKVHXJKNDQKCQ5P6QXR6YRHCPLJ7TOMOYVUEB3XHGYIXY2YRMEC644CQWTCFAVGD6HIWENTVS2JFXM4PLXWNXGD234H4WPCPIGAUW24RBLE5HOESE5ZETLQE2U47Q6DROCAK4QKGVIFZJL3P7RY4YZNHKYF2ZDZUAKQUJCP7N43YOBPSJ4ZVUJBCR7HDOHF4POYN7C4YODQ"
        }
      },
      "context": {
        "System": {
          "application": {
            "applicationId": "amzn1.ask.skill.1004db3c-48e8-4ed3-8204-0fb4512176ec"
          },
          "user": {
            "userId": "amzn1.ask.account.XXQ4QKVHXJKNDQKCQ5P6QXR6YRHCPLJ7TOMOYVUEB3XHGYIXY2YRMEC644CQWTCFAVGD6HIWENTVS2JFXM4PLXWNXGD234H4WPCPIGAUW24RBLE5HOESE5ZETLQE2U47Q6DROCAK4QKGVIFZJL3P7RY4YZNHKYF2ZDZUAKQUJCP7N43YOBPSJ4ZVUJBCR7HDOHF4POYN7C4YODQ"
          },
          "device": {
            "deviceId": "amzn1.ask.device.XX7BQUB6H6DECNQZDNPD6VNC666K4XIPXXQJFDVXLQSESDCED2OCMXOT4CKGO37BA2AVT6DQ74ZT3GK7GLAO4FYEISL5Y3Y6FLQ2Z2CUKC7YZ4I3YTDAYXG5JRUQZ3F2KJWA42KDI4PR3PSA6PI7TSZYLOQCZP7VZ6PQZ27N3WEGNP3W2632M",
            "supportedInterfaces": {}
          },
          "apiEndpoint": "https://api.eu.amazonalexa.com"
        }
      }
    }
  }
}
```

--------------------------------

### Parloa Machine Learning Slot Data Structure Example

Source: https://docs.parloa.com/~gitbook/pdf

Provides an example of the data structure produced by a Machine Learning Slot, illustrating entity recognition, character positioning, confidence level, and captured value.

```APIDOC
Machine Learning Slot Output:
  entity: "product"
  start_char: 40
  end_char: 50
  confidence: 0.997
  value: "strawberries"

  - `entity`: The type of data recognized (e.g., 'product').
  - `start_char`, `end_char`: Character indices within the input text.
  - `confidence`: The model's confidence score for the recognition.
  - `value`: The actual recognized data.
```

--------------------------------

### Customer Number Regex Pattern Example

Source: https://docs.parloa.com/~gitbook/pdf

This snippet provides an example of a regular expression pattern used to validate a specific customer number format. It demonstrates how to match alphanumeric characters, optional spaces, and a sequence of digits.

```regex
KV\s?[Uu]\s?[3]\s?\d{7}
```

--------------------------------

### JavaScript Example for Storage Variable Management

Source: https://docs.parloa.com/~gitbook/pdf

Demonstrates how JavaScript can be used within Parloa to manage storage variables. This includes storing simple text, platform information, or derived values. The example highlights the importance of saving transient data like slot values into uniquely named storage variables to prevent overwriting.

```javascript
// Example: Storing a user's house number into a persistent storage variable
// Assuming 'slots.HouseNumber' holds the value '26'

// Save the slot value to a uniquely named storage variable
storage.userHouseNumber = slots.HouseNumber;

// Later in the conversation, retrieve the stored value
const houseNumber = storage.userHouseNumber;
console.log(`The user's house number is: ${houseNumber}`); // Output: The user's house number is: 26

// Example: Storing platform information
// Assuming the current platform is 'ChatV2'
storage.platformType = 'ChatV2';

// Example: Storing processed user input
// Assuming user said 'May 1st' and it was processed to 'May-01'
storage.processedDate = 'May-01';
```

--------------------------------

### Simple Interaction JSON Example

Source: https://docs.parloa.com/rule-based-automation/analytics-and-debugging/analytics-transactions-data-structure-and-insights

Illustrates a single turn in a bot flow with minimal data, showing transaction ID, request timestamp, intent, and response.

```json
{
  "transactionId": "12345abcd",
  "requestTimestamp": "2024-11-15T10:00:00.000Z",
  "responseTime": 120,
  "intent": {
    "name": "confirm",
    "handled": "locally",
    "explicitlyHandled": true,
    "initialState": {
      "id": "abc123",
      "name": "Initial Confirmation"
    },
    "nextState": {
      "id": "def456",
      "name": "Final State"
    }
  },
  "meta": {
    "errors": { "occurrences": 0, "affectedSteps": [] },
    "warnings": { "occurrences": 0, "affectedSteps": [] }
  },
  "variables": [
    { "id": "userName", "name": "userName", "value": "Alice" }
  ],
  "platform": "phoneV2",
  "request": {
    "text": "Yes",
    "intent": { "name": "confirm", "confidence": 0.95 }
  },
  "response": {
    "prompt": "Thank you for confirming."
  }
}
```

--------------------------------

### DTMF Slot Configuration and Usage

Source: https://docs.parloa.com/~gitbook/pdf

Guides on setting up and integrating DTMF slots within the Parloa platform. This includes creating a DTMF intent and capturing validated caller input using keypad entries.

```APIDOC
DTMF Slot Configuration:

1.  **Create DTMF Intent**: Establish a DTMF intent within the Parloa Speech Assets.
2.  **Integrate into Dialog Flow**: Add the created DTMF slot to your dialog flow to capture and validate caller input.

**Validation Rules Examples (JavaScript within Parloa DSL):**

*   **Customizing Length for Customer Number (6-9 digits):**
    ```
    slots.dtmf && slots.dtmf.length >= 6 && slots.dtmf.length <= 9
    ```
    *   **Description**: This rule ensures that only customer numbers falling within the 6 to 9 digit range are accepted.
    *   **Parameters**: `slots.dtmf` (the captured DTMF input).
    *   **Constraints**: Input length must be between 6 and 9 characters, inclusive.

*   **Setting a Fixed-Length Customer Number (8 digits):**
    ```
    slots.dtmf.length == 8
    ```
    *   **Description**: This rule enforces that customer numbers must be precisely 8 digits long.
    *   **Parameters**: `slots.dtmf` (the captured DTMF input).
    *   **Constraints**: Input length must be exactly 8 characters.
```

--------------------------------

### JSON Response with responseOverwrites

Source: https://docs.parloa.com/~gitbook/pdf

An example JSON response demonstrating the use of 'responseOverwrites' to modify conversational elements, specifically for Google Actions list selection.

```json
{
  "choice": "booksFound",
  "output": {
    "firstTitle": "Albert muss nach Hause"
  },
  "responseOverwrites": {
    "gaction": {
      "systemIntent": {
        "data": {
          "@type": "type.googleapis.com/google.actions.v2.OptionValueSpec",
          "listSelect": {
            "items": [
              {
                "title": "Albert muss nach Hause",
                "description": "Homer Hickam - 2016",
                "image": {
                  "accessibilityText": "Cover Image",
                  "url": "https://storage.googleapis.com/content/Albert_muss_nach_Hause/CoverImage.png"
                },
                "optionInfo": {
                  "key": "Albert_muss_nach_Hause",
                  "synonyms": [
                    "Albert muss nach Hause"
                  ]
                }
              },
              {
                "title": "Das Fundament der Ewigkeit",
                "description": "Ken Follett - 2017",
                "image": {
                  "accessibilityText": "Cover Image",
                  "url": "https://storage.googleapis.com/content/Das_Fundament_der_Ewigkeit/CoverImage.png"
                },
                "optionInfo": {
                  "key": "Das_Fundament_der_Ewigkeit",
                  "synonyms": [
                    "Das Fundament der Ewigkeit"
                  ]
                }
              }
            ],
            "title": "Hörbuch Liste"
          }
        },
        "intent": "actions.intent.OPTION"
      }
    }
  }
}
```

--------------------------------

### Context Variable Usage Example

Source: https://docs.parloa.com/~gitbook/pdf

Demonstrates the use of context variables within a dialogue block to repeat the last prompt heard by the user. `context.previousPrompt` repeats SSML content, while `context.previousPromptText` repeats plain text.

```APIDOC
context.previousPrompt
  - Repeats the last SSML (Speech Synthesis Markup Language) content.
  - Useful for repeating prompts with specific intonation or speech pacing.

context.previousPromptText
  - Repeats the plain text version of the last message.
  - Useful for text-based platforms or debugging.
```

--------------------------------

### Parloa Storage Block Configuration

Source: https://docs.parloa.com/~gitbook/pdf

Documentation for the Parloa Storage block, which allows dynamic data management throughout a conversation by setting and retrieving variables. It details the 'Set' and 'To' fields and provides usage examples.

```APIDOC
Storage Block:
  Purpose: Stores and manages data dynamically throughout a conversation.
  Functionality:
    - Allows setting variables that can be utilized across different stages of the interaction.
    - Enables personalized and context-aware experiences.
    - Requires a separate Storage block at each point where data needs to be altered.

  Fields:
    Set:
      Description: The variable name to which you want to assign a value.
      Requirements: Should be descriptive of the data it holds.
    To:
      Description: Defines the value assigned to the variable.
      Types: Text, Number, JavaScript expression.

  Examples:
    Storing a Caller's Input:
      Set: InquiryReason
      To: "{{caller_input}}"
      Description: Saves the reason for a caller's inquiry to the 'InquiryReason' variable.

    Dynamic Data Capture:
      Set: EscalationReason
      To: "A technical error occurred."
      Description: Sets the 'EscalationReason' variable to indicate a technical error, useful for summaries or guiding conversation flow.
```
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