Farasa

https://farasa.qcri.org/
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### Python Example

Source: https://farasa.qcri.org/POS

Example of how to use the Farasa POS Tagging API with Python.

```APIDOC
## POST /webapi/pos/

### Description
This endpoint performs Part-of-Speech (POS) tagging on the provided text using the Farasa API.

### Method
POST

### Endpoint
https://farasa.qcri.org/webapi/pos/

### Parameters
#### Request Body
- **text** (string) - Required - The text to be tagged.
- **api_key** (string) - Required - Your API key for authentication.

### Request Example
```json
{
  "text": "يُشار إلى أن اللغة العربية",
  "api_key": "#####################"
}
```

### Response
#### Success Response (200)
- **response** (json) - The POS tagged result.

### Response Example
```json
{
  "example": "response body"
}
```
```

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

### Java Example

Source: https://farasa.qcri.org/POS

Example of how to use the Farasa POS Tagging API with Java.

```APIDOC
## POST /webapi/pos/

### Description
This endpoint performs Part-of-Speech (POS) tagging on the provided text using the Farasa API.

### Method
POST

### Endpoint
https://farasa.qcri.org/webapi/pos/

### Parameters
#### Request Body
- **text** (string) - Required - The text to be tagged.
- **api_key** (string) - Required - Your API key for authentication.

### Request Example
```json
{
  "text": "يُشار إلى أن اللغة العربية يتحدثها أكثر من 422 مليون",
  "api_key": "#####################"
}
```

### Response
#### Success Response (200)
- **response** (json) - The POS tagged result.

### Response Example
```json
{
  "example": "response body"
}
```
```

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

### Java Example

Source: https://farasa.qcri.org/lemmatization

Example of how to use the Farasa Lemmatization API with Java HTTPURLConnection.

```APIDOC
## Java Request

### Description
This snippet shows how to lemmatize Arabic text using the Farasa Web API with Java.

### Method
POST

### Endpoint
https://farasa.qcri.org/webapi/lemmatization/

### Parameters
#### Request Body
- **text** (string) - Required - The Arabic text to lemmatize.
- **api_key** (string) - Required - Your API key for authentication.

### Request Example
```json
{
  "text": "يُشار إلى أن اللغة العربية يتحدثها أكثر من 422 مليون",
  "api_key": "#####################"
}
```

### Response
#### Success Response (200)
- The response will be a JSON object containing the lemmatized text and related information.
```

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

### Python Example

Source: https://farasa.qcri.org/lemmatization

Example of how to use the Farasa Lemmatization API with Python requests.

```APIDOC
## Python Request

### Description
This snippet demonstrates how to perform lemmatization using the Farasa Web API with Python.

### Method
POST

### Endpoint
https://farasa.qcri.org/webapi/lemmatization/

### Parameters
#### Request Body
- **text** (string) - Required - The Arabic text to lemmatize.
- **api_key** (string) - Required - Your API key for authentication.

### Request Example
```json
{
  "text": "يُشار إلى أن اللغة العربية",
  "api_key": "#####################"
}
```

### Response
#### Success Response (200)
- The response will be a JSON object containing the lemmatized text and related information.
```

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

### cURL Example

Source: https://farasa.qcri.org/lemmatization

Example of how to use the Farasa Lemmatization API with cURL.

```APIDOC
## cURL Request

### Description
This snippet shows how to perform lemmatization using the Farasa Web API via cURL.

### Method
POST

### Endpoint
https://farasa.qcri.org/webapi/lemmatization/

### Parameters
#### Request Body
- **text** (string) - Required - The Arabic text to lemmatize.
- **api_key** (string) - Required - Your API key for authentication.

### Request Example
```json
{
  "text": "'يُشار إلى أن اللغة العربية'",
  "api_key": "'###################'"
}
```

### Response
#### Success Response (200)
- The response will be a JSON object containing the lemmatized text and related information.
```

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

### cURL Example

Source: https://farasa.qcri.org/POS

Example of how to use the Farasa POS Tagging API with cURL.

```APIDOC
## POST /webapi/pos/

### Description
This endpoint performs Part-of-Speech (POS) tagging on the provided text using the Farasa API.

### Method
POST

### Endpoint
https://farasa.qcri.org/webapi/pos/

### Parameters
#### Request Body
- **text** (string) - Required - The text to be tagged.
- **api_key** (string) - Required - Your API key for authentication.

### Request Example
```json
{
  "text": "'يُشار إلى أن اللغة العربية'",
  "api_key": "'###################'"
}
```

### Response
#### Success Response (200)
- **response** (json) - The POS tagged result.

### Response Example
```json
{
  "example": "response body"
}
```
```

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

### JavaScript Example

Source: https://farasa.qcri.org/lemmatization

Example of how to use the Farasa Lemmatization API with JavaScript AJAX.

```APIDOC
## JavaScript Request

### Description
This snippet demonstrates lemmatization using the Farasa Web API with JavaScript and jQuery AJAX.

### Method
POST

### Endpoint
https://farasa.qcri.org/webapi/lemmatization/

### Parameters
#### Request Body
- **text** (string) - Required - The Arabic text to lemmatize.
- **api_key** (string) - Required - Your API key for authentication.

### Request Example
```json
{
  "text": "يُشار إلى أن اللغة العربية",
  "api_key": "#####################"
}
```

### Response
#### Success Response (200)
- The response will be a JSON object containing the lemmatized text and related information.
```

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

### JavaScript Example for Farasa Web API

Source: https://farasa.qcri.org/?hashtag=footer-area

Provides a JavaScript example for calling the Farasa Web API. Remember to replace 'YOUR_API_KEY' with your valid API key.

```javascript
const url = "https://farasa.qcri.org/webapi/segmentation?text=أحب اللغة العربية&key=YOUR_API_KEY";

fetch(url)
  .then(response => {
    if (!response.ok) {
      throw new Error(`HTTP error! status: ${response.status}`);
    }
    return response.json();
  })
  .then(data => {
    console.log(data);
  })
  .catch(error => {
    console.error('Error:', error);
  });
```

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

### Curl Example for Farasa Web API

Source: https://farasa.qcri.org/?hashtag=footer-area

Illustrates how to use Curl to interact with the Farasa Web API. Substitute 'YOUR_API_KEY' with your actual key.

```bash
curl -G "https://farasa.qcri.org/webapi/segmentation" --data-urlencode "text=أحب اللغة العربية" -d "key=YOUR_API_KEY"
```

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

### Java Example for Farasa Web API

Source: https://farasa.qcri.org/?hashtag=footer-area

Shows how to interact with the Farasa Web API using Java. Replace 'YOUR_API_KEY' with your actual API key.

```java
import java.io.IOException;
import org.apache.http.client.ClientProtocolException;
import org.apache.http.client.methods.CloseableHttpResponse;
import org.apache.http.client.methods.HttpGet;
import org.apache.http.client.utils.URIBuilder;
import org.apache.http.impl.client.CloseableHttpClient;
import org.apache.http.impl.client.HttpClients;
import org.apache.http.util.EntityUtils;

public class FarasaApi {

    public static void main(String[] args) {
        final String uri = "https://farasa.qcri.org/webapi/segmentation";
        final String apiKey = "YOUR_API_KEY";
        final String text = "أحب اللغة العربية";

        try (CloseableHttpClient httpclient = HttpClients.createDefault()) {
            URIBuilder builder = new URIBuilder(uri);
            builder.addParameter("text", text);
            builder.addParameter("key", apiKey);

            HttpGet request = new HttpGet(builder.build());
            request.setHeader("Content-type", "application/json");

            try (CloseableHttpResponse response = httpclient.execute(request)) {
                System.out.println(EntityUtils.toString(response.getEntity()));
            }
        } catch (ClientProtocolException e) {
            e.printStackTrace();
        } catch (IOException e) {
            e.printStackTrace();
        } catch (Exception e) {
            e.printStackTrace();
        }
    }
}
```

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

### Curl Example for Farasa Web API

Source: https://farasa.qcri.org/?hashtag=contact

This Curl command shows how to access the Farasa Web API. Substitute 'YOUR_API_KEY' with your actual API key.

```bash
curl "https://farasa.qcri.org/webapi/process?text=النص المراد معالجته&key=YOUR_API_KEY&service=segmentation"
```

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

### Java Example for Farasa Web API

Source: https://farasa.qcri.org/?hashtag=contact

This Java snippet shows how to interact with the Farasa Web API. Replace 'YOUR_API_KEY' with your actual API key.

```java
import java.io.IOException;
import java.net.URI;
import java.net.http.HttpClient;
import java.net.http.HttpRequest;
import java.net.http.HttpResponse;

public class FarasaApiClient {

    public static void main(String[] args) throws IOException, InterruptedException {
        HttpClient client = HttpClient.newHttpClient();
        String apiKey = "YOUR_API_KEY";
        String textToProcess = "النص المراد معالجته";
        String service = "segmentation";

        HttpRequest request = HttpRequest.newBuilder()
            .uri(URI.create("https://farasa.qcri.org/webapi/process?text=" + textToProcess + "&key=" + apiKey + "&service=" + service))
            .build();

        HttpResponse<String> response = client.send(request, HttpResponse.BodyHandlers.ofString());

        System.out.println("Status Code: " + response.statusCode());
        System.out.println("Response Body: " + response.body());
    }
}
```

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

### Python Segmentation API

Source: https://farasa.qcri.org/segmentation

Example of how to use the Farasa Segmentation API with Python.

```APIDOC
## Python Segmentation API

### Description
This snippet demonstrates how to perform word segmentation using the Farasa API with Python.

### Method
POST

### Endpoint
https://farasa.qcri.org/webapi/segmentation/

### Parameters
#### Request Body
- **text** (string) - Required - The Arabic text to be segmented.
- **api_key** (string) - Required - Your API key for authentication.

### Request Example
```json
{
  "text": "يُشار إلى أن اللغة العربية",
  "api_key": "#####################"
}
```

### Response
#### Success Response (200)
- **result** (object) - Contains the segmented text and other relevant information.

### Response Example
```json
{
  "result": "يُشار إلى أن اللغة العربية"
}
```
```

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

### Java Segmentation API

Source: https://farasa.qcri.org/segmentation

Example of how to use the Farasa Segmentation API with Java.

```APIDOC
## Java Segmentation API

### Description
This snippet demonstrates how to perform word segmentation using the Farasa API with Java.

### Method
POST

### Endpoint
https://farasa.qcri.org/webapi/segmentation/

### Parameters
#### Request Body
- **text** (string) - Required - The Arabic text to be segmented.
- **api_key** (string) - Required - Your API key for authentication.

### Request Example
```json
{
  "text": "يُشار إلى أن اللغة العربية يتحدثها أكثر من 422 مليون",
  "api_key": "#####################"
}
```

### Response
#### Success Response (200)
- **result** (string) - The segmented Arabic text.

### Response Example
```json
{
  "result": "يُشار إلى أن اللغة العربية يتحدثها أكثر من 422 مليون"
}
```
```

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

### JavaScript Example for Farasa Web API

Source: https://farasa.qcri.org/?hashtag=contact

This JavaScript snippet demonstrates how to call the Farasa Web API using fetch. Remember to replace 'YOUR_API_KEY' with your key.

```javascript
const apiKey = "YOUR_API_KEY";
const textToProcess = "النص المراد معالجته";
const service = "segmentation";

fetch(`https://farasa.qcri.org/webapi/process?text=${textToProcess}&key=${apiKey}&service=${service}`)
  .then(response => {
    if (!response.ok) {
      throw new Error(`HTTP error! status: ${response.status}`);
    }
    return response.json();
  })
  .then(data => {
    console.log(data);
  })
  .catch(error => {
    console.error('Error:', error);
  });
```

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

### cURL Segmentation API

Source: https://farasa.qcri.org/segmentation

Example of how to use the Farasa Segmentation API with cURL.

```APIDOC
## cURL Segmentation API

### Description
This snippet demonstrates how to perform word segmentation using the Farasa API with cURL.

### Method
POST

### Endpoint
https://farasa.qcri.org/webapi/segmentation/

### Parameters
#### Request Body
- **text** (string) - Required - The Arabic text to be segmented.
- **api_key** (string) - Required - Your API key for authentication.

### Request Example
```json
{
  "text": "'يُشار إلى أن اللغة العربية'",
  "api_key": "'###################'"
}
```

### Response
#### Success Response (200)
- **result** (string) - The segmented Arabic text.

### Response Example
```json
{
  "result": "يُشار إلى أن اللغة العربية"
}
```
```

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

### JavaScript Segmentation API

Source: https://farasa.qcri.org/segmentation

Example of how to use the Farasa Segmentation API with JavaScript.

```APIDOC
## JavaScript Segmentation API

### Description
This snippet demonstrates how to perform word segmentation using the Farasa API with JavaScript.

### Method
POST

### Endpoint
https://farasa.qcri.org/webapi/segmentation/

### Parameters
#### Request Body
- **text** (string) - Required - The Arabic text to be segmented.
- **api_key** (string) - Required - Your API key for authentication.

### Request Example
```json
{
  "text": "يُشار إلى أن اللغة العربية",
  "api_key": "#####################"
}
```

### Response
#### Success Response (200)
- **result** (string) - The segmented Arabic text.

### Response Example
```json
{
  "result": "يُشار إلى أن اللغة العربية"
}
```
```

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

### Python Example for Farasa Web API

Source: https://farasa.qcri.org/?hashtag=footer-area

Demonstrates how to use the Farasa Web API for text processing in Python. Ensure you have registered and obtained an API key.

```python
import requests

url = "https://farasa.qcri.org/webapi/segmentation"
params = {
    "text": "أحب اللغة العربية",
    "key": "YOUR_API_KEY"
}

response = requests.get(url, params=params)

if response.status_code == 200:
    print(response.json())
else:
    print(f"Error: {response.status_code}")
```

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

### Use Farasa NER as a Library in Java

Source: https://farasa.qcri.org/NER

Integrate Farasa NER into your Java application. This example demonstrates initializing the segmenter, POS tagger, and NER components, then processing text.

```java
package tryingfarasa;

import com.qcri.farasa.segmenter.Farasa;
import com.qcri.farasa.pos.FarasaPOSTagger;
import com.qcri.farasa.ner.ArabicNER;

import java.io.FileNotFoundException;
import java.io.IOException;
import java.io.UnsupportedEncodingException;
import java.util.ArrayList;

public class TryingFarasaPOS {
    public static void main(String[] args) throws IOException, FileNotFoundException, ClassNotFoundException,
    UnsupportedEncodingException, InterruptedException, Exception {





        ArrayList segOutput = farasa.segmentLine("النص المراد معالجته");

        Sentence sentence = farasaPOS.tagLine(segOutput);

        for (Clitic w : sentence.clitics)
        System.out.println(w.surface + "/" + w.guessPOS + ((w.genderNumber!="")?"-"+w.genderNumber:"")+" ");

public static void main(String[] args) throws IOException, FileNotFoundException, ClassNotFoundException, UnsupportedEncodingException, InterruptedException, Exception {
        Farasa segmenter = new Farasa();
        FarasaPOSTagger tagger = new FarasaPOSTagger(segmenter);
        ArabicNER ner = new ArabicNER(segmenter, tagger);



        ArrayList output = ner.tagLine("النص المراد معالجته");

    int loc = 0;
    for (String s : output)
        {
        String plusSign = " ";
        if (loc == 0)
        {
            plusSign = "";
        }
                System.out.println(plusSign + s.trim());

        loc++;
        }
     }
}

```

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

### Use Farasa Segmenter as a Java Library

Source: https://farasa.qcri.org/lemmatization

Example code demonstrating how to import and use the Farasa segmentation package as a library in a Java application. Ensure the farasaSeg.jar is imported into your project.

```java
package tryingfarasa;

import com.qcri.farasa.segmenter.Farasa;
import java.io.FileNotFoundException;
import java.io.IOException;
import java.util.ArrayList;

public class TryingSeg {

    ...

    public static void main(String[] args) throws IOException, FileNotFoundException, ClassNotFoundException {
         ...

        Farasa farasa = new Farasa();
        ArrayList output = farasa.segmentLine("النص المراد معالجته");
                for(String s: output)
                System.out.println(s);
         ...
     }
     ...
}
```

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

### Python Example for Farasa Web API

Source: https://farasa.qcri.org/?hashtag=contact

This Python snippet demonstrates how to use the Farasa Web API for text processing. Ensure you have registered and obtained an API key.

```python
import requests

url = "https://farasa.qcri.org/webapi/process"
params = {
    "text": "النص المراد معالجته",
    "key": "YOUR_API_KEY",
    "service": "segmentation"
}

response = requests.get(url, params=params)

if response.status_code == 200:
    print(response.json())
else:
    print(f"Error: {response.status_code}")
```

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

### Python Spell Check API

Source: https://farasa.qcri.org/spellcheck

Example of how to use the Farasa Spell Check API with Python.

```APIDOC
## Python Spell Check API

### Description
This snippet demonstrates how to perform spell checking using the Farasa API with Python.

### Method
POST

### Endpoint
https://farasa.qcri.org/webapi/spellcheck/

### Parameters
#### Request Body
- **text** (string) - Required - The text to spell check.
- **api_key** (string) - Required - Your Farasa API key.

### Request Example
```json
{
  "text": "يُشار إلى أن اللغة العربية",
  "api_key": "#####################"
}
```

### Response
#### Success Response (200)
- **output** (string) - The spell-checked text or suggestions.

### Response Example
```json
{
  "output": "[Spell check results]"
}
```
```

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

### JavaScript Spell Check API

Source: https://farasa.qcri.org/spellcheck

Example of how to use the Farasa Spell Check API with JavaScript.

```APIDOC
## JavaScript Spell Check API

### Description
This snippet demonstrates how to perform spell checking using the Farasa API with JavaScript.

### Method
POST

### Endpoint
https://farasa.qcri.org/webapi/spellcheck/

### Parameters
#### Request Body
- **text** (string) - Required - The text to spell check.
- **api_key** (string) - Required - Your Farasa API key.

### Request Example
```json
{
  "text": "يُشار إلى أن اللغة العربية",
  "api_key": "#####################"
}
```

### Response
#### Success Response (200)
- **output** (string) - The spell-checked text or suggestions.

### Response Example
```json
{
  "output": "[Spell check results]"
}
```
```

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

### Java Spell Check API

Source: https://farasa.qcri.org/spellcheck

Example of how to use the Farasa Spell Check API with Java.

```APIDOC
## Java Spell Check API

### Description
This snippet demonstrates how to perform spell checking using the Farasa API with Java.

### Method
POST

### Endpoint
https://farasa.qcri.org/webapi/spellcheck/

### Parameters
#### Request Body
- **text** (string) - Required - The text to spell check.
- **api_key** (string) - Required - Your Farasa API key.

### Request Example
```json
{
  "text": "يُشار إلى أن اللغة العربية يتحدثها أكثر من 422 مليون",
  "api_key": "#####################"
}
```

### Response
#### Success Response (200)
- **output** (string) - The spell-checked text or suggestions.

### Response Example
```json
{
  "output": "[Spell check results]"
}
```
```

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

### cURL Spell Check API

Source: https://farasa.qcri.org/spellcheck

Example of how to use the Farasa Spell Check API with cURL.

```APIDOC
## cURL Spell Check API

### Description
This snippet demonstrates how to perform spell checking using the Farasa API with cURL.

### Method
POST

### Endpoint
https://farasa.qcri.org/webapi/spellcheck/

### Parameters
#### Request Body
- **text** (string) - Required - The text to spell check.
- **api_key** (string) - Required - Your Farasa API key.

### Request Example
```bash
curl --header "Content-Type: application/json" -d "{\"text\":\"يُشار إلى أن اللغة العربية\", \"api_key\":\"###################\"}" https://farasa.qcri.org/webapi/spellcheck/
```

### Response
#### Success Response (200)
- **output** (string) - The spell-checked text or suggestions.

### Response Example
```json
{
  "output": "[Spell check results]"
}
```
```

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

### Use Farasa POS Tagger as a Library in Java

Source: https://farasa.qcri.org/POS

Integrate the Farasa POS Tagger into your Java application. Build the project using 'make.sh', import the FarasaPOS.jar, and use the provided classes for segmentation and POS tagging. This example demonstrates basic usage.

```java
package tryingfarasa;

import com.qcri.farasa.segmenter.Farasa;
import com.qcri.farasa.pos.FarasaPOSTagger;
import com.qcri.farasa.pos.Sentence;
import com.qcri.farasa.pos.Clitic;
import java.io.FileNotFoundException;
import java.io.IOException;
import java.io.UnsupportedEncodingException;
import java.util.ArrayList;

public class TryingFarasaPOS {
    public static void main(String[] args) throws IOException, FileNotFoundException, ClassNotFoundException,
    UnsupportedEncodingException, InterruptedException, Exception {


        Farasa farasa = new Farasa();
        FarasaPOSTagger farasaPOS = new FarasaPOSTagger(farasa);

        ArrayList segOutput = farasa.segmentLine("النص المراد معالجته");

        Sentence sentence = farasaPOS.tagLine(segOutput);

        for (Clitic w : sentence.clitics)
        System.out.println(w.surface + "/" + w.guessPOS + ((w.genderNumber!="")?"-"+w.genderNumber:"")+" ");
     }
}
```

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

### Diacritize Text using Python

Source: https://farasa.qcri.org/diacritization

Use this Python snippet to send text to the Farasa Diacritization API and receive the diacritized result. Ensure you have the 'requests' library installed.

```python
import json
import requests
url = 'https://farasa.qcri.org/webapi/diacritize/'
text = 'يُشار إلى أن اللغة العربية' 
api_key = "#####################"
payload = {'text': text, 'api_key': api_key}
data = requests.post(url, data=payload)
result = json.loads(data.text)
print(result)  __ 
```

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

### Python POS Tagging Web API

Source: https://farasa.qcri.org/POS

Use this Python snippet to send text to the Farasa POS Tagging API and receive the results. Ensure you have the 'requests' library installed.

```python
import json
import requests
url = 'https://farasa.qcri.org/webapi/pos/'
text = 'يُشار إلى أن اللغة العربية'
api_key = "#####################"
payload = {'text': text, 'api_key': api_key}
data = requests.post(url, data=payload)
result = json.loads(data.text)
print(result)  __ 

```

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

### Python Web API Request for Lemmatization

Source: https://farasa.qcri.org/lemmatization

Use this Python snippet to send text to the Farasa Lemmatization API and receive lemmatized results. Ensure you have the 'requests' library installed.

```python
import json
import requests
url = 'https://farasa.qcri.org/webapi/lemmatization/'
text = 'يُشار إلى أن اللغة العربية' 
api_key = "#####################"
payload = {'text': text, 'api_key': api_key}
data = requests.post(url, data=payload)
result = json.loads(data.text)
print(result)  __ 
```

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

### Java Spell Check API Request

Source: https://farasa.qcri.org/spellcheck

Perform a POST request to the Farasa Spell Check API using Java. This example demonstrates setting up the connection, sending parameters, and reading the response.

```java
import java.io.BufferedReader;
import java.io.DataOutputStream;
import java.io.IOException;
import java.io.InputStreamReader;
import java.net.HttpURLConnection;
import java.net.URL;
import java.nio.charset.StandardCharsets;

public class FarasaSegmenter {
    private static HttpURLConnection con;
    public static void main(String[] args) throws IOException {
        var url = "https://farasa.qcri.org/webapi/spellcheck/";
        var text = "يُشار إلى أن اللغة العربية يتحدثها أكثر من 422 مليون";
        var api_key = "#####################";
        var urlParameters = "text=" + text + "&api_key=" + api_key;
        byte[] postData = urlParameters.getBytes(StandardCharsets.UTF_8);
        try {
            var myurl = new URL(url);
            con = (HttpURLConnection) myurl.openConnection();
            con.setDoOutput(true);
            con.setRequestMethod("POST");
            con.setRequestProperty("User-Agent", "Java client");
            con.setRequestProperty("Content-Type", "application/json");
            try (var wr = new DataOutputStream(con.getOutputStream())) {
                wr.write(postData);
            }
            try (var br = new BufferedReader(
                    new InputStreamReader(con.getInputStream()))) {
                String line = br.readLine();
                System.out.println(line);
            }
        } finally {
            con.disconnect();
        }
    }
}
__

```

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

### Run Farasa NER JAR from Command Line

Source: https://farasa.qcri.org/NER

Execute the FarasaNERJar.jar file from the command prompt. Ensure all required dependency JAR files are placed in a 'lib' directory next to the main JAR.

```bash
java -jar FarasaNERJar.jar -i  -o 
```

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

### Run Farasa Dependency Parser JAR

Source: https://farasa.qcri.org/dependency

Use this command to run the Farasa Dependency Parser JAR file from the command prompt. Ensure the 'lib' directory is next to the JAR file.

```bash
java -jar FarasaDependencyJar.jar -i  -o 
```

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

### Run Farasa Constituency Parser Jar

Source: https://farasa.qcri.org/constituency

Use this command to run the Farasa Constituency Parser from the downloaded jar file. Ensure the 'lib' directory is next to the jar file.

```bash
java -jar FarasaConstituencyJar.jar -i  -o 
```

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

### Run Farasa Segmenter Standalone (File Input/Output)

Source: https://farasa.qcri.org/lemmatization

Process a text file with UTF-8 encoding as input and specify an output file name for the Farasa Segmenter.

```bash
java -jar dist/farasaSeg.jar -i <inputfile> -o <output_file>
```

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

### Python Segmentation API Request

Source: https://farasa.qcri.org/segmentation

Use this Python snippet to send text to the Farasa segmentation API and receive the results. Ensure you have the 'requests' library installed.

```python
import json
import requests
url = 'https://farasa.qcri.org/webapi/segmentation/'
text = 'يُشار إلى أن اللغة العربية' 
api_key = "#####################"
payload = {'text': text, 'api_key': api_key}
data = requests.post(url, data=payload)
result = json.loads(data.text)
print(result)  __ 
```

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

### Run Farasa POS Tagger Standalone

Source: https://farasa.qcri.org/POS

Execute the Farasa POS Tagger package as a standalone application by providing an input text file and specifying an output file name. Ensure the input file is UTF-8 encoded.

```bash
java -jar dist/farasaPOSJar.jar -i <inputfile> -o <output_file>
```

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

### Compile Farasa POS Tagger Source Code

Source: https://farasa.qcri.org/POS

Use these commands to compile the source code and build the JAR file for the Farasa POS Tagger.

```bash
ant java
ant jar
```

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

### Run Farasa Segmenter Standalone (Interactive)

Source: https://farasa.qcri.org/lemmatization

Run the Farasa Segmenter package in interactive mode using this command.

```bash
java -jar dist/farasaSeg.jar
```

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

### Run Farasa Diacritizer Standalone

Source: https://farasa.qcri.org/seq2seq_diacritization

Execute the Farasa diacritizer as a standalone application using its JAR file. Specify input and output files using command-line arguments.

```bash
java -jar dist/farasaDiacritizeJar.jar -i <inputfile> -o <output_file>
```

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

### Python Seq2seq Diacritization API Request

Source: https://farasa.qcri.org/seq2seq_diacritization

Use this Python snippet to send text for diacritization to the Seq2seq API. Ensure you have the 'requests' library installed. Replace '#####################' with your actual API key.

```python
import json
import requests
url = 'https://farasa.qcri.org/webapi/seq2seq_diacritize/'
text = 'يُشار إلى أن اللغة العربية'
api_key = "#####################"
dialect = "mor"
payload = {'text': text, 'api_key': api_key, "dialect": dialect}
data = requests.post(url, data=payload)
result = json.loads(data.text)
print(result)  __ 
```

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

### Python NER API Request

Source: https://farasa.qcri.org/NER

Use this Python snippet to send text to the Farasa NER API and receive the results. Ensure you have the 'requests' library installed and replace '#####################' with your actual API key.

```python
import json
import requests
url = 'https://farasa.qcri.org/webapi/ner/'
text = 'يُشار إلى أن اللغة العربية'
api_key = "#####################"
payload = {'text': text, 'api_key': api_key}
data = requests.post(url, data=payload)
result = json.loads(data.text)
print(result)  __ 
```

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

### Java NER API Request

Source: https://farasa.qcri.org/NER

This Java code demonstrates how to make a POST request to the Farasa NER API. It includes setting up the connection, sending the text and API key, and reading the response. Replace '#####################' with your API key.

```java
import java.io.BufferedReader;
import java.io.DataOutputStream;
import java.io.IOException;
import java.io.InputStreamReader;
import java.net.HttpURLConnection;
import java.net.URL;
import java.nio.charset.StandardCharsets;

public class FarasaSegmenter {
    private static HttpURLConnection con;
    public static void main(String[] args) throws IOException {
        var url = "https://farasa.qcri.org/webapi/ner";
        var text = "يُشار إلى أن اللغة العربية يتحدثها أكثر من 422 مليون";
        var api_key = "#####################";
        var urlParameters = "text=" + text + "&api_key=" + api_key;
        byte[] postData = urlParameters.getBytes(StandardCharsets.UTF_8);
        try {
            var myurl = new URL(url);
            con = (HttpURLConnection) myurl.openConnection();
            con.setDoOutput(true);
            con.setRequestMethod("POST");
            con.setRequestProperty("User-Agent", "Java client");
            con.setRequestProperty("Content-Type", "application/json");
            try (var wr = new DataOutputStream(con.getOutputStream())) {
                wr.write(postData);
            }
            try (var br = new BufferedReader(
                    new InputStreamReader(con.getInputStream()))) {
                String line = br.readLine();
                System.out.println(line);
            }
        } finally {
            con.disconnect();
        }
    }
}__

```

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

### Java Web API Request for Lemmatization

Source: https://farasa.qcri.org/lemmatization

This Java code demonstrates how to connect to the Farasa Lemmatization API using an HTTP POST request. It handles sending text and API key, then prints the response.

```java
import java.io.BufferedReader;
import java.io.DataOutputStream;
import java.io.IOException;
import java.io.InputStreamReader;
import java.net.HttpURLConnection;
import java.net.URL;
import java.nio.charset.StandardCharsets;

public class FarasaLemmatization {
    private static HttpURLConnection con;
    public static void main(String[] args) throws IOException {
        var url = "https://farasa.qcri.org/webapi/lemmatization/";
        var text = "يُشار إلى أن اللغة العربية يتحدثها أكثر من 422 مليون";
        var api_key = "#####################";
        var urlParameters = "text=" + text + "&api_key=" + api_key;
        byte[] postData = urlParameters.getBytes(StandardCharsets.UTF_8);
        try {
            var myurl = new URL(url);
            con = (HttpURLConnection) myurl.openConnection();
            con.setDoOutput(true);
            con.setRequestMethod("POST");
            con.setRequestProperty("User-Agent", "Java client");
            con.setRequestProperty("Content-Type", "application/json");
            try (var wr = new DataOutputStream(con.getOutputStream())) {
                wr.write(postData);
            }
            try (var br = new BufferedReader(
                    new InputStreamReader(con.getInputStream()))) {
                String line = br.readLine();
                System.out.println(line);
            }
        } finally {
            con.disconnect();
        }
    }
}__

```

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

### RESTful Web API - NER Module

Source: https://farasa.qcri.org/NER

Code snippets demonstrating how to use the Farasa NER RESTful Web API for text analysis.

```APIDOC
## POST /webapi/ner/

### Description
This endpoint performs Named Entity Recognition on the provided text using the Farasa NER module.

### Method
POST

### Endpoint
https://farasa.qcri.org/webapi/ner/

### Parameters
#### Request Body
- **text** (string) - Required - The text to analyze for named entities.
- **api_key** (string) - Required - Your API key for authentication.

### Request Example
```json
{
  "text": "يُشار إلى أن اللغة العربية",
  "api_key": "#####################"
}
```

### Response
#### Success Response (200)
- **entities** (array) - A list of named entities found in the text, with their types and positions.

### Response Example
```json
{
  "entities": [
    {
      "text": "اللغة العربية",
      "type": "MISC",
      "start": 18,
      "end": 30
    }
  ]
}
```
```

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

### Java POS Tagging Web API

Source: https://farasa.qcri.org/POS

This Java code demonstrates how to connect to the Farasa POS Tagging API using an HTTP POST request. It handles URL connection, parameter encoding, and response reading.

```java
import java.io.BufferedReader;
import java.io.DataOutputStream;
import java.io.IOException;
import java.io.InputStreamReader;
import java.net.HttpURLConnection;
import java.net.URL;
import java.nio.charset.StandardCharsets;

public class FarasaSegmenter {
    private static HttpURLConnection con;
    public static void main(String[] args) throws IOException {
        var url = "https://farasa.qcri.org/webapi/pos/";
        var text = "يُشار إلى أن اللغة العربية يتحدثها أكثر من 422 مليون";
        var api_key = "#####################";
        var urlParameters = "text=" + text + "&api_key=" + api_key;
        byte[] postData = urlParameters.getBytes(StandardCharsets.UTF_8);
        try {
            var myurl = new URL(url);
            con = (HttpURLConnection) myurl.openConnection();
            con.setDoOutput(true);
            con.setRequestMethod("POST");
            con.setRequestProperty("User-Agent", "Java client");
            con.setRequestProperty("Content-Type", "application/json");
            try (var wr = new DataOutputStream(con.getOutputStream())) {
                wr.write(postData);
            }
            try (var br = new BufferedReader(
                    new InputStreamReader(con.getInputStream()))) {
                String line = br.readLine();
                System.out.println(line);
            }
        } finally {
            con.disconnect();
        }
    }
}
__

```

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

### Integrate Farasa Diacritizer as a Library in Java

Source: https://farasa.qcri.org/seq2seq_diacritization

Use the Farasa Diacritizer as a library in your Java application. Import the necessary classes and initialize the DiacritizeText object with the data directory and model files.

```java
package tryingfarasa;

import java.io.FileNotFoundException;
import java.io.IOException;
import java.io.UnsupportedEncodingException;
import java.util.ArrayList;
import com.qcri.farasa.segmenter.Farasa;
import com.qcri.farasa.pos.FarasaPOSTagger;
import com.qcri.farasa.diacritize.DiacritizeText;


public class TryingFarasaPOS {
    public static void main(String[] args) throws IOException, FileNotFoundException, ClassNotFoundException,
    UnsupportedEncodingException, InterruptedException, Exception {

        Farasa farasa = new Farasa();
        FarasaPOSTagger farasaPOS = new FarasaPOSTagger(farasa);

        String dataDirectory = "/var/www/farasa/data/";
        DiacritizeText dt = new DiacritizeText(dataDirectory, "all-text.txt.nocase.blm", farasa, tagger);
        String diacritized = dt.diacritize("النص المراد معالجته");
     }
}
```

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

### cURL POS Tagging Web API

Source: https://farasa.qcri.org/POS

This cURL command demonstrates how to interact with the Farasa POS Tagging API from the command line. It specifies the content type and provides the text and API key in the request body.

```curl
curl --header "Content-Type: application/json" -d "{\"text\":\'يُشار إلى أن اللغة العربية\'", \"api_key\":\'###################\'}" https://farasa.qcri.org/webapi/pos/ __ 

```

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

### cURL Web API Request for Lemmatization

Source: https://farasa.qcri.org/lemmatization

This cURL command shows how to make a POST request to the Farasa Lemmatization API. It specifies the content type and provides the text and API key in the request body.

```curl
curl --header "Content-Type: application/json" -d "{\"text\":\'يُشار إلى أن اللغة العربية\'", \"api_key\":\'###################\'}" https://farasa.qcri.org/webapi/lemmatization/ __ 

```

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

### Java Segmentation API Request

Source: https://farasa.qcri.org/segmentation

This Java code demonstrates how to make a POST request to the Farasa segmentation API. It handles URL connection, request parameters, and response reading.

```java
import java.io.BufferedReader;
import java.io.DataOutputStream;
import java.io.IOException;
import java.io.InputStreamReader;
import java.net.HttpURLConnection;
import java.net.URL;
import java.nio.charset.StandardCharsets;

public class FarasaSegmenter {
    private static HttpURLConnection con;
    public static void main(String[] args) throws IOException {
        var url = "https://farasa.qcri.org/webapi/segmentation/";
        var text = "يُشار إلى أن اللغة العربية يتحدثها أكثر من 422 مليون";
        var api_key = "#####################";
        var urlParameters = "text=" + text + "&api_key=" + api_key;
        byte[] postData = urlParameters.getBytes(StandardCharsets.UTF_8);
        try {
            var myurl = new URL(url);
            con = (HttpURLConnection) myurl.openConnection();
            con.setDoOutput(true);
            con.setRequestMethod("POST");
            con.setRequestProperty("User-Agent", "Java client");
            con.setRequestProperty("Content-Type", "application/json");
            try (var wr = new DataOutputStream(con.getOutputStream())) {
                wr.write(postData);
            }
            try (var br = new BufferedReader(
                    new InputStreamReader(con.getInputStream()))) {
                String line = br.readLine();
                System.out.println(line);
            }
        } finally {
            con.disconnect();
        }
    }
}
__

```

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

### Diacritize Text using Java

Source: https://farasa.qcri.org/diacritization

This Java code demonstrates how to connect to the Farasa Diacritization API using an HTTP POST request. It handles the request and response streams for diacritizing Arabic text.

```java
import java.io.BufferedReader;
import java.io.DataOutputStream;
import java.io.IOException;
import java.io.InputStreamReader;
import java.net.HttpURLConnection;
import java.net.URL;
import java.nio.charset.StandardCharsets;

public class FarasaDiacritizer {
    private static HttpURLConnection con;
    public static void main(String[] args) throws IOException {
        var url = "https://farasa.qcri.org/webapi/diacritize/";
        var text = "يُشار إلى أن اللغة العربية يتحدثها أكثر من 422 مليون";
        var api_key = "#####################";
        var urlParameters = "text=" + text + "&api_key=" + api_key;
        byte[] postData = urlParameters.getBytes(StandardCharsets.UTF_8);
        try {
            var myurl = new URL(url);
            con = (HttpURLConnection) myurl.openConnection();
            con.setDoOutput(true);
            con.setRequestMethod("POST");
            con.setRequestProperty("User-Agent", "Java client");
            con.setRequestProperty("Content-Type", "application/json");
            try (var wr = new DataOutputStream(con.getOutputStream())) {
                wr.write(postData);
            }
            try (var br = new BufferedReader(
                    new InputStreamReader(con.getInputStream()))) {
                String line = br.readLine();
                System.out.println(line);
            }
        } finally {
            con.disconnect();
        }
    }
}
__

```

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

### cURL Seq2seq Diacritization API Request

Source: https://farasa.qcri.org/seq2seq_diacritization

This cURL command shows how to make a POST request to the Seq2seq diacritization API from the command line. It includes the necessary headers and data payload. Replace '###################' with your actual API key.

```curl
curl --header "Content-Type: application/json" -d 
"{\"text\":\'يُشار إلى أن اللغة العربية'\, \"api_key\":\'###################\', \"dialect\":\'mor\'}" https://farasa.qcri.org/webapi/seq2seq_diacritize/ __ 

```

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

### Java Seq2seq Diacritization API Request

Source: https://farasa.qcri.org/seq2seq_diacritization

This Java code demonstrates how to make a POST request to the Seq2seq diacritization API. It handles the HTTP connection, request parameters, and response reading. Replace '#####################' with your actual API key.

```java
import java.io.BufferedReader;
import java.io.DataOutputStream;
import java.io.IOException;
import java.io.InputStreamReader;
import java.net.HttpURLConnection;
import java.net.URL;
import java.nio.charset.StandardCharsets;

public class FarasaDiacritizer {
    private static HttpURLConnection con;
    public static void main(String[] args) throws IOException {
        var url = "https://farasa.qcri.org/webapi/seq2seq_diacritize/";
        var text = "يُشار إلى أن اللغة العربية يتحدثها أكثر من 422 مليون";
        var api_key = "#####################";
        var dialect = "mor"
        var urlParameters = "text=" + text + "&api_key=" + api_key+ "&dialect=" + dialect;
        byte[] postData = urlParameters.getBytes(StandardCharsets.UTF_8);
        try {
            var myurl = new URL(url);
            con = (HttpURLConnection) myurl.openConnection();
            con.setDoOutput(true);
            con.setRequestMethod("POST");
            con.setRequestProperty("User-Agent", "Java client");
            con.setRequestProperty("Content-Type", "application/json");
            try (var wr = new DataOutputStream(con.getOutputStream())) {
                wr.write(postData);
            }
            try (var br = new BufferedReader(
                    new InputStreamReader(con.getInputStream()))) {
                String line = br.readLine();
                System.out.println(line);
            }
        } finally {
            con.disconnect();
        }
    }
}__ 

```
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