Update README.md

README.md

@@ -14,6 +14,7 @@ For a comprehensive understanding of the models and inference details, please co
 - [Setup](#setup)
 - [Installation](#installation)
 - [Run Flask server](#run-flask-server)
+- [API](#api)
 - [Citation for the original repo](#citation-for-the-original-repo)
 
 ### Setup
@@ -22,7 +23,7 @@ Some of the large files in this repo are uploaded using git lfs. Install latest
 Some of the large files in this repository have been uploaded using Git-LFS. 
 To ensure seamless handling of these files, please install Git-LFS by executing the provided commands:
 
-```
+```bash
 curl -s https://packagecloud.io/install/repositories/github/git-lfs/script.python.sh | bash
 sudo apt-get install git-lfs
 git lfs install
@@ -32,14 +33,14 @@ The entire repository, including the models, has been uploaded to Hugging Face
 "[Fastspeech2_HS_Flask_API](https://huggingface.co/k-m-irfan/Fastspeech2_HS_Flask_API)" due to size restrictions on GitHub for Git LFS. 
 To clone the repository from Hugging Face, please use the following command:
 
-```
+```bash
 git clone https://huggingface.co/k-m-irfan/Fastspeech2_HS_Flask_API
 ```
 
 Alternatively, you can download the models from the original repository [Fastspeech2_HS](https://github.com/smtiitm/Fastspeech2_HS) 
 and organize the folder structure as specified below. Skip this step if already cloned the repository from Hugging Face.
 
-```
+```bash
 models
 ├── hindi
 │   ├── female
@@ -58,29 +59,85 @@ models
 ### Installation:
 
 Create a virtual environment and activate it:
-```
+```bash
 python3 -m venv tts-hs-hifigan
 source tts-hs-hifigan/bin/activate
 ```
 
 Install the required dependencies by running:
-```
+```bash
 pip install -r requirements.txt
 ```
 
 ### Run Flask server:
 Ensure the server application is running correctly before proceeding. Use the following commands and check for any errors:
-```
+```bash
 python3 flask_app.py
 # OR
 gunicorn -w 2 -b 0.0.0.0:5000 flask_app:app --timeout 600
 ```
 
 If the application is running without any issues, proceed to start the server using the following command:
-```
+```bash
 bash start.sh
 ```
 
+### API
+```python
+"""
+This is a sample API code to send a text to the server and recieve speech
+for the given text.
+
+Supported languages: 
+
+Assamese, Bengali, Bodo, Gujarati, Hindi, Kannada, Malayalam, Manipuri
+Marathi, Odia, Punjabi, Rajasthani, Tamil, Telugu, Urdu
+
+"""
+import requests
+import json
+import base64
+
+# endpoint
+url = "http://localhost:5000/tts"
+
+lang = 'hindi'
+gender = 'female'
+text = "सुप्रभात, आप कैसे हैं?" # hindi
+# text = "സുപ്രഭാതം, സുഖമാ?" # malayalam
+# text = "সুপ্ৰভাত, তুমি কেনে?" # manipuri
+# text = "सुप्रभात, तुम्ही कसे आहात?" # marathi
+# text = "ಶುಭೋದಯ, ನೀವು ಹೇಗಿದ್ದೀರಿ?" # kannada
+# text = "बसु म्विथ्बो, बरि दिबाबो?" # bodo male yet to be added <---
+# text = "Good morning, how are you?" # english
+# text = "সুপ্ৰভাত, আপুনি কেমন আছে?" # assamese
+# text = "காலை வணக்கம், நீங்கள் எப்படி இருக்கின்றீர்கள்?" # tamil
+# text = "ସୁପ୍ରଭାତ, ଆପଣ କେମିତି ଅଛନ୍ତି?"
+# text = "सुप्रभात, आप कैसे छो?" # rajasthani
+# text = "శుభోదయం, మీరు ఎలా ఉన్నారు?" # telugu
+# text = "সুপ্রভাত, আপনি কেমন আছেন?" # bengali
+# text = "સુપ્રભાત, તમે કેમ છો?" # gujarati
+
+payload = json.dumps(
+    {
+    "input": text,
+    "gender": gender,
+    "lang": lang,
+    "alpha": 1 # to control speed
+    })
+
+headers = {'Content-Type': 'application/json'}
+response = requests.request("POST", url, headers=headers, data=payload).json()
+
+# save the received encoded audio
+audio = response['audio']
+file_name = "tts.wav"
+wav_file = open(file_name,'wb')
+decode_string = base64.b64decode(audio)
+wav_file.write(decode_string)
+wav_file.close()
+```
+
 ### Citation for the original repo
 If you use this Fastspeech2 Model in your research or work, please consider citing:
 
@@ -94,7 +151,6 @@ ELECTRICAL ENGINEERING,
 IIT MADRAS. ALL RIGHTS RESERVED "
 
 
-
 Shield: [![CC BY 4.0][cc-by-shield]][cc-by]
 
 This work is licensed under a