Edit.

Author: Shuyib

README.md

@@ -28,35 +28,37 @@ Learn more about tool calling <https://gorilla.cs.berkeley.edu/leaderboard.html>
 
 
 ## File structure
-.    
-├── Dockerfile.app - template to run the gradio dashboard.   
-├── Dockerfile.ollama - template to run the ollama server.   
-├── docker-compose.yml - use the ollama project and gradio dashboard.   
-├── docker-compose-codecarbon.yml - use the codecarbon project, ollama and gradio dashboard.   
-├── .env - This file contains the environment variables for the project. (Not included in the repository)   
-├── app.py - the function_call.py using gradio as the User Interface.   
-├── Makefile - This file contains the commands to run the project.   
-├── README.md - This file contains the project documentation. This is the file you are currently reading.   
-├── requirements.txt - This file contains the dependencies for the project.   
-├── summary.png - How function calling works with a diagram.   
-├── tests - This directory contains the test files for the project.   
-│   ├── __init__.py - This file initializes the tests directory as a package.   
-│   ├── test_cases.py - This file contains the test cases for the project.   
-│   └── test_run.py - This file contains the code to run the test cases for the function calling LLM.   
-└── utils - This directory contains the utility files for the project.   
-│    ├── __init__.py - This file initializes the utils directory as a package.   
-│    ├── function_call.py - This file contains the code to call a function using LLMs.   
-│    └── communication_apis.py - This file contains the code to do with communication apis & experiments.   
-|    └── models.py - This file contains pydantic schemas for vision models.   
-|    └── constants.py - This file contains system prompts to adjust the model's behavior.   
-└── voice_stt_mode.py - Gradio tabbed interface with Speech-to-text interface that allows edits and a text interface.      
+.
+├── Dockerfile.app - template to run the gradio dashboard.
+├── Dockerfile.ollama - template to run the ollama server.
+├── docker-compose.yml - use the ollama project and gradio dashboard.
+├── docker-compose-codecarbon.yml - use the codecarbon project, ollama and gradio dashboard.
+├── .env - This file contains the environment variables for the project. (Not included in the repository)
+├── app.py - the function_call.py using gradio as the User Interface.
+├── Makefile - This file contains the commands to run the project.
+├── README.md - This file contains the project documentation. This is the file you are currently reading.
+├── requirements.txt - This file contains the dependencies for the project.
+├── summary.png - How function calling works with a diagram.
+├── tests - This directory contains the test files for the project.
+│   ├── __init__.py - This file initializes the tests directory as a package.
+│   ├── test_cases.py - This file contains the test cases for the project.
+│   └── test_run.py - This file contains the code to run the test cases for the function calling LLM.
+└── utils - This directory contains the utility files for the project.
+│    ├── __init__.py - This file initializes the utils directory as a package.
+│    ├── function_call.py - This file contains the code to call a function using LLMs.
+│    └── communication_apis.py - This file contains the code to do with communication apis & experiments.
+|    └── models.py - This file contains pydantic schemas for vision models.
+|    └── constants.py - This file contains system prompts to adjust the model's behavior.
+└── voice_stt_mode.py - Gradio tabbed interface with Speech-to-text interface that allows edits and a text interface.
 
 ### Attribution
 * This project uses the Qwen2.5-0.5B model developed by Alibaba Cloud under the Apache License 2.0. The original project can be found at [Qwen technical report](https://arxiv.org/abs/2412.15115)
 * Inspired by this example for the [Groq interface STT](https://github.com/bklieger-groq/gradio-groq-basics)
 * Microsoft Autogen was used to simulate multistep interactions. The original project can be found at [Microsoft Autogen](https://github.com/microsoft/autogen)
-* The project uses the Africa's Talking API to send airtime and messages to a phone numbers. The original project can be found at [Africa's Talking API](https://africastalking.com/)
+* The project uses the Africa's Talking API to send airtime and messages to a phone numbers. Check them out on this website [Africa's Talking API](https://africastalking.com/)
 * Ollama for model serving and deployment. The original project can be found at [Ollama](https://ollama.com/)
+* The project uses the Gradio library to create a user interface for the function calling LLM. The original project can be found at [Gradio](https://gradio.app/)
+* The Text-to-Speech interface uses Edge TTS by Microsoft. The original project can be found at [Edge TTS](https://github.com/rany2/edge-tts). The voice chosen is Rehema which is a Swahili voice from Tanzania.
 
 
 ### License
@@ -188,6 +190,7 @@ This project uses LLMs to send airtime to a phone number. The difference is that
 - In the Voice Input tab, record audio and click "Transcribe" to preview the transcription. Then click "Process Edited Text" to execute voice commands.
 - In the Text Input tab, directly type commands to send airtime or messages or to search news.
 - An autogen agent has been added to assist with generating translations to other languages. Note that this uses an evaluator-optimizer model and may not always provide accurate translations. However, this paradigm can be used for code generation, summarization, and other tasks.
+- Text-to-Speech (TTS) has been added to the app. You can listen to the output of the commands.
 
 ### Responsible AI Practices
 This project implements several responsible AI practices: