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## Overview

TalkforgeAI is an AI-powered chat software that facilitates the creation of personalized chatbots
using the OpenAI
Assistant API. It allows users to tailor the chat experience by creating individual AI profiles,
known as Personas, each
with its own personality profile and avatar image. In addition to text input, prompts can be
generated via voice input,
and the AI's responses can be delivered through browser-based or Elevenlabs text-to-speech output.
TalkforgeAI is an advanced AI-powered chat software designed to facilitate the creation of highly
personalized chatbots, now referred to as "Assistants". This software integrates with multiple AI
platforms including OpenAI, Mistral, Anthropic, and Ollama, supporting both cloud-based and local AI
models. Users can customize each Assistant with unique personality traits and an avatar image. The
chatbots can interact via text or voice inputs, with responses delivered through browser-based or
Elevenlabs text-to-speech output.

**Note:** This project is still in the early stages of development and may not yet be suitable for
production use.

### Prerequisites

- An OpenAI API key is required to use the OpenAI Assistant API. To obtain one, visit
the [OpenAI website](https://openai.com/) and follow the instructions for API key generation.
- For optional Elevenlabs speech output, an API key is also necessary. Please visit
the [Elevenlabs website](https://elevenlabs.io/) for instructions.
- An API key from any supported AI provider (OpenAI, Mistral, Anthropic, Ollama) is required.
- For optional Elevenlabs speech output, an API key is also necessary.

## Features

- Create individual chatbot profiles with custom personalities using the OpenAI Assistant API.
- Generate a profile picture for your chatbot right inside the app.
- Image generation through DALL-E 3 directly in chat, compatible with both GPT-3.5 and GPT-4 models.
- Access to all relevant GPT models:
- gpt-4
- gpt-4-32k
- gpt-4-vision-preview
- gpt-3.5-turbo
- gpt-3.5-turbo-16k

- Creation of PlantUML diagrams, such as class, sequence, or activity diagrams.
- Graphical enhancement of generated LaTeX code.
- Custom instruction definitions.
- Create and manage multiple, GPT-style, chatbot Assistants with custom personalities using AI
providers like
OpenAI, Mistral, Anthropic, and Ollama.
- Each assistant can be customized with unique personality traits, an avatar image and one of the
supported AI models.
- Support for both cloud-based and local AI models, enhancing flexibility and control over data
processing.
- Support for text and voice input, with text-to-speech output through Elevenlabs or the browser
build-in MS Speech API.
- Generate a profile picture for your Assistant directly inside the app.
- Image generation through DALL-E 3, compatible with various GPT models.
- Advanced diagram creation with PlantUML and graphical enhancement of LaTeX code.
- Code highlighting for generated source code.
- Docker container support for simplified deployment.

## Upcoming Features

- Multi-user support with access control for the features of each Persona, allowing for the
assignment and sharing of
Personas among users.
- Image interpretation, initially supported by Huggingface models.
- Reading and evaluating web links.
- Upload of files to be interpreted by the AI (PDF, TXT, etc.)
- Memory feature to store critical information in the database and retrieve it as needed, allowing
for the persistence
of information beyond the maximum token limit.
- Function support for tasks such as sending emails, querying calendar data, etc.
- Enhanced multi-user support with comprehensive access controls for managing Assistants.
- Support for uploading and interpreting files (PDF, TXT, etc.).
- Persistent memory capabilities for storing essential information.
- Support for Vector Storage like Apache Cassandra, Redis, Neo4j and local storage.
- Expanded task functions like email automation and calendar queries.

## Installation

### Building the Project

- Ensure Java 21 or higher is installed on your system and the JAVA_HOME environment variable is set
correctly.
- Ensure Java 21 or higher is installed on your system and the JAVA_HOME environment variable is
correctly set.

### Starting the Server

- To run from a JAR file, use the following command with the appropriate API keys and data directory
specified:

java -jar ./talkforgeai-0.1.0.jar --server.port=8090 --openai.api-key=[your OpenAI API Key] --elevenlabs.api-key=[you Elevenlabs API-Key] --talkforgeai.datadir=[your TalkforgeAI data directory]
To run from a JAR file, include API keys and specify the data directory as shown in this example:

- Alternatively, use a properties file for configuration:
java -jar ./talkforgeai-0.1.0.jar --server.port=8090 --spring.ai.openai.api-key=[your API Key] --talkforgeai.datadir=[your TalkforgeAI data directory]

java -jar ./talkforgeai-0.1.0.jar --spring.config.additional-location=./talkforgeai.properties
Alternatively, configure using a properties file:

- Available properties:
- server.port: Port to run the server on. Default is 8090.
- openai.api-key: OpenAI API key
- elevenlabs.api-key: Elevenlabs API key
- talkforgeai.datadir: Directory to store data in
- logging.level.com.talkforgeai: Log level for TalkforgeAI. Default is INFO.
java -jar ./talkforgeai-0.1.0.jar --spring.config.additional-location=./talkforgeai.properties

### Using Docker
Example properties file (if you don't want to use a model, leave property empty or remove it from
the file):

- Deploy using Docker with the following command:
spring.ai.openai.api-key=[your API Key]
spring.ai.mistralai.api-key=[your API Key]
spring.ai.anthropic.api-key=[your API Key]
spring.ai.ollama.base-url=http://localhost:11434
elevenlabs.api-key=[your API Key]
server.port=8090
talkforgeai.datadir=[your TalkforgeAI data directory]

docker run -d -p [your local port]:8090 -e TALKFORGEAI_OPENAI_APIKEY=[your OpenAI API Key] -e TALKFORGEAI_ELEVENLABS_APIKEY=[you Elevenlabs API-Key] talkforgeai/talkforgeai:latest
Available properties:

- If you want to use a local properties file, you can mount it into the container:
| Property | Default Value | Description |
|---------------------------------------------|-----------------------------------------------------|------------------------------------------------------|
| `server.port` | `8090` | The port on which the server will run. |
| `talkforgeai.datadir` | `${user.home}/.talkforgeai` | The directory where TalkforgeAI data will be stored. |
| `spring.servlet.multipart.max-file-size` | `5MB` | The maximum file size for multipart file uploads. |
| `spring.servlet.multipart.max-request-size` | `5MB` | The maximum request size for multipart file uploads. |
| `spring.ai.mistralai.api-key` | - | The API key for Mistral AI. |
| `spring.ai.ollama.base-url` | `http://localhost:11434` | The base URL for Ollama AI. |
| `spring.ai.anthropic.api-key` | - | The API key for Anthropic AI. |
| `spring.ai.anthropic.version` | `2023-06-01` | The version of Anthropic AI. |
| `elevenlabs.api-key` | - | The API key for Elevenlabs. |
| `elevenlabs.api-url` | `https://api.elevenlabs.io` | The base URL for Elevenlabs API. |
| `spring.datasource.url` | `jdbc:sqlite:${talkforgeai.datadir}/talkforgeai.db` | The URL for the SQLite database. |
| `spring.datasource.driverClassName` | `org.sqlite.JDBC` | The driver class name for the SQLite database. |
| `spring.jpa.database-platform` | `org.hibernate.community.dialect.SQLiteDialect` | The dialect for the SQLite database. |
| `logging.level.com.talkforgeai` | `INFO` | The log level for TalkforgeAI. |

docker run -d -p [your local port]:8090 -v [your local properties file]:/usr/local/talkforgeai/talkforgeai.properties:ro -v C:/Users/jschmitz/DEV/talkforge-data:/data talkforgeai/talkforgeai:latest
### Using Docker

- If you want to use a local data directory, you can mount it into the container:
Deploy using Docker with commands customized for your local settings:

docker run -d -p [your local port]:8090 -v [your local data directory]:/data talkforgeai/talkforgeai:latest
docker run -d -p [your local port]:8090 -e TALKFORGEAI_APIKEY=[your API Key] talkforgeai/talkforgeai:latest

## Building from Source

- After cloning the repository, building is straightforward with Maven:
After cloning the repository, build the project using Maven:

mvn clean package
mvn clean package

*Note: Replace placeholder text (e.g., [your OpenAI API Key]) with actual API keys and directory
paths as required for
your setup.*
*Note: Replace placeholder text (e.g., [your API Key]) with actual API keys and directory paths as
needed.*

## Contributing

Contributions are welcome! Please read our contributing guidelines for how to proceed.
Contributions are welcome! Review our contributing guidelines to get started.

## License

TalkforgeAI is released under the Apache License 2.0. See the [LICENSE](LICENSE) file for more
details.
TalkforgeAI is released under the Apache License 2.0. See the LICENSE file for more details.

## Support

For support and queries, please open an issue on the GitHub repository or contact the maintainers
For support and inquiries, please open an issue on the GitHub repository or contact the maintainers
directly.

---

This README is a basic guide for getting started with TalkforgeAI. For more detailed documentation,
please refer to the
project's documentation site.

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