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---------
Co-authored-by: Linlang <Lv.Linlang@hotmail.com>
RDAgent aims to automate the most critical and valuable aspects of the industrial R&D process, and we begin with focusing on the data-driven scenarios to streamline the development of models and data.
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Methodologically, we have identified a framework with two key components: 'R' for proposing new ideas and 'D' for implementing them.
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<!-- Tag Cloud -->
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R&D is a very general scenario. The advent of RDAgent can be your
- 🤖 Data Mining Agent: iteratively proposing data [(🎥demo)](https://rdagent.azurewebsites.net/dmm) & models [(🎥demo)](https://rdagent.azurewebsites.net/model_loop) and implementing them by gaining knowledge from data.
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- 🦾 Research Copilot: Auto read research papers [(🎥demo)](https://rdagent.azurewebsites.net/report_model) / financial reports [(🎥demo)](https://rdagent.azurewebsites.net/report_factor) and implement model structures or building datasets.
- 🤖 **Data Mining Agent:** Iteratively proposing data [(🎥Demo Video)](https://rdagent.azurewebsites.net/dmm) & models [(🎥Demo Video)](https://rdagent.azurewebsites.net/model_loop) and implementing them by gaining knowledge from data.
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- 🦾 **Research Copilot:** Auto read research papers [(🎥Demo Video)](https://rdagent.azurewebsites.net/report_model) / financial reports [(🎥Demo Video)](https://rdagent.azurewebsites.net/report_factor) and implement model structures or building datasets.
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- ...
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You can click the 🎥 [link](https://rdagent.azurewebsites.net) above to view the demo. More methods and scenarios are being added to the project to empower your R&D processes and boost productivity.
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<!--
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- TODO: Demo: it fails to display the video in the README.md.
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We have a quick 🎥 demo for one use case of RDAgent.
[](https://rdagent.azurewebsites.net/)
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You can click the links above to view the demo. We're continuously adding more methods and scenarios to the project to enhance your R&D processes and boost productivity.
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Additionally, you can take a closer look at the examples in our **[🖥️ Live Demo](https://rdagent.azurewebsites.net/)**.
<img src="docs/_static/demo.png" alt="Watch the demo" width="80%">
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</a>
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</div>
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# ⚡ Quick start
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```
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### ⚙️ Configuration
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You have to config your GPT model in the `.env`
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```bash
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cat <<EOF > .env
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OPENAI_API_KEY=<your_api_key>
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# EMBEDDING_MODEL=text-embedding-3-small
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CHAT_MODEL=gpt-4-turbo
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EOF
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```
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-You have to config your GPT model in the `.env`
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```bash
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cat <<EOF > .env
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OPENAI_API_KEY=<your_api_key>
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# EMBEDDING_MODEL=text-embedding-3-small
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CHAT_MODEL=gpt-4-turbo
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EOF
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```
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### 🚀 Run the Application
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The 🎥 [demo](https://rdagent.azurewebsites.net) is implemented by the following commands(each item represents one demo, you can select the one you prefer):
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The **[🖥️ Live Demo](https://rdagent.azurewebsites.net/)** is implemented by the following commands(each item represents one demo, you can selectthe one you prefer):
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- Run the **Automated Quantitative Trading & Iterative Factors Evolution**: Qlib self-loop factor proposal and implementation application
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```sh
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rdagent fin_model
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```
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- Run the **Automated Medical Predtion Model Evolution**: medical self-loop model proposal and implementation application
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- Run the **Automated Medical Prediction Model Evolution**: Medical self-loop model proposal and implementation application
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```sh
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rdagent med_model
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```
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- Run the **Automated Quantitative Trading & Factors Extraction from Financial Reports**: Run the Qlib factor extraction and implementation application based on financial reports
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```sh
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rdagent fin_factor_report
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# 1. Generally, you can run this scenario using the following command:
Automating the R&D process in data science is a highly valuable yet underexplored area in industry. We propose a framework to push the boundaries of this important research field.
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The research questions within this framework can be divided into three main categories:
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| Research Area | Paper/Work List |
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|--------------------|-----------------|
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| Benchmark the R&D abilities |[Benchmark](#benchmark)|
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| Idea proposal: Explore new ideas or refine existing ones |[Research](#research)|
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| Ability to realize ideas: Implement and execute ideas |[Development](#development)|
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|**Benchmark the R&D abilities**| [Benchmark](#benchmark) |
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|**Idea proposal:** Explore new ideas or refine existing ones | [Research](#research) |
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|**Ability to realize ideas:** Implement and execute ideas | [Development](#development) |
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We believe that the key to delivering high-quality solutions lies in the ability to evolve R&D capabilities. Agents should learn like human experts, continuously improving their R&D skills.
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More documents can be found in the [📚readthedocs](https://rdagent.readthedocs.io/).
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More documents can be found in the **[📖 readthedocs](https://rdagent.readthedocs.io/)**.
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Based on the principles above, we have established a basic method framework that continuously proposes hypotheses, verifies them, and gets feedback from the real-world practice. This is the first scientific research automation framework that supports linking with real-world verification.
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For more detail, please refer to our [Demos page](https://rdagent.azurewebsites.net).
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For more detail, please refer to our **[🖥️ Live Demo page](https://rdagent.azurewebsites.net)**.
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In modern industry, research and development (R&D) is crucial for the enhancement of industrial productivity, especially in the AI era, where the core aspects of R&D are mainly focused on data and models. We are committed to automate these high-value generic R&D processes through our open source R&D automation tool RDAgent, which let AI drive data-driven AI.
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