This repository contains a Finance Project that leverages various tools and APIs, including LLM (Language Learning Model) from Langchain, Serpa API, OpenAI, vector embeddings, text splitters, and sequential chaining. The project aims to extract relevant information from different websites, identify specific parts of the text related to finance, and retrieve the sources for further analysis.
The Finance Project utilizes state-of-the-art technologies and tools to analyze financial data from various online sources. It employs the following components:
- LLM (Language Learning Model): Utilized from the Langchain library to process and understand textual data related to finance.
- Serpa API: Used to fetch data from different websites and extract relevant information.
- OpenAI: Integrated for advanced natural language processing tasks and text generation.
- Vector Embeddings: Employed for semantic analysis and similarity search in financial texts.
- Text Splitters: Used to segment text into meaningful units for further analysis.
- Sequential Chaining: Implemented to chain multiple operations and extract insights from financial texts.
- Data Extraction: Fetch data from various financial websites and extract relevant information.
- Information Identification: Identify specific parts of the text related to finance, such as stock prices, market trends, company news, etc.
- Source Retrieval: Retrieve the sources of information to validate and cross-reference the extracted data.
- Analysis and Insights: Analyze the extracted data to generate insights, trends, and predictions in the financial domain.
To get started with the Finance Project, follow these steps:
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Installation: Clone the repository to your local machine.
git clone project
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Environment Setup: Set up a Python environment and install the necessary dependencies.
pip install -r requirements.txt
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Configuration: Configure the project settings, including API keys, URLs to monitor, and parameters for data extraction.
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Execution: Run the main script to start the data extraction and analysis process.
python main.py
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Explore Results: Explore the extracted data, identified information, and generated insights from the financial texts.
Contributions to the Finance Project are welcome! If you have ideas for improvements, new features, or bug fixes, feel free to open an issue or submit a pull request.
This project is licensed under the MIT License. You are free to modify and distribute the code for both personal and commercial use.
Special thanks to the developers and contributors of Langchain, Serpa API, OpenAI, and other libraries and tools.