rag_chain added to rag_tutorials

rag_tutorials/rag_chain/README.md

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+# PharmaQuery
+
+## Overview
+PharmaQuery is an advanced Pharmaceutical Insight Retrieval System designed to help users gain meaningful insights from research papers and documents in the pharmaceutical domain.
+
+## PharmaQuery Architecture
+![PharmaQuery-Architecture](https://github.com/user-attachments/assets/c8a2cff7-f004-415c-8b1e-5387999680b4)
+
+## Features
+- **Natural Language Querying**: Ask complex questions about the pharmaceutical industry and get concise, accurate answers.
+- **Custom Database**: Upload your own research documents to enhance the retrieval system's knowledge base.
+- **Similarity Search**: Retrieves the most relevant documents for your query using AI embeddings.
+- **Streamlit Interface**: User-friendly interface for queries and document uploads.
+
+## Technologies Used
+- **Programming Language**: [Python 3.10+](https://www.python.org/downloads/release/python-31011/)
+- **Framework**: [LangChain](https://www.langchain.com/)
+- **Database**: [ChromaDB](https://www.trychroma.com/)
+- **Models**:
+  - Embeddings: [Google Gemini API (embedding-001)](https://ai.google.dev/gemini-api/docs/embeddings)
+  - Chat: [Google Gemini API (gemini-1.5-pro)](https://ai.google.dev/gemini-api/docs/models/gemini#gemini-1.5-pro)
+- **PDF Processing**: [PyPDFLoader](https://python.langchain.com/docs/integrations/document_loaders/pypdfloader/)
+- **Document Splitter**: [SentenceTransformersTokenTextSplitter](https://python.langchain.com/api_reference/text_splitters/sentence_transformers/langchain_text_splitters.sentence_transformers.SentenceTransformersTokenTextSplitter.html)
+
+## Requirements
+1. **Install Dependencies**:
+   ```bash
+   pip install -r requirements.txt
+   ```
+
+2. **Set Up Environment Variables**:
+   Create a `.env` file in the project root directory with the following variables:
+
+    ```bash
+    GOOGLE_API_KEY="your_google_gemini_api_key"
+    ```
+
+    `Note:` Replace `your_google_gemini_api_key` with actual key.
+
+3. **Run the Application**:
+   ```bash
+   streamlit run app.py
+   ```
+
+4. **Use the Application**:
+   - Enter your query in the main interface.
+   - Optionally, upload research papers in the sidebar to enhance the database.
+
+## :mailbox: Connect With Me
+<img align="right" src="https://media.giphy.com/media/2HtWpp60NQ9CU/giphy.gif" alt="handshake gif" width="150">
+
+<p align="left">
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+</p>