add agentic rag

Author: Sumanth077

agentic_rag/.gitignore

@@ -0,0 +1,5 @@
+*.py[cod]
+__pycache__/
+*.db
+.web
+assets/external/

agentic_rag/LICENSE

@@ -0,0 +1,21 @@
+MIT License
+
+Copyright (c) 2023 Pynecone, Inc.
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

agentic_rag/README.md

@@ -0,0 +1,85 @@
+# Agentic RAG with Gemini 2.0 Flash  
+
+This is not just a simple "Chat with PDF" app. It's an **Agentic RAG (Retrieval Augmented Generation)** system powered by **Gemini 2.0 Flash**. The app first searches through the uploaded document for relevant information. If the required information is not found in the document, it seamlessly searches the web and returns a comprehensive response.  
+
+---
+
+## Features  
+- **Upload PDF Documents:** Easily upload any PDF document to start querying.  
+- **Agentic RAG Workflow:** Combines document retrieval with web search for accurate and comprehensive answers.  
+- **Interactive Q&A:** Ask questions about the content of the uploaded PDF or general queries.  
+- **Powered by Gemini 2.0 Flash:** Utilizes Google's Gemini 2.0 Flash model for fast and accurate responses.  
+- **Web Search Integration:** If the document doesn't contain the required information, the app searches the web and provides relevant results.  
+
+---
+
+## Getting Started  
+
+### 1. Clone the Repository  
+Clone the GitHub repository to your local machine:  
+```bash  
+git clone https://github.com/reflex-dev/reflex-llm-examples.git  
+cd reflex-llm-examples/agentic_rag
+```  
+
+### 2. Install Dependencies  
+Install the required dependencies:  
+```bash  
+pip install -r requirements.txt  
+```  
+
+### 3. Set Up Gemini API Key  
+To use the Gemini 2.0 Flash model, you need a **Google API Key**. Follow these steps:  
+Go to [Google AI Studio](https://aistudio.google.com/apikey), get your API Key an set the API key as an environment variable:  
+   ```bash  
+   export GOOGLE_API_KEY="your-api-key-here"  
+   ```  
+
+### 4. Run PgVector  
+The app uses **PgVector** for vector storage and retrieval. Follow these steps to set it up:  
+
+Install Docker Desktop first, then run:  
+```bash  
+docker run -d \
+  -e POSTGRES_DB=ai \
+  -e POSTGRES_USER=ai \
+  -e POSTGRES_PASSWORD=ai \
+  -e PGDATA=/var/lib/postgresql/data/pgdata \
+  -v pgvolume:/var/lib/postgresql/data \
+  -p 5532:5432 \
+  --name pgvector \
+  agnohq/pgvector:16
+```  
+
+### 5. Run the Reflex App  
+Start the application to begin interacting with your PDF:  
+```bash  
+reflex run  
+```  
+
+---
+
+## How It Works  
+1. **Upload a PDF:** The app processes the document and creates a searchable knowledge base.  
+2. **Ask Questions:** The app first searches the uploaded document for relevant information.  
+3. **Web Search Fallback:** If the document doesn't contain the required information, the app searches the web using **DuckDuckGo** and returns the most relevant results.  
+4. **Comprehensive Responses:** The app combines information from the document and the web to provide accurate and detailed answers.  
+
+---
+
+## Why Agentic RAG?  
+- **Document-Centric:** Focuses on extracting information from the uploaded PDF.  
+- **Web-Augmented:** Ensures no query goes unanswered by leveraging web search when needed.  
+- **Efficient and Accurate:** Combines the best of both worlds for a seamless experience.  
+
+---
+
+## Troubleshooting  
+- **Gemini API Key Not Set:** Ensure the `GOOGLE_API_KEY` environment variable is set correctly.  
+- **PgVector Not Running:** Verify that the PgVector Docker container is running and accessible on port `5532`.
+---
+
+## Contributing  
+Contributions are welcome! Feel free to open issues or submit pull requests to improve the app.  
+
+---

agentic_rag/chat/__init__.py

@@ -0,0 +1,35 @@
+import reflex as rx
+from chat.components.chat import State, chat, action_bar, sidebar
+
+def index() -> rx.Component:
+    """The main app."""
+    return rx.box(
+        sidebar(),
+        rx.box(
+            rx.vstack(
+                rx.hstack(
+                    rx.heading("Agentic RAG 🔥"),
+                    rx.button(
+                        "New Chat",
+                        on_click=State.create_new_chat,
+                        margin_left="auto",
+                    ),
+                ),
+                chat(),
+                action_bar(),
+                spacing="4",
+                align_items="center",
+                height="100vh",
+                padding="4em",
+            ),
+            margin_left="300px",
+            width="calc(100% - 300px)",
+        ),
+        width="100%",
+        height="100vh",
+        background_color=rx.color("mauve", 1),
+    )
+
+
+app = rx.App()
+app.add_page(index)