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DocBot: The Google Docs Chatbot
This video demonstrates how to use the DocBot: The Google Docs Chatbot template.
from fastapi import FastAPI
from fastapi.responses import HTMLResponse
from fastapi import Request
import uvicorn
from google_docs_reader import get_google_docs_content
from abilities import llm_prompt
app = FastAPI()
@app.get("/", response_class=HTMLResponse)
async def read_root():
with open('templates/index.html', 'r') as file:
return file.read()
@app.post("/ask/")
async def ask_question(request: Request):
body = await request.json()
doc_urls = body.get("doc_url").split(',')
question = body.get("question")
doc_contents = []
for url in doc_urls:
content = get_google_docs_content(url.strip())
if not content.startswith("Failed"):
doc_contents.append(content)Frequently Asked Questions
How can DocBot: The Google Docs Chatbot benefit my team's productivity?
DocBot can significantly enhance your team's productivity by providing quick access to information stored in Google Docs. Instead of manually searching through documents, team members can ask DocBot questions and receive instant answers based on the content of the shared documents. This saves time, reduces information bottlenecks, and ensures everyone has access to the most up-to-date information.
What types of businesses or industries would find DocBot most useful?
DocBot is particularly valuable for knowledge-intensive industries and businesses that rely heavily on documentation. This includes: - Software development teams (for accessing technical documentation) - Legal firms (for quick reference to case files or legal documents) - Marketing agencies (for retrieving campaign information or brand guidelines) - Educational institutions (for accessing course materials or research papers) - Any organization with extensive internal documentation or knowledge bases
How does DocBot handle multiple Google Docs URLs?
DocBot is designed to process multiple Google Docs URLs simultaneously. In the main.py file, you can see that the app splits the input URLs and processes each one:
python
doc_urls = body.get("doc_url").split(',')
doc_contents = []
for url in doc_urls:
content = get_google_docs_content(url.strip())
if not content.startswith("Failed"):
doc_contents.append(content)
combined_content = " ".join(doc_contents)
This allows users to reference multiple documents in a single query, making DocBot even more powerful for comprehensive information retrieval.
Can DocBot be integrated with other communication tools my team uses?
While the current implementation of DocBot is a standalone web application, its architecture allows for easy integration with other tools. The core functionality is encapsulated in the google_docs_reader.py and main.py files. You could potentially extend DocBot to work with popular communication platforms like Slack or Microsoft Teams by creating appropriate API endpoints and integrations.
How can I customize the HTML interface of DocBot?
The HTML interface for DocBot is defined in the index.html file. You can easily customize it to match your brand or add additional features. For example, to add a new button that clears the chat history, you could add the following HTML and JavaScript:
```html
```
This would add a "Clear Chat" button that, when clicked, removes all previous messages from the chat interface. Remember to style it appropriately to match the existing UI of DocBot.
Created: | Last Updated:
Introduction to the DocBot: The Google Docs Chatbot Template
Welcome to the DocBot template! This template allows you to create an application that can read content from Google Docs and answer questions based on that content. It's perfect for analyzing team documents and providing quick answers without the need to read through the entire document. This step-by-step guide will walk you through how to use this template on the Lazy platform.
Getting Started
To begin using the DocBot template, simply click on Start with this Template on the Lazy platform. This will pre-populate the code in the Lazy Builder interface, so you won't need to copy or paste any code manually.
Initial Setup
Before testing the application, ensure that you have the URLs of the Google Docs you want to analyze. These documents must be "published to the web" to be accessible by the app. Follow the steps provided in the template's code to publish your Google Docs.
Test: Pressing the Test Button
Once you're ready, press the Test button on the Lazy platform. This will deploy your application and launch the Lazy CLI. The Lazy CLI will prompt you for any required user input.
Entering Input
After pressing the Test button, if the application requires user input, the Lazy App's CLI interface will appear. You will be prompted to provide the necessary input there. For this template, you will need to input the URLs of the Google Docs you want to analyze and the questions you want to ask.
Using the App
Once the app is running, you will be provided with a dedicated server link to interact with the app. If you're using the FastAPI framework, you will also receive a link to the API documentation. Use these links to send requests to your application and receive answers to your questions based on the content of the Google Docs.
Integrating the App
If you need to integrate this app into another service or frontend, you can use the server link provided by the Lazy builder CLI. For example, you can add the API endpoints to an external tool or use the server link to send requests from a custom frontend interface.
Here is a sample request you might send to the app:
`POST /ask/ HTTP/1.1
Host: [your-server-link]
Content-Type: application/json
{
"doc_url": "https://docs.google.com/document/d/your-doc-id",
"question": "What is the main topic of the document?"
}`
And here is a sample response you might receive:
{
"answer": "The main topic of the document is..."
}
Remember, the Lazy platform handles all the deployment details, so you don't need to worry about setting up your environment or installing libraries. Just follow the steps above to get your DocBot application up and running!
If you encounter any issues or have questions about the template, refer to the documentation links provided in the code for additional guidance.
Here are 5 key business benefits for the DocBot Google Docs Chatbot template:
Template Benefits
-
Efficient Document Analysis: Enables quick extraction and analysis of information from Google Docs, saving time and improving productivity for teams working with large amounts of documentation.
-
Improved Knowledge Sharing: Facilitates easier access to information across an organization by allowing employees to ask questions about document contents, promoting better knowledge sharing and collaboration.
-
Reduced Information Overload: Helps employees quickly find specific information within lengthy documents, reducing the time spent searching through large amounts of text and mitigating information overload.
-
Enhanced Decision Making: Provides rapid answers to questions based on document content, supporting faster and more informed decision-making processes within an organization.
-
Scalable Document Management: Offers a scalable solution for managing and querying multiple Google Docs simultaneously, making it ideal for organizations with extensive document libraries or frequently updated information.
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