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Merge pull request #255 from shubhagarwal1/pages
ADD Review Submission Page and API Documentation Page
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‎Web_app/movie_reviews.csv

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Name,Movie,Review
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‎Web_app/pages/API_Documentation.py

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import streamlit as st
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st.subheader(" API Documentation", divider="rainbow")
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# Custom CSS for styling
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st.markdown(
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"""
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<style>
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body {
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color: #333;
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font-family: 'Arial', sans-serif;
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}
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.faq-title {
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color: #FF5733;
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font-size: 24px;
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margin-top: 20px;
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font-weight: bold;
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}
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.code-snippet {
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font-family: 'Courier New', monospace;
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background-color: #f0f0f0;
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padding: 10px;
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border-radius: 5px;
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color: black;
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}
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</style>
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""",
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unsafe_allow_html=True,
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)
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# API Product Overview
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st.subheader("🔍 API Product Overview")
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st.write(
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"The IMDb API on AWS Data Exchange offers a GraphQL-based approach, enabling efficient data access for movie and TV series metadata, "
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"ratings, and box office data in real-time. It provides a streamlined JSON structure and single URL access for reduced API calls."
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)
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# Benefits
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st.subheader("🌟 Key Benefits")
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st.markdown(
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"""
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- **One Call, All Data**: Access all data via a single URL.
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- **Flexible Queries**: Request only the specific fields you need, minimizing data over-fetching.
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- **Real-time Updates**: Receive IMDb’s latest data without delay.
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- **Multiple Entities**: Query multiple titles/names simultaneously.
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""",
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unsafe_allow_html=True,
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)
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# Getting Access to the API
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st.subheader("🔑 Getting Access to the API")
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st.write(
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"To access the IMDb API, you need an AWS account and AWS Access Keys. Follow these steps to set up your access."
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)
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st.markdown(
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"""
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1. **Create an AWS Account**: The IMDb API is available through AWS Data Exchange.
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2. **Obtain AWS Access Keys**: Generate your keys for API authentication.
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3. **Enable Cost Explorer (Optional)**: View your usage and cost in AWS Cost Explorer.
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""",
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unsafe_allow_html=True,
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)
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# Authentication and API Key
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st.subheader("🔒 Authentication and API Key")
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st.write(
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"For API calls, the `x-api-key` header must include your API Key. Authenticate requests using AWS credentials in one of the following ways."
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)
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# Code Snippet for AWS CLI
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st.markdown(
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"""
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**Example API Call (AWS CLI)**:
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""",
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unsafe_allow_html=True,
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)
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st.code(
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"""
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aws dataexchange send-api-asset \\
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--data-set-id <Dataset ID> \\
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--revision-id <Revision ID> \\
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--asset-id <Asset ID> \\
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--request-headers "{ 'x-api-key': '<Your API Key>'}" \\
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--region us-east-1 \\
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--body "{ 'query': '{ title(id: \"tt0120338\") { ratingsSummary { aggregateRating voteCount } } }' }"
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""",
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language="bash",
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)
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# Sample GraphQL Query
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st.subheader("💻 Sample Query")
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st.write("Here’s a sample GraphQL query to retrieve the IMDb rating for *Titanic*:")
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st.markdown(
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"""
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<div class="code-snippet">
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{
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title(id: "tt0120338") {
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ratingsSummary {
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aggregateRating
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voteCount
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}
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}
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}
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</div>
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""",
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unsafe_allow_html=True,
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)
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# Response Example
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st.subheader("📊 Sample API Response")
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st.write('{\n "data": {\n "title": {\n "ratingsSummary": {')
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st.write(' "aggregateRating": 7.9,\n "voteCount": 1133828')
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st.write(" }\n }\n }\n}")
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# Additional Code Snippets
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st.subheader("📜 Additional Code Snippets")
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# Code Snippet for Postman Request
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st.write("**Making Requests via Postman**")
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st.markdown(
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"""
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1. **Set Method**: Use `POST` method.
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2. **Request URL**: `https://api-fulfill.dataexchange.us-east-1.amazonaws.com/v1`
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3. **Headers**:
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- `Content-Type`: `application/json`
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- `x-api-key`: `<Your API Key>`
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4. **Body (GraphQL Query)**:
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```graphql
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{
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title(id: "tt0120338") {
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ratingsSummary {
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aggregateRating
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voteCount
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}
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}
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}
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```
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""",
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unsafe_allow_html=True,
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)
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# Code Snippet for Python API Call
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st.write("**Python Code to Make an API Call**")
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st.code(
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"""
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import requests
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url = "https://api-fulfill.dataexchange.us-east-1.amazonaws.com/v1"
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headers = {
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"x-api-key": "<Your API Key>",
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"Content-Type": "application/json"
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}
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query = '''
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{
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title(id: "tt0120338") {
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ratingsSummary {
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aggregateRating
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voteCount
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}
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}
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}
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'''
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response = requests.post(url, headers=headers, data=query)
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print(response.json())
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""",
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language="python",
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)
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# Example Use Cases
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st.subheader("📄 Example Use Cases")
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st.markdown(
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"""
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1. **Retrieve Ratings**: Query title ratings and vote counts.
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2. **Box Office Data**: Access box office gross data.
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3. **Cast and Crew**: Fetch top cast or crew details for movies and shows.
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4. **Search Functionality**: Use keywords to find specific titles or names.
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5. **Real-time Data Access**: Display data updates as they become available on IMDb.
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""",
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unsafe_allow_html=True,
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)
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# Footer
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st.markdown("---")
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st.markdown(
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"<small>For further assistance, contact support at [email protected]</small>",
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unsafe_allow_html=True,
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)

‎Web_app/pages/ReviewSubmission.py

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import streamlit as st
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import os
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import pandas as pd
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# Set the path for storing the reviews
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reviews_file = "movie_reviews.csv"
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# Initialize the reviews file if it doesn't exist
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if not os.path.exists(reviews_file):
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df = pd.DataFrame(columns=["Name", "Movie", "Review"])
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df.to_csv(reviews_file, index=False)
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# Read the existing reviews from the file
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df = pd.read_csv(reviews_file)
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# Initialize session state for showing the review form
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if "show_review_form" not in st.session_state:
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st.session_state.show_review_form = False
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st.title("🎬 Submit Your Movie Review")
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st.markdown(
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"<div style='height: 5px; background: linear-gradient(to right, #FF5733, #FFC300, #DAF7A6, #33FF57, #3380FF);'></div>",
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unsafe_allow_html=True,
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)
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# Updated Custom CSS for Reddit-style reviews with dynamic sizing
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st.markdown(
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"""
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<style>
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.review-box {
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background-color: #f8f9fa;
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padding: 12px;
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border-radius: 4px;
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margin-bottom: 16px;
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border: 1px solid #e3e6e8;
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width: auto;
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max-width: 100%;
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height: auto;
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overflow-wrap: break-word;
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word-wrap: break-word;
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hyphens: auto;
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}
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.review-header {
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color: #1a1a1b;
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font-size: 12px;
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font-weight: 400;
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line-height: 16px;
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display: flex;
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align-items: center;
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margin-bottom: 8px;
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flex-wrap: wrap;
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}
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.review-author {
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color: #1c1c1c;
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font-weight: 700; /* Changed to bold */
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margin-right: 4px;
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text-transform: capitalize;
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}
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.review-movie {
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color: red;
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text-transform: capitalize;
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}
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.review-content {
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font-size: 14px;
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line-height: 21px;
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font-weight: 400;
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color: #1a1a1b;
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white-space: pre-wrap; /* Preserves line breaks and spaces */
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}
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.toggle-button {
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cursor: pointer;
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color: #0079D3;
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}
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</style>
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""",
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unsafe_allow_html=True,
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)
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# Toggle for review form visibility
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show_review_form = st.checkbox(
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"➕ Submit Review", value=st.session_state.show_review_form, key="review_checkbox"
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)
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# Update session state based on checkbox
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st.session_state.show_review_form = show_review_form
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# Form for submitting reviews
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if st.session_state.show_review_form:
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with st.form(key="review_form"):
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name = st.text_input("Your Name")
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movie_name = st.text_input("Movie Name")
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review = st.text_area("Your Review", height=80)
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submit_button = st.form_submit_button(label="Submit Review")
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if submit_button:
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if name and movie_name and review:
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new_review = pd.DataFrame(
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{
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"Name": [name],
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"Movie": [movie_name],
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"Review": [review],
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}
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)
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df = pd.concat([df, new_review], ignore_index=True)
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df.to_csv(reviews_file, index=False)
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st.success("Thank you for your review!")
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st.session_state.show_review_form = False
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st.rerun()
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else:
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st.error("Please fill in all fields before submitting.")
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# Display the reviews in a Reddit-style comment format
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st.subheader("📜 Reviews")
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if not df.empty:
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for index, row in df.iterrows():
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st.markdown(
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f"""
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<div class="review-box">
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<div class="review-header">
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<span class="review-author">{row['Name']}</span>
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<span class="review-movie">{row['Movie']}</span>
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</div>
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<div class="review-content">{row['Review']}</div>
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</div>
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""",
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unsafe_allow_html=True,
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)
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else:
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st.write("No reviews yet. Be the first to leave one!")

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