ADD Review Submission Page and API Documentation Page

Web_app/movie_reviews.csv

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+Name,Movie,Review
+

Web_app/pages/API_Documentation.py

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

Web_app/pages/ReviewSubmission.py

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