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.env

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+GROQ_API_KEY=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
+BRIGHT_API_KEY=ded1bc00-4d84-4dee-b4d6-c896cadf2417
+BRIGHT_ZONE=web_unlocker2

app.py

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+import os
+import json
+import requests
+import re
+from bs4 import BeautifulSoup
+from groq import Groq
+import gradio as gr
+from dotenv import load_dotenv
+from youtube_transcript_api import YouTubeTranscriptApi
+
+load_dotenv()
+
+
+# ENV VARIABLES
+
+GROQ_API_KEY = os.getenv("GROQ_API_KEY")
+BRIGHT_API_KEY = os.getenv("BRIGHT_API_KEY")
+BRIGHT_ZONE = os.getenv("BRIGHT_ZONE")
+
+client = Groq(api_key=GROQ_API_KEY)
+
+CHAT_FILE = "chat_history.json"
+PREF_FILE = "preferences.json"
+
+
+# SAFE LOAD & SAVE
+
+def load_json(file, default):
+    if os.path.exists(file):
+        try:
+            with open(file, "r") as f:
+                return json.load(f)
+        except:
+            return default
+    return default
+
+def save_json(file, data):
+    with open(file, "w") as f:
+        json.dump(data, f, indent=4)
+
+conversation_history = load_json(CHAT_FILE, [])
+user_preferences = load_json(PREF_FILE, {"style": "Default"})
+
+
+# BRIGHT DATA SCRAPER
+
+def brightdata_request(target_url):
+    response = requests.post(
+        "https://api.brightdata.com/request",
+        headers={
+            "Content-Type": "application/json",
+            "Authorization": f"Bearer {BRIGHT_API_KEY}"
+        },
+        json={
+            "zone": BRIGHT_ZONE,
+            "url": target_url,
+            "format": "raw"
+        }
+    )
+    return response.text
+
+
+def scrape_goodreads(url):
+    html = brightdata_request(url)
+    soup = BeautifulSoup(html, "html.parser")
+
+    books = []
+    rows = soup.find_all("tr")
+
+    for row in rows:
+        title_tag = row.find("a", class_="bookTitle")
+        author_tag = row.find("a", class_="authorName")
+        rating_tag = row.find("span", class_="minirating")
+
+        if title_tag and author_tag and rating_tag:
+            books.append({
+                "title": title_tag.get_text(strip=True),
+                "author": author_tag.get_text(strip=True),
+                "rating": rating_tag.get_text(strip=True)
+            })
+
+    return books[:10]
+
+
+def qa_bot(url, question):
+    books = scrape_goodreads(url)
+
+    if not books:
+        return "No book data found."
+
+    context = "\n".join(
+        [f"{i+1}. {b['title']} by {b['author']} - {b['rating']}"
+         for i, b in enumerate(books)]
+    )
+
+    system_prompt = f"""
+You are a helpful assistant.
+Answer ONLY using the following scraped Goodreads data.
+
+{context}
+"""
+
+    response = client.chat.completions.create(
+        model="llama-3.1-8b-instant",
+        messages=[
+            {"role": "system", "content": system_prompt},
+            {"role": "user", "content": question}
+        ]
+    )
+
+    return response.choices[0].message.content
+
+# YOUTUBE TRANSCRIPT
+
+def extract_video_id(url):
+    pattern = r"(?:v=|youtu\.be/)([a-zA-Z0-9_-]{11})"
+    match = re.search(pattern, url)
+    return match.group(1) if match else None
+
+
+def get_youtube_transcript(url):
+    video_id = extract_video_id(url)
+
+    if not video_id:
+        return "Invalid YouTube URL."
+
+    try:
+        api = YouTubeTranscriptApi()
+        transcript = api.fetch(video_id)
+        full_text = " ".join([entry.text for entry in transcript])
+        return full_text
+    except:
+        return "No transcript available for this video."
+
+
+def youtube_qa(video_url, question):
+    transcript = get_youtube_transcript(video_url)
+
+    if transcript.startswith("No") or transcript.startswith("Invalid"):
+        return transcript
+
+    system_prompt = f"""
+You are a helpful assistant.
+Answer ONLY using this transcript.
+
+Transcript:
+{transcript[:6000]}
+"""
+
+    response = client.chat.completions.create(
+        model="llama-3.1-8b-instant",
+        messages=[
+            {"role": "system", "content": system_prompt},
+            {"role": "user", "content": question}
+        ]
+    )
+
+    return response.choices[0].message.content
+
+
+# VERSION 3 — MEMORY CHAT
+
+def chat_with_memory(user_message, preference_text):
+
+    global conversation_history, user_preferences
+
+    if preference_text and preference_text.strip():
+        user_preferences["style"] = preference_text
+        save_json(PREF_FILE, user_preferences)
+
+    system_prompt = f"""
+You are a helpful AI assistant.
+
+User Preferences:
+{user_preferences.get("style", "Default")}
+
+Follow the preferred style in all responses.
+Maintain conversational memory.
+"""
+
+    messages = [{"role": "system", "content": system_prompt}]
+    messages.extend(conversation_history)
+    messages.append({"role": "user", "content": user_message})
+
+    response = client.chat.completions.create(
+        model="llama-3.1-8b-instant",
+        messages=messages
+    )
+
+    assistant_reply = response.choices[0].message.content
+
+    conversation_history.append({"role": "user", "content": user_message})
+    conversation_history.append({"role": "assistant", "content": assistant_reply})
+
+    save_json(CHAT_FILE, conversation_history)
+
+    return assistant_reply
+
+
+def clear_memory():
+    global conversation_history
+    conversation_history = []
+    save_json(CHAT_FILE, [])
+    return []
+
+
+# GRADIO MULTI-TAB UI
+
+with gr.Blocks() as demo:
+
+    gr.Markdown("# 🚀 Full AI Assistant (V1 + V2 + V3)")
+
+    # TAB 1
+    with gr.Tab("🌐 Website Scraper Q&A"):
+        url_input = gr.Textbox(label="Enter Goodreads URL",
+                               value="https://www.goodreads.com/list/show/1.Best_Books_Ever")
+        question_input = gr.Textbox(label="Ask your question")
+        output1 = gr.Textbox(label="Answer")
+        btn1 = gr.Button("Submit")
+
+        btn1.click(qa_bot, inputs=[url_input, question_input], outputs=output1)
+
+    # TAB 2
+    with gr.Tab("🎥 YouTube Transcript Q&A"):
+        video_input = gr.Textbox(label="Enter YouTube URL")
+        yt_question = gr.Textbox(label="Ask your question")
+        output2 = gr.Textbox(label="Answer")
+        btn2 = gr.Button("Submit")
+
+        btn2.click(youtube_qa, inputs=[video_input, yt_question], outputs=output2)
+
+    # TAB 3
+    with gr.Tab("🧠 Multi-Turn Assistant (Persistent Memory)"):
+
+        chatbot = gr.Chatbot(label="Conversation", value=conversation_history)
+
+        preference_input = gr.Textbox(
+            label="User Preferences (Optional)",
+            placeholder="Example: Respond formally / Be concise / Use bullet points"
+        )
+
+        user_message = gr.Textbox(label="Your Message")
+        send_btn = gr.Button("Send")
+        clear_btn = gr.Button("Clear Memory")
+
+        def chat_interface(user_message, preference_text, chat_display):
+            if not user_message.strip():
+                return "", chat_display
+
+            assistant_reply = chat_with_memory(user_message, preference_text)
+
+            chat_display.append({"role": "user", "content": user_message})
+            chat_display.append({"role": "assistant", "content": assistant_reply})
+
+            return "", chat_display
+
+        send_btn.click(
+            chat_interface,
+            inputs=[user_message, preference_input, chatbot],
+            outputs=[user_message, chatbot]
+        )
+
+        clear_btn.click(
+            clear_memory,
+            outputs=chatbot
+        )
+
+if __name__ == "__main__":
+    demo.launch()

chat_history.json

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+[
+    {
+        "role": "user",
+        "content": "can you tell me my name"
+    },
+    {
+        "role": "assistant",
+        "content": "I don't have any information about your name. We just started our conversation, and I'm a new AI each time you interact with me. I don't have any prior knowledge or memory of previous conversations. \n\nHowever, I can ask: If you'd like, you can tell me your name, and I can remember it and use it in our conversation."
+    }
+]

preferences.json

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+{
+    "style": "provide all ways python code"
+}

requirements.txt

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+gradio
+groq
+requests
+beautifulsoup4
+python-dotenv
+youtube-transcript-api