Update app.py

app.py

@@ -494,13 +494,166 @@
 
 
 
+# import nest_asyncio
+# import streamlit as st
+# import os
+# import requests
+# from youtube_transcript_api import YouTubeTranscriptApi
+# from groq import Groq
+# from bs4 import BeautifulSoup
+# from sentence_transformers import SentenceTransformer
+# import chromadb
+# from chromadb.utils.embedding_functions import SentenceTransformerEmbeddingFunction
+
+# nest_asyncio.apply()
+
+# # --- CONFIGURATION ---
+# YOUTUBE_API_KEY = os.environ.get("YOUTUBE_API_KEY")
+# GROQ_API_KEY = os.environ.get("GROQ_API_KEY")
+# channel_id="UCsv3kmQ5k1eIRG2R9mWN-QA"  #channelId
+
+# BASE_URL = "https://icode.guru"
+
+# groq_client = Groq(api_key=GROQ_API_KEY)
+# embedding_function = SentenceTransformerEmbeddingFunction("all-MiniLM-L6-v2")
+
+# chroma_client = chromadb.Client()
+# collection = chroma_client.get_or_create_collection("icodeguru_knowledge", embedding_function=embedding_function)
+
+# # --- Search persistent vector DB ---
+# def search_vector_data(query):
+#     results = collection.query(query_texts=[query], n_results=3)
+#     if results and results["documents"]:
+#         return "\n\n".join([doc for doc in results["documents"][0]])
+#     return None
+
+# # --- Fetch recent video IDs from YouTube channel ---
+# def get_latest_video_ids(channel_id, max_results=5):
+#     url = f"https://www.googleapis.com/youtube/v3/search?key={YOUTUBE_API_KEY}&channelId={channel_id}&part=snippet,id&order=date&maxResults={max_results}"
+#     response = requests.get(url)
+#     videos = response.json().get('items', [])
+    
+#     valid_videos = []
+#     for v in videos:
+#         if v['id']['kind'] == 'youtube#video':
+#             title = v['snippet']['title']
+#             channel_title = v['snippet']['channelTitle']
+#             video_id = v['id']['videoId']
+#             if "icodeguru" in channel_title.lower():
+#                 valid_videos.append((video_id, title))
+#     return valid_videos
+
+# # --- Get video transcripts ---
+# def get_video_transcripts(video_info):
+#     results = []
+#     for vid, title in video_info:
+#         try:
+#             transcript = YouTubeTranscriptApi.get_transcript(vid)
+#             text = " ".join([t['text'] for t in transcript])
+#             video_link = f"https://www.youtube.com/watch?v={vid}"
+#             results.append({
+#                 "video_id": vid,
+#                 "title": title,
+#                 "link": video_link,
+#                 "transcript": text
+#             })
+#         except:
+#             continue
+#     return results
+
+# # --- Scrape icode.guru ---
+# def scrape_icodeguru(base_url=BASE_URL, max_pages=5):
+#     visited = set()
+#     blocks = []
+
+#     def crawl(url):
+#         if url in visited or len(visited) >= max_pages:
+#             return
+#         visited.add(url)
+#         try:
+#             res = requests.get(url, timeout=10)
+#             soup = BeautifulSoup(res.content, "html.parser")
+#             page_text = soup.get_text(separator=" ", strip=True)
+#             if len(page_text) > 100:
+#                 blocks.append(f"[{url}]({url}):\n{page_text[:1500]}")
+#             for link in soup.find_all("a", href=True):
+#                 href = link['href']
+#                 if href.startswith("/"):
+#                     href = base_url + href
+#                 if href.startswith(base_url):
+#                     crawl(href)
+#         except:
+#             pass
+
+#     crawl(base_url)
+#     return blocks
+
+# # --- Ask Groq ---
+# def ask_groq(context, question):
+#     messages = [
+#         {"role": "system", "content": "You are a helpful assistant. Always provide relevant video and website links if possible."},
+#         {"role": "user", "content": f"Context:\n{context}\n\nQuestion: {question}\nAnswer (include links):"}
+#     ]
+#     chat_completion = groq_client.chat.completions.create(
+#         model="llama3-8b-8192",
+#         messages=messages,
+#     )
+#     return chat_completion.choices[0].message.content.strip()
+
+# #--- STREAMLIT APP ---
+# def main():
+#     st.set_page_config(page_title="EduBot for iCodeGuru", layout="wide")
+#     st.title("🎓 EduBot for @icodeguru0")
+#     st.markdown("Ask anything based on the latest YouTube videos and website content of [icode.guru](https://icode.guru).")
+
+#     user_question = st.text_input("💬 Ask your question:")
+
+#     if user_question:
+#         # Try vector DB first
+#         vector_context = search_vector_data(user_question)
+#         if vector_context:
+#             with st.spinner("🧠 Answering from knowledge base..."):
+#                 answer = ask_groq(vector_context, user_question)
+#                 st.success(answer)
+#         else:
+#             # Fallback to real-time data
+#             with st.spinner("📺 Fetching YouTube videos..."):
+#                 video_info = get_latest_video_ids(channel_id, max_results=5)
+#                 transcripts = get_video_transcripts(video_info)
+
+#             yt_context = ""
+#             relevant_links = []
+#             for vid in transcripts:
+#                 yt_context += f"\n\n[Video: {vid['title']}]({vid['link']}):\n{vid['transcript'][:1500]}"
+#                 if user_question.lower() in vid['transcript'].lower():
+#                     relevant_links.append(vid['link'])
+
+#             with st.spinner("🌐 Scraping icode.guru..."):
+#                 site_blocks = scrape_icodeguru(BASE_URL, max_pages=5)
+#                 site_context = "\n\n".join(site_blocks)
+
+#             full_context = yt_context + "\n\n" + site_context
+
+#             with st.spinner("🧠 Thinking..."):
+#                 answer = ask_groq(full_context, user_question)
+#                 st.success(answer)
+
+#             if relevant_links:
+#                 st.markdown("### 🔗 Related YouTube Links")
+#                 for link in relevant_links:
+#                     st.markdown(f"- [Watch Video]({link})")
+
+#     st.markdown("---")
+#     st.caption("Powered by YouTube, iCodeGuru, and Groq")
+
+# if __name__ == "__main__":
+#     main()
+
+
 import nest_asyncio
 import streamlit as st
 import os
-import requests
-from youtube_transcript_api import YouTubeTranscriptApi
 from groq import Groq
-from bs4 import BeautifulSoup
 from sentence_transformers import SentenceTransformer
 import chromadb
 from chromadb.utils.embedding_functions import SentenceTransformerEmbeddingFunction
@@ -508,15 +661,10 @@ from chromadb.utils.embedding_functions import SentenceTransformerEmbeddingFunct
 nest_asyncio.apply()
 
 # --- CONFIGURATION ---
-YOUTUBE_API_KEY = os.environ.get("YOUTUBE_API_KEY")
 GROQ_API_KEY = os.environ.get("GROQ_API_KEY")
-channel_id="UCsv3kmQ5k1eIRG2R9mWN-QA"  #channelId
-
-BASE_URL = "https://icode.guru"
-
 groq_client = Groq(api_key=GROQ_API_KEY)
-embedding_function = SentenceTransformerEmbeddingFunction("all-MiniLM-L6-v2")
 
+embedding_function = SentenceTransformerEmbeddingFunction("all-MiniLM-L6-v2")
 chroma_client = chromadb.Client()
 collection = chroma_client.get_or_create_collection("icodeguru_knowledge", embedding_function=embedding_function)
 
@@ -527,72 +675,11 @@ def search_vector_data(query):
         return "\n\n".join([doc for doc in results["documents"][0]])
     return None
 
-# --- Fetch recent video IDs from YouTube channel ---
-def get_latest_video_ids(channel_id, max_results=5):
-    url = f"https://www.googleapis.com/youtube/v3/search?key={YOUTUBE_API_KEY}&channelId={channel_id}&part=snippet,id&order=date&maxResults={max_results}"
-    response = requests.get(url)
-    videos = response.json().get('items', [])
-    
-    valid_videos = []
-    for v in videos:
-        if v['id']['kind'] == 'youtube#video':
-            title = v['snippet']['title']
-            channel_title = v['snippet']['channelTitle']
-            video_id = v['id']['videoId']
-            if "icodeguru" in channel_title.lower():
-                valid_videos.append((video_id, title))
-    return valid_videos
-
-# --- Get video transcripts ---
-def get_video_transcripts(video_info):
-    results = []
-    for vid, title in video_info:
-        try:
-            transcript = YouTubeTranscriptApi.get_transcript(vid)
-            text = " ".join([t['text'] for t in transcript])
-            video_link = f"https://www.youtube.com/watch?v={vid}"
-            results.append({
-                "video_id": vid,
-                "title": title,
-                "link": video_link,
-                "transcript": text
-            })
-        except:
-            continue
-    return results
-
-# --- Scrape icode.guru ---
-def scrape_icodeguru(base_url=BASE_URL, max_pages=5):
-    visited = set()
-    blocks = []
-
-    def crawl(url):
-        if url in visited or len(visited) >= max_pages:
-            return
-        visited.add(url)
-        try:
-            res = requests.get(url, timeout=10)
-            soup = BeautifulSoup(res.content, "html.parser")
-            page_text = soup.get_text(separator=" ", strip=True)
-            if len(page_text) > 100:
-                blocks.append(f"[{url}]({url}):\n{page_text[:1500]}")
-            for link in soup.find_all("a", href=True):
-                href = link['href']
-                if href.startswith("/"):
-                    href = base_url + href
-                if href.startswith(base_url):
-                    crawl(href)
-        except:
-            pass
-
-    crawl(base_url)
-    return blocks
-
 # --- Ask Groq ---
 def ask_groq(context, question):
     messages = [
-        {"role": "system", "content": "You are a helpful assistant. Always provide relevant video and website links if possible."},
-        {"role": "user", "content": f"Context:\n{context}\n\nQuestion: {question}\nAnswer (include links):"}
+        {"role": "system", "content": "You are a helpful assistant. Answer only using the provided context."},
+        {"role": "user", "content": f"Context:\n{context}\n\nQuestion: {question}\nAnswer:"}
     ]
     chat_completion = groq_client.chat.completions.create(
         model="llama3-8b-8192",
@@ -600,127 +687,28 @@ def ask_groq(context, question):
     )
     return chat_completion.choices[0].message.content.strip()
 
-#--- STREAMLIT APP ---
+# --- Streamlit App ---
 def main():
     st.set_page_config(page_title="EduBot for iCodeGuru", layout="wide")
     st.title("🎓 EduBot for @icodeguru0")
-    st.markdown("Ask anything based on the latest YouTube videos and website content of [icode.guru](https://icode.guru).")
+    st.markdown("Ask anything based on pre-loaded iCodeGuru knowledge (YouTube, JSON, and site data).")
 
     user_question = st.text_input("💬 Ask your question:")
 
     if user_question:
-        # Try vector DB first
-        vector_context = search_vector_data(user_question)
-        if vector_context:
-            with st.spinner("🧠 Answering from knowledge base..."):
-                answer = ask_groq(vector_context, user_question)
+        with st.spinner("🔍 Searching knowledge base..."):
+            context = search_vector_data(user_question)
+
+        if context:
+            with st.spinner("🤖 Generating answer..."):
+                answer = ask_groq(context, user_question)
                 st.success(answer)
         else:
-            # Fallback to real-time data
-            with st.spinner("📺 Fetching YouTube videos..."):
-                video_info = get_latest_video_ids(channel_id, max_results=5)
-                transcripts = get_video_transcripts(video_info)
-
-            yt_context = ""
-            relevant_links = []
-            for vid in transcripts:
-                yt_context += f"\n\n[Video: {vid['title']}]({vid['link']}):\n{vid['transcript'][:1500]}"
-                if user_question.lower() in vid['transcript'].lower():
-                    relevant_links.append(vid['link'])
-
-            with st.spinner("🌐 Scraping icode.guru..."):
-                site_blocks = scrape_icodeguru(BASE_URL, max_pages=5)
-                site_context = "\n\n".join(site_blocks)
-
-            full_context = yt_context + "\n\n" + site_context
-
-            with st.spinner("🧠 Thinking..."):
-                answer = ask_groq(full_context, user_question)
-                st.success(answer)
-
-            if relevant_links:
-                st.markdown("### 🔗 Related YouTube Links")
-                for link in relevant_links:
-                    st.markdown(f"- [Watch Video]({link})")
+            st.warning("⚠️ No relevant answer found in the embedded knowledge.")
 
     st.markdown("---")
-    st.caption("Powered by YouTube, iCodeGuru, and Groq")
+    st.caption("Powered by ChromaDB 🧠 and Groq ⚡")
 
 if __name__ == "__main__":
     main()
 
-
-
-
-    
-# import os
-# import streamlit as st
-# import nest_asyncio
-# import chromadb
-# from groq import Groq
-# from sentence_transformers import SentenceTransformer
-# from chromadb.utils.embedding_functions import SentenceTransformerEmbeddingFunction
-
-# # --- Setup ---
-# nest_asyncio.apply()
-# GROQ_API_KEY = os.getenv("GROQ_API_KEY") or "your-groq-api-key-here"
-# groq_client = Groq(api_key=GROQ_API_KEY)
-# embed_model = "all-MiniLM-L6-v2"
-# embedding_function = SentenceTransformerEmbeddingFunction(embed_model)
-# chroma_client = chromadb.Client()
-# collection = chroma_client.get_or_create_collection("icodeguru_knowledge", embedding_function=embedding_function)
-
-# # --- Load Uploaded Files into ChromaDB ---
-# def process_uploaded_files(uploaded_files):
-#     for file in uploaded_files:
-#         content = file.read().decode("utf-8", errors="ignore")
-#         doc_id = f"{file.name}_{abs(hash(content))}"
-#         try:
-#             collection.add(documents=[content], metadatas=[{"source": file.name}], ids=[doc_id])
-#         except chromadb.errors.IDAlreadyExistsError:
-#             pass
-#     st.success("✅ Files processed and stored in vector DB.")
-
-# # --- Search Vector DB ---
-# def search_context(query):
-#     results = collection.query(query_texts=[query], n_results=3)
-#     if results and results["documents"]:
-#         return "\n\n".join(results["documents"][0])
-#     return None
-
-# # --- Ask Groq LLaMA-3 with Retrieved Context ---
-# def ask_groq(context, question):
-#     messages = [
-#         {"role": "system", "content": "You are a helpful assistant. Only answer using the provided context."},
-#         {"role": "user", "content": f"Context:\n{context}\n\nQuestion: {question}"}
-#     ]
-#     response = groq_client.chat.completions.create(model="llama3-8b-8192", messages=messages)
-#     return response.choices[0].message.content.strip()
-
-# # --- Streamlit UI ---
-# def main():
-#     st.set_page_config(page_title="📚 EduBot for iCodeGuru", layout="wide")
-#     st.title("🤖 EduBot for iCodeGuru")
-#     st.markdown("Ask anything based on uploaded knowledge files (text, notes, JSON, etc).")
-
-#     uploaded_files = st.file_uploader("📂 Upload Knowledge Files", type=["txt", "json", "md"], accept_multiple_files=True)
-#     if uploaded_files:
-#         process_uploaded_files(uploaded_files)
-
-#     user_question = st.text_input("💬 Ask your question:")
-#     if user_question:
-#         with st.spinner("🔍 Searching knowledge base..."):
-#             context = search_context(user_question)
-
-#         if context:
-#             with st.spinner("🤖 Generating answer..."):
-#                 answer = ask_groq(context, user_question)
-#                 st.success(answer)
-#         else:
-#             st.warning("⚠️ No relevant answer found in uploaded files.")
-
-#     st.markdown("---")
-#     st.caption("🔗 Powered by ChromaDB, Groq API, and Sentence Transformers")
-
-# if __name__ == "__main__":
-#     main()