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README.md

@@ -1,12 +1,10 @@
 ---
-title: VYouTubeVideoChatRobot
-emoji: 👁
-colorFrom: purple
+title: Ask AI over Youtube video
+emoji: 💽
+colorFrom: indigo
 colorTo: blue
 sdk: streamlit
-sdk_version: 1.29.0
-app_file: app.py
-pinned: false
+pinned: true
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

@@ -0,0 +1,237 @@
+import os
+import logging
+from typing import Any, List, Mapping, Optional
+from langchain.llms import HuggingFaceHub
+from gradio_client import Client
+from langchain.schema import Document
+from langchain.text_splitter import RecursiveCharacterTextSplitter
+from langchain.vectorstores import FAISS
+from langchain.embeddings.huggingface import HuggingFaceEmbeddings
+from langchain.callbacks.manager import CallbackManagerForLLMRun
+from langchain.llms.base import LLM
+from langchain.chains import RetrievalQA
+from langchain.prompts import PromptTemplate
+import streamlit as st
+from pytube import YouTube
+# import replicate
+
+DESCRIPTION = """
+<div class="max-w-full overflow-auto">
+    <table>
+        <thead>
+            <tr>
+                <th>Model</th>
+                <th>Llama2</th>
+                <th>Llama2-hf</th>
+                <th>Llama2-chat</th>
+                <th>Llama2-chat-hf</th>
+            </tr>
+        </thead>
+        <tbody>
+            <tr>
+                <td>7B</td>
+                <td><a rel="noopener nofollow" href="https://huggingface.co/meta-llama/Llama-2-7b">Link</a></td>
+                <td><a rel="noopener nofollow" href="https://huggingface.co/meta-llama/Llama-2-7b-hf">Link</a></td>
+                <td><a rel="noopener nofollow" href="https://huggingface.co/meta-llama/Llama-2-7b-chat">Link</a></td>
+                <td><a rel="noopener nofollow" href="https://huggingface.co/meta-llama/Llama-2-7b-chat-hf">Link</a></td>
+            </tr>
+            <tr>
+                <td>13B</td>
+                <td><a rel="noopener nofollow" href="https://huggingface.co/meta-llama/Llama-2-13b">Link</a></td>
+                <td><a rel="noopener nofollow" href="https://huggingface.co/meta-llama/Llama-2-13b-hf">Link</a></td>
+                <td><a rel="noopener nofollow" href="https://huggingface.co/meta-llama/Llama-2-13b-chat">Link</a></td>
+                <td><a rel="noopener nofollow" href="https://huggingface.co/meta-llama/Llama-2-13b-chat-hf">Link</a></td>
+            </tr>
+            <tr>
+                <td>70B</td>
+                <td><a rel="noopener nofollow" href="https://huggingface.co/meta-llama/Llama-2-70b">Link</a></td>
+                <td><a rel="noopener nofollow" href="https://huggingface.co/meta-llama/Llama-2-70b-hf">Link</a></td>
+                <td><a rel="noopener nofollow" href="https://huggingface.co/meta-llama/Llama-2-70b-chat">Link</a></td>
+                <td><a rel="noopener nofollow" href="https://huggingface.co/meta-llama/Llama-2-70b-chat-hf">Link</a></td>
+            </tr>
+        </tbody>
+    </table>
+</div>
+openai/whisper-large-v3
+"""
+
+models = {
+    "Llama2-70b": {
+        "model_link": "https://huggingface.co/meta-llama/Llama-2-70b",
+        "chat_link": "https://ysharma-explore-llamav2-with-tgi.hf.space/",
+    },
+    "Llama2-13b": {
+        "model_link": "https://huggingface.co/meta-llama/Llama-2-13b",
+        "chat_link": "https://huggingface-projects-llama-2-13b-chat.hf.space/",
+    }
+}
+
+DESCRIPTION = """
+Welcome to the **YouTube Video Chatbot** powered by Llama-2 models. Here's what you can do:
+- **Transcribe & Understand**: Provide any YouTube video URL, and our system will transcribe it. Our advanced NLP model will then understand the content, ready to answer your questions.
+- **Ask Anything**: Based on the video's content, ask any question, and get instant, context-aware answers.
+To get started, simply paste a YouTube video URL and select a model in the sidebar, then start chatting with the model about the video's content. Enjoy the experience!
+"""
+st.title("YouTube Video Chatbot")
+st.markdown(DESCRIPTION)
+
+def get_video_title(youtube_url: str) -> str:
+    yt = YouTube(youtube_url)
+    embed_url = f"https://www.youtube.com/embed/{yt.video_id}"
+    embed_html = f'<iframe src="{embed_url}" frameborder="0" allowfullscreen></iframe>'
+    return yt.title, embed_html
+
+def transcribe_video(youtube_url: str, path: str) -> List[Document]:
+    """
+    Transcribe a video and return its content as a Document.
+    """
+    logging.info(f"Transcribing video: {youtube_url}")
+    client = Client("https://sanchit-gandhi-whisper-large-v2.hf.space/")
+    result = client.predict(
+    				youtube_url,	
+    				"transcribe",	
+    				api_name="/predict_2"
+    )
+    return [Document(page_content=result[1], metadata=dict(page=1))]
+
+# def predict(message: str, system_prompt: str = '', temperature: float = 0.7, max_new_tokens: int = 1024,
+#             topp: float = 0.5, repetition_penalty: float = 1.2) -> Any:
+#     """
+#     Predict a response using a client.
+#     """
+#     client = Client("https://osanseviero-mistral-super-fast.hf.space/")
+#     response = client.predict(
+#         message,
+#         temperature,
+#         max_new_tokens,
+#         topp,
+#         repetition_penalty,
+#         api_name="/chat"
+#     )
+#     return response
+
+def predict(input, images = []):
+  client = Client("https://roboflow-gemini.hf.space/--replicas/bkd57/")
+  result = client.predict(
+      None,	
+      images,	
+      0.4,	
+      2048,	
+      "",	
+      32,	
+      1,	
+      [[input,None]],
+                api_name="/bot"
+  )
+  return result[0][1]
+  
+
+PATH = os.path.join(os.path.expanduser("~"), "Data")
+
+def initialize_session_state():
+    if "youtube_url" not in st.session_state:
+        st.session_state.youtube_url = ""
+    if "model_choice" not in st.session_state:
+        st.session_state.model_choice = "Llama2-70b"
+    if "setup_done" not in st.session_state:
+        st.session_state.setup_done = False
+    if "doneYoutubeurl" not in st.session_state:
+        st.session_state.doneYoutubeurl = ""
+
+def sidebar():
+    with st.sidebar:
+        st.markdown("# 💸 **Support our project**")
+        st.markdown("This money would be used for paying for API and supporting our team.")
+        st.markdown("[🔗 Link](https://send.monobank.ua/jar/4mvqDivxmP)")
+        
+        st.markdown("")
+
+        st.markdown("# Enter the YouTube Video URL below🔗")
+        st.session_state.youtube_url = st.text_input("YouTube Video URL:")
+
+        model_choice = st.radio("Choose a Model:", list(models.keys()))
+        st.session_state.model_choice = model_choice
+
+        if st.session_state.youtube_url:
+            # Get the video title
+            video_title, embed_html = get_video_title(st.session_state.youtube_url)
+            st.markdown(f"### {video_title}")
+
+            # Embed the video
+            st.markdown(embed_html, unsafe_allow_html=True)
+sidebar()
+
+initialize_session_state()
+
+text_splitter = RecursiveCharacterTextSplitter(chunk_size=1000, chunk_overlap=0)
+embeddings = HuggingFaceEmbeddings(model_name="sentence-transformers/all-MiniLM-l6-v2")
+
+prompt = PromptTemplate(
+    template="""Given the context about a video. Answer the user in a friendly and precise manner.
+    Context: {context}
+    Human: {question}
+    AI:""",
+    input_variables=["context", "question"]
+)
+
+class LlamaLLM(LLM):
+    """
+    Custom LLM class.
+    """
+
+    @property
+    def _llm_type(self) -> str:
+        return "custom"
+
+    def _call(self, prompt: str, stop: Optional[List[str]] = None, run_manager: Optional[CallbackManagerForLLMRun] = None) -> str:
+        model_link = models[st.session_state.model_choice]["chat_link"]
+        response = predict(prompt)
+        return response
+
+    @property
+    def _identifying_params(self) -> Mapping[str, Any]:
+        """Get the identifying parameters."""
+        return {}
+
+# Check if a new YouTube URL is provided
+if st.session_state.youtube_url != st.session_state.doneYoutubeurl:
+    st.session_state.setup_done = False
+
+if st.session_state.youtube_url and not st.session_state.setup_done:
+    with st.status("Transcribing video..."):
+        data = transcribe_video(st.session_state.youtube_url, PATH)
+
+    with st.status("Running Embeddings..."):
+        docs = text_splitter.split_documents(data)
+
+        docsearch = FAISS.from_documents(docs, embeddings)
+        retriever = docsearch.as_retriever()
+        retriever.search_kwargs["distance_metric"] = "cos"
+        retriever.search_kwargs["k"] = 4
+    with st.status("Running RetrievalQA..."):
+        llama_instance = LlamaLLM()
+        st.session_state.qa = RetrievalQA.from_chain_type(llm=llama_instance, chain_type="stuff", retriever=retriever, chain_type_kwargs={"prompt": prompt})
+
+    st.session_state.doneYoutubeurl = st.session_state.youtube_url
+    st.session_state.setup_done = True  # Mark the setup as done for this URL
+
+if "messages" not in st.session_state:
+    st.session_state.messages = []
+
+for message in st.session_state.messages:
+    with st.chat_message(message["role"], avatar=("🧑‍💻" if message["role"] == "human" else "🦙")):
+        st.markdown(message["content"])
+
+textinput = st.chat_input("Ask anything about the video...")
+
+if prompt := textinput:
+    st.chat_message("human", avatar="🧑‍💻").markdown(prompt)
+    st.session_state.messages.append({"role": "human", "content": prompt})
+    with st.status("Requesting Client..."):
+        video_title, _ = get_video_title(st.session_state.youtube_url)
+        additional_context = f"Given the context about a video titled '{video_title}' available at '{st.session_state.youtube_url}'."
+        response = st.session_state.qa.run(prompt + " " + additional_context)
+    with st.chat_message("assistant", avatar="🦙"):
+        st.markdown(response)
+    # Add assistant response to chat history
+    st.session_state.messages.append({"role": "assistant", "content": response})

requirements.txt

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+gradio-client
+langchain 
+sentence-transformers
+faiss-cpu
+pytube