diff --git a/llama-demo-apps/Llama2_Gradio.ipynb b/llama-demo-apps/Llama2_Gradio.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..1a1ecc6f2e41a2264b7519f1bed28003b21a2700
--- /dev/null
+++ b/llama-demo-apps/Llama2_Gradio.ipynb
@@ -0,0 +1,104 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "id": "928041cc",
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "Init param `input` is deprecated, please use `model_kwargs` instead.\n"
+ ]
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Running on local URL: http://127.0.0.1:7860\n",
+ "\n",
+ "To create a public link, set `share=True` in `launch()`.\n"
+ ]
+ },
+ {
+ "data": {
+ "text/html": [
+ "<div><iframe src=\"http://127.0.0.1:7860/\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
+ ],
+ "text/plain": [
+ "<IPython.core.display.HTML object>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "text/plain": []
+ },
+ "execution_count": 1,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "from langchain.schema import AIMessage, HumanMessage\n",
+ "import gradio as gr\n",
+ "from langchain.llms import Replicate\n",
+ "import os\n",
+ "\n",
+ "os.environ[\"REPLICATE_API_TOKEN\"] = \"<your replicate api token>\"\n",
+ "\n",
+ "llama2_13b_chat = \"meta/llama-2-13b-chat:f4e2de70d66816a838a89eeeb621910adffb0dd0baba3976c96980970978018d\"\n",
+ "\n",
+ "llm = Replicate(\n",
+ " model=llama2_13b_chat,\n",
+ " input={\"temperature\": 0.01, \"max_length\": 2000, \"top_p\": 1},\n",
+ ")\n",
+ "\n",
+ "\n",
+ "def predict(message, history):\n",
+ " history_langchain_format = []\n",
+ " for human, ai in history:\n",
+ " history_langchain_format.append(HumanMessage(content=human))\n",
+ " history_langchain_format.append(AIMessage(content=ai))\n",
+ " history_langchain_format.append(HumanMessage(content=message))\n",
+ " gpt_response = llm(message) #history_langchain_format)\n",
+ " return gpt_response#.content\n",
+ "\n",
+ "gr.ChatInterface(predict).launch()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "5f21f5a4",
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3 (ipykernel)",
+ "language": "python",
+ "name": "python3"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.8.18"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/llama-demo-apps/README.md b/llama-demo-apps/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..1fd67dca8a02c2f1868375ad1ce05b7c25a6e12e
--- /dev/null
+++ b/llama-demo-apps/README.md
@@ -0,0 +1,83 @@
+# Llama2 Demo Apps
+
+This folder showcases the Llama2-powered apps.
+
+## HelloLlama - Quickstart in Running Llama2
+
+This demo app shows how to use [LangChain](https://github.com/langchain-ai/langchain), an open-source framework for building LLM apps, to quickly build Llama2-power apps: to ask Llama2 general or custom-data-specific natural language questions and get answers back, in both single-turn QA mode and multi-turn chat mode. It has three versions:
+
+### Running Llama2 locally on Mac
+To run Llama2 locally on Mac using [llama-cpp-python](https://github.com/abetlen/llama-cpp-python), open a Terminal, execute the commands below to install required packages and launch the notebook to run each cell - notice the cells starting with calling `from langchain.chains import ConversationalRetrievalChain` shows how to have a multi-turn dialog with chat history passed to the next question.
+
+```
+conda create -n llama_demo_apps python=3.8
+conda activate llama_demo_apps
+CMAKE_ARGS="-DLLAMA_METAL=on" FORCE_CMAKE=1 pip install llama-cpp-python
+pip install langchain
+pip install sentence-transformers
+pip install docarray
+pip install jupyter
+cd <your_work_folder>
+git clone https://github.com/facebookresearch/llama-recipes
+cd llama-recipes/llama-demo-apps
+jupyter notebook
+```
+
+Then in the launched browser, select the notebook `HelloLlamaLocal.ipynb` and run each cell - before running cell #3, you need to download the 6GB quantized Llama2-13b-chat model file [here](https://drive.google.com/file/d/1afPv3HOy73BE2MoYCgYJvBDeQNa9rZbj/view?usp=sharing) first, then change the replace <path-to-llama-2-13b-chat-ggml-model-q4_0.gguf> with the path to your downloaded `ggml-model-q4_0.gguf` file.
+
+### Running Llama2 in Google Colab
+To run Llama2 in Google Colab using [llama-cpp-python](https://github.com/abetlen/llama-cpp-python), click the Colab notebook link [here](https://colab.research.google.com/drive/1-uBXt4L-6HNS2D8Iny2DwUpVS4Ub7jnk?usp=sharing) and download the quantized Llama2-13b-chat model [here](https://drive.google.com/file/d/1afPv3HOy73BE2MoYCgYJvBDeQNa9rZbj/view?usp=sharing) and upload it, as well as the nba.csv file in this repo to your Google drive, so you can access those files in cells #6 and #14. Then run each cell. Notice on the Colab T4 GPU, the inference in cell #18 took more than 20 minnutes to return; running the notebook locally on M1 MBP took about 20 seconds.
+
+### Running Llama2 Hosted in the Cloud
+[The Cloud version](HelloLlamaCloud.ipynb) uses LangChain with Llama2 hosted in the cloud on [Replicate](https://replicate.com). The demo shows how to use LangChain to ask Llama2 questions about **unstructured** data stored in a PDF.
+
+[Note on using Replicate](#replicate_note) To run the demo app, you'll need to first sign in with Replicate with your github account, then create a free API token [here](https://replicate.com/account/api-tokens) that you can use for a while. After the free trial ends, you'll need to enter billing info to continue to use Llama2 hosted on Replicate - according to Replicate's [Run time and cost](https://replicate.com/meta/llama-2-13b-chat) for the Llama2-13b-chat model used in our demo apps, the model "costs $0.000725 per second. Predictions typically complete within 10 seconds." This means each call to the Llama2-13b-chat model costs less than $0.01 if the call completes within 10 seconds. If you want absolutely no costs, you can refer to the section "Running Llama2 locally on Mac" above.
+
+## [NBA2023-24](StructuredLlama.ipynb): Ask Llama2 about Structured Data
+This demo app shows how to use LangChain and Llama2 to let users ask questions about **structured** data stored in a SQL DB. As the 2023-24 NBA season is around the corner, we use the NBA roster info saved in a SQLite DB to show you how to ask Llama2 questions about your favorite teams or players.
+
+## [VideoSummary](VideoSummary.ipynb):
+This demo app uses Llama2 to return a text summary of a YouTube video.
+
+## [BreakingNews](LiveSearch.ipynb): Ask Llama2 about Live Data
+This demo app shows how to perform live data augmented generation tasks with Llama2 and [LlamaIndex](https://github.com/run-llama/llama_index), another leading open-source framework for building LLM apps: it uses the [You.com serarch API](https://documentation.you.com/quickstart) to get breaking news and ask Llama2 about them.
+
+## Quick Web UI for Llama2 Chat
+If you prefer to see Llama2 in action in a web UI, instead of the notebooks above, you can try one of the two methods:
+
+### Running [Streamlit](https://streamlit.io/) with Llama2
+Open a Terminal, run the following commands:
+```
+pip install streamlit langchain replicate
+git clone https://github.com/facebookresearch/llama-recipes
+cd llama-recipes/llama-demo-apps
+```
+
+Replace the `<your replicate api token>` in `streamlit_llama2.py` with your API token created [here](https://replicate.com/account/api-tokens) - for more info, see the note [above](#replicate_note).
+
+Then run the command `streamlit run streamlit_llama2.py` and you'll see on your browser the following UI with question and answer - you can enter new text question, click Submit, and see Llama2's answer:
+
+
+
+
+### Running [Gradio](https://www.gradio.app/) with Llama2
+
+To see how to query Llama2 and get answers with the Gradio UI both from the notebook and web, just launch the notebook `Llama2_Gradio.ipynb`, replace the `<your replicate api token>` with your API token created [here](https://replicate.com/account/api-tokens) - for more info, see the note [above](#replicate_note).
+
+enter your question, click Submit. You'll see in the notebook or a browser with URL http://127.0.0.1:7860 the following UI:
+
+
+
+## LICENSE
+
+THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
+AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
+IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
+ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
+LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
+CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
+SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
+INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
+CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
+ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
+POSSIBILITY OF SUCH DAMAGE.
\ No newline at end of file
diff --git a/llama-demo-apps/llama2-streamlit.png b/llama-demo-apps/llama2-streamlit.png
new file mode 100644
index 0000000000000000000000000000000000000000..74f886295df9310b9ed981a6032275cfbf1d3482
Binary files /dev/null and b/llama-demo-apps/llama2-streamlit.png differ
diff --git a/llama-demo-apps/llama2-streamlit2.png b/llama-demo-apps/llama2-streamlit2.png
new file mode 100644
index 0000000000000000000000000000000000000000..b0c464cb7b1ac09cde854af16158c5462dab7038
Binary files /dev/null and b/llama-demo-apps/llama2-streamlit2.png differ
diff --git a/llama-demo-apps/llm_log1.png b/llama-demo-apps/llm_log1.png
new file mode 100644
index 0000000000000000000000000000000000000000..118d0ca2d644fb985d25f583d1f8d29f249c9133
Binary files /dev/null and b/llama-demo-apps/llm_log1.png differ
diff --git a/llama-demo-apps/streamlit_llama2.py b/llama-demo-apps/streamlit_llama2.py
new file mode 100644
index 0000000000000000000000000000000000000000..1f88a555fd467304bdc9873d1def947c04a4c2ad
--- /dev/null
+++ b/llama-demo-apps/streamlit_llama2.py
@@ -0,0 +1,22 @@
+import streamlit as st
+from langchain.llms import Replicate
+import os
+
+st.title("Llama2-powered Streamlit App")
+
+with st.sidebar:
+ os.environ["REPLICATE_API_TOKEN"] = "<your replicate api token>"
+
+def generate_response(input_text):
+ llama2_13b_chat = "meta/llama-2-13b-chat:f4e2de70d66816a838a89eeeb621910adffb0dd0baba3976c96980970978018d"
+
+ llm = Replicate(
+ model=llama2_13b_chat,
+ input={"temperature": 0.01, "max_length": 2000, "top_p": 1},
+ )
+ st.info(llm(input_text))
+
+with st.form("my_form"):
+ text = st.text_area("Enter text:", "What is Generative AI?")
+ submitted = st.form_submit_button("Submit")
+ generate_response(text)
\ No newline at end of file