split rag agent

Author: sbalandi

.ci/ignore_treon_docker.txt

@@ -64,7 +64,7 @@ notebooks/explainable-ai-1-basic/explainable-ai-1-basic.ipynb
 notebooks/explainable-ai-2-deep-dive/explainable-ai-2-deep-dive.ipynb
 notebooks/explainable-ai-3-map-interpretation/explainable-ai-3-map-interpretation.ipynb
 notebooks/phi-3-vision/phi-3-vision.ipynb
-notebooks/llm-agent-react/llm-agent-rag-llamaindex.ipynb
+notebooks/llm-agent-rag-llamaindex/llm-agent-rag-llamaindex.ipynb
 notebooks/stable-audio/stable-audio.ipynb
 notebooks/internvl2/internvl2.ipynb
 notebooks/qwen2-vl/qwen2-vl.ipynb
@@ -73,9 +73,9 @@ notebooks/stable-fast-3d/stable-fast-3d.ipynb
 notebooks/mllama-3.2/mllama-3.2.ipynb
 notebooks/sam2-image-segmentation/segment-anything-2-image.ipynb
 notebooks/pixtral/pixtral.ipynb
-notebooks/llm-agent-react/llm-agent-react.ipynb
+notebooks/llm-native-agent-react/llm-native-agent-react.ipynb
 notebooks/multilora-image-generation/multilora-image-generation.ipynb
-notebooks/llm-agent-react/llm-agent-react-langchain.ipynb
+notebooks/llm-agent-react-langchain/llm-agent-react-langchain.ipynb
 notebooks/multimodal-rag/multimodal-rag-llamaindex.ipynb
 notebooks/llm-rag-langchain/llm-rag-langchain-genai.ipynb
 notebooks/ltx-video/ltx-video.ipynb

.ci/skipped_notebooks.yml

@@ -375,7 +375,7 @@
         - macos-13
         - ubuntu-22.04
         - windows-2019
-- notebook: notebooks/llm-agent-react/llm-agent-rag-llamaindex.ipynb
+- notebook: notebooks/llm-agent-rag-llamaindex/llm-agent-rag-llamaindex.ipynb
   skips:
     - os:
       - macos-13
@@ -425,7 +425,7 @@
         - macos-13
         - ubuntu-22.04
         - windows-2019
-- notebook: notebooks/llm-agent-react/llm-agent-react.ipynb
+- notebook: notebooks/llm-native-agent-react/llm-native-agent-react.ipynb
   skips:
     - os:
         - macos-13
@@ -445,7 +445,7 @@
   skips:
     - os:
         - macos-13
-- notebook: notebooks/llm-agent-react/llm-agent-react-langchain.ipynb
+- notebook: notebooks/llm-agent-react-langchain/llm-agent-react-langchain.ipynb
   skips:
     - os:
         - macos-13

notebooks/README.md

@@ -71,9 +71,9 @@
 - [LLM Instruction-following pipeline with OpenVINO](./llm-question-answering/llm-question-answering.ipynb)
 - [Create an LLM-powered Chatbot using OpenVINO](./llm-chatbot/llm-chatbot.ipynb)
 - [Create an LLM-powered Chatbot using OpenVINO Generate API](./llm-chatbot/llm-chatbot-generate-api.ipynb)
-- [Create a native Agent with OpenVINO](./llm-agent-react/llm-agent-react.ipynb)
-- [Create ReAct Agent using OpenVINO and LangChain](./llm-agent-react/llm-agent-react-langchain.ipynb)
-- [Create an Agentic RAG using OpenVINO and LlamaIndex](./llm-agent-react/llm-agent-rag-llamaindex.ipynb)
+- [Create a native Agent with OpenVINO](./llm-native-agent-react/llm-native-agent-react.ipynb)
+- [Create ReAct Agent using OpenVINO and LangChain](./llm-agent-react-langchain/llm-agent-react-langchain.ipynb)
+- [Create an Agentic RAG using OpenVINO and LlamaIndex](./llm-agent-rag-llamaindex/llm-agent-rag-llamaindex.ipynb)
 - [Create Function-calling Agent using OpenVINO and Qwen-Agent](./llm-agent-functioncall/llm-agent-functioncall-qwen.ipynb)
 - [Visual-language assistant with LLaVA Next and OpenVINO](./llava-next-multimodal-chatbot/llava-next-multimodal-chatbot.ipynb)
 - [Visual-language assistant with LLaVA and Optimum Intel OpenVINO integration](./llava-multimodal-chatbot/llava-multimodal-chatbot-optimum.ipynb)
@@ -277,9 +277,9 @@
 - [LLM Instruction-following pipeline with OpenVINO](./llm-question-answering/llm-question-answering.ipynb)
 - [Create an LLM-powered Chatbot using OpenVINO](./llm-chatbot/llm-chatbot.ipynb)
 - [Create an LLM-powered Chatbot using OpenVINO Generate API](./llm-chatbot/llm-chatbot-generate-api.ipynb)
-- [Create a native Agent with OpenVINO](./llm-agent-react/llm-agent-react.ipynb)
-- [Create ReAct Agent using OpenVINO and LangChain](./llm-agent-react/llm-agent-react-langchain.ipynb)
-- [Create an Agentic RAG using OpenVINO and LlamaIndex](./llm-agent-react/llm-agent-rag-llamaindex.ipynb)
+- [Create a native Agent with OpenVINO](./llm-native-agent-react/llm-native-agent-react.ipynb)
+- [Create ReAct Agent using OpenVINO and LangChain](./llm-agent-react-langchain/llm-agent-react-langchain.ipynb)
+- [Create an Agentic RAG using OpenVINO and LlamaIndex](./llm-agent-rag-llamaindex/llm-agent-rag-llamaindex.ipynb)
 - [Create Function-calling Agent using OpenVINO and Qwen-Agent](./llm-agent-functioncall/llm-agent-functioncall-qwen.ipynb)
 - [Visual-language assistant with LLaVA Next and OpenVINO](./llava-next-multimodal-chatbot/llava-next-multimodal-chatbot.ipynb)
 - [Visual-language assistant with LLaVA and Optimum Intel OpenVINO integration](./llava-multimodal-chatbot/llava-multimodal-chatbot-optimum.ipynb)

notebooks/llm-agent-rag-llamaindex/README.md

@@ -0,0 +1,42 @@
+# Create an Agentic RAG using OpenVINO and LlamaIndex
+
+
+An **agent** is an automated reasoning and decision engine. It takes in a user input/query and can make internal decisions for executing that query in order to return the correct result. The key agent components can include, but are not limited to:
+
+- Breaking down a complex question into smaller ones
+- Choosing an external Tool to use + coming up with parameters for calling the Tool
+- Planning out a set of tasks
+- Storing previously completed tasks in a memory module
+
+[LlamaIndex](https://docs.llamaindex.ai/en/stable/) is a framework for building context-augmented generative AI applications with LLMs.LlamaIndex imposes no restriction on how you use LLMs. You can use LLMs as auto-complete, chatbots, semi-autonomous agents, and more. It just makes using them easier. You can build agents on top of your existing LlamaIndex RAG pipeline to empower it with automated decision capabilities. A lot of modules (routing, query transformations, and more) are already agentic in nature in that they use LLMs for decision making.
+
+![agentic-rag](https://github.com/openvinotoolkit/openvino_notebooks/assets/91237924/871cb90d-27fd-4a87-aa3c-f4cdb199a148)
+
+
+This example will demonstrate using RAG engines as a tool in an agent with OpenVINO and LlamaIndex.
+
+
+### Notebook Contents
+
+The tutorial consists of the following steps:
+
+- Prerequisites
+- Create tools
+- Create prompt template
+- Create LLM
+  - Download model
+  - Select inference device for LLM
+- Create agent
+- Run the agent
+- Interactive Demo
+  - Use built-in tool
+  - Create customized tools
+  - Create AI agent demo with Gradio UI
+
+## Installation Instructions
+
+This is a self-contained example that relies solely on its own code.</br>
+We recommend  running the notebook in a virtual environment. You only need a Jupyter server to start.
+For details, please refer to [Installation Guide](../../README.md).
+
+<img referrerpolicy="no-referrer-when-downgrade" src="https://static.scarf.sh/a.png?x-pxid=5b5a4db0-7875-4bfb-bdbd-01698b5b1a77&file=notebooks/llm-agent-rag-llamaindex/README.md" />

notebooks/llm-agent-react/llm-agent-rag-llamaindex.ipynb renamed to notebooks/llm-agent-rag-llamaindex/llm-agent-rag-llamaindex.ipynb

@@ -44,7 +44,7 @@
     "We recommend  running the notebook in a virtual environment. You only need a Jupyter server to start.\n",
     "For details, please refer to [Installation Guide](https://github.com/openvinotoolkit/openvino_notebooks/blob/latest/README.md#-installation-guide).\n",
     "\n",
-    "<img referrerpolicy=\"no-referrer-when-downgrade\" src=\"https://static.scarf.sh/a.png?x-pxid=5b5a4db0-7875-4bfb-bdbd-01698b5b1a77&file=notebooks/llm-agent-react/llm-agent-rag-llamaindex.ipynb\" />\n"
+    "<img referrerpolicy=\"no-referrer-when-downgrade\" src=\"https://static.scarf.sh/a.png?x-pxid=5b5a4db0-7875-4bfb-bdbd-01698b5b1a77&file=notebooks/llm-agent-rag-llamaindex/llm-agent-rag-llamaindex.ipynb\" />\n"
    ]
   },
   {

notebooks/llm-agent-react-langchain/README.md

@@ -0,0 +1,38 @@
+# Create ReAct Agent using OpenVINO and LangChain
+
+LLM are limited to the knowledge on which they have been trained and the additional knowledge provided as context, as a result, if a useful piece of information is missing the provided knowledge, the model cannot “go around” and try to find it in other sources. This is the reason why we need to introduce the concept of Agents.
+
+The core idea of agents is to use a language model to choose a sequence of actions to take. In agents, a language model is used as a reasoning engine to determine which actions to take and in which order. Agents can be seen as applications powered by LLMs and integrated with a set of tools like search engines, databases, websites, and so on. Within an agent, the LLM is the reasoning engine that, based on the user input, is able to plan and execute a set of actions that are needed to fulfill the request.
+
+![image](https://github.com/user-attachments/assets/b656adab-a448-4784-a6df-a068e0cb45bb)
+
+This notebook explores how to create an ReAct Agent step by step using OpenVINO and LangChain. [ReAct](https://arxiv.org/abs/2210.03629) is an approach to combine reasoning (e.g. chain-of-thought prompting) and acting. ReAct overcomes issues of hallucination and error propagation prevalent in chain-of-thought reasoning by interacting with a simple Wikipedia API, and generates human-like task-solving trajectories that are more interpretable than baselines without reasoning traces.
+
+
+[LangChain](https://python.langchain.com/docs/get_started/introduction) is a framework for developing applications powered by language models. LangChain comes with a number of built-in agents that are optimized for different use cases.
+
+
+### Notebook Contents
+
+The tutorial consists of the following steps:
+
+- Prerequisites
+- Create tools
+- Create prompt template
+- Create LLM
+  - Download model
+  - Select inference device for LLM
+- Create agent
+- Run the agent
+- Interactive Demo
+  - Use built-in tool
+  - Create customized tools
+  - Create AI agent demo with Gradio UI
+
+## Installation Instructions
+
+This is a self-contained example that relies solely on its own code.</br>
+We recommend  running the notebook in a virtual environment. You only need a Jupyter server to start.
+For details, please refer to [Installation Guide](../../README.md).
+
+<img referrerpolicy="no-referrer-when-downgrade" src="https://static.scarf.sh/a.png?x-pxid=5b5a4db0-7875-4bfb-bdbd-01698b5b1a77&file=notebooks/llm-agent-react-langchain/README.md" />

notebooks/llm-agent-react/gradio_helper.py renamed to notebooks/llm-agent-react-langchain/gradio_helper.py

@@ -40,7 +40,7 @@
     "We recommend  running the notebook in a virtual environment. You only need a Jupyter server to start.\n",
     "For details, please refer to [Installation Guide](https://github.com/openvinotoolkit/openvino_notebooks/blob/latest/README.md#-installation-guide).\n",
     "\n",
-    "<img referrerpolicy=\"no-referrer-when-downgrade\" src=\"https://static.scarf.sh/a.png?x-pxid=5b5a4db0-7875-4bfb-bdbd-01698b5b1a77&file=notebooks/llm-agent-react/llm-agent-react-langchain.ipynb\" />\n"
+    "<img referrerpolicy=\"no-referrer-when-downgrade\" src=\"https://static.scarf.sh/a.png?x-pxid=5b5a4db0-7875-4bfb-bdbd-01698b5b1a77&file=notebooks/llm-agent-react-langchain/llm-agent-react-langchain.ipynb\" />\n"
    ]
   },
   {
@@ -985,7 +985,7 @@
    "outputs": [],
    "source": [
     "if not Path(\"gradio_helper.py\").exists():\n",
-    "    r = requests.get(url=\"https://raw.githubusercontent.com/openvinotoolkit/openvino_notebooks/latest/notebooks/llm-agent-react/gradio_helper.py\")\n",
+    "    r = requests.get(url=\"https://raw.githubusercontent.com/openvinotoolkit/openvino_notebooks/latest/notebooks/llm-agent-react-langchain/gradio_helper.py\")\n",
     "    open(\"gradio_helper.py\", \"w\").write(r.text)\n",
     "\n",
     "from gradio_helper import make_demo\n",

notebooks/llm-agent-react/llm-agent-react-langchain.ipynb renamed to notebooks/llm-agent-react-langchain/llm-agent-react-langchain.ipynb

@@ -1,4 +1,4 @@
-# Create a ReAct Agent using OpenVINO
+# Create a native Agent with OpenVINO
 
 LLM are limited to the knowledge on which they have been trained and the additional knowledge provided as context, as a result, if a useful piece of information is missing the provided knowledge, the model cannot “go around” and try to find it in other sources. This is the reason why we need to introduce the concept of Agents.
 
@@ -32,4 +32,4 @@ This is a self-contained example that relies solely on its own code.</br>
 We recommend  running the notebook in a virtual environment. You only need a Jupyter server to start.
 For details, please refer to [Installation Guide](../../README.md).
 
-<img referrerpolicy="no-referrer-when-downgrade" src="https://static.scarf.sh/a.png?x-pxid=5b5a4db0-7875-4bfb-bdbd-01698b5b1a77&file=notebooks/llm-agent-react/README.md" />
+<img referrerpolicy="no-referrer-when-downgrade" src="https://static.scarf.sh/a.png?x-pxid=5b5a4db0-7875-4bfb-bdbd-01698b5b1a77&file=notebooks/llm-native-agent-react/README.md" />

notebooks/llm-agent-react/README.md renamed to notebooks/llm-native-agent-react/README.md

@@ -0,0 +1,75 @@
+from typing import Callable, List
+import gradio as gr
+
+
+def handle_user_message(message, history):
+    """
+    callback function for updating user messages in interface on submit button click
+
+    Params:
+      message: current message
+      history: conversation history
+    Returns:
+      None
+    """
+    # Append the user's message to the conversation history
+    return "", history + [[message, ""]]
+
+
+def make_demo(run_fn: Callable, stop_fn: Callable, examples: List):
+    with gr.Blocks(
+        theme=gr.themes.Soft(),
+        css=".disclaimer {font-variant-caps: all-small-caps;}",
+    ) as demo:
+        gr.Markdown(f"""<h1><center>AI Agent with OpenVINO</center></h1>""")
+        chatbot = gr.Chatbot(height=800)
+        with gr.Row():
+            with gr.Column():
+                msg = gr.Textbox(
+                    label="Chat Message Box",
+                    placeholder="Chat Message Box",
+                    show_label=False,
+                    container=False,
+                )
+            with gr.Column():
+                with gr.Row():
+                    submit = gr.Button("Submit")
+                    stop = gr.Button("Stop")
+                    clear = gr.Button("Clear")
+        gr.Examples(examples, inputs=msg, label="Click on any example and press the 'Submit' button")
+
+        submit_event = msg.submit(
+            fn=handle_user_message,
+            inputs=[msg, chatbot],
+            outputs=[msg, chatbot],
+            queue=False,
+        ).then(
+            fn=run_fn,
+            inputs=[
+                chatbot,
+            ],
+            outputs=chatbot,
+            queue=True,
+        )
+        submit_click_event = submit.click(
+            fn=handle_user_message,
+            inputs=[msg, chatbot],
+            outputs=[msg, chatbot],
+            queue=False,
+        ).then(
+            fn=run_fn,
+            inputs=[
+                chatbot,
+            ],
+            outputs=chatbot,
+            queue=True,
+        )
+        stop.click(
+            fn=stop_fn,
+            inputs=None,
+            outputs=None,
+            cancels=[submit_event, submit_click_event],
+            queue=False,
+        )
+        clear.click(lambda: None, None, chatbot, queue=False)
+    return demo

notebooks/llm-native-agent-react/gradio_helper.py

@@ -37,9 +37,7 @@
     "We recommend  running the notebook in a virtual environment. You only need a Jupyter server to start.\n",
     "For details, please refer to [Installation Guide](https://github.com/openvinotoolkit/openvino_notebooks/blob/latest/README.md#-installation-guide).\n",
     "\n",
-    "<img referrerpolicy=\"no-referrer-when-downgrade\" src=\"https://static.scarf.sh/a.png?x-pxid=5b5a4db0-7875-4bfb-bdbd-01698b5b1a77&file=notebooks/llm-agent-react/llm-agent-rag-llamaindex.ipynb\" />\n",
-    "\n",
-    "<img referrerpolicy=\"no-referrer-when-downgrade\" src=\"https://static.scarf.sh/a.png?x-pxid=5b5a4db0-7875-4bfb-bdbd-01698b5b1a77&file=notebooks/llm-agent-react/llm-agent-react.ipynb\" />\n"
+    "<img referrerpolicy=\"no-referrer-when-downgrade\" src=\"https://static.scarf.sh/a.png?x-pxid=5b5a4db0-7875-4bfb-bdbd-01698b5b1a77&file=notebooks/llm-native-agent-react/llm-agent-react.ipynb\" />\n"
    ]
   },
   {
@@ -764,7 +762,7 @@
    "outputs": [],
    "source": [
     "if not Path(\"gradio_helper.py\").exists():\n",
-    "    r = requests.get(url=\"https://raw.githubusercontent.com/openvinotoolkit/openvino_notebooks/latest/notebooks/llm-agent-react/gradio_helper.py\")\n",
+    "    r = requests.get(url=\"https://raw.githubusercontent.com/openvinotoolkit/openvino_notebooks/latest/notebooks/llm-native-agent-react/gradio_helper.py\")\n",
     "    open(\"gradio_helper.py\", \"w\").write(r.text)\n",
     "\n",
     "from gradio_helper import make_demo\n",