updating StructuredLlama, Messenger and WhatsApp for Llama 3 (#468)

recipes/use_cases/LiveData.ipynb

@@ -9,7 +9,7 @@
     "\n",
     "## This demo app shows:\n",
     "* How to use LlamaIndex, an open source library to help you build custom data augmented LLM applications\n",
-    "* How to ask Llama 3 questions about recent live data via the [Trvily](https://tavily.com) live search API"
+    "* How to ask Llama 3 questions about recent live data via the [Tavily](https://tavily.com) live search API"
    ]
   },
   {
@@ -86,7 +86,7 @@
    "id": "f8ff812b",
    "metadata": {},
    "source": [
-    "Next you will use the [Trvily](https://tavily.com/) search engine to augment the Llama 3's responses. To create a free trial Trvily Search API, sign in with your Google or Github account [here](https://app.tavily.com/sign-in)."
+    "Next you will use the [Tavily](https://tavily.com/) search engine to augment the Llama 3's responses. To create a free trial Tavily Search API, sign in with your Google or Github account [here](https://app.tavily.com/sign-in)."
    ]
   },
   {

recipes/use_cases/README.md

@@ -1,17 +1,17 @@
-## VideoSummary: Ask Llama2 to Summarize a YouTube Video (using [Replicate](VideoSummary.ipynb) or [OctoAI](../llama_api_providers/OctoAI_API_examples/VideoSummary.ipynb))
-This demo app uses Llama2 to return a text summary of a YouTube video. It shows how to retrieve the caption of a YouTube video and how to ask Llama to summarize the content in four different ways, from the simplest naive way that works for short text to more advanced methods of using LangChain's map_reduce and refine to overcome the 4096 limit of Llama's max input token size.
+## [VideoSummary](VideoSummary.ipynb): Ask Llama 3 to Summarize a Long YouTube Video (using Replicate or [OctoAI](../llama_api_providers/OctoAI_API_examples/VideoSummary.ipynb))
+This demo app uses Llama 3 to return a text summary of a YouTube video. It shows how to retrieve the caption of a YouTube video and how to ask Llama to summarize the content in different ways, from the simplest naive way that works for short text to more advanced methods of using LangChain's map_reduce and refine to overcome the 8K context length limit of Llama 3.
 
-## [NBA2023-24](./text2sql/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.
+## [NBA2023-24](./text2sql/StructuredLlama.ipynb): Ask Llama 3 about Structured Data
+This demo app shows how to use LangChain and Llama 3 to let users ask questions about **structured** data stored in a SQL DB. As the 2023-24 NBA season is entering the playoff, we use the NBA roster info saved in a SQLite DB to show you how to ask Llama 3 questions about your favorite teams or players.
 
-## LiveData: Ask Llama2 about Live Data (using [Replicate](LiveData.ipynb) or [OctoAI](../llama_api_providers/OctoAI_API_examples/LiveData.ipynb))
-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 search API](https://documentation.you.com/quickstart) to get live search result and ask Llama2 about them.
+## [LiveData](LiveData.ipynb): Ask Llama 3 about Live Data (using Replicate or [OctoAI](../llama_api_providers/OctoAI_API_examples/LiveData.ipynb))
+This demo app shows how to perform live data augmented generation tasks with Llama 3, [LlamaIndex](https://github.com/run-llama/llama_index), another leading open-source framework for building LLM apps, and the [Tavily](https://tavily.com) live search API.
 
-## [WhatsApp Chatbot](./chatbots/whatsapp_llama/whatsapp_llama2.md): Building a Llama-enabled WhatsApp Chatbot
-This step-by-step tutorial shows how to use the [WhatsApp Business API](https://developers.facebook.com/docs/whatsapp/cloud-api/overview) to build a Llama-enabled WhatsApp chatbot.
+## [WhatsApp Chatbot](./chatbots/whatsapp_llama/whatsapp_llama3.md): Building a Llama 3 Enabled WhatsApp Chatbot
+This step-by-step tutorial shows how to use the [WhatsApp Business API](https://developers.facebook.com/docs/whatsapp/cloud-api/overview) to build a Llama 3 enabled WhatsApp chatbot.
 
-## [Messenger Chatbot](./chatbots/messenger_llama/messenger_llama2.md): Building a Llama-enabled Messenger Chatbot
-This step-by-step tutorial shows how to use the [Messenger Platform](https://developers.facebook.com/docs/messenger-platform/overview) to build a Llama-enabled Messenger chatbot.
+## [Messenger Chatbot](./chatbots/messenger_llama/messenger_llama3.md): Building a Llama 3 Enabled Messenger Chatbot
+This step-by-step tutorial shows how to use the [Messenger Platform](https://developers.facebook.com/docs/messenger-platform/overview) to build a Llama 3 enabled Messenger chatbot.
 
 ### RAG Chatbot Example (running [locally](./chatbots/RAG_chatbot/RAG_Chatbot_Example.ipynb) or on [OctoAI](../llama_api_providers/OctoAI_API_examples/RAG_Chatbot_example/RAG_Chatbot_Example.ipynb))
-A complete example of how to build a Llama 2 chatbot hosted on your browser that can answer questions based on your own data using retrieval augmented generation (RAG). You can run Llama2 locally if you have a good enough GPU or on OctoAI if you follow the note [here](../README.md#octoai_note).
+A complete example of how to build a Llama 3 chatbot hosted on your browser that can answer questions based on your own data using retrieval augmented generation (RAG). You can run Llama2 locally if you have a good enough GPU or on OctoAI if you follow the note [here](../README.md#octoai_note).

recipes/use_cases/chatbots/messenger_llama/llama_messenger.py

@@ -1,5 +1,5 @@
 # Copyright (c) Meta Platforms, Inc. and affiliates.
-# This software may be used and distributed according to the terms of the Llama 2 Community License Agreement.
+# This software may be used and distributed according to the terms of the Llama 3 Community License Agreement.
 
 import langchain
 from langchain.llms import Replicate
@@ -11,11 +11,11 @@ import requests
 import json
 
 os.environ["REPLICATE_API_TOKEN"] = "<your replicate api token>"
-llama2_13b_chat = "meta/llama-2-13b-chat:f4e2de70d66816a838a89eeeb621910adffb0dd0baba3976c96980970978018d"
+llama3_8b_chat = "meta/meta-llama-3-8b-instruct"
 
 llm = Replicate(
-    model=llama2_13b_chat,
-    model_kwargs={"temperature": 0.01, "top_p": 1, "max_new_tokens":500}
+    model=llama3_8b_chat,
+    model_kwargs={"temperature": 0.0, "top_p": 1, "max_new_tokens":500}
 )
 
 app = Flask(__name__)

recipes/use_cases/chatbots/whatsapp_llama/llama_chatbot.py

@@ -1,5 +1,5 @@
 # Copyright (c) Meta Platforms, Inc. and affiliates.
-# This software may be used and distributed according to the terms of the Llama 2 Community License Agreement.
+# This software may be used and distributed according to the terms of the Llama 3 Community License Agreement.
 
 import langchain
 from langchain.llms import Replicate
@@ -39,26 +39,25 @@ class WhatsAppClient:
         return response.status_code
 
 os.environ["REPLICATE_API_TOKEN"] = "<your replicate api token>"    
-llama2_13b_chat = "meta/llama-2-13b-chat:f4e2de70d66816a838a89eeeb621910adffb0dd0baba3976c96980970978018d"
+llama3_8b_chat = "meta/meta-llama-3-8b-instruct"
 
 llm = Replicate(
-    model=llama2_13b_chat,
-    model_kwargs={"temperature": 0.01, "top_p": 1, "max_new_tokens":500}
+    model=llama3_8b_chat,
+    model_kwargs={"temperature": 0.0, "top_p": 1, "max_new_tokens":500}
 )
 client = WhatsAppClient()
 app = Flask(__name__)
 
 @app.route("/")
 def hello_llama():
-    return "<p>Hello Llama 2</p>"
+    return "<p>Hello Llama 3</p>"
 
 @app.route('/msgrcvd', methods=['POST', 'GET'])
 def msgrcvd():    
     message = request.args.get('message')
-    #client.send_template_message("hello_world", "en_US", "14086745477")
     answer = llm(message)
     print(message)
     print(answer)
-    client.send_text_message(llm(message), "14086745477")
+    client.send_text_message(llm(message), "<your phone number>")
     return message + "<p/>" + answer
 

scripts/spellcheck_conf/wordlist.txt

@@ -1296,3 +1296,4 @@ multiturn
 tiktoken
 eos
 ollama
+tavily