Messenger Llama2 Chatbot Tutorial (#311)

README.md

@@ -1,6 +1,6 @@
 # Llama 2 Fine-tuning / Inference Recipes, Examples and Demo Apps
 
-**[Update Nov. 16, 2023] We recently released a series of Llama 2 demo apps [here](./demo_apps). These apps show how to run Llama (locally, in the cloud, or on-prem), how to ask Llama questions in general or about custom data (PDF, DB, or live), how to integrate Llama with WhatsApp, and how to implement an end-to-end chatbot with RAG (Retrieval Augmented Generation).**
+**[Update Dec 14, 2023] We recently released a series of Llama 2 demo apps [here](./demo_apps). These apps show how to run Llama (locally, in the cloud, or on-prem), how to ask Llama questions in general or about custom data (PDF, DB, or live), how to integrate Llama with WhatsApp and Messenger, and how to implement an end-to-end chatbot with RAG (Retrieval Augmented Generation).**
 
 The 'llama-recipes' repository is a companion to the [Llama 2 model](https://github.com/facebookresearch/llama). The goal of this repository is to provide examples to quickly get started with fine-tuning for domain adaptation and how to run inference for the fine-tuned models. For ease of use, the examples use Hugging Face converted versions of the models. See steps for conversion of the model [here](#model-conversion-to-hugging-face).
 

demo_apps/README.md

@@ -13,6 +13,7 @@ This folder contains a series of Llama 2-powered apps:
 2. Ask Llama questions about structured data in a DB
 3. Ask Llama questions about live data on the web
 4. Build a Llama-enabled WhatsApp chatbot
+5. Build a Llama-enabled Messenger chatbot
 
 We also show how to build quick web UI for Llama 2 demo apps using Streamlit and Gradio.
 
@@ -77,7 +78,10 @@ This demo app shows how to use LangChain and Llama2 to let users ask questions a
 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.
 
 ## [WhatsApp Chatbot](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), LangChain and Replicate to build 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.
+
+## [Messenger Chatbot](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.
 
 ## 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:

demo_apps/llama_messenger.py

@@ -0,0 +1,45 @@
+import langchain
+from langchain.llms import Replicate
+
+from flask import Flask
+from flask import request
+import os
+import requests
+import json
+
+os.environ["REPLICATE_API_TOKEN"] = "<your replicate api token>"
+llama2_13b_chat = "meta/llama-2-13b-chat:f4e2de70d66816a838a89eeeb621910adffb0dd0baba3976c96980970978018d"
+
+llm = Replicate(
+    model=llama2_13b_chat,
+    model_kwargs={"temperature": 0.01, "top_p": 1, "max_new_tokens":500}
+)
+
+app = Flask(__name__)
+
+@app.route('/msgrcvd_pager', methods=['POST', 'GET'])
+def msgrcvd_pager():    
+    message = request.args.get('message')
+    sender = request.args.get('sender')
+    recipient = request.args.get('recipient')
+
+    answer = llm(message)
+    print(message)
+    print(answer)
+
+    url = f"https://graph.facebook.com/v18.0/{recipient}/messages"
+    params = {
+        'recipient': '{"id": ' + sender + '}',
+        'message': json.dumps({'text': answer}),
+        'messaging_type': 'RESPONSE',
+        'access_token': "<your page access token>"
+    }
+    headers = {
+        'Content-Type': 'application/json'
+    }
+    response = requests.post(url, params=params, headers=headers)
+    print(response.status_code)
+    print(response.text)
+
+    return message + "<p/>" + answer
+

scripts/spellcheck_conf/wordlist.txt

@@ -1209,6 +1209,9 @@ venv
 webhook
 webhook's
 whatsapp
+business
+js
+webhooks
 Anyscale
 ADDR
 ckpt