├── .gitignore
├── README.md
├── app.py
├── assets
    └── mx_bot.png
├── data
    └── data.txt
├── generate_index.py
└── requirements.txt


/.gitignore:
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1 | /Pipfile
2 | /Pipfile.lock
3 | .env
4 | __pycache__/
5 | .idea/
6 | index_*.json
7 | /data/*
8 | /data/data.txt
9 | 


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/README.md:
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 1 | # AI powered FAQ Chatbot
 2 | Build your own ChatGPT powered faq / knowledge base chatbot that can infer and answer queries based on the information provided via an external data source 
 3 | ## Requirements for running it locally on laptop ##
 4 | 
 5 | * Windows / Mac / Linux with Git installed
 6 | * Python 3.8+
 7 | * MessengerX.io API Token - FREE for Indie Developers
 8 | * Open AI Key
 9 | * Ngrok for Tunneling 
10 | 
11 | ### Install requirements ###
12 | ```bash
13 | pip install -r requirements.txt
14 | ```
15 | 
16 | ### Create a new .env file in the root directory ###
17 | * For Linux / Mac
18 | ```bash
19 | nano -w .env
20 | ```
21 | 
22 | * For Windows
23 | ```bash
24 | type nul > .env 
25 | ```
26 | 
27 | ### Add the following values to your .env file
28 | ```bash
29 | OPENAI_API_KEY=<YOUR_OPEN_AI_KEY> # your open ai key
30 | MESSENGERX_BASE_URL=https://ganglia.machaao.com
31 | OVERRIDE_INDEX_CHECK=False 
32 | ```
33 | * Set OVERRIDE_INDEX_CHECK to ```True``` if you want the bot to automatically 
34 |  retrain your index when you update your data source
35 | 
36 | ### Add your data sources in the ```data``` directory
37 | * It can be of any type (.txt, .pdf etc.) and may contain multiple files. Its totally flexible
38 | 
39 | ### Run your chatbot app on your local server
40 | ```bash
41 | python app.py
42 | ```
43 | 
44 | ### Start ngrok.io tunnel in a new terminal (local development) ###
45 | ```
46 | ngrok http 5000
47 | ```
48 | 
49 | ### Update your webhook to receive messages ###
50 | Update your bot Webhook URL at [MessengerX.io Portal](https://portal.messengerx.io) with the url provided by ngrok
51 | ```
52 | https://<Your NGROK URL>/machaao/hook
53 | ```
54 | 
55 | * If your ```NGROK URL``` is ```https://e9fe-115-187-40-104.in.ngrok.io``` then your bot 
56 | settings page should look like this 👇🏻
57 | ![figure](/assets/mx_bot.png)
58 | 
59 | ### Your chatbot is now ready to start receiving incoming messages from users
60 | ```bash
61 | # HappyCoding
62 | ```
63 | 


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/app.py:
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  1 | import json
  2 | import os
  3 | import sys
  4 | import traceback
  5 | 
  6 | import jwt
  7 | from dotenv import load_dotenv
  8 | from flask import Flask, request, Response
  9 | from machaao import Machaao
 10 | 
 11 | from generate_index import ExtDataIndex
 12 | 
 13 | load_dotenv()
 14 | app = Flask(__name__)
 15 | 
 16 | MESSENGERX_BASE_URL = os.environ.get("MESSENGERX_BASE_URL")
 17 | OPEN_AI_KEY = os.environ.get("OPENAI_API_KEY")
 18 | 
 19 | param_list = [MESSENGERX_BASE_URL, OPEN_AI_KEY]
 20 | 
 21 | for param in param_list:
 22 |     if param is None:
 23 |         raise Exception("Environment variables not set in .env file")
 24 | 
 25 | 
 26 | def exception_handler(exception, data=None):
 27 |     caller = sys._getframe(1).f_code.co_name
 28 |     print(f"{caller} function failed")
 29 |     if hasattr(exception, 'message'):
 30 |         print(exception.message)
 31 |     else:
 32 |         print("Unexpected error: ", sys.exc_info()[0])
 33 | 
 34 |     if data is not None:
 35 |         machaao = Machaao(data['api_token'], MESSENGERX_BASE_URL)
 36 | 
 37 |         payload = {
 38 |             "identifier": "BROADCAST_FB_QUICK_REPLIES",
 39 |             "users": [data['user_id']],
 40 |             "message": {
 41 |                 "text": data['output_text'],
 42 |                 "quick_replies": [{
 43 |                     "content_type": "text",
 44 |                     "payload": "Hi",
 45 |                     "title": "👋🏻 Hi"
 46 |                 }]
 47 |             }
 48 |         }
 49 | 
 50 |         response = machaao.send_message(payload)
 51 |         return Response(
 52 |             mimetype="application/json",
 53 |             response=json.dumps({
 54 |                 "error": True,
 55 |                 "message": response.text
 56 |             }),
 57 |             status=400,
 58 |         )
 59 | 
 60 |     else:
 61 | 
 62 |         return Response(
 63 |             mimetype="application/json",
 64 |             response=json.dumps({
 65 |                 "error": True,
 66 |                 "message": "Server error occurred. Check logs for details"
 67 |             }),
 68 |             status=400,
 69 |         )
 70 | 
 71 | 
 72 | @app.route('/', methods=['GET'])
 73 | def index():
 74 |     return "ok"
 75 | 
 76 | 
 77 | def extract_data(api_token, req):
 78 |     messaging = None
 79 |     user_id = req.headers.get("machaao-user-id", None)
 80 |     raw = req.json["raw"]
 81 | 
 82 |     if raw != "":
 83 |         inp = jwt.decode(str(raw), api_token, algorithms=["HS512"])
 84 |         sub = inp.get("sub", None)
 85 |         if sub and type(sub) is dict:
 86 |             sub = json.dumps(sub)
 87 | 
 88 |         if sub:
 89 |             decoded = json.loads(sub)
 90 |             messaging = decoded.get("messaging", None)
 91 | 
 92 |     return {
 93 |         "user_id": user_id,
 94 |         "messaging": messaging
 95 |     }
 96 | 
 97 | 
 98 | @app.route('/machaao/hook', methods=['POST'])
 99 | def receive():
100 |     _api_token = None
101 |     _user_id = None
102 |     try:
103 |         _api_token = request.headers["bot-token"]
104 |         _user_id = request.headers["machaao-user-id"]
105 | 
106 |         if not _api_token:
107 |             return Response(
108 |                 mimetype="application/json",
109 |                 response=json.dumps({
110 |                     "error": True,
111 |                     "message": "Invalid Request, Check your token"
112 |                 }),
113 |                 status=400,
114 |             )
115 | 
116 |         return incoming(request)
117 | 
118 |     except KeyError as k:
119 |         traceback.print_exc(file=sys.stdout)
120 |         exception_handler(k)
121 |     except AttributeError as a:
122 |         traceback.print_exc(file=sys.stdout)
123 |         exception_handler(a)
124 |     except Exception as e:
125 |         traceback.print_exc(file=sys.stdout)
126 |         if _user_id and _api_token:
127 |             data = dict()
128 |             data['user_id'] = _user_id
129 |             data['api_token'] = _api_token
130 |             data['output_text'] = "Oops!! Our bot is currently unavailable"
131 |             exception_handler(e, data)
132 |         else:
133 |             exception_handler(e)
134 | 
135 | 
136 | def incoming(req):
137 |     api_token = req.headers.get("bot-token", None)
138 |     incoming_data = extract_data(api_token, req)
139 |     print(f"incoming: {incoming_data}")
140 | 
141 |     machaao = Machaao(api_token, MESSENGERX_BASE_URL)
142 |     messaging = incoming_data["messaging"]
143 |     user_id = incoming_data["user_id"]
144 |     message = messaging[0]["message_data"]["text"].lower()
145 | 
146 |     if message == "hi":
147 |         output_text = "Hello!! I am an FAQ bot demonstrating the indexing performance of llama index on your External " \
148 |                       "data source. Ask me an FAQ relevant to your data source"
149 |     else:
150 |         output_text = str(idx_obj.query(message)).strip()
151 | 
152 |     payload = {
153 |         "identifier": "BROADCAST_FB_QUICK_REPLIES",
154 |         "users": [user_id],
155 |         "message": {
156 |             "text": output_text,
157 |             "quick_replies": [{
158 |                 "content_type": "text",
159 |                 "payload": "Hi",
160 |                 "title": "👋🏻 Hi"
161 |             }]
162 |         }
163 |     }
164 | 
165 |     response = machaao.send_message(payload)
166 |     output_payload = {
167 |         "success": True,
168 |         "message": response.text
169 |     }
170 | 
171 |     return Response(
172 |         mimetype="application/json",
173 |         response=json.dumps(output_payload),
174 |         status=200,
175 |     )
176 | 
177 | 
178 | if __name__ == '__main__':
179 |     idx_obj = ExtDataIndex()
180 |     app.run(debug=True)
181 | 


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/assets/mx_bot.png:
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https://raw.githubusercontent.com/machaao/chatgpt-faq/129ee76071c4b11f3daaebb3212d77db09ad3684/assets/mx_bot.png


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/data/data.txt:
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 1 | Q- Who was the only Sikh President of India?
 2 | A: Giani Zail Singh.
 3 | 
 4 | Q- Which city hosted the first ever Asian Games?
 5 | A: New Delhi.
 6 | 
 7 | Q- Which Indian Prime Minister held the shortest term in office?
 8 | A: Gulzarilal Nanda.
 9 | 
10 | Q- Where did India win the first Cricket World Cup?
11 | A: The Lords stadium in London.
12 | 
13 | Q- In which year was Rashtrapati Bhavan built?
14 | A: 1929.
15 | 
16 | Q- Who was India’s first female playback singer?
17 | A: Rajkumari Dubey.
18 | 
19 | Q- Who is the only spiritual personality to be awarded the Bharat Ratna, the highest civilian award in India?
20 | A: Mother Teresa (also called Saint Mother Teresa of Kolkata).
21 | 
22 | Q- Where is the largest Hindu Temple in the world?
23 | A: Angkor Vat, Cambodia.
24 | 
25 | Q- Which are the two newest ministries of the Indian government?
26 | A: Ministry of Skills Development & Entrepreneurship and Ministry of AYUSH
27 | 
28 | Q- How many times has India won the Hockey World Cup?
29 | A: Once.


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/generate_index.py:
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 1 | import os
 2 | import pathlib
 3 | 
 4 | from langchain import OpenAI
 5 | from llama_index import SimpleDirectoryReader, GPTSimpleVectorIndex, LLMPredictor, PromptHelper
 6 | 
 7 | 
 8 | class ExtDataIndex:
 9 |     def __init__(self):
10 |         self.data_loc = 'data'
11 |         self.model_name = "gpt-3.5-turbo"
12 |         self.index_name = f"index_{self.model_name}.json"
13 |         self.root = os.path.dirname(os.path.abspath(__file__))
14 |         self.override_latest_index_check = os.environ.get('OVERRIDE_INDEX_CHECK', None)
15 |         if self.override_latest_index_check is not None:
16 |             self.override_latest_index_check = eval(self.override_latest_index_check)
17 |         self.index = self.load_index()
18 | 
19 |     def check_is_data_source_updated(self):
20 |         if self.override_latest_index_check:
21 |             print("Skipping latest index check")
22 |             return False
23 | 
24 |         idx_f = pathlib.Path(f"{self.root}/{self.index_name}")
25 |         data_f = pathlib.Path(f"{self.root}/{self.data_loc}")
26 | 
27 |         data_modified_time = data_f.stat().st_mtime
28 |         idx_modified_time = idx_f.stat().st_mtime
29 | 
30 |         if idx_modified_time < data_modified_time:
31 |             print("Data source has been updated. Creating new index")
32 |             return True
33 |         else:
34 |             print("Data source has not been updated")
35 |             return False
36 | 
37 |     def query(self, query_str):
38 |         resp = self.index.query(query_str, mode='default')
39 |         print(f'Question: {query_str}')
40 |         print(resp)
41 |         return resp
42 | 
43 |     def load_index(self):
44 |         idx_loaded = False
45 |         idx_exists = os.path.exists(f"{self.root}/{self.index_name}")
46 |         data_path = f"{self.root}/{self.data_loc}"
47 | 
48 |         data_dir_contents = os.listdir(data_path)
49 | 
50 |         if not data_dir_contents:
51 |             print("Please add a data source")
52 |             raise Exception("No data source present")
53 | 
54 |         if idx_exists:
55 |             idx_updated = self.check_is_data_source_updated()
56 |             if not idx_updated:
57 |                 print("Index loaded from disk")
58 |                 index = GPTSimpleVectorIndex.load_from_disk(f"{self.index_name}")
59 |                 idx_loaded = True
60 | 
61 |         if not idx_loaded:
62 |             index = self.build_index()
63 | 
64 |         return index
65 | 
66 |     def build_index(self):
67 |         # define prompt helper
68 |         # set maximum input size
69 |         max_input_size = 4096
70 |         # set number of output tokens
71 |         num_output = 256
72 |         # set maximum chunk overlap
73 |         max_chunk_overlap = 20
74 |         prompt_helper = PromptHelper(max_input_size, num_output, max_chunk_overlap)
75 |         llm_predictor = LLMPredictor(llm=OpenAI(temperature=0, model_name=self.model_name))
76 | 
77 |         documents = SimpleDirectoryReader(f'{self.data_loc}').load_data()
78 | 
79 |         index = GPTSimpleVectorIndex(
80 |             documents,
81 |             llm_predictor=llm_predictor,
82 |             prompt_helper=prompt_helper,
83 |         )
84 | 
85 |         print("New index created and saved to disk")
86 |         index.save_to_disk(f"{self.index_name}")
87 |         return index
88 | 
89 | 
90 | 


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/requirements.txt:
--------------------------------------------------------------------------------
 1 | aiohttp==3.8.4
 2 | aiosignal==1.3.1
 3 | anyio==3.6.2
 4 | async-timeout==4.0.2
 5 | asyncio==3.4.3
 6 | attrs==22.2.0
 7 | beautifulsoup4==4.11.2
 8 | bs4==0.0.1
 9 | certifi==2022.12.7
10 | charset-normalizer==3.0.1
11 | click==8.1.3
12 | colorama==0.4.6
13 | dataclasses-json==0.5.7
14 | docopt==0.6.2
15 | filelock==3.9.0
16 | Flask==2.2.3
17 | Flask-API==3.0.post1
18 | Flask-Executor==1.0.0
19 | frozenlist==1.3.3
20 | greenlet==2.0.2
21 | h11==0.14.0
22 | httpcore==0.16.3
23 | httpx==0.23.3
24 | huggingface-hub==0.12.1
25 | idna==3.4
26 | importlib-metadata==6.0.0
27 | itsdangerous==2.1.2
28 | Jinja2==3.1.2
29 | joblib==1.2.0
30 | langchain==0.0.92
31 | llama-index==0.4.8
32 | machaao==0.3.18
33 | MarkupSafe==2.1.2
34 | marshmallow==3.19.0
35 | marshmallow-enum==1.5.1
36 | multidict==6.0.4
37 | mypy-extensions==1.0.0
38 | nltk==3.8.1
39 | numpy==1.24.2
40 | openai==0.26.5
41 | packaging==23.0
42 | pandas==1.5.3
43 | Pillow==9.4.0
44 | pipreqs==0.4.11
45 | pydantic==1.10.5
46 | PyJWT==2.6.0
47 | python-dateutil==2.8.2
48 | python-dotenv==1.0.0
49 | pytz==2022.7.1
50 | PyYAML==6.0
51 | regex==2022.10.31
52 | requests==2.28.2
53 | rfc3986==1.5.0
54 | six==1.16.0
55 | sniffio==1.3.0
56 | soupsieve==2.4
57 | SQLAlchemy==1.4.46
58 | tenacity==8.1.0
59 | tokenizers==0.13.2
60 | torch==1.13.1+cu116
61 | torchaudio==0.13.1+cu116
62 | torchvision==0.14.1+cu116
63 | tqdm==4.64.1
64 | transformers==4.26.1
65 | typing-inspect==0.8.0
66 | typing_extensions==4.5.0
67 | urllib3==1.26.14
68 | websockets==10.4
69 | Werkzeug==2.2.3
70 | yarg==0.1.9
71 | yarl==1.8.2
72 | zipp==3.15.0
73 | 


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