File size: 13,097 Bytes
e43f92e
31d62a0
0f705a4
 
e43f92e
0f705a4
 
 
 
 
7a1a853
 
3c48c3b
0f705a4
e43f92e
85c6280
 
 
 
e43f92e
 
 
 
 
85c6280
e43f92e
 
 
 
 
85c6280
ec2ae5c
e43f92e
7a1a853
 
 
 
 
 
 
85c6280
 
ec2ae5c
85c6280
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
0793441
85c6280
 
 
 
 
0793441
 
 
 
 
 
 
 
a987701
0793441
 
 
a987701
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
0793441
85c6280
 
 
0f705a4
 
7a1a853
 
 
 
 
 
 
 
0793441
 
 
0f705a4
 
 
 
 
 
0e8504c
 
 
0793441
05b3af6
0f705a4
 
3c48c3b
85c6280
ec2ae5c
85c6280
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
0793441
 
 
a987701
 
7a1a853
 
 
 
0793441
 
 
7a1a853
e43f92e
0793441
 
4883d8e
e3e7c89
 
 
 
 
0793441
7a1a853
 
 
 
0793441
7a1a853
0793441
7a1a853
0793441
7a1a853
e3e7c89
7a1a853
 
4883d8e
 
0793441
 
a987701
0793441
a987701
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
0793441
a3b7031
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
from time import sleep
import streamlit as st
import openai
import pinecone
from postgres_db import query_postgresql_realvest

PINECONE_API_KEY = st.secrets["PINECONE_API_KEY"]
OPENAI_API_KEY = st.secrets["OPENAI_API_KEY"]
INDEX_NAME = 'realvest-data-v2'
EMBEDDING_MODEL = "text-embedding-ada-002"  # OpenAI's best embeddings as of Apr 2023
MAX_LENGTH_DESC = 200
MATCH_SCORE_THR = 0.0
TOP_K = 20





def query_pinecone(xq, top_k: int=3, include_metadata: bool=True, sleep_time: int=10):
    MAX_TRIALS = 5
    trial = 0
    out = None
    while (out is None) and (trial < MAX_TRIALS):
        try:
            out = st.session_state['index'].query(xq, top_k=top_k, include_metadata=include_metadata)
            return out
        except pinecone.core.exceptions.PineconeProtocolError as err:
            print(f"Error, sleep! {err}")
            sleep(sleep_time)
            trial = trial + 1
    return out
    

def sort_dict_by_value(d: dict, ascending: bool=True):
    """
    Sort dictionary {k1: v1, k2: v2} by its value. The output is
    a sorted list of tuples [(k1, v1), (k2, v2)]
    """
    return sorted(d.items(), key=lambda x: x[1], reverse=not ascending)

# initialize connection to pinecone (get API key at app.pinecone.io)
from tenacity import retry, stop_after_attempt, wait_fixed

pinecone.init(
    api_key=PINECONE_API_KEY,
    environment="us-central1-gcp"  # may be different, check at app.pinecone.io
)


@retry(stop=stop_after_attempt(5), wait=wait_fixed(15))
def setup_pinecone_index():
    try:
        print("Attempting to set up Pinecone index...")  # add this line
        if "index" not in st.session_state:
            st.session_state['index'] = pinecone.Index(INDEX_NAME)
        return st.session_state['index']
    except AttributeError as e:
        print("Caught an AttributeError:", e)
        raise  # Re-raise the exception so that tenacity can catch it and retry
    except Exception as e:  # add this block
        print("Caught an unexpected exception:", e)
        raise



def init_session_state():
    try:
        st.session_state['index']  = setup_pinecone_index()
        # stats = test_pinecone()
    except Exception as e:
        print("Failed to set up Pinecone index after several attempts. Error:", e)
    if 'display_results' not in st.session_state:
        st.session_state['display_results'] = False

    if 'count_checked' not in st.session_state:
        st.session_state['count_checked'] = 0

def callback_count_checked():
    st.session_state['count_checked'] = 0
    st.session_state['checked_boxes'] = []
    for key in list(st.session_state.keys()):
        if (key.split('__')[0] == 'cb_compare') and (st.session_state[key] == True):
            st.session_state['count_checked'] += 1
            st.session_state['checked_boxes'].append(key)

def summarize_products(products: list) -> str:
    """
    Input:
    products = [
        {text information of product#1},
        {text information of product#2},
        {text information of product#3},
    ]

    Output:
    summary = "{summary of all products}"
    """
    NEW_LINE = '\n'
    prompt = f"""
    Based on the product information below, please read and try to understand it.
    { f"{NEW_LINE*2}---{NEW_LINE*2}".join(products) }
    Please write a concise and insightful summary table (display as HTML) to compare the products for investors, which should inlcude but not limited to:
    - description
    - category
    - asking price
    - location
    - potential profit margin
    """
    print(f"prompt: {prompt}")
    
    openai.api_key = OPENAI_API_KEY
    completion = openai.ChatCompletion.create(
        model="gpt-4",
        messages=[
            {"role": "system", "content": "You are a helpful assistant."},
            {"role": "user", "content": prompt}
        ]
    )

    summary = completion.choices[0].message
    return summary





### Main
# st.set_page_config(layout="centered")
css='''
<style>
    section.main > div {max-width:70rem}
</style>
'''
st.markdown(css, unsafe_allow_html=True)

# initialize state
init_session_state()

# Create a text input field
query = st.text_input("What are you looking for?")

# Create a button
if st.button('Submit'):

    # # initialize
    # st.session_state.clear()
    # init_session_state()

    # ### call OpenAI text-embedding
    res = openai.Embedding.create(model=EMBEDDING_MODEL, input=[query], api_key=OPENAI_API_KEY)
    xq = res['data'][0]['embedding']
    out = query_pinecone(xq, top_k=TOP_K, include_metadata=True)
 
    if (out is not None) and ('matches' in out):
        metadata = {match['metadata']['product_id']: match['metadata'] for match in out['matches'] if 'metadata' in match and match['metadata'] is not None}


        ### candidates
        metadata = {match['metadata']['product_id']: match['metadata'] for match in out['matches']}
        match_score = {match['metadata']['product_id']: match['score'] for match in out['matches']}
        above_thr_sorted = [
            item 
            for item in sort_dict_by_value(match_score, ascending=False) 
            if item[1] > MATCH_SCORE_THR
        ]
        pids = metadata.keys()

        ### query pids
        pids_str = [f"'{pid}'" for pid, _ in above_thr_sorted]
        query = f"""
        SELECT productid, name, category, alternatename, url, logo, description
        FROM main_products
        WHERE productid in ({', '.join(pids_str)});
        """

        results = query_postgresql_realvest(query)
        results = {
            result['productid']: result
            for result in results
        }

        ### For test
        # print(f"above_thr_sorted: {above_thr_sorted}")
        # print(f"results: {results}")
        # print(f"metadata: {metadata}")
        # # TEST ONLY
        # above_thr_sorted = [('2086773', 0.800059378), ('1951083', 0.797319531), ('1998714', 0.795623)]
        # results = {'1951083': {'productid': '1951083', 'name': '2 for 1 Turn-key Business Opportunity in Lynnwood, Washington - BizBuySell', 'category': 'Other', 'alternatename': None, 'url': 'https://www.bizbuysell.com/Business-Opportunity/2-for-1-Turn-key-Business-Opportunity/1951083/', 'logo': 'https://images.bizbuysell.com/shared/listings/195/1951083/87198e08-a191-4d97-a33b-9e9f40fa02f4-W768.jpg', 'description': 'Your chance to own a successful Korean traditional KBBQ grill restaurant and Korean dive bar. Owner is retiring after 19 years of business. This Korean BBQ restaurant utilizes a traditional grill called "Sot Ttu Kkeong" widely found in Korea. There are 10 separate grilling tables with a unique hood system to eliminate odors immediately. The bar next door may be able to extend hours into the summer. With one shared full kitchen, the new owner will be able to maximize business and potentially earn double income.'}, '1998714': {'productid': '1998714', 'name': 'Portland CPA Firm in Portland, Oregon - BizBuySell', 'category': 'Accounting and Tax Practices', 'alternatename': None, 'url': 'https://www.bizbuysell.com/Business-Opportunity/Portland-CPA-Firm/1998714/', 'logo': 'https://images.bizbuysell.com/shared/listings/199/1998714/cd02bdb9-32c9-409d-b82e-d0531c12eb39-W768.jpg', 'description': 'OR1002: UPDATED :The seller of this Portland CPA firm is approaching retirement and ready to sell the firm. The firm has a great reputation, has good systems in place, is paperless, and has a great staff. The mix of services offers a consistent stream of cash flow to the owner. The seller is seeking a CPA buyer. The office space is available for continued lease after the sale. Revenues for sale include:7% Accounting, bookkeeping and payroll services26% Income tax preparation services for individual clients35% Income tax preparation services for business and other clients28% Audits and reviews4% Consulting services'}, '2086773': {'productid': '2086773', 'name': 'Asian Grocery Supermarket, 1 owner for 29 years in Salem, Oregon - BizBuySell', 'category': 'Grocery Stores and Supermarkets', 'alternatename': None, 'url': 'https://www.bizbuysell.com/Business-Real-Estate-For-Sale/Asian-Grocery-Supermarket-1-owner-for-29-years/2086773/', 'logo': 'https://images.bizbuysell.com/shared/listings/208/2086773/861f6ba6-a994-4e90-9c62-0a593dae2a31-W768.jpg', 'description': 'Great location, well established and profitable supermarket.We have been the sole owner for almost 29 years, so business boasts of a great reputation.'}}
        # metadata = {'2086773': {'asking_price': 1000000.0, 'asking_price_currency': 'USD', 'building_status': 'Established', 'category': 'Grocery Stores and Supermarkets', 'chunk_type': 'profile', 'city': 'Salem', 'document': '# Listing Profile\n    \nAsking Price (USD): 1000000            \n\nReason for Selling: Retire                                                                ', 'listing_type': 'Retail', 'location': 'Salem, OR', 'main_category': 'Grocery Stores and Supermarkets', 'offer_type': 'Offer', 'offers__available_from__address__locality': 'Salem', 'offers__available_from__address__region': 'Oregon', 'offers__available_from__address__type': 'PostalAddress', 'offers__available_from__type': 'Place', 'product_id': '2086773', 'similar_pids': ['2074401', '2087795', '2068650'], 'state_code': 'OR'}, '1951083': {'asking_price': 200000.0, 'asking_price_currency': 'USD', 'category': 'Other', 'chunk_type': 'profile', 'city': 'Lynnwood', 'document': '# Listing Profile\n    \nAsking Price (USD): 200000            \n\nReason for Selling: Retiring                                                                ', 'location': 'Lynnwood, WA', 'main_category': 'Other', 'offer_type': 'Offer', 'offers__available_from__address__locality': 'Lynnwood', 'offers__available_from__address__region': 'Washington', 'offers__available_from__address__type': 'PostalAddress', 'offers__available_from__type': 'Place', 'product_id': '1951083', 'similar_pids': ['2113741', '2033980', '2034855'], 'state_code': 'WA'}, '1998714': {'asking_price': 900000.0, 'asking_price_currency': 'USD', 'category': 'Accounting and Tax Practices', 'chunk_type': 'profile', 'city': 'Portland', 'document': '# Listing Profile\n    \nAsking Price (USD): 900000            \n\nReason for Selling: Approaching retirement                                                                ', 'fin__gross_revenue': 958000.0, 'location': 'Portland, OR', 'main_category': 'Accounting and Tax Practices', 'offer_type': 'Offer', 'offers__available_from__address__locality': 'Portland', 'offers__available_from__address__region': 'Oregon', 'offers__available_from__address__type': 'PostalAddress', 'offers__available_from__type': 'Place', 'product_id': '1998714', 'similar_pids': ['2026155', '2066311'], 'state_code': 'OR'}}    

        # update
        st.session_state['above_thr_sorted'] = above_thr_sorted
        st.session_state['results'] = results
        st.session_state['metadata'] = metadata

        st.session_state['display_results'] = True
    else:
        print("No matches found.")
        metadata = {}

if st.session_state['display_results']:

    summary_container = st.empty()

    st.header("Results")
    st.divider()

    # display matched results
    for pid, match_score in st.session_state['above_thr_sorted']:

        if pid not in st.session_state['results']:
            continue

        metadata_pid = st.session_state['metadata'][pid]
        result = st.session_state['results'][pid]
        col_icon, col_info, col_compare = st.columns([2, 6, 1])

        with col_icon:
            st.image(result["logo"])

        with col_info:
            # TODO: make asking price display $xxx,xxx
            st.markdown(f"""match score: { round(100 * match_score, 2) }
            <br>
            **{result['name']}**
            <br>
            _Asking Price:_ {metadata_pid.get('asking_price', 'N/A')}
            <br>
            _Category:_ {metadata_pid.get('category', 'N/A')}
            <br>
            _Location:_ {metadata_pid.get('location', 'N/A')}
            """, unsafe_allow_html=True)

            st.markdown(f"""**_Description:_** {result['description'][:MAX_LENGTH_DESC]}...[more]({result['url']})
            """)

        with col_compare:
            st.checkbox('compare', key=f"cb_compare__{pid}", on_change=callback_count_checked)

# display summary tab
if st.session_state['count_checked'] > 0:
    with summary_container.container():
        st.header('Summary')
        if st.button('Compare Products'):
            products = []
            for key in st.session_state['checked_boxes']:
                # TODO: Need to pull all the document
                # TODO: Need to dedup the pid too
                pid = key.split('__')[-1]
                products.append(
                    st.session_state['metadata'][pid].get('document')
                )
            summary = summarize_products(products)
            st.markdown(summary.get("content"), unsafe_allow_html=True)
else:
    try:
        summary_container.empty()
    except NameError:
        pass


with st.expander("developer tool"):
    st.json(st.session_state)