def Finance_Predictions_Price_SingleStcok(utterance, context):
if context and 'DATE' in context.user_data:
try:
today_date = datetime.datetime.strptime(context.user_data["DATE"], '%m/%d/%Y').date()
except Exception as e:
print(e)
return 'Please enter date in format mm/dd/yyyy eg: 01/13/2020'
print(f'today:{today_date}')
else:
return 'No date set in context. Please use /date command to set date'
slots = slotsdetection(utterance)
print("slot : ", slots)
if not slots or 'stockname' not in slots:
return slotfill.stockname()
else:
period_slot = slots['numberofdays'] if slots and 'numberofdays' in slots else None
# period_slot = random.choice([1, 3, 5, None])
stock_slot = slots['stockname']
col_dict = {1: '1_day_return',
3: '3_day_return',
5: '5_day_return'}
cols = [col_dict[period_slot]] if period_slot else list(col_dict.values())
return_list = predictor.get_values(cols=cols, ticker=stock_slot, rdate=today_date).values.flatten().tolist()
col_names_str = ", ".join([c[:-6].replace('_', ' ').rstrip() for c in cols])
return_format = lambda r: str(math.ceil(r * 100) / 100.0) + '%'
returns_str = ', '.join([return_format(r) for r in return_list])
replies = [f'The {col_names_str} returns predicted for {stock_slot} are {returns_str}',
f'The predicted price movements for {col_names_str} is {returns_str}',
f'Here are the predicted prices for {col_names_str}: {returns_str}']
return random.choice(replies)
def Finance_News_Today(utterance):
replies = ["this is my reply"]
slots = slotsdetection(utterance)
print("slot : ", slots)
print(slots)
return random.choice(replies)
def Finance_Predictions_Sentiments_SingleStock(utterance, context):
if context and 'DATE' in context.user_data:
try:
today_date = datetime.datetime.strptime(context.user_data["DATE"], '%m/%d/%Y').date()
except Exception as e:
print(e)
return 'Please enter date in format mm/dd/yyyy eg: 01/13/2020'
print(f'today:{today_date}')
else:
return 'No date set in context. Please use /date command to set date'
slots = slotsdetection(utterance)
print("slot : ", slots)
if not slots or not slots['stockname']:
return slotfill.stockname()
else:
stock_slot = slots['stockname']
cols = ['bearish_score_mean', 'bullish_score_mean']
sentiments = predictor.get_values(cols=cols, ticker=stock_slot, rdate=today_date).values.flatten().tolist()
def sentiment_format(r): return str(math.ceil(r * 10000) / 100.0) + '%'
bear_sent, bull_sent = [sentiment_format(s)for s in sentiments]
sentiment_label = 'Bullish' if np.argmax(sentiments) else 'Bearish'
replies = [f'The sentiment for {stock_slot} is {bear_sent} bearish and {bull_sent} bullish',
f'{stock_slot} is {bull_sent} bullish',
f'Overall sentiment for {stock_slot} is currently {sentiment_label}']
return random.choice(replies)
def Finance_News_Trending(utterance, context):
slots = slotsdetection(utterance)
print("slot : ", slots)
print("stockname : ", slots.get('stockname'))
if not bool(slots):
reply = slotfill.stockname()
else:
results = GetTrendingNews.GetAnswer()
replies = [["The Trending news are :"], ["The following are the trending news :"], ["Found trending news :"], ["Are you interested in the following trending news?"]]
reply = random.choice(replies)
reply.append("\n\n")
reply.append(results)
return reply
def Finance_News_Stock(utterance, context):
print(settings.store)
countlength = len(utterance.split())
if countlength == 1:
utterance = "for " + utterance
slots = slotsdetection(utterance)
print("slot : ", slots)
print("stockname : ", slots.get('stockname'))
if not bool(slots["stockname"]):
reply = slotfill.stockname()
else:
stockName = slots.get('stockname')
results = GetStockNews.GetAnswer(stockName)
replies = [["The Stock news are :"], ["The following are the Stock news :"], ["Found the Stock news :"], ["Are you interested in the following Stock news?"]]
reply = random.choice(replies)
reply.append("\n\n")
reply.append(results)
return (reply)
def Finance_Predictions_Price_Bullish(utterance, context):
if context and 'DATE' in context.user_data:
try:
today_date = datetime.datetime.strptime(context.user_data["DATE"], '%m/%d/%Y').date()
except Exception as e:
print(e)
return 'Please enter date in format mm/dd/yyyy eg: 01/13/2020'
print(f'today:{today_date}')
else:
return 'No date set in context. Please use /date command to set date'
slots = slotsdetection(utterance)
print("slot : ", slots)
df_subset = predictor.get_values(cols=['bullish_score_mean', 'ticker'], rdate=today_date)
symbols = df_subset.sort_values(by='bullish_score_mean', ascending=False)['ticker'][:3].to_list()
symbols_str = ", ".join(symbols)
replies = [f'The most bullish stocks are {symbols_str}',
f'Here are the most bullish stocks {symbols_str}',
f'{symbols_str} are the most bullish stocks in the market currently']
return random.choice(replies)
def Finance_News_Watchlist(utterance, context):
replies = ["this is my reply"]
slots = slotsdetection(utterance)
print("slot : ", slots)
return random.choice(replies)
def Finance_General_Whatcanido(utterance, context):
replies = [["I can help you with Technology Stock price direction predictions and the stock news itself or any trending technology stock news or topics"],
["I can make sentiment predictions on Technology Stock price direction and retrieve stock news and trending topics"]]
slots = slotsdetection(utterance)
print("slot : ", slots)
return random.choice(replies)
def Finance_General_CurrentPrice(utterance, context):
replies = ["this is my reply"]
slots = slotsdetection(utterance)
print("slot : ", slots)
return random.choice(replies)
def Finance_WatchlistE_Clear(utterance):
replies = ["this is my reply"]
slots = slotsdetection(utterance)
print("slot : ", slots)
return random.choice(replies)
def Finance_General_Whatcanido(utterance):
replies = ["this is my reply"]
slots = slotsdetection(utterance)
print("slot : ", slots)
return random.choice(replies)
def Finance_Predictions_Price_Bullish(utterance):
replies = ["this is my reply"]
slots = slotsdetection(utterance)
print("slot : ", slots)
return random.choice(replies)
def Finance_Predictions_Sentiments_Watchlist(utterance):
replies = ["this is my reply"]
slots = slotsdetection(utterance)
print("slot : ", slots)
return random.choice(replies)
