forked from hebertcisco/deploy-python-fastapi-in-vercel
-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy pathindex.py
224 lines (207 loc) · 9.93 KB
/
index.py
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
from fastapi import FastAPI, Request, WebSocket
from fastapi.responses import Response
from twilio.twiml.messaging_response import MessagingResponse
from twilio.twiml.voice_response import VoiceResponse, Start, Connect, Stream, Gather
import requests
import json
import base64
from pydantic import BaseModel
import boto3
from botocore.exceptions import NoCredentialsError
#url_api = "https://apps.beam.cloud/e928s"
url_api = "https://fjoie.apps.beam.cloud"
url_webhook = "wss://incubo.serveo.net" #"wss://twilio-asphere.herokuapp.com"
headers = {
"Accept": "*/*",
"Accept-Encoding": "gzip, deflate",
"Authorization": "Basic NjU1M2Y0MTQzZGI2ZTJiOGY5ZmI3ZmI4NDE5OThlMzE6ODZlOWFlYmZmNTFhOWRlMDdjOGEzNTk2NjljMmIzODY=",
"Connection": "keep-alive",
"Content-Type": "application/json"
}
# AWS Credentials - Ils doivent être stockés de manière sécurisée
aws_access_key_id = 'AKIA5ZNQFWXGBYOQAJNX'
aws_secret_access_key = 'dy6aw3RAqXmbuZD9yB2YVPjKmL/VTU/ExSeCehF4'
#aws_session_token = 'your_session_token' # facultatif
s3_client = boto3.client('s3',
aws_access_key_id=aws_access_key_id,
aws_secret_access_key=aws_secret_access_key)#,
#aws_session_token=aws_session_token)
bucket_name = 'api-beam'
parent_folder = 'twilio'
app = FastAPI()
@app.get("/")
async def root():
return {"message": "Hello World"}
@app.get("/hello/{name}")
async def say_hello(name: str):
return {"message": f"Hello {name}"}
@app.post('/webhook/call')
async def webhook(request: Request):
print('ICI', request)
class StreamData(BaseModel):
event: str
start: dict = None
media: dict = None
@app.post("/webhook/voice")
async def answer_call(request: Request):
form_data = await request.form()
call_sid = form_data.get('CallSid')
print(call_sid)
# Créer un dossier dans S3
folder_name = f"{parent_folder}/{call_sid}/"
s3_client.put_object(Bucket=bucket_name, Key=(folder_name))
response = VoiceResponse()
#gather = Gather(input='dtmf', num_digits=4)
#gather.say('Please enter the 4 digit code on your screen to get started.')
#response.append(gather)
#response.say("Bienvenue, je suis en train d'écouter et de transcrire ce que vous dites.", voice='alice')
response.say("Hello world. Bonjour, bienvenue Benjamin.", voice='alice')
#response.play('https://demo.twilio.com/docs/classic.mp3')
start = Connect()#Start()
start.stream(url=url_webhook)
response.append(start)
# Use <Record> to record the caller's message
#response.record()
# End the call with <Hangup>
#response.hangup()
# Créer une instance de `Response` avec le type de contenu correct
print(str(response))
xml_response = Response(content=str(response), media_type="application/xml")
print(xml_response)
return xml_response
@app.get("/webhook/voice")
def record():
answer_call()
@app.websocket("/stream")
async def websocket_endpoint(websocket: WebSocket):
print(11)
await websocket.accept()
print(12)
while True:
print(13)
data = await websocket.receive_json()
stream_data = StreamData(**data)
print(14)
if stream_data.media:
print(15)
audio_data = base64.b64decode(stream_data.media['payload'])
print(type(audio_data))
# Maintenant, `audio_data` contient l'audio brut que vous pouvez passer à votre fonction de transcription
# transcription = your_transcription_function(audio_data)
# TODO: Générer une réponse vocale en temps réel (ceci n'est pas pris en charge par Twilio au moment de l'écriture)
'''
data = await websocket.receive_text()
data = json.loads(data)
if 'payload' in data:
audio_data = base64.b64decode(data['payload'])
print(type(audio_data))
'''
@app.post('/webhook/whatsapp')
async def webhook(request: Request):
print('ICI', request)
form_data = await request.form()
sender_number = form_data.get('From') # Récupère le numéro de téléphone de l'expéditeur
message_received = form_data.get('Body')
num_media = int(form_data.get('NumMedia', 0))
print('num_media', num_media)
response = MessagingResponse()
# Créer un message avec un média attaché
msg = response.message()
if message_received and num_media > 0:
if media_type.startswith("audio/"):
print(f"Audio reçu : {media_url}")
payload = {'cloning': 1, "speaker_wav_url": f"{media_url}", "text": f"{message_received}"}
response_beam = requests.request("POST", url_api, headers=headers, data=json.dumps(payload))
print(response_beam.content)
# Supposons que 'response_beam' est un objet 'Response' de la bibliothèque 'requests'
response_data = json.loads(response_beam.content) # Convertissez le contenu JSON en dictionnaire Python
#print(response_data) # Accédez à l'attribut 'pred' du dictionnaire
if 'text' in response_data:
print('Réponse API text', response_data['output'])
msg.body(f"{response_data['output']}")
if 'audio' in response_data:
msg.media(response_data['url'])
if 'image' in response_data:
msg.media(response_data['url'])
if 'video' in response_data:
msg.media(response_data['url'])
if message_received:
print(f"Message reçu : {message_received}")
payload = {'user_id': sender_number, "prompt": f"{message_received}"}
if message_received.lower() == 'acc':
payload['has_spent'] = True
if message_received.lower() == 'ref':
payload['has_spent'] = False
response_beam = requests.request("POST", url_api, headers=headers, data=json.dumps(payload))
#print('Réponse API', response_beam.content)
# Supposons que 'response_beam' est un objet 'Response' de la bibliothèque 'requests'
response_data = json.loads(response_beam.content) # Convertissez le contenu JSON en dictionnaire Python
#print(response_data) # Accédez à l'attribut 'pred' du dictionnaire
if 'text' in response_data:
print('Réponse API text', response_data['output'])
msg.body(f"{response_data['output']}")
if 'image' in response_data:
msg.media(response_data['url'])
if 'video' in response_data:
msg.media(response_data['url'])
if 'audio' in response_data:
msg.media(response_data['url'])
#response.message("Hello, World!")
if num_media > 0:
images = []
videos = []
for i in range(num_media):
media_url = form_data.get(f'MediaUrl{i}')
media_type = form_data.get(f'MediaContentType{i}')
if media_type.startswith("audio/"):
print(f"Audio reçu : {media_url}")
payload = {'user_id': sender_number, 'audio': 1, "url": f"{media_url}"}
if message_received.lower() == 'acc':
payload['has_spent'] = True
if message_received.lower() == 'ref':
payload['has_spent'] = False
response_beam = requests.request("POST", url_api, headers=headers, data=json.dumps(payload))
print(response_beam.content)
# Supposons que 'response_beam' est un objet 'Response' de la bibliothèque 'requests'
response_data = json.loads(response_beam.content) # Convertissez le contenu JSON en dictionnaire Python
#print(response_data) # Accédez à l'attribut 'pred' du dictionnaire
if 'text' in response_data:
print('Réponse API text', response_data['output'])
msg.body(f"{response_data['output']}")
if 'image' in response_data:
msg.media(response_data['url'])
if 'video' in response_data:
msg.media(response_data['url'])
if 'audio' in response_data:
msg.media(response_data['url'])
#else:
#response.message("")
elif media_type.startswith("image/"):
print(f"Image reçue : {media_url}")
images.append(media_url)
#response.message("Vous avez envoyé une image.")
elif media_type.startswith("video/"):
print(f"Vidéo reçue : {media_url}")
videos.append(media_url)
#response.message("Vous avez envoyé une vidéo.")
else:
print(f"Type de média non pris en charge : {media_type}")
response.message("Type de média non pris en charge.")
if len(images) > 0:
payload = {'image': 1, "urls": [f"{media_url}"]}
response_beam = requests.request("POST", url_api, headers=headers, data=json.dumps(payload))
print(response_beam.content)
# Supposons que 'response_beam' est un objet 'Response' de la bibliothèque 'requests'
response_data = json.loads(response_beam.content) # Convertissez le contenu JSON en dictionnaire Python
print('Réponse API images', response_data) # Accédez à l'attribut 'pred' du dictionnaire
if len(videos) > 0:
payload = {'video': 1, "urls": [f"{media_url}"]}
response_beam = requests.request("POST", url_api, headers=headers, data=json.dumps(payload))
print(response_beam.content)
# Supposons que 'response_beam' est un objet 'Response' de la bibliothèque 'requests'
response_data = json.loads(response_beam.content) # Convertissez le contenu JSON en dictionnaire Python
print('Réponse API videos', response_data) # Accédez à l'attribut 'pred' du dictionnaire
return Response(content=str(response), media_type="application/xml")
if __name__ == '__main__':
import uvicorn
uvicorn.run(app, host="127.0.0.1", port=8000)