File size: 3,247 Bytes
4f4d036 297c90d 15f0db2 4f4d036 297c90d 4f4d036 f9c6994 15f0db2 4f4d036 a749ad1 4f4d036 297c90d 4f4d036 15f0db2 bdc9b47 15f0db2 bdc9b47 15f0db2 4f4d036 15f0db2 f9c6994 2cb7341 15f0db2 2cb7341 15f0db2 2cb7341 4f4d036 15f0db2 f9c6994 15f0db2 2cb7341 15f0db2 4f4d036 15f0db2 4f4d036 15f0db2 916a98f 15f0db2 916a98f 15f0db2 06bd9b9 15f0db2 4f4d036 15f0db2 f9c6994 15f0db2 |
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 |
import os
import hydra
import aiflows
from aiflows.backends.api_info import ApiInfo
from aiflows.utils.general_helpers import read_yaml_file, quick_load_api_keys
from aiflows import logging
from aiflows.flow_cache import CACHING_PARAMETERS, clear_cache
from aiflows.utils import serving
from aiflows.workers import run_dispatch_worker_thread
from aiflows.messages import FlowMessage
from aiflows.interfaces import KeyInterface
from aiflows.utils.colink_utils import start_colink_server
from aiflows.workers import run_dispatch_worker_thread
CACHING_PARAMETERS.do_caching = False # Set to True in order to disable caching
# clear_cache() # Uncomment this line to clear the cache
logging.set_verbosity_debug()
dependencies = [
{"url": "aiflows/ChatFlowModule", "revision": os.getcwd()},
]
from aiflows import flow_verse
flow_verse.sync_dependencies(dependencies)
if __name__ == "__main__":
#1. ~~~~~ Set up a colink server ~~~~
FLOW_MODULES_PATH = "./"
cl = start_colink_server()
#2. ~~~~~Load flow config~~~~~~
root_dir = "."
cfg_path = os.path.join(root_dir, "demo.yaml")
cfg = read_yaml_file(cfg_path)
#2.1 ~~~ Set the API information ~~~
# OpenAI backend
api_information = [ApiInfo(backend_used="openai",
api_key = os.getenv("OPENAI_API_KEY"))]
# # Azure backend
# api_information = ApiInfo(backend_used = "azure",
# api_base = os.getenv("AZURE_API_BASE"),
# api_key = os.getenv("AZURE_OPENAI_KEY"),
# api_version = os.getenv("AZURE_API_VERSION") )
quick_load_api_keys(cfg, api_information, key="api_infos")
#3. ~~~~ Serve The Flow ~~~~
serving.serve_flow(
cl=cl,
flow_class_name="flow_modules.aiflows.ChatFlowModule.ChatAtomicFlow",
flow_endpoint="ChatAtomicFlow",
)
#4. ~~~~~Start A Worker Thread~~~~~
run_dispatch_worker_thread(cl)
#5. ~~~~~Mount the flow and get its proxy~~~~~~
proxy_flow= serving.get_flow_instance(
cl=cl,
flow_endpoint="ChatAtomicFlow",
user_id="local",
config_overrides= cfg
)
#6. ~~~ Get the data ~~~
data = {"id": 0, "question": "What is the capital of France?"} # This can be a list of samples
# data = {"id": 0, "question": "Who was the NBA champion in 2023?"} # This can be a list of samples
#option2: use the proxy_flow
input_message = proxy_flow.package_input_message(data = data)
#7. ~~~ Run inference ~~~
future = proxy_flow.get_reply_future(input_message)
#uncomment this line if you would like to get the full message back
#reply_message = future.get_message()
reply_data = future.get_data()
# ~~~ Print the output ~~~
print("~~~~~~Reply~~~~~~")
print(reply_data)
#8. ~~~~ (Optional) apply output interface on reply ~~~~
# output_interface = KeyInterface(
# keys_to_rename={"api_output": "answer"},
# )
# print("Output: ", output_interface(reply_data))
#9. ~~~~~Optional: Unserve Flow~~~~~~
# serving.delete_served_flow(cl, "ReverseNumberAtomicFlow_served")
|