File size: 3,440 Bytes
8cb7e14 463dbd4 8cb7e14 463dbd4 8cb7e14 463dbd4 8cb7e14 463dbd4 8cb7e14 |
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 |
from copy import deepcopy
from typing import Dict, Any
import hydra
<<<<<<< HEAD
from langchain import PromptTemplate
=======
from flows.prompt_template import JinjaPrompt
>>>>>>> removed langchain dependency
from flows.base_flows import AtomicFlow
from flows.messages import UpdateMessage_Generic
from flows.utils import logging
# logging.set_verbosity_debug() # ToDo: Has no effect on the logger for __name__. Level is warn, and info is not printed
log = logging.get_logger(f"flows.{__name__}") # ToDo: Is there a better fix?
class HumanStandardInputFlow(AtomicFlow):
REQUIRED_KEYS_CONFIG = ["request_multi_line_input_flag"]
query_message_prompt_template: JinjaPrompt = None
__default_flow_config = {
"end_of_input_string": "EOI",
"input_keys": [],
"description": "Reads input from the user's standard input.",
"query_message_prompt_template": {
"_target_": "flows.prompt_template.JinjaPrompt",
"template": "",
"input_variables": [],
"partial_variables": {},
}
}
def __init__(self, query_message_prompt_template, **kwargs):
super().__init__(**kwargs)
self.query_message_prompt_template = query_message_prompt_template
@classmethod
def _set_up_prompts(cls, config):
kwargs = {}
kwargs["query_message_prompt_template"] = \
hydra.utils.instantiate(config['query_message_prompt_template'], _convert_="partial")
return kwargs
@classmethod
def instantiate_from_config(cls, config):
flow_config = deepcopy(config)
kwargs = {"flow_config": flow_config}
# ~~~ Set up prompts ~~~
kwargs.update(cls._set_up_prompts(flow_config))
# ~~~ Instantiate flow ~~~
return cls(**kwargs)
@staticmethod
def _get_message(prompt_template, input_data: Dict[str, Any]):
template_kwargs = {}
for input_variable in prompt_template.input_variables:
template_kwargs[input_variable] = input_data[input_variable]
msg_content = prompt_template.format(**template_kwargs)
return msg_content
def _read_input(self):
if not self.flow_config["request_multi_line_input_flag"]:
log.info("Please enter you single-line response and press enter.")
human_input = input()
return human_input
end_of_input_string = self.flow_config["end_of_input_string"]
log.info(f"Please enter your multi-line response below. "
f"To submit the response, write `{end_of_input_string}` on a new line and press enter.")
content = []
while True:
line = input()
if line == self.flow_config["end_of_input_string"]:
break
content.append(line)
human_input = "\n".join(content)
return human_input
def run(self,
input_data: Dict[str, Any]) -> Dict[str, Any]:
query_message = self._get_message(self.query_message_prompt_template, input_data)
state_update_message = UpdateMessage_Generic(
created_by=self.flow_config['name'],
updated_flow=self.flow_config["name"],
data={"query_message": query_message},
)
self._log_message(state_update_message)
log.info(query_message)
human_input = self._read_input()
return {"human_input": human_input}
|