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Refactor imports and add missing newline at end of file

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This commit is contained in:
bobo 2024-01-31 13:26:55 +08:00
parent ea535717fc
commit 82e064b876
2 changed files with 30 additions and 26 deletions
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26
libs/foundation/__init__.py
View File

@ -1,17 +1,17 @@
from .foundation import (
get_context_contents,
get_devchat_site_packages_path,
get_llm_model,
get_parent_hash,
get_user_input_files,
get_user_input_text
get_context_contents,
get_devchat_site_packages_path,
get_llm_model,
get_parent_hash,
get_user_input_files,
get_user_input_text,
)
__all__ = [
"get_context_contents",
"get_devchat_site_packages_path",
"get_llm_model",
"get_parent_hash",
"get_user_input_files",
"get_user_input_text"
]
"get_context_contents",
"get_devchat_site_packages_path",
"get_llm_model",
"get_parent_hash",
"get_user_input_files",
"get_user_input_text",
]

30
libs/foundation/foundation.py
View File

@ -1,5 +1,5 @@
import os
import json
import os
def get_devchat_site_packages_path():
@ -7,7 +7,7 @@ def get_devchat_site_packages_path():
Retrieve the DevChat site packages path from the environment variable.
Returns:
str: The path stored in DEVCHAT_PYTHONPATH environment variable,
str: The path stored in DEVCHAT_PYTHONPATH environment variable,
or an empty string if the variable isn't set.
"""
return os.environ.get("DEVCHAT_PYTHONPATH", "")
@ -18,7 +18,7 @@ def get_llm_model():
Retrieve the DevChat LLM model from the environment variable.
Returns:
str: The LLM model stored in LLM_MODEL environment variable,
str: The LLM model stored in LLM_MODEL environment variable,
or an empty string if the variable isn't set.
"""
return os.environ.get("LLM_MODEL", "gpt-3.5-turbo-1106")
@ -28,8 +28,10 @@ def get_parent_hash():
"""@DevChatApi
Retrieves the parent hash value from the environment variable.
This function is designed to obtain the hash value of the parent message in a sequence of chat interactions,
where each pair of question and response is associated with respective hash values. It helps in reconstructing
This function is designed to obtain the hash value of the parent message in a sequence of
chat interactions,
where each pair of question and response is associated with respective hash values.
It helps in reconstructing
the order of conversation threads by providing the parent hash for the current message.
Returns:
@ -43,15 +45,19 @@ def get_context_contents():
"""@DevChatApi
Retrieve the chat context history from an environment variable.
This function looks up the `CONTEXT_CONTENTS` environment variable, parses it as JSON, and returns the result.
This function looks up the `CONTEXT_CONTENTS` environment variable, parses it as JSON,
and returns the result.
It's used to obtain the historical content of the chat, which is stored in a JSON array format.
Each item in the array represents a message with a sender role and content, for example:
[{"role": "user", "content": "User's message"}, {"role": "assistant", "content": "Assistant's reply"}].
[{"role": "user", "content": "User's message"},
{"role": "assistant", "content": "Assistant's reply"}].
Returns:
list: A list of dictionaries representing the chat history. Each dictionary contains the keys 'role' and
'content', corresponding to who sent the message and what the message was, respectively.
If the `CONTEXT_CONTENTS` variable is not set, an empty list is returned.
list: A list of dictionaries representing the chat history. Each dictionary
contains the keys 'role' and
'content', corresponding to who sent the message and what the message was,
respectively. If the `CONTEXT_CONTENTS` variable is not set, an empty list
is returned.
"""
return json.loads(os.environ.get("CONTEXT_CONTENTS", "[]"))
@ -66,7 +72,7 @@ def get_user_input_text():
context, assuming it's from the user, returning it as a string. If the
context is empty, an empty string is returned. This function is typically
used to get the last input provided by the user in the chat interface.
Returns:
str: The content of the most recent user input message if it exists,
otherwise an empty string.
@ -103,5 +109,3 @@ def get_user_input_files():
if last_index == len(contexts):
return []
return [item["content"] for item in contexts[last_index:]]