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Merge remote-tracking branch 'origin/main' into dev

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This commit is contained in:
Gabriel Luiz Freitas Almeida 2023-09-19 16:07:39 -03:00
commit f081a0079c
16 changed files with 274 additions and 179 deletions
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6
src/backend/langflow/__main__.py
View file

@ -55,7 +55,7 @@ def display_results(results):
def update_settings(
config: str,
cache: str,
cache: Optional[str] = None,
dev: bool = False,
remove_api_keys: bool = False,
components_path: Optional[Path] = None,
@ -153,10 +153,10 @@ def run(
log_file: Path = typer.Option(
"logs/langflow.log", help="Path to the log file.", envvar="LANGFLOW_LOG_FILE"
),
cache: str = typer.Option(
cache: Optional[str] = typer.Option(
envvar="LANGFLOW_LANGCHAIN_CACHE",
help="Type of cache to use. (InMemoryCache, SQLiteCache)",
default="SQLiteCache",
default=None,
),
jcloud: bool = typer.Option(False, help="Deploy on Jina AI Cloud"),
dev: bool = typer.Option(False, help="Run in development mode (may contain bugs)"),

10
src/backend/langflow/api/v1/validate.py
View file

@ -58,6 +58,16 @@ def post_validate_prompt(prompt_request: ValidatePromptRequest):
def get_old_custom_fields(prompt_request):
try:
if (
len(prompt_request.frontend_node.custom_fields) == 1
and prompt_request.name == ""
):
# If there is only one custom field and the name is empty string
# then we are dealing with the first prompt request after the node was created
prompt_request.name = list(
prompt_request.frontend_node.custom_fields.keys()
)[0]
old_custom_fields = prompt_request.frontend_node.custom_fields[
prompt_request.name
].copy()

57
src/backend/langflow/interface/types.py
View file

@ -290,31 +290,42 @@ def add_base_classes(frontend_node, return_types: List[str]):
def build_langchain_template_custom_component(custom_component: CustomComponent):
"""Build a custom component template for the langchain"""
logger.debug("Building custom component template")
frontend_node = build_frontend_node(custom_component)
try:
logger.debug("Building custom component template")
frontend_node = build_frontend_node(custom_component)
if frontend_node is None:
return None
logger.debug("Built base frontend node")
template_config = custom_component.build_template_config
if frontend_node is None:
return None
logger.debug("Built base frontend node")
template_config = custom_component.build_template_config
update_attributes(frontend_node, template_config)
logger.debug("Updated attributes")
field_config = build_field_config(custom_component)
logger.debug("Built field config")
add_extra_fields(
frontend_node, field_config, custom_component.get_function_entrypoint_args
)
logger.debug("Added extra fields")
frontend_node = add_code_field(
frontend_node, custom_component.code, field_config.get("code", {})
)
logger.debug("Added code field")
add_base_classes(
frontend_node, custom_component.get_function_entrypoint_return_type
)
logger.debug("Added base classes")
return frontend_node
update_attributes(frontend_node, template_config)
logger.debug("Updated attributes")
field_config = build_field_config(custom_component)
logger.debug("Built field config")
add_extra_fields(
frontend_node, field_config, custom_component.get_function_entrypoint_args
)
logger.debug("Added extra fields")
frontend_node = add_code_field(
frontend_node, custom_component.code, field_config.get("code", {})
)
logger.debug("Added code field")
add_base_classes(
frontend_node, custom_component.get_function_entrypoint_return_type
)
logger.debug("Added base classes")
return frontend_node
except Exception as exc:
raise HTTPException(
status_code=400,
detail={
"error": (
"Invalid type convertion. Please check your code and try again."
),
"traceback": traceback.format_exc(),
},
) from exc
def load_files_from_path(path: str):

17
src/backend/langflow/interface/utils.py
View file

@ -77,9 +77,16 @@ def set_langchain_cache(settings):
import langchain
from langflow.interface.importing.utils import import_class
cache_type = os.getenv("LANGFLOW_LANGCHAIN_CACHE")
cache_class = import_class(f"langchain.cache.{cache_type or settings.CACHE}")
if cache_type := os.getenv("LANGFLOW_LANGCHAIN_CACHE"):
try:
cache_class = import_class(
f"langchain.cache.{cache_type or settings.CACHE}"
)
logger.debug(f"Setting up LLM caching with {cache_class.__name__}")
langchain.llm_cache = cache_class()
logger.info(f"LLM caching setup with {cache_class.__name__}")
logger.debug(f"Setting up LLM caching with {cache_class.__name__}")
langchain.llm_cache = cache_class()
logger.info(f"LLM caching setup with {cache_class.__name__}")
except ImportError:
logger.warning(f"Could not import {cache_type}. ")
else:
logger.info("No LLM cache set.")

5
src/backend/langflow/processing/process.py
View file

@ -146,9 +146,8 @@ def generate_result(langchain_object: Union[Chain, VectorStore], inputs: dict):
elif isinstance(langchain_object, Document):
result = langchain_object.dict()
else:
raise ValueError(
f"Unknown langchain_object type: {type(langchain_object).__name__}"
)
logger.warning(f"Unknown langchain_object type: {type(langchain_object)}")
result = langchain_object
return result

2
src/backend/langflow/services/settings/base.py
View file

@ -37,7 +37,7 @@ class Settings(BaseSettings):
DEV: bool = False
DATABASE_URL: Optional[str] = None
CACHE: str = "InMemoryCache"
CACHE: Optional[str] = None
REMOVE_API_KEYS: bool = False
COMPONENTS_PATH: List[str] = []