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fix: astra-assistants types (#2881)

Browse source 
* merge

* [autofix.ci] apply automated fixes

* support for MultilineSecretInput

* add support for MultilineSecretInput

* [autofix.ci] apply automated fixes

* ruff

* align eye-icon

* tweaks and modal

* [autofix.ci] apply automated fixes

* textare edit modal hidden text plus eye icon

* fix pydantic serialization warning

* [autofix.ci] apply automated fixes

* chore: Add password visibility toggle to text area components

* [autofix.ci] apply automated fixes

* fix list assistants

* fix: remove extraneous property from is-unicode-supported dependency

* fix: update TextAreaComponent styling for edit node table

Adjust the styling of the TextAreaComponent in the edit node table to fix the positioning of the side-bar button. The right margin of the button was changed from 5.2rem to 4.2rem to align it correctly with the text area. This change improves the visual consistency of the edit node table.

* fix modal not sync with outside state

* add comment for future devs

---------

Co-authored-by: autofix-ci[bot] <114827586+autofix-ci[bot]@users.noreply.github.com>
Co-authored-by: anovazzi1 <otavio2204@gmail.com>
This commit is contained in:
Sebastián Estévez 2024-07-29 13:56:05 -04:00 • committed by GitHub
commit cffed2c9be
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18 changed files with 415 additions and 237 deletions
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83
src/backend/base/langflow/components/astra_assistants/create_assistant.py
View file

@ -1,50 +1,55 @@
from typing import Optional
from astra_assistants import patch # type: ignore
from openai import OpenAI
from langflow.custom import CustomComponent
from langflow.custom import Component
from langflow.inputs import StrInput, MultilineInput
from langflow.template import Output
from langflow.schema.message import Message
class AssistantsCreateAssistant(CustomComponent):
class AssistantsCreateAssistant(Component):
icon = "bot"
display_name = "Create Assistant"
description = "Creates an Assistant and returns it's id"
def build_config(self):
return {
"name": {
"display_name": "Assistant Name",
"advanced": False,
"info": "Name for the assistant being created",
},
"instructions": {
"display_name": "Instructions",
"info": "Instructions for the assistant, think of these as the system prompt.",
"advanced": False,
},
"model": {
"display_name": "Model name",
"advanced": False,
"info": (
"Model for the assistant.\n\n"
"Environment variables for provider credentials can be set with the Dotenv Component.\n\n"
"Models are supported via LiteLLM, see (https://docs.litellm.ai/docs/providers) for supported model names and env vars."
),
},
"env_set": {
"display_name": "Environment Set",
"advanced": False,
"info": "Dummy input to allow chaining with Dotenv Component.",
},
}
inputs = [
StrInput(
name="assistant_name",
display_name="Assistant Name",
info="Name for the assistant being created",
),
StrInput(
name="instructions",
display_name="Instructions",
info="Instructions for the assistant, think of these as the system prompt.",
),
StrInput(
name="model",
display_name="Model name",
info=(
"Model for the assistant.\n\n"
"Environment variables for provider credentials can be set with the Dotenv Component.\n\n"
"Models are supported via LiteLLM, see (https://docs.litellm.ai/docs/providers) for supported model names and env vars."
),
# refresh_model=True
),
MultilineInput(
name="env_set",
display_name="Environment Set",
info="Dummy input to allow chaining with Dotenv Component.",
),
]
def build(self, name: str, instructions: str, model: str, env_set: Optional[str] = None) -> str:
if env_set is None:
raise Exception("Environment variables not set")
outputs = [
Output(display_name="Assistant ID", name="assistant_id", method="process_inputs"),
]
def process_inputs(self) -> Message:
print(f"env_set is {self.env_set}")
client = patch(OpenAI())
assistant = client.beta.assistants.create(
name=name,
instructions=instructions,
model=model,
name=self.assistant_name,
instructions=self.instructions,
model=self.model,
)
return assistant.id
message = Message(text=assistant.id)
return message

34
src/backend/base/langflow/components/astra_assistants/create_thread.py
View file

@ -1,28 +1,32 @@
from typing import Optional
from astra_assistants import patch # type: ignore
from langflow.custom import Component
from openai import OpenAI
from langflow.custom import CustomComponent
from langflow.inputs import MultilineInput
from langflow.schema.message import Message
from langflow.template import Output
class AssistantsCreateThread(CustomComponent):
class AssistantsCreateThread(Component):
display_name = "Create Assistant Thread"
description = "Creates a thread and returns the thread id"
def build_config(self):
return {
"env_set": {
"display_name": "Environment Set",
"advanced": False,
"info": "Dummy input to allow chaining with Dotenv Component.",
},
}
inputs = [
MultilineInput(
name="env_set",
display_name="Environment Set",
info="Dummy input to allow chaining with Dotenv Component.",
),
]
def build(self, env_set: Optional[str] = None) -> str:
outputs = [
Output(display_name="Thread ID", name="thread_id", method="process_inputs"),
]
def process_inputs(self) -> Message:
client = patch(OpenAI())
thread = client.beta.threads.create()
thread_id = thread.id
return thread_id
message = Message(text=thread_id)
return message

46
src/backend/base/langflow/components/astra_assistants/dotenv.py
View file

@ -1,30 +1,32 @@
import io
from dotenv import load_dotenv
from langflow.custom import CustomComponent
from langflow.custom import Component
from langflow.inputs import MultilineSecretInput
from langflow.schema.message import Message
from langflow.template import Output
class Dotenv(CustomComponent):
class Dotenv(Component):
display_name = "Dotenv"
description = "Load .env file into env vars"
def build_config(self):
return {
"dotenv_file_content": {
"display_name": "Dotenv file content",
"advanced": False,
"info": (
"Paste the content of your .env file directly\n\n"
"Since contents are sensitive, using a Global variable set as 'password' is recommended"
),
},
}
inputs = [
MultilineSecretInput(
name="dotenv_file_content",
display_name="Dotenv file content",
info="Paste the content of your .env file directly, since contents are sensitive, using a Global variable set as 'password' is recommended",
)
]
def build(self, dotenv_file_content: str) -> str:
try:
fake_file = io.StringIO(dotenv_file_content)
result = load_dotenv(stream=fake_file, override=True)
return "Loaded .env" if result else "No variables found in .env"
except Exception as e:
raise e
outputs = [
Output(display_name="env_set", name="env_set", method="process_inputs"),
]
def process_inputs(self) -> Message:
fake_file = io.StringIO(self.dotenv_file_content)
result = load_dotenv(stream=fake_file, override=True)
message = Message(text="No variables found in .env")
if result:
message = Message(text="Loaded .env")
return message

47
src/backend/base/langflow/components/astra_assistants/get_assistant.py
View file

@ -1,30 +1,37 @@
from typing import Optional
from astra_assistants import patch # type: ignore
from langflow.custom import Component
from openai import OpenAI
from langflow.custom import CustomComponent
from langflow.inputs import StrInput, MultilineInput
from langflow.schema.message import Message
from langflow.template import Output
class AssistantsGetAssistantName(CustomComponent):
class AssistantsGetAssistantName(Component):
client = patch(OpenAI())
display_name = "Get Assistant name"
description = "Assistant by id"
def build_config(self):
return {
"assistant_id": {
"display_name": "Assistant ID",
"advanced": False,
},
"env_set": {
"display_name": "Environment Set",
"advanced": False,
"info": "Dummy input to allow chaining with Dotenv Component.",
},
}
inputs = [
StrInput(
name="assistant_id",
display_name="Assistant ID",
info="ID of the assistant",
),
MultilineInput(
name="env_set",
display_name="Environment Set",
info="Dummy input to allow chaining with Dotenv Component.",
),
]
def build(self, assistant_id: str, env_set: Optional[str] = None) -> str:
client = patch(OpenAI())
assistant = client.beta.assistants.retrieve(
assistant_id=assistant_id,
outputs = [
Output(display_name="Assistant Name", name="assistant_name", method="process_inputs"),
]
def process_inputs(self) -> Message:
assistant = self.client.beta.assistants.retrieve(
assistant_id=self.assistant_id,
)
return assistant.name
message = Message(text=assistant.name)
return message

28
src/backend/base/langflow/components/astra_assistants/getenvvar.py
View file

@ -1,14 +1,30 @@
import os
from langflow.custom import CustomComponent
from langflow.custom import Component
from langflow.inputs import StrInput
from langflow.schema.message import Message
from langflow.template import Output
class GetEnvVar(CustomComponent):
class GetEnvVar(Component):
display_name = "Get env var"
description = "Get env var"
icon = "custom_components"
def build_config(self):
return {"env_var_name": {"display_name": "Env var name"}}
inputs = [
StrInput(
name="env_var_name",
display_name="Env var name",
info="Name of the environment variable to get",
)
]
def build(self, env_var_name: str) -> str:
return os.environ[env_var_name]
outputs = [
Output(display_name="Env var value", name="env_var_value", method="process_inputs"),
]
def process_inputs(self) -> Message:
if self.env_var_name not in os.environ:
raise Exception(f"Environment variable {self.env_var_name} not set")
else:
message = Message(text=os.environ[self.env_var_name])
return message

26
src/backend/base/langflow/components/astra_assistants/list_assistants.py
View file

@ -1,20 +1,24 @@
from typing import List
from astra_assistants import patch # type: ignore
from langflow.template.field.base import Output
from langflow.custom import Component
from openai import OpenAI
from langflow.custom import CustomComponent
from langflow.schema.message import Message
class AssistantsListAssistants(CustomComponent):
class AssistantsListAssistants(Component):
client = patch(OpenAI())
display_name = "List Assistants"
description = "Returns a list of assistant id's"
def build_config(self):
return {}
outputs = [
Output(display_name="Assistants", name="assistants", method="process_inputs"),
]
def build(self) -> List[str]:
client = patch(OpenAI())
assistants = client.beta.assistants.list()
def process_inputs(self) -> Message:
assistants = self.client.beta.assistants.list()
id_list = [assistant.id for assistant in assistants]
return id_list
message = Message(
# get text from list
text="\n".join(id_list)
)
return message

135
src/backend/base/langflow/components/astra_assistants/run.py
View file

@ -1,67 +1,94 @@
from typing import Optional
from astra_assistants import patch # type: ignore
from typing import Any, Optional
from langflow.custom import Component
from openai import OpenAI
from openai.lib.streaming import AssistantEventHandler
from langflow.custom import CustomComponent
from langflow.inputs import MultilineInput
from langflow.schema import dotdict
from langflow.schema.message import Message
from langflow.template import Output
class AssistantsRun(CustomComponent):
class AssistantsRun(Component):
client = patch(OpenAI())
display_name = "Run Assistant"
description = "Executes an Assistant Run against a thread"
def build_config(self):
return {
"assistant_id": {
"display_name": "Assistant ID",
"advanced": False,
"info": (
"The ID of the assistant to run. \n\n"
"Can be retrieved using the List Assistants component or created with the Create Assistant component."
),
},
"user_message": {
"display_name": "User Message",
"info": "User message to pass to the run.",
"advanced": False,
},
"thread_id": {
"display_name": "Thread ID",
"advanced": False,
"info": "Thread ID to use with the run. If not provided, a new thread will be created.",
},
"env_set": {
"display_name": "Environment Set",
"advanced": False,
"info": "Dummy input to allow chaining with Dotenv Component.",
},
}
def update_build_config(
self,
build_config: dotdict,
field_value: Any,
field_name: Optional[str] = None,
):
if field_name == "thread_id":
if field_value is None:
thread = self.client.beta.threads.create()
self.thread_id = thread.id
field_value
build_config["thread_id"] = field_value
def build(
self, assistant_id: str, user_message: str, thread_id: Optional[str] = None, env_set: Optional[str] = None
) -> str:
text = ""
client = patch(OpenAI())
inputs = [
MultilineInput(
name="assistant_id",
display_name="Assistant ID",
info=(
"The ID of the assistant to run. \n\n"
"Can be retrieved using the List Assistants component or created with the Create Assistant component."
),
),
MultilineInput(
name="user_message",
display_name="User Message",
info="User message to pass to the run.",
),
MultilineInput(
name="thread_id",
display_name="Thread ID",
required=False,
info="Thread ID to use with the run. If not provided, a new thread will be created.",
),
MultilineInput(
name="env_set",
display_name="Environment Set",
info="Dummy input to allow chaining with Dotenv Component.",
),
]
if thread_id is None:
thread = client.beta.threads.create()
thread_id = thread.id
outputs = [Output(display_name="Assistant Response", name="assistant_response", method="process_inputs")]
# add the user message
client.beta.threads.messages.create(thread_id=thread_id, role="user", content=user_message)
def process_inputs(self) -> Message:
try:
text = ""
class EventHandler(AssistantEventHandler):
def __init__(self):
super().__init__()
if self.thread_id is None:
thread = self.client.beta.threads.create()
self.thread_id = thread.id
event_handler = EventHandler()
with client.beta.threads.runs.create_and_stream(
thread_id=thread_id,
assistant_id=assistant_id,
event_handler=event_handler,
) as stream:
# return stream.text_deltas
for part in stream.text_deltas:
text += part
print(part)
return text
# add the user message
self.client.beta.threads.messages.create(thread_id=self.thread_id, role="user", content=self.user_message)
class EventHandler(AssistantEventHandler):
def __init__(self):
super().__init__()
def on_exception(self, exception: Exception) -> None:
print(f"Exception: {exception}")
raise exception
event_handler = EventHandler()
with self.client.beta.threads.runs.create_and_stream(
thread_id=self.thread_id,
assistant_id=self.assistant_id,
event_handler=event_handler,
) as stream:
# return stream.text_deltas
for part in stream.text_deltas:
text += part
print(part)
message = Message(text=text)
return message
except Exception as e:
print(e)
raise Exception(f"Error running assistant: {e}")

2
src/backend/base/langflow/inputs/__init__.py
View file

@ -11,6 +11,7 @@ from .inputs import (
MessageInput,
MessageTextInput,
MultilineInput,
MultilineSecretInput,
NestedDictInput,
PromptInput,
SecretStrInput,
@ -30,6 +31,7 @@ __all__ = [
"IntInput",
"MessageInput",
"MultilineInput",
"MultilineSecretInput",
"NestedDictInput",
"PromptInput",
"SecretStrInput",

15
src/backend/base/langflow/inputs/inputs.py
View file

@ -199,6 +199,20 @@ class MultilineInput(MessageTextInput, MultilineMixin, InputTraceMixin):
multiline: CoalesceBool = True
class MultilineSecretInput(MessageTextInput, MultilineMixin, InputTraceMixin):
"""
Represents a multiline input field.
Attributes:
field_type (Optional[SerializableFieldTypes]): The type of the field. Defaults to FieldTypes.TEXT.
multiline (CoalesceBool): Indicates whether the input field should support multiple lines. Defaults to True.
"""
field_type: Optional[SerializableFieldTypes] = FieldTypes.PASSWORD
multiline: CoalesceBool = True
password: CoalesceBool = Field(default=True)
class SecretStrInput(BaseInputMixin, DatabaseLoadMixin):
"""
Represents a field with password field type.
@ -354,6 +368,7 @@ InputTypes = Union[
HandleInput,
IntInput,
MultilineInput,
MultilineSecretInput,
NestedDictInput,
PromptInput,
SecretStrInput,

2
src/backend/base/langflow/io/__init__.py
View file

@ -11,6 +11,7 @@ from langflow.inputs import (
MessageInput,
MessageTextInput,
MultilineInput,
MultilineSecretInput,
NestedDictInput,
PromptInput,
SecretStrInput,
@ -31,6 +32,7 @@ __all__ = [
"IntInput",
"MessageInput",
"MultilineInput",
"MultilineSecretInput",
"NestedDictInput",
"PromptInput",
"SecretStrInput",