only getting first few letters of the output

[aj2620]

Describe the bug I have tried langflow with mistral ai and in the output I'm getting only a few letters of the output

Browser and Version Google Chrome -Version 125.0.6422.142

To Reproduce Steps to reproduce the behavior:

1. Add chat input and chat output with mistral ai and mistral ai embeddings and a database attached to them
2. in the playground if I give any prompt only the first few letters of the output is being shown in the ui.

Screenshots

Additional context I have also attached a screen shot of the error showing in the terminal. Everything is working fine but the output is not being generated completely

[dosubot[bot]]

Hello, @aj2620! I'm here to help you with any bugs, questions, or contributions you may have.

The issue with getting only a few letters of the response when using Langflow with Mistral AI could be related to the max_tokens parameter. Ensure that the max_tokens parameter is set to a sufficiently high value to allow for a complete response. Additionally, check the stream parameter to see if it is set to True, which might affect how the response is being processed and displayed.

Here is an example configuration for the MistralAIModelComponent:

from typing import Optional

from langchain_mistralai import ChatMistralAI
from pydantic.v1 import SecretStr

from langflow.custom import CustomComponent
from langflow.field_typing import BaseLanguageModel

class MistralAIModelComponent(CustomComponent):
    display_name: str = "MistralAI"
    description: str = "Generate text using MistralAI LLMs."
    icon = "MistralAI"

    field_order = [
        "model",
        "mistral_api_key",
        "max_tokens",
        "temperature",
        "mistral_api_base",
    ]

    def build_config(self):
        return {
            "model": {
                "display_name": "Model Name",
                "options": [
                    "open-mistral-7b",
                    "open-mixtral-8x7b",
                    "open-mixtral-8x22b",
                    "mistral-small-latest",
                    "mistral-medium-latest",
                    "mistral-large-latest",
                ],
                "info": "Name of the model to use.",
                "required": True,
                "value": "open-mistral-7b",
            },
            "mistral_api_key": {
                "display_name": "Mistral API Key",
                "required": True,
                "password": True,
                "info": "Your Mistral API key.",
            },
            "max_tokens": {
                "display_name": "Max Tokens",
                "field_type": "int",
                "advanced": True,
                "value": 256,
            },
            "temperature": {
                "display_name": "Temperature",
                "field_type": "float",
                "value": 0.1,
            },
            "mistral_api_base": {
                "display_name": "Mistral API Base",
                "advanced": True,
                "info": "Endpoint of the Mistral API. Defaults to 'https://api.mistral.ai' if not specified.",
            },
            "code": {"show": False},
        }

    def build(
        self,
        model: str,
        temperature: float = 0.1,
        mistral_api_key: Optional[str] = None,
        max_tokens: Optional[int] = None,
        mistral_api_base: Optional[str] = None,
    ) -> BaseLanguageModel:
        # Set default API endpoint if not provided
        if not mistral_api_base:
            mistral_api_base = "https://api.mistral.ai"

        try:
            output = ChatMistralAI(
                model_name=model,
                api_key=(SecretStr(mistral_api_key) if mistral_api_key else None),
                max_tokens=max_tokens or None,
                temperature=temperature,
                endpoint=mistral_api_base,
            )
        except Exception as e:
            raise ValueError("Could not connect to Mistral API.") from e

        return output

For the validation issues in the TransactionModel, ensure that the target_args field is correctly validated and parsed as JSON if it is a string. Here is the relevant part of the TransactionModel with the target_args validator:

class TransactionModel(BaseModel):
    id: Optional[int] = Field(default=None, alias="id")
    timestamp: Optional[datetime] = Field(default_factory=datetime.now, alias="timestamp")
    source: str
    target: str
    target_args: dict
    status: str
    error: Optional[str] = None

    class Config:
        from_attributes = True
        populate_by_name = True

    # validate target_args in case it is a JSON
    @validator("target_args", pre=True)
    def validate_target_args(cls, v):
        if isinstance(v, str):
            return json.loads(v)
        return v

This validator ensures that if target_args is provided as a JSON string, it will be parsed into a dictionary. If target_args is already a dictionary, it will be returned as is. This should resolve any validation issues related to the target_args field in the TransactionModel ^[1][2][3][4].

To continue talking to Dosu, mention @dosu.

[aj2620]

@dosu I tried increasing the max tokens value to 1000 and now I'm getting a new error

[dosubot[bot]]

To resolve the ValidationError indicating that the sender_name field in ChatOutputResponse should be a valid string, but a generator object was provided instead, you need to ensure that the sender_name field is assigned a string value and not a generator object.

Here's an example of how you might be incorrectly assigning a generator to sender_name:

response = ChatOutputResponse(
    message="Hello, world!",
    sender="User",
    sender_name=(name for name in ["AI"])  # This is a generator, which is incorrect
)

To fix this, you should assign a string directly to sender_name:

response = ChatOutputResponse(
    message="Hello, world!",
    sender="User",
    sender_name="AI"  # This is a valid string
)

Ensure that wherever you are creating an instance of ChatOutputResponse, the sender_name is a string and not a generator or any other non-string type. The ChatOutputResponse class, as defined, expects sender_name to be an Optional[str] with a default value of "AI", so providing a string directly will resolve the validation error ^[1][2].

To continue talking to Dosu, mention @dosu.

[anovazzi1]

It looks like you selected the wrong field in the chatOutput component. Could you please provide a screenshot of your flow?