API Request ERROR
alex-ge123 opened this issue · comments
When there are multiple AzureopenAI modules, an error occurs when calling the api interface
To resolve the 500 Internal Server Error when calling the API interface with multiple Azure OpenAI modules, ensure the following configurations are correctly set:
- API Key: Verify that the API key is valid and correctly set.
- Azure Endpoint: Ensure the Azure endpoint URL is correctly formatted and includes the resource.
- Deployment Name: Confirm the deployment name is accurate.
- API Version: Use a valid API version from the supported list.
- Model Name: Ensure you are using a valid model name from the
AZURE_OPENAI_MODELSlist. - Temperature and Max Tokens: Set valid values for temperature and max tokens.
Here is an example of how you might configure these parameters in your Java project:
import java.net.HttpURLConnection;
import java.net.URL;
import java.io.OutputStream;
public class AzureOpenAIClient {
private static final String API_URL = "https://example-resource.azure.openai.com/";
private static final String DEPLOYMENT_NAME = "your-deployment-name";
private static final String API_VERSION = "2023-09-01-preview";
private static final String API_KEY = "your-api-key";
private static final String MODEL = "gpt-4";
private static final double TEMPERATURE = 0.7;
private static final int MAX_TOKENS = 1000;
public static void main(String[] args) {
try {
URL url = new URL(API_URL + "openai/deployments/" + DEPLOYMENT_NAME + "/completions?api-version=" + API_VERSION);
HttpURLConnection connection = (HttpURLConnection) url.openConnection();
connection.setRequestMethod("POST");
connection.setRequestProperty("Content-Type", "application/json");
connection.setRequestProperty("Authorization", "Bearer " + API_KEY);
connection.setDoOutput(true);
String inputJson = "{"
+ "\"model\": \"" + MODEL + "\","
+ "\"temperature\": " + TEMPERATURE + ","
+ "\"max_tokens\": " + MAX_TOKENS + ","
+ "\"prompt\": \"Your input prompt here\""
+ "}";
try (OutputStream os = connection.getOutputStream()) {
byte[] input = inputJson.getBytes("utf-8");
os.write(input, 0, input.length);
}
int responseCode = connection.getResponseCode();
if (responseCode == 500) {
System.out.println("Internal Server Error: Check your configuration and API key.");
} else {
System.out.println("Response Code: " + responseCode);
// Handle the response
}
} catch (Exception e) {
e.printStackTrace();
}
}
}Ensure all parameters are correctly set and the API key is valid. If the error persists, check the Azure OpenAI service status or contact Azure support for further assistance [1].
this is my api curl
curl -X POST
"http://192.168.0.29:7860/api/v1/run/a912a0a3-a1b3-4dd8-80df-835016ea2dae?stream=false"
-H 'Content-Type: application/json'
-H 'x-api-key: '
-d '{"input_value": "message",
"output_type": "chat",
"input_type": "chat",
"tweaks": {
"ChatInput-S3vqS": {},
"ChatOutput-ZIsW5": {},
"MemoryComponent-OfrPd": {},
"IDGenerator-iGWjc": {},
"Prompt-XzfNj": {},
"Prompt-e7qUH": {},
"TextOutput-no6Nj": {},
"TextOperator-s3kmU": {},
"TextOperator-zskCY": {},
"Pass-CP7JO": {},
"CombineText-CEx4H": {},
"TextInput-dgFKO": {},
"CombineText-Qr2bX": {},
"APIRequest-jEuXi": {},
"RecordsOutput-LgcE9": {},
"RecordsToText-Ryeud": {},
"Prompt-bum9a": {},
"AzureOpenAIModel-Ae4b9": {},
"TextInput-nmKuw": {},
"TextInput-9Inko": {},
"TextInput-d26Mx": {},
"AzureOpenAIModel-4sLz7": {},
"AzureOpenAIModel-xnHhY": {},
"AzureOpenAIModel-SmZ8l": {},
"TextInput-pmxV5": {},
"Prompt-5i7dg": {},
"CombineText-CJX2Q": {},
"CreateRecord-YQSRu": {},
"CreateRecord-4mspE": {},
"TextInput-Wm08d": {},
"TextInput-HxJ1a": {},
"TextInput-AIu7U": {},
"AzureOpenAIModel-YZawU": {},
"Prompt-jcR0T": {},
"TextInput-E07ke": {},
"APIRequest-f1LJz": {},
"TextOutput-FPSMu": {},
"RecordsOutput-rfPmB": {}
}}'
My project has multiple Azure OpenAI components
To resolve the 500 Internal Server Error when making an API request with multiple Azure OpenAI components, ensure that all required parameters are correctly configured and valid. Specifically, check the following:
- Azure Endpoint: Ensure that the
azure_endpointis correctly formatted and points to a valid Azure resource. Example:https://example-resource.azure.openai.com/. - Deployment Name: Verify that the
azure_deploymentis correct and exists in your Azure resource. - API Version: Make sure the
api_versionis one of the supported versions listed in theAPI_VERSION_OPTIONS. - API Key: Ensure that the
api_keyis valid and has the necessary permissions. - Model Name: Confirm that the
modelis one of the supported models listed in theAZURE_OPENAI_MODELS.
Here is an example of how to configure these parameters in Python:
from langflow.base.models.model import LCModelComponent
from langchain_openai import AzureChatOpenAI
from pydantic.v1 import SecretStr
from langflow.field_typing import Text
from typing import Optional
class AzureChatOpenAIComponent(LCModelComponent):
display_name: str = "Azure OpenAI"
description: str = "Generate text using Azure OpenAI LLMs."
documentation: str = "https://python.langchain.com/docs/integrations/llms/azure_openai"
beta = False
icon = "Azure"
field_order = [
"model",
"azure_endpoint",
"azure_deployment",
"api_version",
"api_key",
"temperature",
"max_tokens",
"input_value",
"system_message",
"stream",
]
AZURE_OPENAI_MODELS = [
"gpt-35-turbo",
"gpt-35-turbo-16k",
"gpt-35-turbo-instruct",
"gpt-4",
"gpt-4-32k",
"gpt-4-vision",
]
API_VERSION_OPTIONS = [
"2022-12-01",
"2023-03-15-preview",
"2023-05-15",
"2023-06-01-preview",
"2023-07-01-preview",
"2023-08-01-preview",
]
def build_config(self):
return {
"model": {
"display_name": "Model Name",
"value": self.AZURE_OPENAI_MODELS[0],
"options": self.AZURE_OPENAI_MODELS,
},
"azure_endpoint": {
"display_name": "Azure Endpoint",
"info": "Your Azure endpoint, including the resource. Example: `https://example-resource.azure.openai.com/`",
},
"azure_deployment": {
"display_name": "Deployment Name",
},
"api_version": {
"display_name": "API Version",
"options": self.API_VERSION_OPTIONS,
"value": self.API_VERSION_OPTIONS[-1],
"advanced": True,
},
"api_key": {"display_name": "API Key", "password": True},
"temperature": {
"display_name": "Temperature",
"value": 0.7,
},
"max_tokens": {
"display_name": "Max Tokens",
"advanced": True,
"info": "The maximum number of tokens to generate. Set to 0 for unlimited tokens.",
},
"code": {"show": False},
"input_value": {"display_name": "Input", "input_types": ["Text", "Record", "Prompt"]},
"stream": {
"display_name": "Stream",
"info": STREAM_INFO_TEXT,
"advanced": True,
},
"system_message": {
"display_name": "System Message",
"info": "System message to pass to the model.",
"advanced": True,
},
}
def build(
self,
model: str,
azure_endpoint: str,
input_value: Text,
azure_deployment: str,
api_version: str,
api_key: str,
temperature: float,
system_message: Optional[str] = None,
max_tokens: Optional[int] = 1000,
stream: bool = False,
) -> Text:
if api_key:
secret_api_key = SecretStr(api_key)
else:
secret_api_key = None
try:
output = AzureChatOpenAI(
model=model,
azure_endpoint=azure_endpoint,
azure_deployment=azure_deployment,
api_version=api_version,
api_key=secret_api_key,
temperature=temperature,
max_tokens=max_tokens or None,
)
except Exception as e:
raise ValueError("Could not connect to AzureOpenAI API.") from e
return self.get_chat_result(output, stream, input_value, system_message)Ensure that the values for model, azure_endpoint, azure_deployment, api_version, and api_key are correctly set before making the API request [1][2].
Duplicated by #2294