API Request ERROR #2203
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To resolve the 500 Internal Server Error when calling the API interface with multiple Azure OpenAI modules, ensure the following configurations are correctly set:
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]. |
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this is my api curl curl -X POST My project has multiple Azure OpenAI components |
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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:
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 |
When there are multiple AzureopenAI modules, an error occurs when calling the api interface
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