HTTPS API#

The HttpsApi class provides a generic interface for interacting with LLM APIs over HTTPS. It supports any OpenAI-compatible API endpoint that uses bearer token authentication.

Overview#

The HttpsApi class extends the base LLM class and provides a flexible way to connect to various LLM API providers through HTTPS. It implements the OpenAI Chat Completions API format, making it compatible with any provider that follows this standard.

Key Features: - Generic HTTPS-based API calls - Bearer token authentication - Configurable request parameters (temperature, max_tokens, top_p) - Built-in error handling with retry logic - Debug mode for detailed error reporting

Setup Requirements#

Before using HttpsApi, ensure you have the following:

API Endpoint: A valid HTTPS endpoint that supports the OpenAI Chat Completions API format.
API Key: A valid API key for authentication.
Model Name: The model identifier as recognized by your API provider.

API Reference#

Class Definition#

class HttpsApi#: A concrete implementation of the LLM base class that interfaces with HTTPS-based LLM APIs.

Constructor#

__init__(self, host: str, key: str, model: str, timeout: int = 60, **kwargs)#

Initialize the HTTPS API client.

Parameters:

host (str) – The hostname of the API endpoint. Note: Do NOT include https:// prefix. Example: "api.openai.com" or "api.example.com"
key (str) – The API key for authentication. This will be used in the Bearer token.
model (str) – The LLM model identifier to use (e.g., "gpt-4", "gpt-3.5-turbo").
timeout (int, optional) – Request timeout in seconds. Defaults to 60.
kwargs (Any, optional) – Additional parameters for the API request: - max_tokens: Maximum tokens to generate (default: 4096) - top_p: Nucleus sampling parameter (default: None) - temperature: Sampling temperature (default: 1.0)

Warning

The host parameter should NOT include the https:// prefix. The class automatically establishes an HTTPS connection.

Note

The User-Agent is set to "Apifox/1.0.0 (https://apifox.com)" by default.

Methods#

draw_sample(self, prompt: str | Any, *args, **kwargs) → str#

Generate a response from the LLM API based on the provided prompt.

Parameters:

prompt (str | Any) – The input prompt. Can be either: - A string containing the user message - A list of message dictionaries with ‘role’ and ‘content’ keys
args – Additional positional arguments (unused).
kwargs – Additional keyword arguments to override default request parameters. Can include max_tokens, top_p, temperature, etc.

Returns:

The generated text content from the LLM response.

Return type:

str

Raises:

RuntimeError – After 10 consecutive errors when in debug mode.

Note

When passing a string prompt, it is automatically wrapped in a user message format
The method has built-in retry logic: it will retry indefinitely (in non-debug mode) or up to 10 times (in debug mode) on failure
The response is automatically extracted from the OpenAI-compatible format

Note

Inherits debug_mode from the parent LLM class. When debug_mode=True, errors are accumulated and a RuntimeError is raised after 10 consecutive failures.

Examples#

Example 1: Using OpenAI API via HTTPS#

from llm4ad.tools.llm.llm_api_https import HttpsApi

# Initialize with OpenAI API credentials
sampler = HttpsApi(
    host="api.openai.com",
    key="your-openai-api-key",
    model="gpt-4",
    timeout=60
)

# Generate a response
response = sampler.draw_sample("What is the capital of Japan?")
print(response)  # Output: Tokyo

Example 2: Using Third-Party API Service#

from llm4ad.tools.llm.llm_api_https import HttpsApi

# Using an alternative API provider
sampler = HttpsApi(
    host="api.another-provider.com",  # No https:// prefix
    key="your-provider-api-key",
    model="gpt-3.5-turbo",
    timeout=30
)

response = sampler.draw_sample("Explain quantum computing in simple terms.")

Example 3: Customizing Request Parameters#

from llm4ad.tools.llm.llm_api_https import HttpsApi

# Initialize with default parameters
sampler = HttpsApi(
    host="api.openai.com",
    key="your-api-key",
    model="gpt-4",
    timeout=60,
    max_tokens=2000,      # Max tokens in response
    temperature=0.7,      # Creativity level (0.0 to 2.0)
    top_p=0.9            # Nucleus sampling
)

# Override parameters per request
response = sampler.draw_sample(
    prompt="Write a short story about AI.",
    temperature=0.9,      # Override default temperature
    max_tokens=1000      # Override default max_tokens
)

Example 4: Using Chat Message Format#

from llm4ad.tools.llm.llm_api_https import HttpsApi

sampler = HttpsApi(
    host="api.openai.com",
    key="your-api-key",
    model="gpt-4"
)

# Using multi-turn conversation format
messages = [
    {"role": "system", "content": "You are a helpful Python programming assistant."},
    {"role": "user", "content": "How do I sort a dictionary by value in Python?"},
    {"role": "assistant", "content": "You can use the sorted() function with a lambda..."},
    {"role": "user", "content": "Can you show me an example?"}
]

response = sampler.draw_sample(messages)
print(response)

Example 5: Integration with LLM4AD Platform#

from llm4ad.tools.llm.llm_api_https import HttpsApi
import llm4ad

# Create HTTPS API sampler
sampler = HttpsApi(
    host="api.openai.com",
    key="your-api-key",
    model="gpt-4",
    timeout=60,
    temperature=0.8
)

# Use with an LLM4AD method
task = llm4ad.tasks.optimization.SymReg(
    dimension=5,
    num_samples=100,
    eval_budget=1000
)

method = llm4ad.methods.eoh.EoH(
    task=task,
    sampler=sampler,
    num_iterations=50
)

result = method.run()
print(f"Best solution: {result.best_solution}")
print(f"Best fitness: {result.best_fitness}")

Example 6: Using Debug Mode#

from llm4ad.tools.llm.llm_api_https import HttpsApi

sampler = HttpsApi(
    host="api.openai.com",
    key="your-api-key",
    model="gpt-4"
)

# Enable debug mode for detailed error reporting
sampler.debug_mode = True

try:
    response = sampler.draw_sample("Hello!")
    print(response)
except RuntimeError as e:
    print(f"Error: {e}")
    # Check API key and host configuration

Compatible Providers#

The HttpsApi class is compatible with any provider that supports the OpenAI Chat Completions API format, including:

OpenAI: api.openai.com - GPT-4, GPT-3.5 Turbo
Azure OpenAI: <your-resource>.openai.azure.com
Anthropic (via compatible proxy): Various endpoints
Local LLM Servers: Local deployments with OpenAI-compatible API
Third-Party Aggregators: Various OpenAI-compatible services

Common Issues and Troubleshooting#

Connection Refused: Check that the host is correct and the service is running.
Authentication Error (401): Verify your API key is correct and has not expired.
Rate Limiting (429): Implement exponential backoff or reduce request frequency.
Invalid Request (400): Check model name and parameter values are valid.
Timeout Issues: Increase the timeout parameter for slower connections.
SSL/TLS Errors: Ensure your environment has proper SSL certificates installed.
Host Format: Remember NOT to include https:// in the host parameter.

HTTPS API

Contents

HTTPS API#

Overview#

Setup Requirements#

API Reference#

Class Definition#

Constructor#

Methods#

Examples#

Example 1: Using OpenAI API via HTTPS#

Example 2: Using Third-Party API Service#

Example 3: Customizing Request Parameters#

Example 4: Using Chat Message Format#

Example 5: Integration with LLM4AD Platform#

Example 6: Using Debug Mode#

Compatible Providers#

Common Issues and Troubleshooting#

See Also#