implement load balancing across LLM providers to scale

[sorcerer2073]

o scale AgentForge for high availability and cost efficiency, we need to balance requests across multiple LLM providers (e.g., OpenAI, Grok, Ollama) based on availability or cost. How can we implement this in llm_providers.py?

[kunwar-vikrant]

We can implement a load balancer in llm_providers.py by selecting providers dynamically based on criteria like response time, cost, or availability. something like this should work?
pythonimport random
import time
import requests
import os

class LLMProvider:
def init(self, name, api_key_var, url, model):
self.name = name
self.api_key = os.getenv(api_key_var)
self.url = url
self.model = model
self.last_response_time = float('inf') # Track performance

providers = [
LLMProvider('openai', 'OPENAI_API_KEY', 'https://api.openai.com/v1/chat/completions', 'gpt-4o-mini'),
LLMProvider('grok', 'XAI_API_KEY', 'https://api.x.ai/v1/chat/completions', 'grok-beta'),
LLMProvider('ollama', None, 'http://localhost:11434/api/chat', 'llama3')
]

def get_llm_response(prompt):
# Select provider with lowest recent response time
available = [p for p in providers if p.api_key or p.name == 'ollama']
if not available:
raise ValueError("No available providers")
provider = min(available, key=lambda p: p.last_response_time, default=random.choice(available))

start_time = time.time()
headers = {"Authorization": f"Bearer {provider.api_key}", "Content-Type": "application/json"} if provider.api_key else {}
data = {"model": provider.model, "messages": [{"role": "user", "content": prompt}]}
try:
    response = requests.post(provider.url, headers=headers, json=data, timeout=10)
    response.raise_for_status()
    provider.last_response_time = time.time() - start_time
    return response.json()['choices'][0]['message']['content']
except requests.exceptions.RequestException:
    provider.last_response_time = float('inf')  # Mark as slow/unavailable
    raise

This selects the fastest-responding provider for each request, updating based on recent performance. We could extend it with weights for cost or add failover logic to retry with another provider on failure.