Runtime Resolution

from praisonaiagents import Agent

researcher = Agent(
    name="Researcher",
    instructions="Research the topic and summarise it",
    llm="gpt-4o-mini",
)

writer = Agent(
    name="Writer",
    instructions="Write a polished article",
    llm="gpt-4o-mini",
    handoffs=[researcher],
)

# Swap the researcher to a different model at any point
researcher.llm = "claude-3-sonnet"

# The next invocation automatically uses claude-3-sonnet for the researcher
writer.start("Research and write about ocean currents")

from praisonaiagents.runtime import get_runtime_cache, clear_runtime_cache

# See what runtimes are cached across sessions
cache = get_runtime_cache()
for session_id, entries in cache.items():
    for cache_key, (runtime, cached_at) in entries.items():
        print(f"{cache_key}: {runtime.provider}/{runtime.model_ref}")

# Force fresh resolution for a specific session
clear_runtime_cache(session_id="session_123")

# Clear all cached runtimes
clear_runtime_cache()

from praisonaiagents import Agent
from praisonaiagents.runtime import (
    set_global_resolver,
    SessionContext,
)
from praisonaiagents.runtime.resolve import (
    RuntimeResolver,
    AgentRuntimeProtocol,
    LLMRuntimeWrapper,
)
from praisonaiagents.llm.llm import LLM

class MyResolver(RuntimeResolver):
    def supports_model(self, model_ref: str) -> bool:
        return model_ref.startswith(("gpt-", "claude-", "my-model-"))

    def resolve(self, agent_id, model_ref, session_ctx, **kwargs):
        # Route "my-model-*" to a custom endpoint
        if model_ref.startswith("my-model-"):
            llm = LLM(model="gpt-4o-mini", api_base="https://my.endpoint/v1")
        else:
            llm = LLM(model=model_ref)
        return LLMRuntimeWrapper(llm=llm, model_ref=model_ref, agent_id=agent_id)

set_global_resolver(MyResolver())

agent = Agent(name="MyAgent", instructions="Help users", llm="my-model-fast")
agent.start("Hello!")