Parallel Multi-Agent Workflow

import concurrent.futures

class ParallelResearchOrchestrator:
    def __init__(self):
        self.researchers = {
            "market_researcher": self._market_research,
            "competitor_researcher": self._competitor_research,
            "technical_researcher": self._technical_research,
        }

    def _market_research(self, topic: str) -> dict:
        print(f"    [Market Researcher] Researching market for: {topic}")
        return {"segment": "Enterprise", "size_usd_bn": 45, "growth_pct": 35}

    def _competitor_research(self, topic: str) -> dict:
        print(f"    [Competitor Researcher] Finding competitors for: {topic}")
        return {"top_competitors": ["OpenAI", "Anthropic", "Google"],
                "market_leader": "OpenAI"}

    def _technical_research(self, topic: str) -> dict:
        print(f"    [Technical Researcher] Analysing technology for: {topic}")
        return {"primary_tech": "Transformer LLMs",
                "maturity": "Growing",
                "key_frameworks": ["LangChain", "LlamaIndex"]}

    def research_parallel(self, topic: str) -> dict:
        print(f"Launching {len(self.researchers)} researchers in parallel for: {topic}")
        results = {}

        with concurrent.futures.ThreadPoolExecutor() as executor:
            futures = {
                executor.submit(fn, topic): name
                for name, fn in self.researchers.items()
            }
            for future in concurrent.futures.as_completed(futures):
                name = futures[future]
                try:
                    results[name] = future.result()
                    print(f"    ✓ {name} complete")
                except Exception as e:
                    results[name] = {"error": str(e)}

        # Coordinator synthesises all results
        return self._synthesise(topic, results)

    def _synthesise(self, topic: str, results: dict) -> dict:
        print("    [Coordinator] Synthesising research...")
        return {
            "topic": topic,
            "market": results.get("market_researcher"),
            "competitors": results.get("competitor_researcher"),
            "technology": results.get("technical_researcher"),
            "synthesis_complete": True
        }

orchestrator = ParallelResearchOrchestrator()
final = orchestrator.research_parallel("Agentic AI")
print(f"\nSynthesis complete: {final['synthesis_complete']}")
print(f"Market size: $" + str(final['market']['size_usd_bn']) + "B")