Update llm/aggregator.py

llm/aggregator.py

@@ -1,10 +1,80 @@
-def aggregate_responses(responses: list) -> str:
-    if not responses:
-        return "No responses received."
+import asyncio
+import httpx
+import os
 
-    # Sanitize: only join valid strings
-    safe_responses = [r if isinstance(r, str) else str(r) for r in responses]
+OPENROUTER_BASE = "https://openrouter.ai/api/v1/chat/completions"
+HEADERS = {
+    "Authorization": f"Bearer {os.getenv('OPENROUTER_API_KEY')}",
+    "Content-Type": "application/json",
+}
 
-    combined = "\n".join(safe_responses)
+ALLOWED_MODELS = [
+    "deepseek/deepseek-chat-v3-0324:free",
+    "google/gemini-2.0-flash-exp:free",
+    "meta-llama/llama-4-maverick:free",
+    "microsoft/mai-ds-r1:free",
+    "meta-llama/llama-4-scout:free",
+    "google/gemma-3-27b-it:free",
+    "qwen/qwq-32b:free",
+    "qwen/qwen2.5-vl-72b-instruct:free",
+    "qwen/qwen-2.5-72b-instruct:free",
+    "google/gemini-2.5-pro-exp-03-25:free",
+    "deepseek/deepseek-r1:free",
+]
 
-    return f"Final synthesized response based on multiple agents:\n{combined}"
+async def call_openrouter(model: str, prompt: str, system_prompt: str = None) -> str:
+    messages = []
+    if system_prompt:
+        messages.append({"role": "system", "content": system_prompt})
+    messages.append({"role": "user", "content": prompt})
+
+    body = {
+        "model": model,
+        "messages": messages,
+        "temperature": 0.7,
+    }
+    async with httpx.AsyncClient(timeout=30) as client:
+        response = await client.post(OPENROUTER_BASE, headers=HEADERS, json=body)
+        response.raise_for_status()
+        return response.json()["choices"][0]["message"]["content"]
+
+async def query_llm_agent(name: str, prompt: str, settings: dict) -> str:
+    selected_model = settings.get("models", {}).get(name)
+
+    if not selected_model:
+        return f"[{name}] No model selected."
+
+    if selected_model not in ALLOWED_MODELS:
+        return f"[{name}] Model '{selected_model}' is not supported."
+
+    try:
+        response = await call_openrouter(selected_model, prompt)
+        return f"[{name}] {response}"
+    except Exception as e:
+        return f"[{name}] Error: {str(e)}"
+
+async def query_all_llms(prompt: str, settings: dict) -> list:
+    agents = ["LLM-A", "LLM-B", "LLM-C"]
+    tasks = [query_llm_agent(agent, prompt, settings) for agent in agents]
+    results = await asyncio.gather(*tasks)
+    return results
+
+def query_all_llms_sync(prompt: str, settings: dict) -> list:
+    return asyncio.run(query_all_llms(prompt, settings))
+
+# Aggregator logic
+async def query_aggregator(responses: list, settings: dict) -> str:
+    aggregator_model = settings.get("aggregator", "meta-llama/llama-4-scout:free")
+
+    if aggregator_model not in ALLOWED_MODELS:
+        return "[Aggregator] Model not allowed."
+
+    system_prompt = "You are an AI tasked with synthesizing the following responses from multiple language models into a single, coherent, high-quality answer."
+    joined_input = "\n\n".join(responses)
+    try:
+        return await call_openrouter(aggregator_model, joined_input, system_prompt)
+    except Exception as e:
+        return f"[Aggregator] Error: {str(e)}"
+
+def aggregate_responses(responses: list, settings: dict) -> str:
+    return asyncio.run(query_aggregator(responses, settings))