Update mcp/orchestrator.py

mcp/orchestrator.py

@@ -16,6 +16,7 @@ from mcp.disgenet import disease_to_genes
 from mcp.gemini import gemini_summarize, gemini_qa
 from mcp.openai_utils import ai_summarize, ai_qa
 
+
 async def _safe_call(
     func: Any,
     *args,
@@ -26,12 +27,13 @@ async def _safe_call(
     Safely call an async function, returning a default on HTTP or other failures.
     """
     try:
-        return await func(*args, **kwargs)
+        return await func(*args, **kwargs)  # type: ignore
     except httpx.HTTPStatusError:
         return default
     except Exception:
         return default
 
+
 async def _gather_tasks(tasks: List[asyncio.Task]) -> List[Any]:
     """
     Await a list of asyncio.Tasks and return their results in order.
@@ -45,19 +47,17 @@ def _flatten_unique(items: List[Union[List[Any], Any]]) -> List[Any]:
     then deduplicate preserving order.
     """
     flat: List[Any] = []
-    seen = set()
     for elem in items:
         if isinstance(elem, list):
             for x in elem:
-                if x not in seen:
-                    seen.add(x)
+                if x not in flat:
                     flat.append(x)
-        elif elem is not None:
-            if elem not in seen:
-                seen.add(elem)
+        else:
+            if elem is not None and elem not in flat:
                 flat.append(elem)
     return flat
 
+
 async def orchestrate_search(
     query: str,
     llm: Literal['openai', 'gemini'] = 'openai',
@@ -75,7 +75,6 @@ async def orchestrate_search(
     Individual fetch functions that fail with an HTTP error will return an empty default,
     ensuring the pipeline always completes.
     """
-    # Launch parallel tasks with safe wrapper for potential HTTP errors
     tasks = {
         'pubmed': asyncio.create_task(fetch_pubmed(query, max_results=max_papers)),
         'arxiv': asyncio.create_task(fetch_arxiv(query, max_results=max_papers)),
@@ -93,18 +92,14 @@ async def orchestrate_search(
         'disgenet': asyncio.create_task(_safe_call(disease_to_genes, query, default=[])),
     }
 
-    # Await all tasks
     results = await _gather_tasks(list(tasks.values()))
     data = dict(zip(tasks.keys(), results))
 
-    # Consolidate gene sources
     gene_sources = [data['ncbi_gene'], data['mygene'], data['ensembl'], data['opentargets']]
     genes = _flatten_unique(gene_sources)
 
-    # Merge literature results
     papers = (data['pubmed'] or []) + (data['arxiv'] or [])
 
-    # AI-driven summary
     summaries = " ".join(p.get('summary', '') for p in papers)
     if llm == 'gemini':
         ai_summary = await gemini_summarize(summaries)
@@ -126,6 +121,7 @@ async def orchestrate_search(
         'llm_used': llm_used,
     }
 
+
 async def answer_ai_question(
     question: str,
     context: str = "",