Update orchestrator.py

orchestrator.py

@@ -1,29 +1,58 @@
 from agents import *
+from prompts import *
 
-AGENT_MAP = {
-    "Market": market_agent,
-    "Finance": finance_agent,
-    "Risk": risk_agent,
-    "Ethics": ethics_agent
+
+AGENTS = {
+    "Market": (market_agent, MARKET_PROMPT),
+    "Finance": (finance_agent, FINANCE_PROMPT),
+    "Risk": (risk_agent, RISK_PROMPT),
+    "Ethics": (ethics_agent, ETHICS_PROMPT)
 }
 
-def run_workflow(problem, agent_order, bias=False):
+
+def parse_order(order_text):
+
+    order = [
+        x.strip().title()
+        for x in order_text.split(",")
+        if x.strip()
+    ]
+
+    return order
+
+
+def run_workflow(problem, order_text, bias=False):
+
+    order = parse_order(order_text)
+
     memory = []
     outputs = {}
 
-    for agent_name in agent_order:
-        agent_fn = AGENT_MAP[agent_name]
+    for name in order:
+
+        if name not in AGENTS:
+            continue
+
+        fn, prompt = AGENTS[name]
+
         context = "\n\n".join(memory)
 
-        result = agent_fn(problem, context)
+        result = fn(problem, context, prompt)
+
+        # Inject bias
+        if bias and name == "Market":
+            result += "\n\n⚠️ WARNING: Over-optimistic bias detected."
+
+        outputs[name] = result
 
-        if bias and agent_name == "Market":
-            result += "\n\n[NOTE: This analysis is overly optimistic.]"
+        memory.append(f"{name} Agent:\n{result}")
 
-        outputs[agent_name] = result
-        memory.append(f"{agent_name} Agent:\n{result}")
+    final = synthesis_agent(
+        problem,
+        "\n\n".join(memory),
+        SYNTHESIS_PROMPT
+    )
 
-    final = synthesiser_agent(problem, "\n\n".join(memory))
-    outputs["Final Recommendation"] = final
+    outputs["Final"] = final
 
     return outputs