Update src/chimera_core.py

src/chimera_core.py

@@ -1,42 +1,52 @@
-from google import genai
 import os
 import sys
+from google import genai
+from openai import OpenAI
 
 class Chimera:
     def __init__(self):
-        # On Hugging Face, we use os.getenv to grab the secret key safely
-        self.api_key = os.getenv("GEMINI_API_KEY")
-        
-        # Fallback for local testing if env var is missing
-        if not self.api_key:
+        # 1. SETUP GEMINI (Google)
+        self.gemini_key = os.getenv("GEMINI_API_KEY")
+        if not self.gemini_key:
+            # Fallback for local testing if env var is missing
             try:
                 import config
-                self.api_key = config.API_KEY
+                self.gemini_key = config.API_KEY
             except ImportError:
                 pass
+        
+        if self.gemini_key:
+            self.gemini_client = genai.Client(api_key=self.gemini_key)
+            self.gemini_model = "gemini-2.5-flash"
+            print(f"🦁 Gemini Core: ONLINE [{self.gemini_model}]")
+        else:
+            raise ValueError("❌ CRITICAL: GEMINI_API_KEY missing in Secrets!")
 
-        if not self.api_key:
-            raise ValueError("❌ CRITICAL: API Key missing! Set GEMINI_API_KEY in Secrets.")
-
-        self.client = genai.Client(api_key=self.api_key)
-        self.model_name = "gemini-2.5-flash"
-        print(f"🦁 Chimera Core: ONLINE [{self.model_name}]")
+        # 2. SETUP GPT-4o (OpenAI)
+        self.openai_key = os.getenv("OPENAI_API_KEY")
+        self.openai_client = None
+        if self.openai_key:
+            self.openai_client = OpenAI(api_key=self.openai_key)
+            print("🟢 OpenAI Core: ONLINE [gpt-4o]")
+        else:
+            print("⚠️ OpenAI Key not found. GPT-4o disabled.")
 
     def _route_task(self, prompt):
-        """ The Router: Classifies the task automatically. """
+        """ The Router: Decides between Gemini (Fast) and GPT-4o (Smart) """
+        # We use Gemini for routing because it's cheaper/faster
         routing_prompt = f"""
-        Classify this user task into one of these roles:
-        [ASM] - Abstract Symbology Module (Code, Math)
-        [SFE] - Sensory Fusion Engine (Data, Science)
-        [CSM] - Creative Synthesis Module (Story, Art)
-        [CHAT] - General conversation.
+        Classify this task.
+        [ASM] - Coding/Math (Best for GPT-4o)
+        [SFE] - Data/Science (Best for Gemini)
+        [CSM] - Creative/Story (Best for Gemini)
+        [CHAT] - Casual (Best for Gemini)
 
         User Task: "{prompt}"
-        Reply ONLY with the tag (e.g., [ASM]).
+        Reply ONLY with the tag.
         """
         try:
-            response = self.client.models.generate_content(
-                model=self.model_name,
+            response = self.gemini_client.models.generate_content(
+                model=self.gemini_model,
                 contents=routing_prompt
             )
             tag = response.text.strip().replace("[", "").replace("]", "")
@@ -45,36 +55,54 @@ class Chimera:
             return "CHAT"
 
     def process_request(self, user_message, history, manual_role="Auto"):
-        """
-        Main Processor with Manual Override.
-        """
-        # 1. Determine Role (Auto or Manual)
+        # 1. Determine Role
         if manual_role and manual_role != "Auto":
-            role = manual_role  # User forced this role
-            print(f"👉 Manual Override: [{role}]")
+            role = manual_role
         else:
             role = self._route_task(user_message)
-            print(f"👉 Auto-Routing to: [{role}]")
+        
+        print(f"👉 Routing to: [{role}]")
 
-        # 2. Assign the Persona
+        # 2. Assign Persona & Model
         system_instruction = ""
+        model_to_use = "Gemini"
+
         if role == "ASM":
-            system_instruction = "You are the ASM (Abstract Symbology Module). You are an expert Software Architect and Mathematician. Your responses must be code-centric, precise, and optimized."
+            system_instruction = "You are the ASM (Abstract Symbology Module). You are an expert Python Developer. Write efficient code."
+            # ASM (Coding) is better with GPT-4o if available
+            if self.openai_client:
+                model_to_use = "OpenAI"
+        
         elif role == "SFE":
-            system_instruction = "You are the SFE (Sensory Fusion Engine). You are a Lead Data Scientist. Analyze this request using logic, empirical data, and patterns."
+            system_instruction = "You are the SFE (Sensory Fusion Engine). You are a Data Scientist. Analyze facts objectively."
+        
         elif role == "CSM":
-            system_instruction = "You are the CSM (Creative Synthesis Module). You are a Visionary Author. Respond with creativity, rich imagery, and narrative flair."
+            system_instruction = "You are the CSM (Creative Synthesis Module). You are a Novelist. Write with creativity."
+        
         else:
-            system_instruction = "You are Project Chimera, an advanced multi-persona AI system."
+            system_instruction = "You are Project Chimera."
 
-        # 3. Generate
-        full_prompt = f"System Instruction: {system_instruction}\n\nUser Message: {user_message}"
-        
+        # 3. Execute
         try:
-            response = self.client.models.generate_content(
-                model=self.model_name,
-                contents=full_prompt
-            )
-            return response.text, role
+            if model_to_use == "OpenAI" and self.openai_client:
+                # Call GPT-4o
+                response = self.openai_client.chat.completions.create(
+                    model="gpt-4o",
+                    messages=[
+                        {"role": "system", "content": system_instruction},
+                        {"role": "user", "content": user_message}
+                    ]
+                )
+                return response.choices[0].message.content, f"{role} (GPT-4o)"
+            
+            else:
+                # Call Gemini
+                full_prompt = f"System Instruction: {system_instruction}\n\nUser Message: {user_message}"
+                response = self.gemini_client.models.generate_content(
+                    model=self.gemini_model,
+                    contents=full_prompt
+                )
+                return response.text, f"{role} (Gemini)"
+
         except Exception as e:
             return f"❌ System Error: {str(e)}", "ERR"