Update src/chimera_core.py

src/chimera_core.py

@@ -1,103 +1,118 @@
 import os
+import random
 from google import genai
 from groq import Groq
+from duckduckgo_search import DDGS
+from huggingface_hub import InferenceClient
+from PIL import Image
 
 class Chimera:
     def __init__(self):
-        # 1. GEMINI (Google) - Router & Planner
+        # 1. SETUP GEMINI (Router + Vision)
         self.gemini_key = os.getenv("GEMINI_API_KEY")
-        self.gemini_client = None
         if self.gemini_key:
-            try:
-                self.gemini_client = genai.Client(api_key=self.gemini_key)
-                self.gemini_model = "gemini-2.5-flash"
-                print(f"🦁 Gemini: ONLINE")
-            except: pass
+            self.gemini_client = genai.Client(api_key=self.gemini_key)
+            print("👁️ VIM (Gemini Vision): ONLINE")
 
-        # 2. GROQ (The Factory)
+        # 2. SETUP GROQ (Coding + Reasoning)
         self.groq_key = os.getenv("GROQ_API_KEY")
-        self.groq_client = None
         if self.groq_key:
-            try:
-                self.groq_client = Groq(api_key=self.groq_key)
-                print(f"⚡ Groq (Llama 3.3 + Qwen 3): ONLINE")
-            except: pass
+            self.groq_client = Groq(api_key=self.groq_key)
+            print("⚡ ASM (Qwen/Llama): ONLINE")
 
-    def _call_model(self, client, model, prompt, system_msg):
-        """ Generic handler for any model """
-        if not client: return None
+        # 3. SETUP HUGGING FACE (Image Generation)
+        self.hf_token = os.getenv("HF_TOKEN")
+        if self.hf_token:
+            self.hf_client = InferenceClient("black-forest-labs/FLUX.1-schnell", token=self.hf_token)
+            print("🎨 IGM (Flux Art): ONLINE")
+
+    # --- MODULE 1: NET (Web Search) ---
+    def _web_search(self, query):
+        print(f"   ↳ 🌐 Searching web for: {query}")
         try:
-            if "gemini" in model:
-                res = client.models.generate_content(
-                    model=model, contents=f"System: {system_msg}\nUser: {prompt}"
-                )
-                return res.text
-            else:
-                # Groq / OpenAI style
-                res = client.chat.completions.create(
-                    model=model,
-                    messages=[
-                        {"role": "system", "content": system_msg},
-                        {"role": "user", "content": prompt}
-                    ]
-                )
-                return res.choices[0].message.content
+            results = DDGS().text(query, max_results=3)
+            summary = "\n".join([f"- {r['title']}: {r['body']}" for r in results])
+            return summary
         except Exception as e:
-            print(f"⚠️ Error calling {model}: {e}")
-            return None
+            return f"Search Error: {e}"
 
-    def _trinity_pipeline(self, user_prompt):
-        """
-        THE QWEN TRINITY (UPDATED FOR 2026):
-        1. Gemini: Plan (Strategy)
-        2. Qwen 3: Code (Draft) - NEW MODEL ID
-        3. Llama 3.3: Refine (Polish)
-        """
-        
-        # --- PHASE 1: STRATEGY (Gemini) ---
-        print("   ↳ Phase 1: Gemini Planning...")
-        strategy = self._call_model(self.gemini_client, "gemini-2.5-flash", user_prompt, "You are a Software Architect. Outline the logic for this code task.")
-        if not strategy: strategy = user_prompt
+    # --- MODULE 2: IGM (Image Generation) ---
+    def _generate_image(self, prompt):
+        print(f"   ↳ 🎨 Generating image for: {prompt}")
+        if not self.hf_client: return None, "❌ HF_TOKEN missing."
+        try:
+            image = self.hf_client.text_to_image(prompt)
+            # Save to a temporary path so Gradio can display it
+            path = f"/tmp/gen_{random.randint(0,9999)}.png"
+            image.save(path)
+            return path, f"![Generated Image](/file={path})"
+        except Exception as e:
+            return None, f"Generation Error: {e}"
 
-        # --- PHASE 2: DRAFTING (Qwen 3 - The Coder) ---
-        print("   ↳ Phase 2: Qwen 3 Coding...")
-        # UPDATED MODEL ID: qwen/qwen3-32b
-        qwen_code = self._call_model(self.groq_client, "qwen/qwen3-32b", f"Plan: {strategy}\n\nTask: {user_prompt}", "You are an expert Python Developer. Write the code.")
-        
-        # Fallback if Qwen 3 fails -> Try Llama 3.3 directly
-        if not qwen_code:
-            print("   ⚠️ Qwen 3 failed. Falling back to Llama 3.3")
-            qwen_code = self._call_model(self.groq_client, "llama-3.3-70b-versatile", user_prompt, "You are an expert Python Developer.")
+    # --- MODULE 3: VIM (Vision Analysis) ---
+    def _analyze_image(self, text, image_path):
+        print("   ↳ 👁️ Analyzing Image...")
+        try:
+            pil_image = Image.open(image_path)
+            response = self.gemini_client.models.generate_content(
+                model="gemini-2.5-flash",
+                contents=[text, pil_image]
+            )
+            return response.text
+        except Exception as e:
+            return f"Vision Error: {e}"
 
-        # --- PHASE 3: REFINEMENT (Llama 3.3 - The Critic) ---
-        print("   ↳ Phase 3: Llama Refining...")
-        final_code = self._call_model(self.groq_client, "llama-3.3-70b-versatile", f"Refine this code:\n{qwen_code}", "You are a Senior Engineer. Fix bugs, optimize, and add comments.")
-        
-        if final_code:
-            return final_code, "ASM (Qwen 3 + Llama)"
-        else:
-            return qwen_code, "ASM (Qwen 3 Draft)"
+    def process_request(self, message, history, manual_role, image_input=None):
+        # 1. PRIORITY: VIM (If image is uploaded)
+        if image_input:
+            return self._analyze_image(message or "Describe this.", image_input), "VIM (Vision)"
 
-    def process_request(self, user_message, history, manual_role="Auto"):
-        # Router logic
+        # 2. DETECT INTENT (Router)
         role = manual_role
         if role == "Auto":
-            if any(x in user_message.lower() for x in ["code", "python", "function", "script", "app"]):
+            msg_lower = message.lower()
+            if any(x in msg_lower for x in ["generate", "draw", "create image", "paint"]):
+                role = "IGM"
+            elif any(x in msg_lower for x in ["search", "news", "price", "latest"]):
+                role = "NET"
+            elif any(x in msg_lower for x in ["code", "python", "script"]):
                 role = "ASM"
             else:
                 role = "CHAT"
 
         print(f"👉 Routing to: [{role}]")
 
-        # Execute
-        if role == "ASM" and self.groq_client:
-            return self._trinity_pipeline(user_message)
-        
-        elif role == "SFE":
-            return self._call_model(self.groq_client, "llama-3.3-70b-versatile", user_message, "You are a Scientist."), "SFE (Llama)"
-        
-        elif role == "CSM":
-            return self._call_model(self.gemini_client, "gemini-2.5-flash", user_message, "You are a Creative Writer."), "CSM (Gemini)"
-        
-        else:
-            return self._call_model(self.gemini_client, "gemini-2.5-flash", user_message, "You are Chimera."), "CHAT"
+        # 3. EXECUTE MODULES
+        if role == "IGM":
+            # Image Gen Mode
+            path, markdown = self._generate_image(message)
+            return markdown, "IGM (Flux)"
+
+        elif role == "NET":
+            # Web Search Mode
+            search_data = self._web_search(message)
+            # Synthesize answer with Gemini
+            prompt = f"User Question: {message}\n\nSearch Results:\n{search_data}\n\nAnswer the user based on these results."
+            response = self.gemini_client.models.generate_content(model="gemini-2.5-flash", contents=prompt)
+            return response.text, "NET (Web)"
+
+        elif role == "ASM":
+            # Coding Mode (Qwen/Llama) - Simplified for stability
+            if self.groq_client:
+                try:
+                    res = self.groq_client.chat.completions.create(
+                        model="qwen-2.5-32b", # Or qwen/qwen3-32b
+                        messages=[{"role":"user", "content": message}]
+                    )
+                    return res.choices[0].message.content, "ASM (Qwen)"
+                except:
+                     pass # Fallback to Gemini
+            
+        # Default Fallback (Gemini)
+        try:
+            res = self.gemini_client.models.generate_content(
+                model="gemini-2.5-flash", contents=message
+            )
+            return res.text, f"{role} (Gemini)"
+        except:
+            return "System Error.", "ERR"