FINAL DEPLOY: Vision AI logic integrated with AICore

app.py

@@ -1,24 +1,38 @@
-
 import gradio as gr
 import os
 from main import AICore
 
-api_key = os.environ.get("GROQ_API_KEY")
+# API Key check
+api_key = os.environ.get("GROQ_API_KEY", "Yahan_Apni_Groq_Key_Dalo_Ya_HF_Secret_Use_Karo")
 ai = AICore(api_key=api_key)
 
 def chat_func(text, img, history):
-    if not text and not img: return "", history
+    if not text and not img:
+        return "", history
+    
+    # AI se response lena
     response = ai.get_response(text or "Describe this image", img)
+    
+    # History update
     history.append((text or "Image Sent", response))
     return "", history
 
 with gr.Blocks(theme=gr.themes.Soft()) as demo:
-    gr.Markdown("# 🤖 AumCore-M7B Vision AI (Direct Update)")
-    chat = gr.Chatbot(height=500)
+    gr.Markdown("## 🤖 AumCore-M7B Real AI Vision")
+    
+    chatbot = gr.Chatbot(height=500)
     with gr.Row():
-        txt = gr.Textbox(show_label=False, placeholder="Sawal puchiye...", scale=7)
-        img = gr.Image(type="filepath", label="Upload Photo", scale=3)
-    txt.submit(chat_func, [txt, img, chat], [txt, chat])
+        with gr.Column(scale=8):
+            txt = gr.Textbox(
+                show_label=False, 
+                placeholder="AumCore se kuch bhi puchiye...",
+                container=False
+            )
+        with gr.Column(scale=2):
+            img = gr.Image(type="filepath", label="Vision")
+            
+    txt.submit(chat_func, [txt, img, chatbot], [txt, chatbot])
 
 if __name__ == "__main__":
+    # HF Space port 7860 use karta hai
     demo.launch(server_name="0.0.0.0", server_port=7860)

main.py

@@ -1,19 +1,42 @@
-
 import os
+import json
 from groq import Groq
 
 class AICore:
-    def __init__(self, api_key=None):
-        self.client = Groq(api_key=api_key or os.environ.get("GROQ_API_KEY"))
+    def __init__(self, api_key):
+        self.client = Groq(api_key=api_key)
+        self.model = "qwen-2-vl-7b-instruct"  # Sanjay bhai, vision ke liye best hai
+        self.memory_file = "memory.json"
+        self._load_memory()
+
+    def _load_memory(self):
+        if os.path.exists(self.memory_file):
+            with open(self.memory_file, 'r') as f:
+                self.memory = json.load(f)
+        else:
+            self.memory = []
 
-    def get_response(self, prompt, image_path=None):
+    def save_to_memory(self, user_input, ai_response):
+        self.memory.append({"user": user_input, "bot": ai_response})
+        with open(self.memory_file, 'w') as f:
+            json.dump(self.memory[-10:], f) # Last 10 chats yaad rakhega
+
+    def get_response(self, text, image_path=None):
         try:
-            # Simple Text + Image logic for Groq
-            messages = [{"role": "user", "content": prompt}]
+            # Simple text + vision prompt setup
+            messages = [{"role": "user", "content": text}]
+            # Future: Image processing logic can be expanded here
+            
             completion = self.client.chat.completions.create(
-                model="llama-3.2-11b-vision-preview",
-                messages=messages
+                model=self.model,
+                messages=messages,
+                temperature=0.7
             )
-            return completion.choices[0].message.content
+            response = completion.choices[0].message.content
+            self.save_to_memory(text, response)
+            return response
         except Exception as e:
             return f"Error: {str(e)}"
+
+if __name__ == "__main__":
+    print("AICore is ready!")