Update app.py

app.py

@@ -1,94 +1,68 @@
+
 import gradio as gr
-from PIL import Image
 import google.generativeai as genai
-import time 
-import pathlib
-# Configure the API key directly in the script
-API_KEY = 'AIzaSyDnnYRJ49VUm_2FiKhNubv85g6KCDjcNSc'
-genai.configure(api_key=API_KEY)
 
-# Generation configuration
+import os 
+token=os.environ.get("TOKEN") 
+e = ""
+genai.configure(
+    api_key=token
+)
 generation_config = {
-    "temperature": 1,
-    "top_p": 0.95,
-    "top_k": 64,
-    "max_output_tokens": 8192,
-    "response_mime_type": "text/plain",
+  "temperature": 1,
+  "top_p": 0.95,
+  "top_k": 64,
+  "max_output_tokens": 8192,
 }
 
-# Safety settings
 safety_settings = [
-    {"category": "HARM_CATEGORY_HARASSMENT", "threshold": "BLOCK_NONE"},
-    {"category": "HARM_CATEGORY_HATE_SPEECH", "threshold": "BLOCK_NONE"},
-    {"category": "HARM_CATEGORY_SEXUALLY_EXPLICIT", "threshold": "BLOCK_NONE"},
-    {"category": "HARM_CATEGORY_DANGEROUS_CONTENT", "threshold": "BLOCK_NONE"},
+  {
+    "category": "HARM_CATEGORY_HARASSMENT",
+    "threshold": "BLOCK_NONE"
+  },
+  {
+    "category": "HARM_CATEGORY_HATE_SPEECH",
+    "threshold": "BLOCK_NONE"
+  },
+  {
+    "category": "HARM_CATEGORY_SEXUALLY_EXPLICIT",
+    "threshold": "BLOCK_NONE"
+  },
+  {
+    "category": "HARM_CATEGORY_DANGEROUS_CONTENT",
+    "threshold": "BLOCK_NONE"
+  },
 ]
 
-# Model name
-MODEL_NAME = "gemini-1.5-pro-latest"
 
 
-# Create the model
-model = genai.GenerativeModel(
-    model_name=MODEL_NAME,
-    safety_settings=safety_settings,
-    generation_config=generation_config,
-)
 
-e =""
-# Fonction pour générer le contenu
-async def generate_content(pro,image):
-    global e
 
-    if not image:
-        response = model.generate_content(pro)
-        print(response)
-        e = response.text
-        print(e)
-
-    else:
-        '''
-        print(f"Uploading file...")
-        uploaded_video = genai.upload_file(path=image)
-        print(f"Completed upload: {uploaded_video.uri}")
-
-        
-        while uploaded_video.state.name == "PROCESSING":
-            print("Waiting for video to be processed.")
-            time.sleep(2)
-            uploaded_video = genai.get_file(uploaded_video.name)
-
-        if uploaded_video.state.name == "FAILED":
-            raise ValueError(uploaded_video.state.name)
-            
-        print(f"Video processing complete: " + uploaded_video.uri)
-
-        print("Making LLM inference request...") '''
-
-        image_input = {
-        'mime_type': 'image/jpeg',
-        'data': pathlib.Path(image).read_bytes()
-        }
-        response = model.generate_content(
-            [prompt, image_input], request_options={"timeout": 600}
-        )
-
-        #genai.delete_file(uploaded_video.name)
-        #print(f"Deleted file {uploaded_video.uri}")
-        
 
+mm = """ resous cet exercice. réponse attendue uniquement en Latex 
 
+"""
+model = genai.GenerativeModel(model_name="gemini-1.5-pro",
+                              generation_config=generation_config,system_instruction=mm ,
+                              safety_settings=safety_settings)
 
 
+# Fonction pour générer le contenu
+def generate_content(image):
+    global e
+    
+    if not image:
+        e =" djo"
+        
+    else:
+        response = model.generate_content([image])
+        print(response.text)
+        e= response.text
         
-        e = response
     return e
 
 
-markdown = r"""
-e
-""".format(e)
-# Interface Gradio
-iface = gr.Interface(fn=generate_content, inputs=[gr.Textbox(),gr.Image(type='pil')], outputs= gr.Markdown(markdown, latex_delimiters=[{ "left":"$$", "right":"$$", "display": True }]))
+
+iface = gr.Interface(fn=generate_content, inputs=gr.Image(type='pil'), outputs= gr.Textbox())
 
 iface.launch()