Update app.py

app.py

@@ -1,51 +1,92 @@
 import gradio as gr
 from groq import Groq
 import os
+import base64
+from io import BytesIO
+import pandas as pd
+from markdown import markdown
+from bs4 import BeautifulSoup
+import tempfile
 
 # Initialize Groq client
 client = Groq(api_key=os.getenv("GROQ_API_KEY"))
 
-def process_image_and_get_response(image, user_description):
-    """
-    Process the uploaded image and user description, then get a response from Groq.
-    Since Groq's API doesn't support images, we use the description as input.
-    """
-    if not user_description:
-        user_description = "Extrait le tableau en entier de cette image et recopie le à l'identique ici pour que je puisse le copier coller."  # Placeholder for image-to-text
+def image_to_base64(image):
+    """Convert PIL image to base64 string for Groq API."""
+    buffered = BytesIO()
+    image.save(buffered, format="JPEG")  # Ou PNG si besoin
+    return base64.b64encode(buffered.getvalue()).decode("utf-8")
+
+def parse_markdown_table_to_df(text):
+    """Parse a Markdown table from text to Pandas DataFrame."""
+    html = markdown(text)
+    soup = BeautifulSoup(html, "html.parser")
+    table = soup.find("table")
+    if not table:
+        return None  # Pas de tableau trouvé
+    headers = [th.text for th in table.find_all("th")]
+    rows = [[td.text for td in tr.find_all("td")] for tr in table.find_all("tr")]
+    return pd.DataFrame(rows, columns=headers) if headers else pd.DataFrame(rows)
+
+def process_image_and_get_response(image):
+    """Process the uploaded image, send to Groq vision model, parse response to table, and generate Excel."""
+    if image is None:
+        return "Veuillez uploader une image.", None
+
+    # Convert image to base64
+    base64_image = image_to_base64(image)
+
+    # Prompt optimisé
+    prompt = "Extraie le tableau complet de cette image. Recopie-le à l'identique sous forme de tableau Markdown (avec des lignes | et --- pour les séparateurs). Assure-toi que les en-têtes et les lignes sont alignés correctement. Si l'image ne contient pas de tableau, dis-le explicitement."
+
     try:
         completion = client.chat.completions.create(
-            model="meta-llama/llama-4-maverick-17b-128e-instruct",
+            model="llama-3.2-11b-vision-preview",  # Modèle vision Groq
             messages=[
                 {
                     "role": "user",
-                    "content": user_description
+                    "content": [
+                        {"type": "text", "text": prompt},
+                        {
+                            "type": "image_url",
+                            "image_url": {"url": f"data:image/jpeg;base64,{base64_image}"}
+                        }
+                    ]
                 }
             ],
-            temperature=1,
-            max_completion_tokens=1024,
+            temperature=0.5,  # Plus bas pour plus de précision
+            max_completion_tokens=2048,
             top_p=1,
-            stream=True,
+            stream=False,  # Non-stream pour parsing facile
             stop=None
         )
 
-        # Collect streamed response
-        response = ""
-        for chunk in completion:
-            response += chunk.choices[0].delta.content or ""
-        return response
+        response = completion.choices[0].message.content
+
+        # Parse la réponse en DataFrame
+        df = parse_markdown_table_to_df(response)
+        excel_file = None
+        if df is not None:
+            # Crée un fichier Excel temporaire
+            with tempfile.NamedTemporaryFile(delete=False, suffix=".xlsx") as tmp:
+                df.to_excel(tmp.name, index=False)
+                excel_file = tmp.name
+
+        return response, excel_file
+
     except Exception as e:
-        return f"Error: {str(e)}"
+        return f"Erreur : {str(e)}", None
 
 # Define Gradio interface
 iface = gr.Interface(
     fn=process_image_and_get_response,
-    inputs=[
-        gr.Image(type="pil", label="Upload an Image"),
-        gr.Textbox(label="Describe the image (optional)", placeholder="Enter a description or leave blank")
+    inputs=gr.Image(type="pil", label="Uploader une image contenant un tableau"),
+    outputs=[
+        gr.Textbox(label="Réponse de l'IA (tableau Markdown)"),
+        gr.File(label="Télécharger le fichier Excel généré")
     ],
-    outputs=gr.Textbox(label="Groq AI Response"),
-    title="Image-based Groq AI Chat",
-    description="Upload an image and optionally provide a description. The Groq AI will respond based on the description."
+    title="Extraction de Tableau depuis Image avec Groq et Export Excel",
+    description="Uploader une image avec un tableau. L'IA Groq l'extrait en Markdown, et un Excel est généré automatiquement."
 )
 
 # Launch the interface