Update app.py

app.py

@@ -7,16 +7,17 @@ import fitz  # PyMuPDF for PDFs
 # ----------------------------
 # SECRETS FROM ENVIRONMENT
 # ----------------------------
-HF_API_KEY = os.environ.get("HF_API_KEY")
-OCR_API_KEY = os.environ.get("OCR_API_KEY")
-
-if not HF_API_KEY or not OCR_API_KEY:
-    raise ValueError("HF_API_KEY or OCR_API_KEY not found in environment variables.")
+GROQ_API_KEY = os.environ.get("GROQ_API_KEY")
+if not GROQ_API_KEY:
+    raise ValueError("GROQ_API_KEY not found in environment variables.")
 
 # ----------------------------
 # OCR FUNCTION
 # ----------------------------
 def extract_text_from_image(file_path):
+    OCR_API_KEY = os.environ.get("OCR_API_KEY")
+    if not OCR_API_KEY:
+        return ""
     url = "https://api.ocr.space/parse/image"
     with open(file_path, "rb") as f:
         r = requests.post(
@@ -36,9 +37,12 @@ def extract_text_from_image(file_path):
 # ----------------------------
 def extract_text_from_pdf(file_path):
     text = ""
-    doc = fitz.open(file_path)
-    for page in doc:
-        text += page.get_text()
+    try:
+        doc = fitz.open(file_path)
+        for page in doc:
+            text += page.get_text()
+    except:
+        text = ""
     return text
 
 # ----------------------------
@@ -75,10 +79,8 @@ def build_prompt(user_text, file_text, link_info, mentions, hashtags, custom_pro
     return prompt
 
 # ----------------------------
-# GENERATE POST FUNCTION
+# GENERATE POST FUNCTION (Groq GPT)
 # ----------------------------
-HF_MODEL = "Qwen2.5-Coder-7B-Instruct"  # Hugging Face model
-
 def generate_post(file, user_text, link_info, mentions, hashtags, custom_prompt, checked_suggestions):
     file_text = ""
     if file:
@@ -89,14 +91,19 @@ def generate_post(file, user_text, link_info, mentions, hashtags, custom_prompt,
     
     prompt = build_prompt(user_text, file_text, link_info, mentions, hashtags, custom_prompt, checked_suggestions)
     
-    headers = {"Authorization": f"Bearer {HF_API_KEY}"}
-    json_data = {"inputs": prompt, "parameters": {"max_new_tokens": 400}}
-    
-    response = requests.post(f"https://api-inference.huggingface.co/models/{HF_MODEL}", headers=headers, json=json_data)
-    
+    url = "https://api.groq.com/v1/generate"  # Replace with correct Groq GPT endpoint if needed
+    headers = {
+        "Authorization": f"Bearer {GROQ_API_KEY}",
+        "Content-Type": "application/json"
+    }
+    data = {
+        "model": "groq-gpt-large",   # Example model, change to available Groq GPT model
+        "prompt": prompt,
+        "max_tokens": 400
+    }
+    r = requests.post(url, headers=headers, json=data)
     try:
-        result = response.json()
-        return result[0]["generated_text"]
+        return r.json()["text"]
     except Exception as e:
         return f"Error generating post: {str(e)}"
 
@@ -104,7 +111,7 @@ def generate_post(file, user_text, link_info, mentions, hashtags, custom_prompt,
 # GRADIO UI
 # ----------------------------
 with gr.Blocks() as demo:
-    gr.Markdown("## LinkedIn Post Generator (HF + Gradio)")
+    gr.Markdown("## LinkedIn Post Generator (Groq GPT + Gradio)")
     
     file_input = gr.File(label="Upload PDF/Image", type="filepath")
     user_text = gr.Textbox(label="Main Text", lines=3)