Resolved merge conflict: fixed prompt file names

agent.py

@@ -0,0 +1,51 @@
+import os
+import requests
+
+GROQ_API_URL = "https://api.groqcloud.com/v1/chat/completions"
+GROQ_API_KEY = os.getenv("GROQ_API_KEY")  # Secure key from Hugging Face Secrets
+
+if not GROQ_API_KEY:
+    raise ValueError("GROQ_API_KEY is missing! Set it in Hugging Face Secrets.")
+    
+# Helper function to load system prompt from txt files
+def load_prompt(filename):
+    with open(f'config/system_prompts/{filename}', 'r') as file:
+        return file.read()
+
+# Function to call Groq API with system prompt and user input
+def call_groq(system_prompt, user_input):
+    headers = {"Authorization": f"Bearer {GROQ_API_KEY}"}
+    payload = {
+        "model": "mixtral-8x7b-32768",
+        "messages": [
+            {"role": "system", "content": system_prompt},
+            {"role": "user", "content": user_input}
+        ]
+    }
+    print("Sending payload to Groq API...")
+    print(payload)
+    response = requests.post(GROQ_API_URL, json=payload, headers=headers)
+    print("Groq API response status:", response.status_code)
+    print("Groq API response body:", response.text)
+
+    if response.status_code != 200:
+        raise Exception(f"Groq API error: {response.status_code} - {response.text}")
+    
+    data = response.json()
+    if 'choices' not in data or not data['choices']:
+        raise Exception("Groq API returned no choices.")
+
+    return data['choices'][0]['message']['content']
+
+def ad_copy_agent(product, description, audience, tone):
+    system_prompt = load_prompt("ad_copy_prompt.txt")
+    user_input = f"Product: {product}\nDescription: {description}\nAudience: {audience}\nTone: {tone}"
+    return call_groq(system_prompt, user_input)
+
+def sentiment_agent(social_data):
+    system_prompt = load_prompt("sentiment_prompt.txt")
+    return call_groq(system_prompt, social_data)
+
+def timing_agent(platform):
+    system_prompt = load_prompt("timing_prompt.txt")
+    return call_groq(system_prompt, f"Platform: {platform}")

app.py

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+import gradio as gr
+from agent import ad_copy_agent, sentiment_agent, timing_agent
+
+# Gradio UI definition
+with gr.Blocks() as demo:
+    gr.Markdown("# 📈 Marketing AI Dashboard")
+
+    with gr.Tab("Ad Copy Generator"):
+        prod = gr.Textbox(label="Product")
+        desc = gr.Textbox(label="Description")
+        audience = gr.Textbox(label="Audience")
+        tone = gr.Textbox(label="Tone")
+        ad_output = gr.Textbox(label="Generated Ads")
+        ad_button = gr.Button("Generate Ads")
+        ad_button.click(ad_copy_agent, [prod, desc, audience, tone], ad_output)
+
+    with gr.Tab("Sentiment Analyzer"):
+        social_input = gr.Textbox(label="Social Media Mentions / Input")
+        sentiment_output = gr.Textbox(label="Sentiment Analysis")
+        sentiment_button = gr.Button("Analyze Sentiment")
+        sentiment_button.click(sentiment_agent, social_input, sentiment_output)
+
+    with gr.Tab("Post Timing Recommender"):
+        platform_input = gr.Textbox(label="Platform (e.g., Facebook, Instagram)")
+        timing_output = gr.Textbox(label="Recommended Times")
+        timing_button = gr.Button("Get Recommendations")
+        timing_button.click(timing_agent, platform_input, timing_output)
+
+demo.launch()

config/system_prompts/timing_prompt.txt

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+You are a social media strategist. Recommend the 3 best time slots to post on social media for maximum engagement.
+
+Rules:
+- Base suggestions on typical platform engagement patterns.
+- Mention time zones.
+- Briefly explain why these times work.
+- Suggest one experimental or underused time.