updated app.py

app.py

@@ -1,7 +1,50 @@
 import gradio as gr
+from llama_cpp import Llama
 
-def greet(name):
-    return "Hello " + name + "!!"
+llm = Llama.from_pretrained(
+    repo_id="amir22010/fine_tuned_product_marketing_email_gemma_2_9b_q4_k_m",
+    filename="unsloth.Q4_K_M.gguf",
+    verbose=False
+)
 
-demo = gr.Interface(fn=greet, inputs="text", outputs="text")
+#marketing prompt
+marketing_email_prompt = """Below is a product and description, please write a marketing email for this product.
+
+### Product:
+{}
+
+### Description:
+{}
+
+### Marketing Email:
+{}"""
+
+def greet(product,description):
+    output = llm.create_chat_completion(
+    messages=[
+        {
+            "role": "system",
+            "content": "Your go-to Email Marketing Guru - I'm here to help you craft compelling campaigns, boost conversions, and take your business to the next level.",
+        },
+        {"role": "user", "content":  marketing_email_prompt.format(
+    product, # product
+    description, # description
+    "", # output - leave this blank for generation!
+    )},
+    ],
+    # response_format={
+    #     "type": "json_object",
+    # },
+    max_tokens=8192,
+    temperature=0.7,
+    stream=True
+    )
+    for chunk in output:
+        delta = chunk['choices'][0]['delta']
+        if 'role' in delta:
+            yield delta['role']
+        elif 'content' in delta:
+            yield delta['content']
+
+demo = gr.Interface(fn=greet, inputs=["text","text"], outputs="text")
 demo.launch()

requirements.txt

@@ -0,0 +1,3 @@
+torch
+huggingface-hub
+llama-cpp-python