Create app.py

app.py

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+import gradio as gr
+from huggingface_hub import InferenceClient
+import gradio as gr
+import random
+
+checkpoint = "mistralai/Mixtral-8x7B-Instruct-v0.1"
+client = InferenceClient(checkpoint)
+
+
+def format_prompt(raw_Prompt):
+    better_prompt = f"[INST] {raw_Prompt} [/INST]"
+    return better_prompt
+
+
+def findShops(target_platform, target_region, target_field, target_rangeFrom, target_rangeTo, target_crossSelling, target_similarArticles, target_amount):
+    requestPrompt = f"""
+    Search for {target_amount} Shops that use the platform {target_platform}.
+    Make sure the recommended shops are located in {target_region}.
+    The websites of the recommended shops should have between {target_rangeFrom} and {target_rangeTo} monthly visitors."""
+    crossSellingPrompt = """
+    The recommended shops should be potential customers for a software that improves the cross-selling on their website."""
+    similarArticlesPrompt = """
+    The recommended shops should be potential customers for a software that can recommend similar products to the customers."""
+    fieldPrompt = f"""
+    Focus on shops that have a focus on the topic'{target_field}'."""
+    stylePrompt = """
+    Leave an empty line between your recommendations.
+    Present your results in a list with the names of the shops as the headings."""
+    fullPrompt = requestPrompt
+    if target_crossSelling:
+        fullPrompt += crossSellingPrompt
+    if target_similarArticles:
+        fullPrompt += similarArticlesPrompt
+    if target_field != 'All':
+        fullPrompt += fieldPrompt
+    fullPrompt += stylePrompt
+    generate_kwargs = dict(
+        temperature=0.2,
+        max_new_tokens=10000,
+        top_p=0.9,
+        repetition_penalty=1.0,
+        do_sample=True,
+        seed=random.randint(0, 100000),
+    )
+    stream = client.text_generation(format_prompt(fullPrompt),
+                                    **generate_kwargs,
+                                    stream=True,
+                                    details=True,
+                                    return_full_text=False)
+    output = ""
+    for response in stream:
+        output += response.token.text
+    output = output.removesuffix('</s>')
+    return output
+
+
+with gr.Blocks(title="Shop finder",
+               theme=gr.themes.Soft(primary_hue="sky")) as app:
+    gr.Markdown(
+        "##  Shop finder")
+    gr.Markdown(
+        "Choose the right settings and click **FIND** to search for shops.")
+    with gr.Group():
+        gr.Markdown("**FILTERS**")
+        with gr.Column():
+            platform = gr.Dropdown(choices=['Shopware', 'Shopify'],
+                                   value='Shopware',
+                                   interactive=True,
+                                   label="PLATFORM")
+            region = gr.Dropdown(choices=['Germany', 'England', 'France', 'Italy', 'Austria'],
+                                 value='Germany',
+                                 interactive=True,
+                                 label="REGION")
+            field = gr.Dropdown(choices=['All', 'Home & Living', 'Clothing', 'Electronics', 'Sports', 'Toys'],
+                                value='All',
+                                interactive=True,
+                                label="FIELD")
+    with gr.Group():
+        gr.Markdown("**MONTHLY VISITORS**")
+        with gr.Row():
+            range_from = gr.Slider(minimum=0,
+                                   maximum=1_000_000,
+                                   value=100,
+                                   step=100,
+                                   label="FROM",
+                                   interactive=True)
+            range_to = gr.Slider(minimum=0,
+                                 maximum=1_000_000,
+                                 value=10_000,
+                                 step=100,
+                                 label="TO",
+                                 interactive=True)
+    with gr.Group():
+        gr.Markdown("**POTENTIAL PRODUCT**")
+        with gr.Row():
+            opt_crossSelling = gr.Checkbox(value=False,
+                                           label='CROSSELLING POTENTIAL',
+                                           interactive=True)
+            opt_similarArticles = gr.Checkbox(value=False,
+                                              label='SIMILARITY POTENTIAL',
+                                              interactive=True)
+    numberOfShops = gr.Slider(minimum=1,
+                              maximum=50,
+                              value=10,
+                              step=1,
+                              label="AMOUNT",
+                              interactive=True)
+
+    btn = gr.Button("FIND")
+    with gr.Group():
+        gr.Markdown("**RESULTS**")
+        out = gr.Textbox(lines=10,
+                         max_lines=100,
+                         label='POTENTIAL SHOPS')
+    btn.click(fn=findShops,
+              inputs=[platform, region, field,
+                      range_from, range_to,
+                      opt_crossSelling,
+                      opt_similarArticles,
+                      numberOfShops],
+              outputs=out)
+
+app.launch(show_api=False)