Create app.py

app.py

@@ -0,0 +1,42 @@
+import gradio as gr
+import gradio_client
+from gradio_client import Client 
+
+
+
+def chat_api_interface(messages, model, frequency_penalty=0, logit_bias=None, max_tokens=None, n=1, presence_penalty=0, response_format="text", seed=None, stop=None, stream=False, temperature=1, top_p=1, tools=None, tool_choice="none", user=None):
+    # PASS
+    # PASS
+    return "API response here"
+
+with gr.Blocks() as demo:
+    with gr.Row():
+        with gr.Column():
+            messages = gr.Textbox(label="Messages (JSON format)", placeholder="Enter messages as a JSON array")
+            model = gr.Textbox(label="Model ID", placeholder="Enter the model ID")
+            frequency_penalty = gr.Number(label="Frequency Penalty", value=0)
+            logit_bias = gr.Textbox(label="Logit Bias (JSON format)", placeholder="Enter logit bias as JSON")
+            max_tokens = gr.Number(label="Max Tokens", optional=True)
+            n = gr.Number(label="N", value=1)
+            presence_penalty = gr.Number(label="Presence Penalty", value=0)
+            response_format = gr.Radio(label="Response Format", choices=["text", "json_object"], value="text")
+            seed = gr.Number(label="Seed", optional=True)
+            stop = gr.Textbox(label="Stop Sequence(s)", placeholder="Enter stop sequences")
+            stream = gr.Checkbox(label="Stream", value=False)
+            temperature = gr.Slider(label="Temperature", minimum=0, maximum=2, value=1)
+            top_p = gr.Slider(label="Top P", minimum=0, maximum=1, value=1)
+            tools = gr.Textbox(label="Tools (JSON format)", optional=True, placeholder="Enter tools as JSON")
+            tool_choice = gr.Textbox(label="Tool Choice", value="none", placeholder="Enter tool choice")
+            user = gr.Textbox(label="User", optional=True, placeholder="Enter user identifier")
+
+        with gr.Column():
+            submit_btn = gr.Button("Submit")
+            output = gr.Textbox(label="API Response", readonly=True)
+
+    submit_btn.click(
+        chat_api_interface, 
+        inputs=[messages, model, frequency_penalty, logit_bias, max_tokens, n, presence_penalty, response_format, seed, stop, stream, temperature, top_p, tools, tool_choice, user],
+        outputs=output
+    )
+
+demo.launch()