app.py

app.py

@@ -1,3 +1,153 @@
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+app.py
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 import gradio as gr
+import requests
+import json
+import os
+from screenshot import (
+    before_prompt,
+    prompt_to_generation,
+    after_generation,
+    js_save,
+    js_load_script,
+)
+from spaces_info import description, examples, initial_prompt_value
+
+API_URL = os.getenv("API_URL")
+HF_API_TOKEN = os.getenv("HF_API_TOKEN")
+
+
+def query(payload):
+    print(payload)
+    response = requests.request("POST", API_URL, json=payload, headers={"Authorization": f"Bearer {HF_API_TOKEN}"})
+    print(response)
+    return json.loads(response.content.decode("utf-8"))
+
+
+def inference(input_sentence, max_length, sample_or_greedy, seed=42):
+    if sample_or_greedy == "Sample":
+        parameters = {
+            "max_new_tokens": max_length,
+            "top_p": 0.9,
+            "do_sample": True,
+            "seed": seed,
+            "early_stopping": False,
+            "length_penalty": 0.0,
+            "eos_token_id": None,
+        }
+    else:
+        parameters = {
+            "max_new_tokens": max_length,
+            "do_sample": False,
+            "seed": seed,
+            "early_stopping": False,
+            "length_penalty": 0.0,
+            "eos_token_id": None,
+        }
+
+    payload = {"inputs": input_sentence, "parameters": parameters,"options" : {"use_cache": False} }
+
+    data = query(payload)
+
+    if "error" in data:
+        return (None, None, f"<span style='color:red'>ERROR: {data['error']} </span>")
+
+    generation = data[0]["generated_text"].split(input_sentence, 1)[1]
+    return (
+        before_prompt
+        + input_sentence
+        + prompt_to_generation
+        + generation
+        + after_generation,
+        data[0]["generated_text"],
+        "",
+    )
+
+
+if __name__ == "__main__":
+    demo = gr.Blocks()
+    with demo:
+        with gr.Row():
+            gr.Markdown(value=description)
+        with gr.Row():
+            with gr.Column():
+                text = gr.Textbox(
+                    label="Input",
+                    value=" ",  # should be set to " " when plugged into a real API
+                )
+                tokens = gr.Slider(1, 64, value=32, step=1, label="Tokens to generate")
+                sampling = gr.Radio(
+                    ["Sample", "Greedy"], label="Sample or greedy", value="Sample"
+                )
+                sampling2 = gr.Radio(
+                    ["Sample 1", "Sample 2", "Sample 3", "Sample 4", "Sample 5"],
+                    value="Sample 1",
+                    label="Sample other generations (only work in 'Sample' mode)",
+                    type="index",
+                )
+
+                with gr.Row():
+                    submit = gr.Button("Submit")
+                    load_image = gr.Button("Generate Image")
+            with gr.Column():
+                text_error = gr.Markdown(label="Log information")
+                text_out = gr.Textbox(label="Output")
+                display_out = gr.HTML(label="Image")
+                display_out.set_event_trigger(
+                    "load",
+                    fn=None,
+                    inputs=None,
+                    outputs=None,
+                    no_target=True,
+                    js=js_load_script,
+                )
+        with gr.Row():
+            gr.Examples(examples=examples, inputs=[text, tokens, sampling, sampling2])
+
+        submit.click(
+            inference,
+            inputs=[text, tokens, sampling, sampling2],
+            outputs=[display_out, text_out, text_error],
+        )
+
+        load_image.click(fn=None, inputs=None, outputs=None, _js=js_save)
+
+    demo.launch()
 
-gr.Interface.load("models/bigscience/bloom").launch()