Add request to the model

.gitignore

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+*.env

app.py

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+import gradio as gr
+import os
+from dotenv import load_dotenv
+from text_generation import Client
+
+load_dotenv()
+
+API_TOKEN = os.environ.get("API_TOKEN", None)
+MODEL_URL = os.environ.get("MODEL_URL", None)
+
+def evaluate(hotel_request: str, **kwargs):
+    hf_client = Client(
+        MODEL_URL,
+        headers={"Authorization": f"Bearer {API_TOKEN}"},
+    )
+
+    stream = hf_client.generate_stream(
+        hotel_request,
+        **kwargs,
+    )
+
+    for response in stream:
+        output += response.token.text
+        yield output
+
+    return output
+
+gr.Interface(
+        fn=evaluate,
+        inputs=[
+        #     gr.components.Textbox(
+        #         lines=2,
+        #         label="Instruction",
+        #         placeholder="Tell me about alpacas.",
+        #     ),
+            gr.components.Textbox(lines=2, label="Input", placeholder="Request for the Hotel"),
+        #     gr.components.Slider(
+        #         minimum=0, maximum=1, value=0.1, label="Temperature"
+        #     ),
+        #     gr.components.Slider(
+        #         minimum=0, maximum=1, value=0.75, label="Top p"
+        #     ),
+        #     gr.components.Slider(
+        #         minimum=0, maximum=100, step=1, value=40, label="Top k"
+        #     ),
+        #     gr.components.Slider(
+        #         minimum=1, maximum=4, step=1, value=4, label="Beams"
+        #     ),
+        #     gr.components.Slider(
+        #         minimum=1, maximum=2000, step=1, value=128, label="Max tokens"
+        #     ),
+        #     gr.components.Checkbox(label="Stream output"),
+        ],
+        outputs=[
+            gr.inputs.Textbox(
+                lines=1,
+                label="Guest Name",
+            ),
+            gr.inputs.Textbox(
+                lines=1,
+                label="Hotel",
+            ),
+            gr.inputs.Textbox(
+                lines=1,
+                label="Location",
+            ),
+            gr.inputs.Textbox(
+                lines=1,
+                label="Date",
+            )
+        ],
+        allow_flagging="never",
+        title="Falcon-LoRA",
+        description="Falcon-LoRA is a 1B-parameter LLM finetuned to follow instructions. It is trained on the [Hotel Requests](https://huggingface.co/datasets/MichaelAI23/hotel_requests) dataset.",  # noqa: E501
+    ).queue().launch(server_name="0.0.0.0", server_port=8080)

requirements.txt

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+python-dotenv
+gradio
+bitsandbytes
+text-generation