Duplicate from cahya/indochat

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README.md

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+---
+title: Indochat
+emoji: 🇮🇩
+colorFrom: purple
+colorTo: red
+sdk: gradio
+sdk_version: 3.18.0
+app_file: app.py
+pinned: false
+license: creativeml-openrail-m
+duplicated_from: cahya/indochat
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

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+import gradio as gr
+import os
+from mtranslate import translate
+import requests
+
+HF_AUTH_TOKEN = os.environ.get("HF_AUTH_TOKEN")
+indochat_api = 'https://cahya-indonesian-whisperer.hf.space/api/indochat/v1'
+indochat_api_auth_token = os.getenv("INDOCHAT_API_AUTH_TOKEN", "")
+
+def get_answer(user_input, decoding_method, num_beams, top_k, top_p, temperature, repetition_penalty, penalty_alpha):
+    print(user_input, decoding_method, top_k, top_p, temperature, repetition_penalty, penalty_alpha)
+    headers = {'Authorization': 'Bearer ' + indochat_api_auth_token}
+    data = {
+        "text": user_input,
+        "min_length": len(user_input) + 50,
+        "max_length": 300,
+        "decoding_method": decoding_method,
+        "num_beams": num_beams,
+        "top_k": top_k,
+        "top_p": top_p,
+        "temperature": temperature,
+        "seed": -1,
+        "repetition_penalty": repetition_penalty,
+        "penalty_alpha": penalty_alpha
+    }
+    r = requests.post(indochat_api, headers=headers, data=data)
+    if r.status_code == 200:
+        result = r.json()
+        answer = result["generated_text"]
+        user_input_en = translate(user_input, "en", "id")
+        answer_en = translate(answer, "en", "id")
+        return [(f"{user_input}\n", None), (answer, "")], \
+            [(f"{user_input_en}\n", None), (answer_en, "")]
+    else:
+        return "Error: " + r.text
+
+
+css = """
+#answer_id span {white-space: pre-line}
+#answer_id span.label {display: none}
+#answer_en span {white-space: pre-line}
+#answer_en span.label {display: none}
+"""
+
+with gr.Blocks(css=css) as demo:
+    with gr.Row():
+        gr.Markdown("""## IndoChat
+        
+        A Prove of Concept of a multilingual Chatbot (in this case a bilingual, English and Indonesian), fine-tuned with 
+        multilingual instructions dataset. The base model is a GPT2-Medium (340M params) which was pretrained with 75GB 
+        of Indonesian and English dataset, where English part is only less than 1% of the whole dataset.
+        """)
+    with gr.Row():
+        with gr.Column():
+            user_input = gr.inputs.Textbox(placeholder="",
+                                           label="Ask me something in Indonesian or English",
+                                           default="Bagaimana cara mendidik anak supaya tidak berbohong?")
+            decoding_method = gr.inputs.Dropdown(["Beam Search", "Sampling", "Contrastive Search"],
+                                                  default="Sampling", label="Decoding Method")
+            num_beams = gr.inputs.Slider(label="Number of beams for beam search",
+                                     default=1, minimum=1, maximum=10, step=1)
+            top_k = gr.inputs.Slider(label="Top K",
+                                     default=30, maximum=50, minimum=1, step=1)
+            top_p = gr.inputs.Slider(label="Top P", default=0.9, step=0.05, minimum=0.1, maximum=1.0)
+            temperature = gr.inputs.Slider(label="Temperature", default=0.5, step=0.05, minimum=0.1, maximum=1.0)
+            repetition_penalty = gr.inputs.Slider(label="Repetition Penalty", default=1.1, step=0.05, minimum=1.0, maximum=2.0)
+            penalty_alpha = gr.inputs.Slider(label="The penalty alpha for contrastive search",
+                                             default=0.5, step=0.05, minimum=0.05, maximum=1.0)
+            with gr.Row():
+                button_generate_story = gr.Button("Submit")
+        with gr.Column():
+            # generated_answer = gr.Textbox()
+            generated_answer = gr.HighlightedText(
+                elem_id="answer_id",
+                label="Generated Text",
+                combine_adjacent=True,
+                css="#htext span {white-space: pre-line}",
+            ).style(color_map={"": "blue", "-": "green"})
+            generated_answer_en = gr.HighlightedText(
+                elem_id="answer_en",
+                label="Translation",
+                combine_adjacent=True,
+            ).style(color_map={"": "blue", "-": "green"})
+    with gr.Row():
+        gr.Markdown("![visitor badge](https://visitor-badge.glitch.me/badge?page_id=cahya_indochat)")
+
+    button_generate_story.click(get_answer,
+                                inputs=[user_input, decoding_method, num_beams, top_k, top_p, temperature,
+                                        repetition_penalty, penalty_alpha],
+                                outputs=[generated_answer, generated_answer_en])
+
+demo.launch(enable_queue=False)

requirements.txt

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+torch
+transformers
+mtranslate