Roll back to Llama 3

chatbot_as_block.py

@@ -0,0 +1,44 @@
+import gradio as gr
+from huggingface_hub import InferenceClient
+import os
+
+HF_TOKEN = os.getenv('HF_TOKEN')
+
+client = InferenceClient("meta-llama/Meta-Llama-3-8B-Instruct", token=HF_TOKEN)
+
+def respond(
+    message,
+    history: list[tuple[str, str]],
+    code: str,
+):
+    messages = [{"role": "system", "content": "Tu es un assistant appelé Fabrice"}]
+
+    print(code)
+
+    for val in history:
+        if val[0]:
+            messages.append({"role": "user", "content": val[0] + ' \n' + code})
+        if val[1]:
+            messages.append({"role": "assistant", "content": val[1]})
+
+    messages.append({"role": "user", "content": message + ' \n' + code})
+
+    response = ""
+
+    for message in client.chat_completion(
+        messages,
+        max_tokens=512,
+        stream=True,
+        temperature=0.7,
+        top_p=0.4,
+    ):
+        token = message.choices[0].delta.content
+
+        response += token
+        yield response
+
+with gr.Blocks(analytics_enabled=True) as demo:
+    code = gr.Code(language="python")
+    gr.ChatInterface(respond, additional_inputs=code)
+
+demo.launch()