fix build

lib/model_prompts.json

@@ -1,12 +0,0 @@
-{
-    "alpaca": "Below is an instruction that describes a task. Write a response that appropriately completes the request.\n\n### Instruction:\n{prompt}\n\n### Response:\n\n",
-    "ggml": "A chat between a curious human and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the human's questions.\n\n### Human: Hello, Assistant.\n### Assistant: Hello. How may I help you today?\n### Human: ${prompt}",
-    "gpt4": "### Instruction:\n{prompt}\n\n### Response:\n",
-    "hermes": "### Instruction:\n{prompt}\n\n### Response:\n",
-    "oasst": "{prompt}",
-    "orca": "### System:\nYou are an AI assistant that follows instruction extremely well. Help as much as you can.\n\n### User:\n{prompt}\n\n### Response:",
-    "qlora": "### Human: {prompt}\n### Assistant:",
-    "tulu": "\n{prompt}\n\n(include newline)",
-    "vicuna": "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions.\n\nUSER: {prompt}\nASSISTANT:",
-    "wizardlm": "{prompt}\n\n### Response:"
-}

lib/template.py

@@ -1,20 +0,0 @@
-from difflib import SequenceMatcher
-import json
-
-with open("model_prompts.json", "r") as f:
-    model_prompts = json.load(f)
-
-
-def template(model, prompt):
-    max_ratio = 0
-    closest_key = ""
-    model_name = model.lower()
-    # Find the specialized prompt with the closest name match
-    for key in model_prompts.keys():
-        ratio = SequenceMatcher(None, model_name, key).ratio()
-        if ratio > max_ratio:
-            max_ratio = ratio
-            closest_key = key
-    # Return the value of the closest match
-    p = model_prompts.get(closest_key)  # TODO: provide a better default template
-    return p.format(prompt=prompt)