Flatten 1_raw_dataset submodules into plain tracked files

FocalLoRA, Should-It-Be-Executed-Or-Processed, and topicattack were
nested git repos (with an inner FocalLoRA/data/FocalLoRA/.git as well).
Drop their .git history and track the contents directly in this repo
instead of as submodules/gitlinks.

Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>

Codes/1_raw_dataset/topicattack/chatbot.py

@@ -0,0 +1,172 @@
+import time
+
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import torch
+import pprint
+from openai import OpenAI
+# openai.api_key =
+from utils import load_text
+import datetime
+
+
+
+class HuggingfaceChatbot:
+    def __init__(self, model, system_prompt, max_mem_per_gpu='40GiB'):
+        self.model = self.load_hugging_face_model(model, max_mem_per_gpu)
+        self.tokenizer = AutoTokenizer.from_pretrained(model)
+        self.system_prompt = load_text(system_prompt)
+
+    def load_hugging_face_model(self, model, max_mem_per_gpu='40GiB'):
+        MAX_MEM_PER_GPU = max_mem_per_gpu
+        map_list = {}
+        for i in range(torch.cuda.device_count()):
+            map_list[i] = MAX_MEM_PER_GPU
+        model = AutoModelForCausalLM.from_pretrained(
+            model,
+            device_map="auto",
+            max_memory=map_list,
+            torch_dtype="auto"
+        )
+        return model
+
+    def respond(self, message, max_new_tokens=256, defense_cross_prompt=False):
+        # global  SYS_INPUT
+        if isinstance(message, list):
+            messages = [{"role":"system", "content": self.system_prompt}] + message
+        else:
+            messages = [
+                {"role":"system", "content": self.system_prompt},
+                {"role": "user", "content": message},
+            ]
+
+        input_ids = self.tokenizer.apply_chat_template(
+            messages,
+            tokenize=True,
+            add_generation_prompt=True
+        )
+        # input_ids = self.tokenizer(message).input_ids
+        input_ids = torch.tensor(input_ids).view(1,-1).to(self.model.device)
+        generation_config = self.model.generation_config
+        generation_config.max_length = 8192
+        generation_config.max_new_tokens = max_new_tokens
+        generation_config.do_sample = False
+        # generation_config.do_sample = True
+        generation_config.temperature = 0.0
+        output = self.model.generate(
+            input_ids,
+            generation_config=generation_config
+        )
+        response = self.tokenizer.batch_decode(output[:, input_ids.shape[1]:], skip_special_tokens=True)[0]
+        response = response.strip()
+        return response
+
+class GPTChatbot:
+    def __init__(self, model, system_prompt):
+        self.model = model
+        self.system_prompt = load_text(system_prompt)
+    def respond(self, message, max_new_tokens=256, seed=42):
+        if isinstance(message, list):
+            messages = [{"role":"system", "content": self.system_prompt}] + message
+        else:
+            messages = [
+                {"role":"system", "content": self.system_prompt},
+                {"role": "user", "content": message},
+            ]
+        client = OpenAI(
+            api_key="API_KEY",  # This is the default and can be omitted
+        )
+        # time.sleep(1)
+        for _ in range(10):
+            try:
+                response = client.chat.completions.create(
+                    messages=messages,
+                    model=self.model,
+                    max_tokens=max_new_tokens,
+                    n=1,
+                    temperature=0.0,
+                    seed=seed
+                ).choices[0].message.content
+
+                response = response.strip()
+                return response
+            except Exception as e:
+                print(e)
+
+        return "fail"
+
+
+
+class OpensourceAPIChatbot:
+    def __init__(self, model, system_prompt):
+        self.model = model
+        self.system_prompt = load_text(system_prompt)
+        self.provider = {
+            "meta-llama/llama-3.3-70b-instruct":
+                {
+                    "HTTP-Referer": "https://openrouter.ai/provider/sambanova", # Optional. Site URL for rankings on openrouter.ai.
+                    "X-Title": "SambaNova", # Optional. Site title for rankings on openrouter.ai.
+                },
+            "qwen/qwen-2-72b-instruct":
+                {
+                    "HTTP-Referer": "https://openrouter.ai/provider/together",
+                    "X-Title": "Together",  # Optional. Site title for rankings on openrouter.ai.
+                },
+            "meta-llama/llama-3-70b-instruct":
+                {
+                    "HTTP-Referer": "https://openrouter.ai/provider/deepinfra",
+                    "X-Title": "DeepInfra",  # Optional. Site title for rankings on openrouter.ai.
+                },
+            "meta-llama/llama-3.1-405b-instruct":
+                {
+                    "HTTP-Referer": "https://openrouter.ai/provider/deepinfra",
+                    "X-Title": "DeepInfra",
+                },
+            "meta-llama/llama-3.1-70b-instruct":
+                {
+                    "HTTP-Referer": "https://openrouter.ai/provider/sambanova",
+                    "X-Title": "SambaNova",
+                },
+            "google/gemma-3-27b-it":{
+                    "HTTP-Referer": "https://openrouter.ai/provider/deepinfra",
+                    "X-Title": "DeepInfra",
+            },
+            "qwen/qwen3-32b":{
+                    "HTTP-Referer": "https://openrouter.ai/provider/deepinfra",
+                    "X-Title": "DeepInfra",
+            }
+
+
+
+
+        }
+
+    def respond(self, message, max_new_tokens=256, seed=42):
+        # global  SYS_INPUT
+        if isinstance(message, list):
+            messages = [{"role":"system", "content": self.system_prompt}] + message
+        else:
+            messages = [
+                # {"role": "system", "content": "Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request."},
+                {"role":"system", "content": self.system_prompt},
+                {"role": "user", "content": message},
+            ]
+        client = OpenAI(
+          base_url="https://openrouter.ai/api/v1",
+          api_key="API_KEY",
+        )
+        # time.sleep(1)
+        for _ in range(10):
+            try:
+                response = client.chat.completions.create(
+                  extra_headers=self.provider[self.model],
+                  extra_body={},
+                  model=self.model,
+                  messages=messages,
+                  temperature=0.0,
+                  max_tokens=max_new_tokens,
+                  seed=seed
+                ).choices[0].message.content
+                return response
+            except Exception as e:
+                print(e)
+        return "Fail"