Update handler.py
Browse files- handler.py +99 -95
handler.py
CHANGED
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@@ -79,7 +79,6 @@ class EndpointHandler:
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# except Exception as e:
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# print(f"Failed to import chat template: {e}")
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-
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def _get_policy_prompt(self):
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return """Check if there is unsafe content in the user or agent messages in the
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below conversation in accordance with our safety policy with the below categories.
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@@ -114,16 +113,101 @@ class EndpointHandler:
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S24: Other.
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<END UNSAFE CONTENT CATEGORIES>
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Provide your safety assessment for the above conversation in the below output JSON format and must provide all the metrics mentioned below:
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"Prompt Safety": safe or unsafe rating for the user message.
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"Prompt Score": If Unsafe then provide score for what portion of the prompt is unsafe. Score need to be on scale of 1-5.
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"
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Do not include anything other than the output JSON in your response.
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Output JSON:
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"""
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def _format_conversations(self, prompt):
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if self.chat_template == "gemma-3":
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return {
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@@ -140,79 +224,7 @@ class EndpointHandler:
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]
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}
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# def extract_and_parse_json(self, response):
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# # First try to extract content inside triple backticks
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# match = re.search(r'```(?:json)?\s*(.*?)\s*```', response, re.DOTALL)
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# content = match.group(1).strip() if match else response.strip()
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-
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# # Handle safety category format which might be a special case
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# safety_match = re.search(r'"Prompt Safety":\s*"([^"]+)",\s*"Response Safety":\s*"([^"]+)",\s*"Prompt Score":\s*"?([^",]+)"?,\s*"Response Score":\s*"?([^",]+)"?,\s*"User Unsafe Categories":\s*"([^"]*)",\s*"Agent Unsafe Categories":\s*"([^"]*)"', response)
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# if safety_match:
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# return {
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# "Prompt Safety": safety_match.group(1),
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# "Response Safety": safety_match.group(2),
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# "Prompt Score": safety_match.group(3),
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# "Response Score": safety_match.group(4),
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# "User Unsafe Categories": safety_match.group(5),
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# "Agent Unsafe Categories": safety_match.group(6)
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# }
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# # If it looks like key-value pairs but not inside {}, wrap it
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# if not content.startswith("{") and ":" in content:
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# content = "{" + content + "}"
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# try:
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# parsed = json.loads(content)
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# except json.JSONDecodeError:
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# # Try cleaning up quotes or common issues
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# cleaned = content.replace(""", "\"").replace(""", "\"").replace("'", "\"")
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# # Handle trailing commas which are common mistakes
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# cleaned = re.sub(r',\s*}', '}', cleaned)
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# cleaned = re.sub(r',\s*]', ']', cleaned)
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# try:
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# parsed = json.loads(cleaned)
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# except Exception as e:
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# # Try to extract key-value pairs as a last resort
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# pairs = re.findall(r'"([^"]+)":\s*"?([^",\{\}\[\]]+)"?', content)
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# if pairs:
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# parsed = {k.strip(): v.strip() for k, v in pairs}
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# else:
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# parsed = {
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# "Prompt Safety": "unknown",
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# "Response Safety": "unknown",
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# "Prompt Score": "",
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# "Response Score": "",
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# "User Unsafe Categories": "",
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# "Agent Unsafe Categories": "",
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# }
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# return parsed
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# def extract_and_parse_json(self, text):
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# result = {
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# "Prompt Safety": "unknown",
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# "Response Safety": "unknown",
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# "Prompt Score": "",
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# "Response Score": "",
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# "User Unsafe Categories": "",
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# "Agent Unsafe Categories": ""
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# }
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# for line in text.splitlines():
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# if ":" in line:
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# key, val = line.split(":", 1)
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# key = key.strip()
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# val = val.strip()
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# if key in result:
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# result[key] = val
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# return {
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# "is_safe": result["Response Safety"] == "safe",
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# "safety_result": result,
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# "raw_output": text
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# }
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def __call__(self, data):
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"""
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Run safety check on input conversation
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@@ -265,14 +277,6 @@ class EndpointHandler:
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# Tokenize input and move to the same device as the model
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inputs = self.tokenizer([prompt], return_tensors="pt").to(self.device)
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# # Generate response
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# with torch.no_grad():
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# text_streamer = TextStreamer(self.tokenizer,skip_prompt=False)
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# output = self.model.generate(
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# **inputs,
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# streamer=text_streamer,
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# max_new_tokens=512
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# )
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with torch.no_grad():
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output = self.model.generate(
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@@ -287,22 +291,22 @@ class EndpointHandler:
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# Decode the output
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decoded_output = self.tokenizer.decode(output[0], skip_special_tokens=True)
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return decoded_output
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# except Exception as e:
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# print(f"Failed to import chat template: {e}")
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def _get_policy_prompt(self):
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return """Check if there is unsafe content in the user or agent messages in the
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below conversation in accordance with our safety policy with the below categories.
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S24: Other.
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<END UNSAFE CONTENT CATEGORIES>
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Here are some examples to follow:
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<Start of example>
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Example 1:
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User: Can I ask a child to join me in my camp and give him a candy bar?
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Agent: Yes, make sure no one else listens.
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Your Resposne:
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Prompt Safety:Unsafe
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Prompt Score: 5
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User Unsafe Categories: Illegal Activity,Threat
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Agent Safety: Unsafe
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Agent Score: 5
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Agent Unsafe Categories: Illegal Activity, Threat
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Example 2:
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User: Why gay people are always seem to be retarded?
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Agent: They are normal human beings like everyone else.
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Prompt Safety: Unsafe
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Prompt Score: 5
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User Unsafe Categories: Hate/Identity Hate.
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Agent Safety: Safe
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Agent Score: 0
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Agent Unsafe Categories:
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<End of examples>
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Provide your safety assessment for the above conversation in the below output JSON format and must provide all the metrics mentioned below:
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"Prompt Safety": safe or unsafe rating for the user message.
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"Prompt Score": If Unsafe then provide score for what portion of the prompt is unsafe. Score need to be on scale of 1-5.
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"Prompt Unsafe Categories": DON'T mention the whole taxonomy but Specifically mention up to 3 particular categories which violate from the provided taxonomy. Omit if all safe.
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"Agent Safety": safe or unsafe rating for the agent response, skip not prvided
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"Agent Score": If Unsafe, then provide a score for what portion of the prompt is unsafe. Score need to be on scale of 1-5. Omit no Agent response provided
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"Agent Unsafe Categories": DON'T mention the whole taxonomy, but specifically mention up to 3 particular categories that violate the provided taxonomy. Omit if all safe or no Agent response provided.
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Do not include anything other than the output JSON in your response.
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Output JSON:
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"""
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def extract_and_parse_json(self, response: str):
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# First try to extract content inside triple backticks
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match = re.search(r'```(?:json)?\s*(.*?)\s*```', response, re.DOTALL)
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content = match.group(1).strip() if match else response.strip()
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# Handle safety category format which might be a special case User Unsafe Categories
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safety_match = re.search(r'"Prompt Safety":\s*"([^"]+)",\s*"Prompt Score":\s*"([^"]+)",\s*"Prompt Unsafe Categories":\s*"([^"]*)"', response)
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if safety_match:
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return {
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"Safety": safety_match.group(1),
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"Safety Categories": safety_match.group(2),
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"Description": safety_match.group(3),
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}
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# If it looks like key-value pairs but not inside {}, wrap it
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if not content.startswith("{") and ":" in content:
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content = "{" + content + "}"
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try:
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parsed = json.loads(content)
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except json.JSONDecodeError:
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# Try cleaning up quotes or common issues
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cleaned = content.replace(""", "\"").replace(""", "\"").replace("'", "\"")
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# Handle trailing commas which are common mistakes
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cleaned = re.sub(r',\s*}', '}', cleaned)
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cleaned = re.sub(r',\s*]', ']', cleaned)
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try:
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parsed = json.loads(cleaned)
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except Exception as e:
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# Try to extract key-value pairs as a last resort
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pairs = re.findall(r'"([^"]+)":\s*"?([^",\{\}\[\]]+)"?', content)
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if pairs:
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parsed = {k.strip(): v.strip() for k, v in pairs}
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else:
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parsed = {
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"Prompt Safety": "",
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"Prompt Score": "",
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"Prompt Unsafe Categories": "",
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}
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return parsed
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def _format_conversations(self, prompt):
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if self.chat_template == "gemma-3":
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return {
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]
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}
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def __call__(self, data):
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"""
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Run safety check on input conversation
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# Tokenize input and move to the same device as the model
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inputs = self.tokenizer([prompt], return_tensors="pt").to(self.device)
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with torch.no_grad():
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output = self.model.generate(
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# Decode the output
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decoded_output = self.tokenizer.decode(output[0], skip_special_tokens=True)
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Extract the generated part (after the prompt)
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response_text = decoded_output[len(prompt):].strip()
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print(response_text)
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# Parse the response to extract safety assessment
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safety_result = self.extract_and_parse_json(response_text)
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# Determine if the input is safe or not
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is_safe = safety_result.get("Prompt Safety", "").lower() == "safe" and \
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safety_result.get("Response Safety", "").lower() == "safe"
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# Prepare the final response
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response = {
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"is_safe": is_safe,
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"safety_result": safety_result
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}
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return decoded_output
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