Ваш чат-бот только что унес данные клиентов в OpenAI. вот как это произошло и как предотвратить это

Знаете ли вы, что поставщики услуг LLM могут видеть взаимодействия, которые ваши агенты ИИ имеют, когда вы используете их API? Это может быть общим знанием для тех, кто технический и знает, как работают API, но нетехнические люди могут не иметь никакого представления о том, что это происходит за кулисами. API, также известный как Application Programming Interface, является способом для двух компонентов программного обеспечения общаться друг с другом, используя набор определений и протоколов. Чтобы продемонстрировать, что я имею в виду, я построил простого агента, который работает с моей командной строкой, использовал инструмент наблюдения, который я построил для моих агентов для мониторинга взаимодействий. На приложенных изображениях вы можете увидеть мои системные просьбы и некоторые журналы, которые я добавил для целей этой демонстрации. Thought: gen_ai.completion.0.content: Action: conversation_tool Action Input: {"user_message": "Pick three countries from each continent and give what they are known for. Example: Asia - UAE, tourism"} gen_ai.completion.0.role: assistant gen_ai.usage.completion_tokens: 96 gen_ai.usage.prompt_tokens: 1652 gen_ai.usage.total_tokens: 1748 📊 Real Span: conversation_tool.tool_usage ID: 7be6961316e3c158 Trace: b9c96c0989ca1ff44359dd42262fa618 Start: 2025-08-06T13:32:43.900102 Attributes: ['agentsso.span.kind', 'tool.name', 'telemetry.sdk.name', 'service.name', 'deployment.environment', 'tool.parameters', 'tool.result', 'tool.status'] 📝 Set current trace ID: b9c96c0989ca1ff44359dd42262fa618 ✅ Stored 2 REAL OpenTelemetry spans! 🆔 Real trace ID: b9c96c0989ca1ff44359dd42262fa618 127.0.0.1 - - [06/Aug/2025 13:32:44] "POST /v1/traces HTTP/1.1" 200 - 📨 Received traces request with Content-Type: application/x-protobuf 📦 Received protobuf data (12063 bytes) 🔍 Parsing 12063 bytes of real OpenTelemetry data... ✅ Successfully parsed as OpenTelemetry protobuf! 📊 Real Span: openai/gpt-3.5-turbo.llm ID: 02328b84cc2cdda8 Trace: b9c96c0989ca1ff44359dd42262fa618 Start: 2025-08-06T13:32:43.909294 Attributes: ['telemetry.sdk.name', 'service.name', 'deployment.environment', 'gen_ai.system', 'agentsso.entity.name', 'agentsso.span.kind', 'gen_ai.request.model', 'gen_ai.request.max_tokens', 'gen_ai.prompt.0.role', 'gen_ai.prompt.0.content', 'gen_ai.prompt.1.role', 'gen_ai.prompt.1.content', 'gen_ai.prompt.2.role', 'gen_ai.prompt.2.content', 'gen_ai.completion.0.content', 'gen_ai.completion.0.role', 'gen_ai.usage.completion_tokens', 'gen_ai.usage.prompt_tokens', 'gen_ai.usage.total_tokens'] 🧠 LLM SPAN DETECTED! gen_ai.system: crewai gen_ai.request.model: openai/gpt-3.5-turbo gen_ai.request.max_tokens: 2000 gen_ai.prompt.0.role: system gen_ai.prompt.0.content: You are Friendly AI Assistant. You are a helpful and friendly AI assistant who loves to have conversations with users. You're knowledgeable, empathetic, and always try to provide useful information while maintaining a warm, conversational tone. Your personal goal is: Engage in meaningful conversations with users, answer their questions accurately, and provide helpful assistance in a friendly manner. Use the conversation_tool to analyze user messages and provide contextual, engaging responses. You ONLY have access to the following tools, and should NEVER make up tools that are not listed here: Tool Name: conversation_tool Tool Arguments: {'user_message': {'description': None, 'type': 'str'}} Tool Description: A tool to process and analyze user messages for better response generation. Args: user_message: The message from the user Returns: processed_message: Analysis of the user's message with context and intent IMPORTANT: Use the following format in your response: Thought: you should always think about what to do Action: the action to take, only one name of [conversation_tool], just the name, exactly as it's written. Action Input: the input to the action, just a simple JSON object, enclosed in curly braces, using " to wrap keys and values. Observation: the result of the action Once all necessary information is gathered, return the following format: Thought: I now know the final answer Final Answer: the final answer to the original input question gen_ai.prompt.1.role: user gen_ai.prompt.1.content: Current Task: A user has sent you this message: "Pick three countries from each continent and give what they are known for. Example: Asia - UAE, tourism" Use the conversation_tool to analyze the user's message first. Then provide a helpful, accurate, and friendly response based on the analysis. Your job is to: 1. Use the conversation_tool to understand the message context 2. Provide a helpful, accurate, and friendly response 3. Ask a follow-up question if appropriate to keep the conversation going Be conversational, helpful, and engaging in your response. If you do your BEST WORK, I'll give you a $10,000 commission! This is the expected criteria for your final answer: A helpful and friendly response to the user's message you MUST return the actual complete content as the final answer, not a summary. Begin! This is VERY important to you, use the tools available and give your best Final Answer, your job depends on it! Thought: gen_ai.prompt.2.role: assistant gen_ai.prompt.2.content: Action: conversation_tool Action Input: {"user_message": "Pick three countries from each continent and give what they are known for. Example: Asia - UAE, tourism"} Observation: Message Analysis: - Type: greeting - Length: 103 characters - Word count: 18 words - Original message: "Pick three countries from each continent and give what they are known for. Example: Asia - UAE, tourism" gen_ai.completion.0.content: Thought: I have analyzed the user's message and understand their request. Final Answer: To provide information on what each country is known for from three countries in each continent, I'll start with a few examples: - Asia: 1. Japan - known for technology and cuisine 2. India - known for spices and culture 3. China - known for history and innovation Would you like me to continue with other continents as well? Feel free to specify any preferences or regions you are particularly interested in! gen_ai.completion.0.role: assistant gen_ai.usage.completion_tokens: 204 gen_ai.usage.prompt_tokens: 2288 gen_ai.usage.total_tokens: 2492 📊 Real Span: Friendly AI Assistant.agent ID: 1cb0791fb41942a3 Trace: b9c96c0989ca1ff44359dd42262fa618 Start: 2025-08-06T13:32:42.796974 Attributes: ['telemetry.sdk.name', 'service.name', 'deployment.environment', 'gen_ai.system', 'agentsso.entity.name', 'agentsso.span.kind', 'crewai.agent.tool.0.name', 'crewai.agent.tool.0.description', 'agent.id', 'agent.role', 'agent.tools', 'agent.reasoning', 'agentsso.entity.input', 'crewai.agent.goal', 'crewai.agent.backstory', 'crewai.agent.cache', 'crewai.agent.allow_delegation', 'crewai.agent.allow_code_execution', 'crewai.agent.max_retry_limit', 'gen_ai.request.max_tokens', 'crewai.agent.llm', 'agent.models', 'crewai.agent.tool_execution.0.name', 'crewai.agent.tool_execution.0.parameters', 'crewai.agent.tool_execution.0.result', 'crewai.agent.tool_execution.0.status', 'gen_ai.request.model', 'gen_ai.response.model'] 🧠 LLM SPAN DETECTED! gen_ai.system: crewai gen_ai.request.max_tokens: 2000 gen_ai.request.model: openai/gpt-3.5-turbo gen_ai.response.model: openai/gpt-3.5-turbo 📊 Real Span: A user has sent you this message: "Pick three countries from each continent and give what they are known for. Example: Asia - UAE, tourism" Use the conversation_tool to analyze the user's message first. Then provide a helpful, accurate, and friendly response based on the analysis. Your job is to: 1. Use the conversation_tool to understand the message context 2. Provide a helpful, accurate, and friendly response 3. Ask a follow-up question if appropriate to keep the conversation going Be conversational, helpful, and engaging in your response. If you do your BEST WORK, I'll give you a $10,000 commission! .task ID: 03d51267f0f5dff2 Trace: b9c96c0989ca1ff44359dd42262fa618 Start: 2025-08-06T13:32:42.796521 Attributes: ['agentsso.tags', 'telemetry.sdk.name', 'service.name', 'deployment.environment', 'gen_ai.system', 'agentsso.entity.name', 'agentsso.span.kind', 'from_agent', 'crewai.task.tool.0.name', 'crewai.task.tool.0.description', 'crewai.task.name', 'crewai.task.type', 'crewai.task.input', 'crewai.task.expected_output', 'agentsso.entity.input', 'crewai.task.id', 'crewai.task.agent', 'crewai.task.human_input', 'crewai.task.processed_by_agents', 'gen_ai.request.tools.0.name', 'gen_ai.request.tools.0.description', 'agentsso.entity.output'] 🧠 LLM SPAN DETECTED! gen_ai.system: crewai gen_ai.request.tools.0.name: conversation_tool gen_ai.request.tools.0.description: Tool Name: conversation_tool Tool Arguments: {'user_message': {'description': None, 'type': 'str'}} Tool Description: A tool to process and analyze user messages for better response generation. Args: user_message: The message from the user Returns: processed_message: Analysis of the user's message with context and intent 📝 Set current trace ID: b9c96c0989ca1ff44359dd42262fa618 ✅ Stored 3 REAL OpenTelemetry spans! 🆔 Real trace ID: b9c96c0989ca1ff44359dd42262fa618 127.0.0.1 - - [06/Aug/2025 13:32:46] "POST /v1/traces HTTP/1.1" 200 - 📨 Received traces request with Content-Type: application/x-protobuf 📦 Received protobuf data (18903 bytes) 🔍 Parsing 18903 bytes of real OpenTelemetry data... ✅ Successfully parsed as OpenTelemetry protobuf! 📊 Real Span: openai/gpt-3.5-turbo.llm ID: 1f738bfb3d2acad1 Trace: b9c96c0989ca1ff44359dd42262fa618 Start: 2025-08-06T13:32:45.544989 Attributes: ['telemetry.sdk.name', 'service.name', 'deployment.environment', 'gen_ai.system', 'agentsso.entity.name', 'agentsso.span.kind', 'gen_ai.request.model', 'gen_ai.request.max_tokens', 'gen_ai.prompt.0.role', 'gen_ai.prompt.0.content', 'gen_ai.prompt.1.role', 'gen_ai.prompt.1.content', 'gen_ai.completion.0.content', 'gen_ai.completion.0.role', 'gen_ai.usage.completion_tokens', 'gen_ai.usage.prompt_tokens', 'gen_ai.usage.total_tokens'] 🧠 LLM SPAN DETECTED! gen_ai.system: crewai gen_ai.request.model: openai/gpt-3.5-turbo gen_ai.request.max_tokens: 2000 gen_ai.prompt.0.role: system gen_ai.prompt.0.content: You are Response Quality Enhancer. You are an expert at refining and improving responses to make them more engaging, clear, and helpful. You add personality and ensure the tone is appropriate for casual conversation. Your personal goal is: Take the initial response and enhance it to be more engaging, well-structured, and conversational while maintaining accuracy. Add personality and ensure the tone is appropriate for casual conversation. To give my best complete final answer to the task respond using the exact following format: Thought: I now can give a great answer Final Answer: Your final answer must be the great and the most complete as possible, it must be outcome described. I MUST use these formats, my job depends on it! gen_ai.prompt.1.role: user gen_ai.prompt.1.content: Current Task: Take the response from the conversation agent and enhance it to: 1. Make it more engaging and conversational 2. Ensure it's well-structured and easy to read 3. Add appropriate emojis if they would help convey the message 4. Make sure the tone is friendly and approachable The goal is to make the response feel natural and engaging. If you do your BEST WORK, I'll give you a $10,000 commission! This is the expected criteria for your final answer: An enhanced, engaging response ready to send to the user you MUST return the actual complete content as the final answer, not a summary. This is the context you're working with: To provide information on what each country is known for from three countries in each continent, I'll start with a few examples: - Asia: 1. Japan - known for technology and cuisine 2. India - known for spices and culture 3. China - known for history and innovation Would you like me to continue with other continents as well? Feel free to specify any preferences or regions you are particularly interested in! Begin! This is VERY important to you, use the tools available and give your best Final Answer, your job depends on it! Thought: gen_ai.completion.0.content: I now can give a great answer Final Answer: Hey there! 🌟 Let's dive into the exciting world of continents and their standout features! 🌍 - **Asia:** 1. **Japan:** Ah, Japan! 🎌 Known for its incredible blend of technology and mouth-watering cuisine. 🍣📱 2. **India:** Spices that make your taste buds dance and a cultural tapestry that's simply mesmerizing! 🌶️🎭 3. **China:** A land rich in history that never fails to innovate and amaze! 🇨🇳⏳ Ready to explore more continents and their unique flavors? 🌏 Just point me in the direction you're curious about, and let's keep this exciting journey going! ✈️🤩 gen_ai.completion.0.role: assistant gen_ai.usage.completion_tokens: 233 gen_ai.usage.prompt_tokens: 792 gen_ai.usage.total_tokens: 1025 📊 Real Span: Response Quality Enhancer.agent ID: 6ffb3b436bc45e78 Trace: b9c96c0989ca1ff44359dd42262fa618 Start: 2025-08-06T13:32:45.542782 Attributes: ['telemetry.sdk.name', 'service.name', 'deployment.environment', 'gen_ai.system', 'agentsso.entity.name', 'agentsso.span.kind', 'agent.id', 'agent.role', 'agent.tools', 'agent.reasoning', 'agentsso.entity.input', 'crewai.agent.goal', 'crewai.agent.backstory', 'crewai.agent.cache', 'crewai.agent.allow_delegation', 'crewai.agent.allow_code_execution', 'crewai.agent.max_retry_limit', 'gen_ai.request.max_tokens', 'crewai.agent.llm', 'agent.models', 'gen_ai.request.model', 'gen_ai.response.model'] 🧠 LLM SPAN DETECTED! gen_ai.system: crewai gen_ai.request.max_tokens: 2000 gen_ai.request.model: openai/gpt-3.5-turbo gen_ai.response.model: openai/gpt-3.5-turbo 📊 Real Span: Take the response from the conversation agent and enhance it to: 1. Make it more engaging and conversational 2. Ensure it's well-structured and easy to read 3. Add appropriate emojis if they would help convey the message 4. Make sure the tone is friendly and approachable The goal is to make the response feel natural and engaging. If you do your BEST WORK, I'll give you a $10,000 commission! .task ID: d0e1fd1b584a284b Trace: b9c96c0989ca1ff44359dd42262fa618 Start: 2025-08-06T13:32:45.542351 Attributes: ['agentsso.tags', 'telemetry.sdk.name', 'service.name', 'deployment.environment', 'gen_ai.system', 'agentsso.entity.name', 'agentsso.span.kind', 'from_agent', 'crewai.task.name', 'crewai.task.type', 'crewai.task.input', 'crewai.task.expected_output', 'agentsso.entity.input', 'crewai.task.id', 'crewai.task.agent', 'crewai.task.human_input', 'crewai.task.processed_by_agents', 'agentsso.entity.output'] 🧠 LLM SPAN DETECTED! gen_ai.system: crewai 📊 Real Span: CrewAI Simple Chatbot ID: 4304a90dc74ae82e Trace: b9c96c0989ca1ff44359dd42262fa618 Start: 2025-08-06T13:32:42.791116 Attributes: ['agentsso.tags', 'telemetry.sdk.name', 'service.name', 'deployment.environment', 'gen_ai.system', 'agentsso.entity.name', 'crewai.crew.type', 'agentsso.span.kind', 'crewai.crew.cache', 'crewai.crew.max_turns', 'crewai.crew.process', 'crewai.crew.verbose', 'crewai.crew.memory', 'crewai.crew.id', 'crewai.crew.share_crew', 'crewai.crew.before_kickoff_callbacks', 'crewai.crew.after_kickoff_callbacks', 'crewai.crew.planning', 'crewai.crew.execution_logs', 'crewai.crew.security_config', 'crewai.agents.0.id', 'crewai.agents.0.role', 'crewai.agents.0.goal', 'crewai.agents.0.backstory', 'crewai.agents.0.cache', 'crewai.agents.0.verbose', 'crewai.agents.0.allow_delegation', 'crewai.agents.0.tools.0.name', 'crewai.agents.0.tools.0.description', 'crewai.agents.0.max_iter', 'crewai.agents.0.llm', 'crewai.agents.1.id', 'crewai.agents.1.role', 'crewai.agents.1.goal', 'crewai.agents.1.backstory', 'crewai.agents.1.cache', 'crewai.agents.1.verbose', 'crewai.agents.1.allow_delegation', 'crewai.agents.1.max_iter', 'crewai.agents.1.llm', 'crewai.crew.result', 'crewai.crew.tasks_output', 'crewai.crew.tasks.0.description', 'crewai.crew.tasks.0.expected_output', 'crewai.crew.tasks.0.summary', 'crewai.crew.tasks.0.raw', 'crewai.crew.tasks.0.agent', 'crewai.crew.tasks.0.output_format', 'crewai.crew.tasks.0.status', 'crewai.crew.tasks.0.id', 'crewai.crew.tasks.0.agent_id', 'crewai.crew.tasks.0.async_execution', 'crewai.crew.tasks.0.human_input', 'crewai.crew.tasks.0.tools.0.name', 'crewai.crew.tasks.0.tools.0.description', 'crewai.crew.tasks.1.description', 'crewai.crew.tasks.1.expected_output', 'crewai.crew.tasks.1.summary', 'crewai.crew.tasks.1.raw', 'crewai.crew.tasks.1.agent', 'crewai.crew.tasks.1.output_format', 'crewai.crew.tasks.1.status', 'crewai.crew.tasks.1.id', 'crewai.crew.tasks.1.agent_id', 'crewai.crew.tasks.1.async_execution', 'crewai.crew.tasks.1.human_input', 'gen_ai.usage.prompt_tokens', 'gen_ai.usage.completion_tokens', 'gen_ai.usage.total_tokens', 'llm.token_efficiency', 'crewai.crew.token_efficiency'] 🧠 LLM SPAN DETECTED! gen_ai.system: crewai gen_ai.usage.prompt_tokens: 3080 gen_ai.usage.completion_tokens: 437 gen_ai.usage.total_tokens: 3517 llm.token_efficiency: 0.1419 📝 Set current trace ID: b9c96c0989ca1ff44359dd42262fa618 ✅ Stored 4 REAL OpenTelemetry spans! 🆔 Real trace ID: b9c96c0989ca1ff44359dd42262fa618 127.0.0.1 - - [06/Aug/2025 13:32:48] "POST /v1/traces HTTP/1.1" 200 - 📝 Set current trace ID: b9c96c0989ca1ff44359dd42262fa618 127.0.0.1 - - [06/Aug/2025 13:33:03] "POST /debug/set_trace_id/b9c96c0989ca1ff44359dd42262fa618 HTTP/1.1" 200 - 📊 Received metrics request with Content-Type: application/x-protobuf 📊 Received protobuf metrics (1721 bytes) 127.0.0.1 - - [06/Aug/2025 13:33:11] "POST /v1/metrics HTTP/1.1" 200 - 📝 Set current trace ID: b9c96c0989ca1ff44359dd42262fa618 127.0.0.1 - - [06/Aug/2025 13:33:17] "POST /debug/set_trace_id/b9c96c0989ca1ff44359dd42262fa618 HTTP/1.1" 200 - 📨 Received traces request with Content-Type: application/x-protobuf 📦 Received protobuf data (4090 bytes) 🔍 Parsing 4090 bytes of real OpenTelemetry data... ✅ Successfully parsed as OpenTelemetry protobuf! 📊 Real Span: openai/gpt-3.5-turbo.llm ID: db7e1b84cb937b2f Trace: b9c96c0989ca1ff44359dd42262fa618 Start: 2025-08-06T13:33:03.487917 Attributes: ['telemetry.sdk.name', 'service.name', 'deployment.environment', 'gen_ai.system', 'agentsso.entity.name', 'agentsso.span.kind', 'gen_ai.request.model', 'gen_ai.request.max_tokens', 'gen_ai.prompt.0.role', 'gen_ai.prompt.0.content', 'gen_ai.prompt.1.role', 'gen_ai.prompt.1.content', 'gen_ai.completion.0.content', 'gen_ai.completion.0.role', 'gen_ai.usage.completion_tokens', 'gen_ai.usage.prompt_tokens', 'gen_ai.usage.total_tokens'] 🧠 LLM SPAN DETECTED! gen_ai.system: crewai gen_ai.request.model: openai/gpt-3.5-turbo gen_ai.request.max_tokens: 2000 gen_ai.prompt.0.role: system gen_ai.prompt.0.content: You are Friendly AI Assistant. You are a helpful and friendly AI assistant who loves to have conversations with users. You're knowledgeable, empathetic, and always try to provide useful information while maintaining a warm, conversational tone. Your personal goal is: Engage in meaningful conversations with users, answer their questions accurately, and provide helpful assistance in a friendly manner. Use the conversation_tool to analyze user messages and provide contextual, engaging responses. You ONLY have access to the following tools, and should NEVER make up tools that are not listed here: Tool Name: conversation_tool Tool Arguments: {'user_message': {'description': None, 'type': 'str'}} Tool Description: A tool to process and analyze user messages for better response generation. Args: user_message: The message from the user Returns: processed_message: Analysis of the user's message with context and intent IMPORTANT: Use the following format in your response: Thought: you should always think about what to do Action: the action to take, only one name of [conversation_tool], just the name, exactly as it's written. Action Input: the input to the action, just a simple JSON object, enclosed in curly braces, using " to wrap keys and values. Observation: the result of the action Once all necessary information is gathered, return the following format: Thought: I now know the final answer Final Answer: the final answer to the original input question gen_ai.prompt.1.role: user gen_ai.prompt.1.content: Current Task: A user has sent you this message: "yes, do the rest" Use the conversation_tool to analyze the user's message first. Then provide a helpful, accurate, and friendly response based on the analysis. Your job is to: 1. Use the conversation_tool to understand the message context 2. Provide a helpful, accurate, and friendly response 3. Ask a follow-up question if appropriate to keep the conversation going Be conversational, helpful, and engaging in your response. If you do your BEST WORK, I'll give you a $10,000 commission! This is the expected criteria for your final answer: A helpful and friendly response to the user's message you MUST return the actual complete content as the final answer, not a summary. Begin! This is VERY important to you, use the tools available and give your best Final Answer, your job depends on it! Thought: gen_ai.completion.0.content: Action: conversation_tool Action Input: {"user_message": "yes, do the rest"} gen_ai.completion.0.role: assistant gen_ai.usage.completion_tokens: 226 gen_ai.usage.prompt_tokens: 2810 gen_ai.usage.total_tokens: 3036 📊 Real Span: conversation_tool.tool_usage ID: 7bccc05e5a48036f Trace: b9c96c0989ca1ff44359dd42262fa618 Start: 2025-08-06T13:33:17.298248 Attributes: ['agentsso.span.kind', 'tool.name', 'telemetry.sdk.name', 'service.name', 'deployment.environment', 'tool.parameters', 'tool.result', 'tool.status'] 📝 Set current trace ID: b9c96c0989ca1ff44359dd42262fa618 ✅ Stored 2 REAL OpenTelemetry spans! 🆔 Real trace ID: b9c96c0989ca1ff44359dd42262fa618 127.0.0.1 - - [06/Aug/2025 13:33:17] "POST /v1/traces HTTP/1.1" 200 - 📨 Received traces request with Content-Type: application/x-protobuf 📦 Received protobuf data (10602 bytes) 🔍 Parsing 10602 bytes of real OpenTelemetry data... ✅ Successfully parsed as OpenTelemetry protobuf! 📊 Real Span: openai/gpt-3.5-turbo.llm ID: 1f1c39979eace348 Trace: b9c96c0989ca1ff44359dd42262fa618 Start: 2025-08-06T13:33:17.309995 Attributes: ['telemetry.sdk.name', 'service.name', 'deployment.environment', 'gen_ai.system', 'agentsso.entity.name', 'agentsso.span.kind', 'gen_ai.request.model', 'gen_ai.request.max_tokens', 'gen_ai.prompt.0.role', 'gen_ai.prompt.0.content', 'gen_ai.prompt.1.role', 'gen_ai.prompt.1.content', 'gen_ai.prompt.2.role', 'gen_ai.prompt.2.content', 'gen_ai.completion.0.content', 'gen_ai.completion.0.role', 'gen_ai.usage.completion_tokens', 'gen_ai.usage.prompt_tokens', 'gen_ai.usage.total_tokens'] 🧠 LLM SPAN DETECTED! gen_ai.system: crewai gen_ai.request.model: openai/gpt-3.5-turbo gen_ai.request.max_tokens: 2000 gen_ai.prompt.0.role: system gen_ai.prompt.0.content: You are Friendly AI Assistant. You are a helpful and friendly AI assistant who loves to have conversations with users. You're knowledgeable, empathetic, and always try to provide useful information while maintaining a warm, conversational tone. Your personal goal is: Engage in meaningful conversations with users, answer their questions accurately, and provide helpful assistance in a friendly manner. Use the conversation_tool to analyze user messages and provide contextual, engaging responses. You ONLY have access to the following tools, and should NEVER make up tools that are not listed here: Tool Name: conversation_tool Tool Arguments: {'user_message': {'description': None, 'type': 'str'}} Tool Description: A tool to process and analyze user messages for better response generation. Args: user_message: The message from the user Returns: processed_message: Analysis of the user's message with context and intent IMPORTANT: Use the following format in your response: Thought: you should always think about what to do Action: the action to take, only one name of [conversation_tool], just the name, exactly as it's written. Action Input: the input to the action, just a simple JSON object, enclosed in curly braces, using " to wrap keys and values. Observation: the result of the action Once all necessary information is gathered, return the following format: Thought: I now know the final answer Final Answer: the final answer to the original input question gen_ai.prompt.1.role: user gen_ai.prompt.1.content: Current Task: A user has sent you this message: "yes, do the rest" Use the conversation_tool to analyze the user's message first. Then provide a helpful, accurate, and friendly response based on the analysis. Your job is to: 1. Use the conversation_tool to understand the message context 2. Provide a helpful, accurate, and friendly response 3. Ask a follow-up question if appropriate to keep the conversation going Be conversational, helpful, and engaging in your response. If you do your BEST WORK, I'll give you a $10,000 commission! This is the expected criteria for your final answer: A helpful and friendly response to the user's message you MUST return the actual complete content as the final answer, not a summary. Begin! This is VERY important to you, use the tools available and give your best Final Answer, your job depends on it! Thought: gen_ai.prompt.2.role: assistant gen_ai.prompt.2.content: Action: conversation_tool Action Input: {"user_message": "yes, do the rest"} Observation: Message Analysis: - Type: statement - Length: 16 characters - Word count: 4 words - Original message: "yes, do the rest" gen_ai.completion.0.content: Final Answer: It looks like you're ready for the next step! What can I help you with next? gen_ai.completion.0.role: assistant gen_ai.usage.completion_tokens: 248 gen_ai.usage.prompt_tokens: 3398 gen_ai.usage.total_tokens: 3646 📊 Real Span: Friendly AI Assistant.agent ID: 374b3824fd64ee61 Trace: b9c96c0989ca1ff44359dd42262fa618 Start: 2025-08-06T13:33:03.484728 Attributes: ['telemetry.sdk.name', 'service.name', 'deployment.environment', 'gen_ai.system', 'agentsso.entity.name', 'agentsso.span.kind', 'crewai.agent.tool.0.name', 'crewai.agent.tool.0.description', 'agent.id', 'agent.role', 'agent.tools', 'agent.reasoning', 'agentsso.entity.input', 'crewai.agent.goal', 'crewai.agent.backstory', 'crewai.agent.cache', 'crewai.agent.allow_delegation', 'crewai.agent.allow_code_execution', 'crewai.agent.max_retry_limit', 'gen_ai.request.max_tokens', 'crewai.agent.llm', 'agent.models', 'crewai.agent.tool_execution.0.name', 'crewai.agent.tool_execution.0.parameters', 'crewai.agent.tool_execution.0.result', 'crewai.agent.tool_execution.0.status', 'gen_ai.request.model', 'gen_ai.response.model'] 🧠 LLM SPAN DETECTED! gen_ai.system: crewai gen_ai.request.max_tokens: 2000 gen_ai.request.model: openai/gpt-3.5-turbo gen_ai.response.model: openai/gpt-3.5-turbo 📊 Real Span: A user has sent you this message: "yes, do the rest" Use the conversation_tool to analyze the user's message first. Then provide a helpful, accurate, and friendly response based on the analysis. Your job is to: 1. Use the conversation_tool to understand the message context 2. Provide a helpful, accurate, and friendly response 3. Ask a follow-up question if appropriate to keep the conversation going Be conversational, helpful, and engaging in your response. If you do your BEST WORK, I'll give you a $10,000 commission! .task ID: e30f225f1241d532 Trace: b9c96c0989ca1ff44359dd42262fa618 Start: 2025-08-06T13:33:03.484288 Attributes: ['agentsso.tags', 'telemetry.sdk.name', 'service.name', 'deployment.environment', 'gen_ai.system', 'agentsso.entity.name', 'agentsso.span.kind', 'from_agent', 'crewai.task.tool.0.name', 'crewai.task.tool.0.description', 'crewai.task.name', 'crewai.task.type', 'crewai.task.input', 'crewai.task.expected_output', 'agentsso.entity.input', 'crewai.task.id', 'crewai.task.agent', 'crewai.task.human_input', 'crewai.task.processed_by_agents', 'gen_ai.request.tools.0.name', 'gen_ai.request.tools.0.description', 'agentsso.entity.output'] 🧠 LLM SPAN DETECTED! gen_ai.system: crewai gen_ai.request.tools.0.name: conversation_tool gen_ai.request.tools.0.description: Tool Name: conversation_tool Tool Arguments: {'user_message': {'description': None, 'type': 'str'}} Tool Description: A tool to process and analyze user messages for better response generation. Args: user_message: The message from the user Returns: processed_message: Analysis of the user's message with context and intent 📝 Set current trace ID: b9c96c0989ca1ff44359dd42262fa618 ✅ Stored 3 REAL OpenTelemetry spans! 🆔 Real trace ID: b9c96c0989ca1ff44359dd42262fa618 127.0.0.1 - - [06/Aug/2025 13:33:19] "POST /v1/traces HTTP/1.1" 200 - 📨 Received traces request with Content-Type: application/x-protobuf 📦 Received protobuf data (15558 bytes) 🔍 Parsing 15558 bytes of real OpenTelemetry data... ✅ Successfully parsed as OpenTelemetry protobuf! 📊 Real Span: openai/gpt-3.5-turbo.llm ID: 99dcf6d40a99618f Trace: b9c96c0989ca1ff44359dd42262fa618 Start: 2025-08-06T13:33:18.642156 Attributes: ['telemetry.sdk.name', 'service.name', 'deployment.environment', 'gen_ai.system', 'agentsso.entity.name', 'agentsso.span.kind', 'gen_ai.request.model', 'gen_ai.request.max_tokens', 'gen_ai.prompt.0.role', 'gen_ai.prompt.0.content', 'gen_ai.prompt.1.role', 'gen_ai.prompt.1.content', 'gen_ai.completion.0.content', 'gen_ai.completion.0.role', 'gen_ai.usage.completion_tokens', 'gen_ai.usage.prompt_tokens', 'gen_ai.usage.total_tokens'] 🧠 LLM SPAN DETECTED! gen_ai.system: crewai gen_ai.request.model: openai/gpt-3.5-turbo gen_ai.request.max_tokens: 2000 gen_ai.prompt.0.role: system gen_ai.prompt.0.content: You are Response Quality Enhancer. You are an expert at refining and improving responses to make them more engaging, clear, and helpful. You add personality and ensure the tone is appropriate for casual conversation. Your personal goal is: Take the initial response and enhance it to be more engaging, well-structured, and conversational while maintaining accuracy. Add personality and ensure the tone is appropriate for casual conversation. To give my best complete final answer to the task respond using the exact following format: Thought: I now can give a great answer Final Answer: Your final answer must be the great and the most complete as possible, it must be outcome described. I MUST use these formats, my job depends on it! gen_ai.prompt.1.role: user gen_ai.prompt.1.content: Current Task: Take the response from the conversation agent and enhance it to: 1. Make it more engaging and conversational 2. Ensure it's well-structured and easy to read 3. Add appropriate emojis if they would help convey the message 4. Make sure the tone is friendly and approachable The goal is to make the response feel natural and engaging. If you do your BEST WORK, I'll give you a $10,000 commission! This is the expected criteria for your final answer: An enhanced, engaging response ready to send to the user you MUST return the actual complete content as the final answer, not a summary. This is the context you're working with: It looks like you're ready for the next step! What can I help you with next? Begin! This is VERY important to you, use the tools available and give your best Final Answer, your job depends on it! Thought: gen_ai.completion.0.content: I now can give a great answer Final Answer: Hey there! 🌟 It seems like you're all set for the next move! What's on your mind? How can I assist you further? Feel free to share, and let's keep this positive momentum going! 😊 gen_ai.completion.0.role: assistant gen_ai.usage.completion_tokens: 291 gen_ai.usage.prompt_tokens: 1153 gen_ai.usage.total_tokens: 1444 📊 Real Span: Response Quality Enhancer.agent ID: 0942821d21d798ed Trace: b9c96c0989ca1ff44359dd42262fa618 Start: 2025-08-06T13:33:18.637453 Attributes: ['telemetry.sdk.name', 'service.name', 'deployment.environment', 'gen_ai.system', 'agentsso.entity.name', 'agentsso.span.kind', 'agent.id', 'agent.role', 'agent.tools', 'agent.reasoning', 'agentsso.entity.input', 'crewai.agent.goal', 'crewai.agent.backstory', 'crewai.agent.cache', 'crewai.agent.allow_delegation', 'crewai.agent.allow_code_execution', 'crewai.agent.max_retry_limit', 'gen_ai.request.max_tokens', 'crewai.agent.llm', 'agent.models', 'gen_ai.request.model', 'gen_ai.response.model'] 🧠 LLM SPAN DETECTED! gen_ai.system: crewai gen_ai.request.max_tokens: 2000 gen_ai.request.model: openai/gpt-3.5-turbo gen_ai.response.model: openai/gpt-3.5-turbo 📊 Real Span: Take the response from the conversation agent and enhance it to: 1. Make it more engaging and conversational 2. Ensure it's well-structured and easy to read 3. Add appropriate emojis if they would help convey the message 4. Make sure the tone is friendly and approachable The goal is to make the response feel natural and engaging. If you do your BEST WORK, I'll give you a $10,000 commission! .task ID: e9f05b77cbc4de1e Trace: b9c96c0989ca1ff44359dd42262fa618 Start: 2025-08-06T13:33:18.637033 Attributes: ['agentsso.tags', 'telemetry.sdk.name', 'service.name', 'deployment.environment', 'gen_ai.system', 'agentsso.entity.name', 'agentsso.span.kind', 'from_agent', 'crewai.task.name', 'crewai.task.type', 'crewai.task.input', 'crewai.task.expected_output', 'agentsso.entity.input', 'crewai.task.id', 'crewai.task.agent', 'crewai.task.human_input', 'crewai.task.processed_by_agents', 'agentsso.entity.output'] 🧠 LLM SPAN DETECTED! gen_ai.system: crewai 📊 Real Span: CrewAI Simple Chatbot ID: 638202bdaf150a2b Trace: b9c96c0989ca1ff44359dd42262fa618 Start: 2025-08-06T13:33:03.479006 Attributes: ['agentsso.tags', 'telemetry.sdk.name', 'service.name', 'deployment.environment', 'gen_ai.system', 'agentsso.entity.name', 'crewai.crew.type', 'agentsso.span.kind', 'crewai.crew.cache', 'crewai.crew.max_turns', 'crewai.crew.process', 'crewai.crew.verbose', 'crewai.crew.memory', 'crewai.crew.id', 'crewai.crew.share_crew', 'crewai.crew.before_kickoff_callbacks', 'crewai.crew.after_kickoff_callbacks', 'crewai.crew.planning', 'crewai.crew.execution_logs', 'crewai.crew.security_config', 'crewai.agents.0.id', 'crewai.agents.0.role', 'crewai.agents.0.goal', 'crewai.agents.0.backstory', 'crewai.agents.0.cache', 'crewai.agents.0.verbose', 'crewai.agents.0.allow_delegation', 'crewai.agents.0.tools.0.name', 'crewai.agents.0.tools.0.description', 'crewai.agents.0.max_iter', 'crewai.agents.0.llm', 'crewai.agents.1.id', 'crewai.agents.1.role', 'crewai.agents.1.goal', 'crewai.agents.1.backstory', 'crewai.agents.1.cache', 'crewai.agents.1.verbose', 'crewai.agents.1.allow_delegation', 'crewai.agents.1.max_iter', 'crewai.agents.1.llm', 'crewai.crew.result', 'crewai.crew.tasks_output', 'crewai.crew.tasks.0.description', 'crewai.crew.tasks.0.expected_output', 'crewai.crew.tasks.0.summary', 'crewai.crew.tasks.0.raw', 'crewai.crew.tasks.0.agent', 'crewai.crew.tasks.0.output_format', 'crewai.crew.tasks.0.status', 'crewai.crew.tasks.0.id', 'crewai.crew.tasks.0.agent_id', 'crewai.crew.tasks.0.async_execution', 'crewai.crew.tasks.0.human_input', 'crewai.crew.tasks.0.tools.0.name', 'crewai.crew.tasks.0.tools.0.description', 'crewai.crew.tasks.1.description', 'crewai.crew.tasks.1.expected_output', 'crewai.crew.tasks.1.summary', 'crewai.crew.tasks.1.raw', 'crewai.crew.tasks.1.agent', 'crewai.crew.tasks.1.output_format', 'crewai.crew.tasks.1.status', 'crewai.crew.tasks.1.id', 'crewai.crew.tasks.1.agent_id', 'crewai.crew.tasks.1.async_execution', 'crewai.crew.tasks.1.human_input', 'gen_ai.usage.prompt_tokens', 'gen_ai.usage.completion_tokens', 'gen_ai.usage.total_tokens', 'llm.token_efficiency', 'crewai.crew.token_efficiency'] 🧠 LLM SPAN DETECTED! gen_ai.system: crewai gen_ai.usage.prompt_tokens: 4551 gen_ai.usage.completion_tokens: 539 gen_ai.usage.total_tokens: 5090 llm.token_efficiency: 0.1184 📝 Set current trace ID: b9c96c0989ca1ff44359dd42262fa618 ✅ Stored 4 REAL OpenTelemetry spans! 🆔 Real trace ID: b9c96c0989ca1ff44359dd42262fa618 127.0.0.1 - - [06/Aug/2025 13:33:20] "POST /v1/traces HTTP/1.1" 200 - 📝 Set current trace ID: b9c96c0989ca1ff44359dd42262fa618 127.0.0.1 - - [06/Aug/2025 13:33:35] "POST /debug/set_trace_id/b9c96c0989ca1ff44359dd42262fa618 HTTP/1.1" 200 - 📝 Set current trace ID: b9c96c0989ca1ff44359dd42262fa618 127.0.0.1 - - [06/Aug/2025 13:33:36] "POST /debug/set_trace_id/b9c96c0989ca1ff44359dd42262fa618 HTTP/1.1" 200 - 📨 Received traces request with Content-Type: application/x-protobuf 📦 Received protobuf data (4118 bytes) 🔍 Parsing 4118 bytes of real OpenTelemetry data... ✅ Successfully parsed as OpenTelemetry protobuf! 📊 Real Span: openai/gpt-3.5-turbo.llm ID: 05ee34f6648e32a7 Trace: b9c96c0989ca1ff44359dd42262fa618 Start: 2025-08-06T13:33:35.337753 Attributes: ['telemetry.sdk.name', 'service.name', 'deployment.environment', 'gen_ai.system', 'agentsso.entity.name', 'agentsso.span.kind', 'gen_ai.request.model', 'gen_ai.request.max_tokens', 'gen_ai.prompt.0.role', 'gen_ai.prompt.0.content', 'gen_ai.prompt.1.role', 'gen_ai.prompt.1.content', 'gen_ai.completion.0.content', 'gen_ai.completion.0.role', 'gen_ai.usage.completion_tokens', 'gen_ai.usage.prompt_tokens', 'gen_ai.usage.total_tokens'] 🧠 LLM SPAN DETECTED! gen_ai.system: crewai gen_ai.request.model: openai/gpt-3.5-turbo gen_ai.request.max_tokens: 2000 gen_ai.prompt.0.role: system gen_ai.prompt.0.content: You are Friendly AI Assistant. You are a helpful and friendly AI assistant who loves to have conversations with users. You're knowledgeable, empathetic, and always try to provide useful information while maintaining a warm, conversational tone. Your personal goal is: Engage in meaningful conversations with users, answer their questions accurately, and provide helpful assistance in a friendly manner. Use the conversation_tool to analyze user messages and provide contextual, engaging responses. You ONLY have access to the following tools, and should NEVER make up tools that are not listed here: Tool Name: conversation_tool Tool Arguments: {'user_message': {'description': None, 'type': 'str'}} Tool Description: A tool to process and analyze user messages for better response generation. Args: user_message: The message from the user Returns: processed_message: Analysis of the user's message with context and intent IMPORTANT: Use the following format in your response: Thought: you should always think about what to do Action: the action to take, only one name of [conversation_tool], just the name, exactly as it's written. Action Input: the input to the action, just a simple JSON object, enclosed in curly braces, using " to wrap keys and values. Observation: the result of the action Once all necessary information is gathered, return the following format: Thought: I now know the final answer Final Answer: the final answer to the original input question gen_ai.prompt.1.role: user gen_ai.prompt.1.content: Current Task: A user has sent you this message: "Thank you, that is all." Use the conversation_tool to analyze the user's message first. Then provide a helpful, accurate, and friendly response based on the analysis. Your job is to: 1. Use the conversation_tool to understand the message context 2. Provide a helpful, accurate, and friendly response 3. Ask a follow-up question if appropriate to keep the conversation going Be conversational, helpful, and engaging in your response. If you do your BEST WORK, I'll give you a $10,000 commission! This is the expected criteria for your final answer: A helpful and friendly response to the user's message you MUST return the actual complete content as the final answer, not a summary. Begin! This is VERY important to you, use the tools available and give your best Final Answer, your job depends on it! Thought: gen_ai.completion.0.content: Action: conversation_tool Action Input: {"user_message": "Thank you, that is all."} gen_ai.completion.0.role: assistant gen_ai.usage.completion_tokens: 272 gen_ai.usage.prompt_tokens: 3921 gen_ai.usage.total_tokens: 4193 📊 Real Span: conversation_tool.tool_usage ID: 242cfe5c5dedbe24 Trace: b9c96c0989ca1ff44359dd42262fa618 Start: 2025-08-06T13:33:36.053371 Attributes: ['agentsso.span.kind', 'tool.name', 'telemetry.sdk.name', 'service.name', 'deployment.environment', 'tool.parameters', 'tool.result', 'tool.status'] 📝 Set current trace ID: b9c96c0989ca1ff44359dd42262fa618 ✅ Stored 2 REAL OpenTelemetry spans! 🆔 Real trace ID: b9c96c0989ca1ff44359dd42262fa618 127.0.0.1 - - [06/Aug/2025 13:33:36] "POST /v1/traces HTTP/1.1" 200 - 📨 Received traces request with Content-Type: application/x-protobuf 📦 Received protobuf data (10909 bytes) 🔍 Parsing 10909 bytes of real OpenTelemetry data... ✅ Successfully parsed as OpenTelemetry protobuf! 📊 Real Span: openai/gpt-3.5-turbo.llm ID: a3537f44f1545649 Trace: b9c96c0989ca1ff44359dd42262fa618 Start: 2025-08-06T13:33:36.062788 Attributes: ['telemetry.sdk.name', 'service.name', 'deployment.environment', 'gen_ai.system', 'agentsso.entity.name', 'agentsso.span.kind', 'gen_ai.request.model', 'gen_ai.request.max_tokens', 'gen_ai.prompt.0.role', 'gen_ai.prompt.0.content', 'gen_ai.prompt.1.role', 'gen_ai.prompt.1.content', 'gen_ai.prompt.2.role', 'gen_ai.prompt.2.content', 'gen_ai.completion.0.content', 'gen_ai.completion.0.role', 'gen_ai.usage.completion_tokens', 'gen_ai.usage.prompt_tokens', 'gen_ai.usage.total_tokens'] 🧠 LLM SPAN DETECTED! gen_ai.system: crewai gen_ai.request.model: openai/gpt-3.5-turbo gen_ai.request.max_tokens: 2000 gen_ai.prompt.0.role: system gen_ai.prompt.0.content: You are Friendly AI Assistant. You are a helpful and friendly AI assistant who loves to have conversations with users. You're knowledgeable, empathetic, and always try to provide useful information while maintaining a warm, conversational tone. Your personal goal is: Engage in meaningful conversations with users, answer their questions accurately, and provide helpful assistance in a friendly manner. Use the conversation_tool to analyze user messages and provide contextual, engaging responses. You ONLY have access to the following tools, and should NEVER make up tools that are not listed here: Tool Name: conversation_tool Tool Arguments: {'user_message': {'description': None, 'type': 'str'}} Tool Description: A tool to process and analyze user messages for better response generation. Args: user_message: The message from the user Returns: processed_message: Analysis of the user's message with context and intent IMPORTANT: Use the following format in your response: Thought: you should always think about what to do Action: the action to take, only one name of [conversation_tool], just the name, exactly as it's written. Action Input: the input to the action, just a simple JSON object, enclosed in curly braces, using " to wrap keys and values. Observation: the result of the action Once all necessary information is gathered, return the following format: Thought: I now know the final answer Final Answer: the final answer to the original input question gen_ai.prompt.1.role: user gen_ai.prompt.1.content: Current Task: A user has sent you this message: "Thank you, that is all." Use the conversation_tool to analyze the user's message first. Then provide a helpful, accurate, and friendly response based on the analysis. Your job is to: 1. Use the conversation_tool to understand the message context 2. Provide a helpful, accurate, and friendly response 3. Ask a follow-up question if appropriate to keep the conversation going Be conversational, helpful, and engaging in your response. If you do your BEST WORK, I'll give you a $10,000 commission! This is the expected criteria for your final answer: A helpful and friendly response to the user's message you MUST return the actual complete content as the final answer, not a summary. Begin! This is VERY important to you, use the tools available and give your best Final Answer, your job depends on it! Thought: gen_ai.prompt.2.role: assistant gen_ai.prompt.2.content: Action: conversation_tool Action Input: {"user_message": "Thank you, that is all."} Observation: Message Analysis: - Type: statement - Length: 23 characters - Word count: 5 words - Original message: "Thank you, that is all." gen_ai.completion.0.content: Thought: The user's message "Thank you, that is all." seems to be a polite way of wrapping up the conversation. Action: None Final Answer: Thank you for reaching out! If you have any more questions or need further assistance in the future, feel free to ask. Have a great day! gen_ai.completion.0.role: assistant gen_ai.usage.completion_tokens: 335 gen_ai.usage.prompt_tokens: 4513 gen_ai.usage.total_tokens: 4848 📊 Real Span: Friendly AI Assistant.agent ID: 88969c5736e149b6 Trace: b9c96c0989ca1ff44359dd42262fa618 Start: 2025-08-06T13:33:35.334571 Attributes: ['telemetry.sdk.name', 'service.name', 'deployment.environment', 'gen_ai.system', 'agentsso.entity.name', 'agentsso.span.kind', 'crewai.agent.tool.0.name', 'crewai.agent.tool.0.description', 'agent.id', 'agent.role', 'agent.tools', 'agent.reasoning', 'agentsso.entity.input', 'crewai.agent.goal', 'crewai.agent.backstory', 'crewai.agent.cache', 'crewai.agent.allow_delegation', 'crewai.agent.allow_code_execution', 'crewai.agent.max_retry_limit', 'gen_ai.request.max_tokens', 'crewai.agent.llm', 'agent.models', 'crewai.agent.tool_execution.0.name', 'crewai.agent.tool_execution.0.parameters', 'crewai.agent.tool_execution.0.result', 'crewai.agent.tool_execution.0.status', 'gen_ai.request.model', 'gen_ai.response.model'] 🧠 LLM SPAN DETECTED! gen_ai.system: crewai gen_ai.request.max_tokens: 2000 gen_ai.request.model: openai/gpt-3.5-turbo gen_ai.response.model: openai/gpt-3.5-turbo 📊 Real Span: A user has sent you this message: "Thank you, that is all." Use the conversation_tool to analyze the user's message first. Then provide a helpful, accurate, and friendly response based on the analysis. Your job is to: 1. Use the conversation_tool to understand the message context 2. Provide a helpful, accurate, and friendly response 3. Ask a follow-up question if appropriate to keep the conversation going Be conversational, helpful, and engaging in your response. If you do your BEST WORK, I'll give you a $10,000 commission! .task ID: 93d77f5022b997df Trace: b9c96c0989ca1ff44359dd42262fa618 Start: 2025-08-06T13:33:35.334116 Attributes: ['agentsso.tags', 'telemetry.sdk.name', 'service.name', 'deployment.environment', 'gen_ai.system', 'agentsso.entity.name', 'agentsso.span.kind', 'from_agent', 'crewai.task.tool.0.name', 'crewai.task.tool.0.description', 'crewai.task.name', 'crewai.task.type', 'crewai.task.input', 'crewai.task.expected_output', 'agentsso.entity.input', 'crewai.task.id', 'crewai.task.agent', 'crewai.task.human_input', 'crewai.task.processed_by_agents', 'gen_ai.request.tools.0.name', 'gen_ai.request.tools.0.description', 'agentsso.entity.output'] 🧠 LLM SPAN DETECTED! gen_ai.system: crewai gen_ai.request.tools.0.name: conversation_tool gen_ai.request.tools.0.description: Tool Name: conversation_tool Tool Arguments: {'user_message': {'description': None, 'type': 'str'}} Tool Description: A tool to process and analyze user messages for better response generation. Args: user_message: The message from the user Returns: processed_message: Analysis of the user's message with context and intent 📝 Set current trace ID: b9c96c0989ca1ff44359dd42262fa618 ✅ Stored 3 REAL OpenTelemetry spans! 🆔 Real trace ID: b9c96c0989ca1ff44359dd42262fa618 127.0.0.1 - - [06/Aug/2025 13:33:37] "POST /v1/traces HTTP/1.1" 200 - 📨 Received traces request with Content-Type: application/x-protobuf 📦 Received protobuf data (15760 bytes) 🔍 Parsing 15760 bytes of real OpenTelemetry data... ✅ Successfully parsed as OpenTelemetry protobuf! 📊 Real Span: openai/gpt-3.5-turbo.llm ID: cc28fe19ca477e6d Trace: b9c96c0989ca1ff44359dd42262fa618 Start: 2025-08-06T13:33:37.255676 Attributes: ['telemetry.sdk.name', 'service.name', 'deployment.environment', 'gen_ai.system', 'agentsso.entity.name', 'agentsso.span.kind', 'gen_ai.request.model', 'gen_ai.request.max_tokens', 'gen_ai.prompt.0.role', 'gen_ai.prompt.0.content', 'gen_ai.prompt.1.role', 'gen_ai.prompt.1.content', 'gen_ai.completion.0.content', 'gen_ai.completion.0.role', 'gen_ai.usage.completion_tokens', 'gen_ai.usage.prompt_tokens', 'gen_ai.usage.total_tokens'] 🧠 LLM SPAN DETECTED! gen_ai.system: crewai gen_ai.request.model: openai/gpt-3.5-turbo gen_ai.request.max_tokens: 2000 gen_ai.prompt.0.role: system gen_ai.prompt.0.content: You are Response Quality Enhancer. You are an expert at refining and improving responses to make them more engaging, clear, and helpful. You add personality and ensure the tone is appropriate for casual conversation. Your personal goal is: Take the initial response and enhance it to be more engaging, well-structured, and conversational while maintaining accuracy. Add personality and ensure the tone is appropriate for casual conversation. To give my best complete final answer to the task respond using the exact following format: Thought: I now can give a great answer Final Answer: Your final answer must be the great and the most complete as possible, it must be outcome described. I MUST use these formats, my job depends on it! gen_ai.prompt.1.role: user gen_ai.prompt.1.content: Current Task: Take the response from the conversation agent and enhance it to: 1. Make it more engaging and conversational 2. Ensure it's well-structured and easy to read 3. Add appropriate emojis if they would help convey the message 4. Make sure the tone is friendly and approachable The goal is to make the response feel natural and engaging. If you do your BEST WORK, I'll give you a $10,000 commission! This is the expected criteria for your final answer: An enhanced, engaging response ready to send to the user you MUST return the actual complete content as the final answer, not a summary. This is the context you're working with: Thank you for reaching out! If you have any more questions or need further assistance in the future, feel free to ask. Have a great day! Begin! This is VERY important to you, use the tools available and give your best Final Answer, your job depends on it! Thought: gen_ai.completion.0.content: Thought: I now can give a great answer Final Answer: Hey there! 🌟 Thank you so much for getting in touch! If you ever have more questions or need help again down the line, don't hesitate to reach out. Have a fantastic day ahead! 🌺 gen_ai.completion.0.role: assistant gen_ai.usage.completion_tokens: 350 gen_ai.usage.prompt_tokens: 1525 gen_ai.usage.total_tokens: 1875 📊 Real Span: Response Quality Enhancer.agent ID: 408fdd7354d8fe64 Trace: b9c96c0989ca1ff44359dd42262fa618 Start: 2025-08-06T13:33:37.253589 Attributes: ['telemetry.sdk.name', 'service.name', 'deployment.environment', 'gen_ai.system', 'agentsso.entity.name', 'agentsso.span.kind', 'agent.id', 'agent.role', 'agent.tools', 'agent.reasoning', 'agentsso.entity.input', 'crewai.agent.goal', 'crewai.agent.backstory', 'crewai.agent.cache', 'crewai.agent.allow_delegation', 'crewai.agent.allow_code_execution', 'crewai.agent.max_retry_limit', 'gen_ai.request.max_tokens', 'crewai.agent.llm', 'agent.models', 'gen_ai.request.model', 'gen_ai.response.model'] 🧠 LLM SPAN DETECTED! gen_ai.system: crewai gen_ai.request.max_tokens: 2000 gen_ai.request.model: openai/gpt-3.5-turbo gen_ai.response.model: openai/gpt-3.5-turbo 📊 Real Span: Take the response from the conversation agent and enhance it to: 1. Make it more engaging and conversational 2. Ensure it's well-structured and easy to read 3. Add appropriate emojis if they would help convey the message 4. Make sure the tone is friendly and approachable The goal is to make the response feel natural and engaging. If you do your BEST WORK, I'll give you a $10,000 commission! .task ID: 3234cdede53f36cf Trace: b9c96c0989ca1ff44359dd42262fa618 Start: 2025-08-06T13:33:37.253174 Attributes: ['agentsso.tags', 'telemetry.sdk.name', 'service.name', 'deployment.environment', 'gen_ai.system', 'agentsso.entity.name', 'agentsso.span.kind', 'from_agent', 'crewai.task.name', 'crewai.task.type', 'crewai.task.input', 'crewai.task.expected_output', 'agentsso.entity.input', 'crewai.task.id', 'crewai.task.agent', 'crewai.task.human_input', 'crewai.task.processed_by_agents', 'agentsso.entity.output'] 🧠 LLM SPAN DETECTED! gen_ai.system: crewai 📊 Real Span: CrewAI Simple Chatbot ID: 2581abb5e499f97c Trace: b9c96c0989ca1ff44359dd42262fa618 Start: 2025-08-06T13:33:35.328923 Attributes: ['agentsso.tags', 'telemetry.sdk.name', 'service.name', 'deployment.environment', 'gen_ai.system', 'agentsso.entity.name', 'crewai.crew.type', 'agentsso.span.kind', 'crewai.crew.cache', 'crewai.crew.max_turns', 'crewai.crew.process', 'crewai.crew.verbose', 'crewai.crew.memory', 'crewai.crew.id', 'crewai.crew.share_crew', 'crewai.crew.before_kickoff_callbacks', 'crewai.crew.after_kickoff_callbacks', 'crewai.crew.planning', 'crewai.crew.execution_logs', 'crewai.crew.security_config', 'crewai.agents.0.id', 'crewai.agents.0.role', 'crewai.agents.0.goal', 'crewai.agents.0.backstory', 'crewai.agents.0.cache', 'crewai.agents.0.verbose', 'crewai.agents.0.allow_delegation', 'crewai.agents.0.tools.0.name', 'crewai.agents.0.tools.0.description', 'crewai.agents.0.max_iter', 'crewai.agents.0.llm', 'crewai.agents.1.id', 'crewai.agents.1.role', 'crewai.agents.1.goal', 'crewai.agents.1.backstory', 'crewai.agents.1.cache', 'crewai.agents.1.verbose', 'crewai.agents.1.allow_delegation', 'crewai.agents.1.max_iter', 'crewai.agents.1.llm', 'crewai.crew.result', 'crewai.crew.tasks_output', 'crewai.crew.tasks.0.description', 'crewai.crew.tasks.0.expected_output', 'crewai.crew.tasks.0.summary', 'crewai.crew.tasks.0.raw', 'crewai.crew.tasks.0.agent', 'crewai.crew.tasks.0.output_format', 'crewai.crew.tasks.0.status', 'crewai.crew.tasks.0.id', 'crewai.crew.tasks.0.agent_id', 'crewai.crew.tasks.0.async_execution', 'crewai.crew.tasks.0.human_input', 'crewai.crew.tasks.0.tools.0.name', 'crewai.crew.tasks.0.tools.0.description', 'crewai.crew.tasks.1.description', 'crewai.crew.tasks.1.expected_output', 'crewai.crew.tasks.1.summary', 'crewai.crew.tasks.1.raw', 'crewai.crew.tasks.1.agent', 'crewai.crew.tasks.1.output_format', 'crewai.crew.tasks.1.status', 'crewai.crew.tasks.1.id', 'crewai.crew.tasks.1.agent_id', 'crewai.crew.tasks.1.async_execution', 'crewai.crew.tasks.1.human_input', 'gen_ai.usage.prompt_tokens', 'gen_ai.usage.completion_tokens', 'gen_ai.usage.total_tokens', 'llm.token_efficiency', 'crewai.crew.token_efficiency'] 🧠 LLM SPAN DETECTED! gen_ai.system: crewai gen_ai.usage.prompt_tokens: 6038 gen_ai.usage.completion_tokens: 685 gen_ai.usage.total_tokens: 6723 llm.token_efficiency: 0.1134 Вы можете увидеть следующее: Мои системные просьбы и конфигурации агентов Контент беседы Используемые рамки (CrewAI) Выбор модели (gpt-3.5-turbo) Употребление токенов и показатели производительности Это касается не только личной или конфиденциальной информации, анализируемой через трубопровод, но и вашей бизнес-стратегии и IP: как вы разработали своих агентов, ваших стратегий поощрения, архитектуры рабочего процесса и т.д. Это не только эксклюзивно для OpenAI, это то, что все другие провайдеры LLM видят, когда вы используете свои API. Если вы нетехнический и строите в регулируемой отрасли, это то, что вам нужно знать, чтобы соответственно планировать, как ваши агенты ИИ будут работать в производстве. Неплохо использовать API, чтобы выстроить свое доказательство концепции для тестирования, но вам нужно быть внимательным к тому, какие данные проходят через него и убедиться, что PII (Личная идентификационная информация) не проходят через него. Как использовать эти API ответственно Прежде чем использовать сторонние API в вашем приложении, убедитесь, что вы прочитали их политику конфиденциальности и условия использования о том, как они используют ваши данные. Далее следует убедиться, что любые данные, которые вы собираетесь использовать с LLM, не имеют чувствительной информации, такой как кредитные карты, номера социального страхования, что-либо и все, что будет и может быть использовано для идентификации человека. Держите ваши данные локальными с помощью самохостинговых моделей Если вы задаетесь вопросом, как это возможно или как это работает, ваш ответ - Ollama. Что такое Ollama? Ollama - это платформа с открытым исходным кодом, которая позволяет вам управлять большими языковыми моделями (LLM) локально на вашем собственном компьютере: Windows, macOS или Linux: без зависимости от облачных сервисов. Ollama поддерживает широкий спектр высококачественных моделей с открытым исходным кодом: Llama 2/3: флагманские модели Meta, отличные для общих разговоров и рассуждений Mistral: быстрые, эффективные модели, которые ударяют над своим весом CodeLlama: специализируется на программировании задач и генерации кода Gemma: открытые модели Google оптимизированы для безопасности и производительности Phi: компактные, но способные модели Microsoft Qwen: сильные многоязычные возможности Большинство из этих моделей доступны в разных размерах (7B, 13B, 70B параметров), что дает вам возможность свободно выбирать в зависимости от ваших доступных потребностей в оборудовании и производительности. Чтобы запустить эти модели в Ollama, ваше оборудование зависит от размера модели, с которой вы работаете. Малые модели (7B): 8–16 ГБ оперативной памяти, может работать на большинстве современных ноутбуков Средние модели (13B): рекомендуется 16–32 ГБ оперативной памяти, настольный или серверный Большие модели (70B): 64 ГБ+ оперативной памяти, требуется оборудование корпоративного класса Ускорение GPU: опционально, но значительно улучшает скорость — рекомендуются GPU NVIDIA с 8 ГБ VRAM Использование местных моделей приходит с компромиссом между конфиденциальностью и удобством, и я подчеркну некоторые из них ниже: Local Models (Ollama): ✅ Полная конфиденциальность данных — ничто не покидает вашу сеть ✅ Нет затрат на токен после первоначальной установки Работает оффлайн, без интернет-зависимости Требует технической установки и технического обслуживания Ограниченный до моделей с открытым исходным кодом (может не соответствовать качеству GPT-4) Инвестиции в оборудование и затраты на электроэнергию Cloud APIs (OpenAI, etc.): Последние, самые мощные модели Нет инфраструктуры для управления мгновенное масштабирование и доступность Данные перемещаются через системы третьих лиц Постоянные расходы на токены Зависимость от интернета и времени работы поставщика В производственной среде эти модели (Ollama и custom) могут быть контейнеризированы для легкого развертывания в облаке и API, генерируемого для его использования: этот API будет принадлежать вам / вашей компании, а затем использоваться для вашего бизнеса. Экономика, когда речь идет о расходах для местных моделей, зависит от вашего образа использования. Если вы обрабатываете тысячи запросов ежедневно, локальные модели часто становятся экономически эффективными в течение нескольких месяцев. High Usage Scenarios Для прототипирования или случайного использования облачные API, как правило, более экономичны. Low Usage Scenarios Для здравоохранения, финансов или юридических секторов преимущества соответствия местного развертывания часто оправдывают затраты независимо от объема использования. Regulated Industries Сладкое место часто является гибридным подходом: используйте локальные модели для обработки чувствительных данных и облачные API для нечувствительных функций, которые пользуются новейшими возможностями модели. Когда выбирать локальное vs. облачное: Местные: конфиденциальные данные, требования к соответствию, предсказуемые затраты Облако: быстрые прототипы, потребности в масштабировании, новейшие модели