آپ کے AI چیٹ بوٹ نے صرف OpenAI میں کسٹمر ڈیٹا پھیلا دیا. یہاں یہ کیسے ہوا اور اس سے روکنے کے لئے کس طرح

کیا آپ جانتے ہیں کہ LLM سروس فراہم کرنے والے آپ کے AI ایجنٹز کے ساتھ ان کے APIز کا استعمال کرتے وقت ان کے تعاملات کو دیکھ سکتے ہیں؟ یہ ان لوگوں کے لئے عام علم ہوسکتا ہے جو تکنیکی ہیں اور جانتے ہیں کہ APIز کیسے کام کرتے ہیں، لیکن غیر تکنیکی لوگوں کو اس بات کا کوئی خیال نہیں ہوسکتا ہے کہ یہ منظر کے پیچھے چلتا ہے. شروع کرنے کے لئے، ایک API کیا ہے؟ ایک API بھی Application Programming Interface کے طور پر جانا جاتا ہے کہ دو سافٹ ویئر اجزاء کی ایک سیٹ کی تعریفوں اور پروٹوکولز کا استعمال کرتے ہوئے ایک دوسرے کے ساتھ بات چیت کرنے کا ایک طریقہ ہے. میں نے اس بات کی تصدیق کرنے کے لئے، میں نے ایک سادہ ایجنٹ بنایا ہے جو میرے کمانڈ لائن کے ساتھ کام کرتا ہے، میں نے اپنے ایجنٹوں کے لئے تعینات کے آلے کا استعمال کیا ہے. یہاں یہ ہے کہ آپ ایک AI ایجنٹ فریم ورک کے ساتھ ان کے API کا استعمال کرتے وقت اصل میں OpenAI کو کیا بھیجا جاتا ہے. یہ صرف ایک نظریہ نہیں ہے لیکن ایک سادہ بات چیت سے ایک حقیقی ٹریک... درج ذیل تصاویر میں، آپ میرے سسٹم کی نوٹس اور کچھ لاگ ان دیکھ سکتے ہیں جو میں نے اس نمائش کے مقصد کے لئے شامل کیا ہے. پھر ذیل میں میرے آلے سے ٹریک کے مواد ہیں: 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 آپ یہ دیکھ سکتے ہیں کہ: My System Prompts اور ایجنٹ کی ترتیبات بات چیت کا مواد استعمال ہونے والے فریم ورک (CrewAI) ماڈل کا انتخاب (gpt-3.5-turbo) Token استعمال اور کارکردگی میٹرک یہ صرف ذاتی یا حساس معلومات کے بارے میں نہیں ہے جو پائپ لائن کے ذریعے تجزیہ کیا جاتا ہے، بلکہ آپ کی کاروباری حکمت عملی اور آئی پی بھی ہے: آپ نے اپنے ایجنٹوں کو کس طرح ڈیزائن کیا ہے، آپ کی حوصلہ افزائی کی حکمت عملی، آپ کے کاروباری عمل کے آرکیٹیکل، وغیرہ. یہ صرف OpenAI کے لئے انفرادی نہیں ہے، یہ تمام دیگر LLM فراہم کرنے والوں کو دیکھتا ہے جب آپ ان کے ای پی ای کا استعمال کرتے ہیں. اگر آپ غیر تکنیکی ہیں اور ایک منظم صنعت میں تعمیر کرتے ہیں، تو یہ آپ کو یہ جاننے کی ضرورت ہے کہ آپ کے AI ایجنٹوں کو پیداوار میں کس طرح کام کرنے کے لئے منصوبہ بندی کرنے کے لۓ. یہ آپ کے تجربات کے لئے آپ کے خیالات کا ثبوت بنانے کے لئے ای پی ای کا استعمال کرنا برا نہیں ہے، لیکن آپ کو اس کے ذریعے جانے والے ڈیٹا کی قسم پر احتیاط کرنا چاہئے اور یقینی بنائیں کہ PII (خاص طور پر شناختی معلومات) اس کے ذریعے نہیں آتے ہیں. ان APIs کو ذمہ دار طریقے سے کیسے استعمال کریں آپ کی درخواست میں تیسرے فریق API کا استعمال کرنے سے پہلے، ان کی رازداری کی پالیسی اور استعمال کی شرائط کو پڑھنے کے لئے یقینی بنائیں کہ وہ آپ کے اعداد و شمار کو کس طرح استعمال کرتے ہیں. کچھ تیسرے فریق آپ کے اعداد و شمار کو بہتر بنانے کے لئے آپ کے اعداد و شمار کے ساتھ تربیت دیتے ہیں، کچھ انونیمز اور تربیت دیتے ہیں، دوسروں کو بالکل نہیں. اگلا یہ یقینی بنانا ہے کہ جو بھی ڈیٹا آپ ایل ای ایمز کے ساتھ استعمال کرنے کے لئے جا رہے ہیں اس میں کریڈٹ کارڈز، سماجی سیکورٹی نمبر، کسی بھی چیز اور کسی بھی چیز کے طور پر حساس معلومات نہیں ہیں جو کسی شخص کی شناخت کرنے کے لئے استعمال کیا جائے گا اور استعمال کیا جا سکتا ہے. اپنے اعداد و شمار کو خود میزبان ماڈل کے ساتھ مقامی رکھیں اگر آپ پوچھ رہے ہیں کہ یہ کس طرح ممکن ہے یا یہ کیسے کام کرتا ہے، تو آپ کا جواب Ollama ہے. Ollama کیا ہے؟ Ollama ایک کھلے ذریعہ پلیٹ فارم ہے جو آپ کو اپنے کمپیوٹر پر مقامی طور پر بڑے زبان ماڈل (LLMs) کو چلانے کی اجازت دیتا ہے: ونڈوز، میکوس یا لینکس: کلاؤڈ سروسز پر منحصر نہیں. Ollama اعلی معیار کے کھلے ذریعہ ماڈل کی ایک وسیع رینج کی حمایت کرتا ہے: Llama 2/3: میٹا کے پرچم ماڈل، عام بات چیت اور تفہیم کے لئے بہترین Mistral: تیزی سے، مؤثر ماڈل جو ان کے وزن کے اوپر گونجتے ہیں CodeLlama: پروگرامنگ کاموں اور کوڈ جنریٹنگ کے لئے مہارت Gemma: گوگل کے کھلے ماڈل محفوظ اور کارکردگی کے لئے بہتر ہیں Phi: مائیکروسافٹ کی کمپیکٹ لیکن طاقتور ماڈل Qwen: مضبوط متعدد زبانوں کی صلاحیتیں ان ماڈلوں میں سے زیادہ تر مختلف سائز (7B، 13B، 70B پیرامیٹرز) میں آتے ہیں، جو آپ کو آپ کے دستیاب ہارڈ ویئر اور کارکردگی کی ضروریات پر مبنی انتخاب کرنے کے لئے آزاد ہے. Ollama کے اندر ان ماڈل کو چلانے کے لئے، آپ کے ہارڈ ویئر آپ کے ساتھ کام کر رہے ہیں کہ ماڈل کے سائز پر منحصر ہے. چھوٹے ماڈل (7B): 8-16GB RAM، زیادہ تر جدید لیپ ٹاپ پر چل سکتا ہے Medium ماڈل (13B): 16-32GB RAM، ڈیسک ٹاپ یا سرور کی سفارش کی جاتی ہے بڑے ماڈل (70B): 64GB + RAM، انٹرپرائز گریڈ ہارڈ ویئر کی ضرورت ہے GPU acceleration: Optional but dramatically improves speed — NVIDIA GPUs with 8GB+ VRAM recommended مقامی ماڈل کا استعمال کرتے ہوئے رازداری اور سہولت کے درمیان ایک تبادلہ خیال کے ساتھ آتا ہے اور میں ان میں سے کچھ درج کریں گے: Local Models (Ollama): ✅ مکمل ڈیٹا رازداری - آپ کے نیٹ ورک سے کچھ بھی نہیں چھوڑتا ✅ ابتدائی تنصیب کے بعد کسی بھی ٹوکن کی لاگت ✅ Offline کام کرتا ہے، کوئی انٹرنیٹ پر منحصر نہیں تکنیکی ترتیب اور برقرار رکھنے کی ضرورت ہے Open-source ماڈلوں کے لئے محدود (GPT-4 معیار کے مطابق نہیں ہوسکتا) ہارڈ ویئر سرمایہ کاری اور بجلی کی لاگت Cloud APIs (OpenAI, etc.): ✅ تازہ ترین، سب سے طاقتور ماڈل ✅ انتظام کرنے کے لئے کوئی زیر ساخت نہیں فوری توسیع اور دستیاب ڈیٹا تیسری پارٹی کے نظام کے ذریعے سفر کرتا ہے فی ٹکٹ کی موجودہ قیمتیں انٹرنیٹ پر منحصر ہے اور سپلائر اپ ٹائم مینوفیکچرنگ ماحول میں، ان ماڈلوں (Ollama اور اپنی مرضی کے مطابق) کو آسانی سے کلاؤڈ میں تنصیب اور اس کے استعمال کے لئے پیدا شدہ API کے لئے کنٹینر کیا جا سکتا ہے: یہ API آپ / آپ کی کمپنی کے لئے ہے، پھر آپ کے کاروبار کے لئے استعمال کیا جائے گا. مقامی ماڈلوں کے لئے اختیارات کے لحاظ سے اقتصادیات آپ کے استعمال کے ماڈل پر منحصر ہے. : اگر آپ روزانہ ہزاروں درخواستوں کو پروسیسنگ کر رہے ہیں تو، مقامی ماڈل اکثر مہینوں کے اندر خزانہ مؤثر بن جاتے ہیں. $ 5،000 سرور جو 24/7 چلتا ہے، آپ کے ماہانہ اوپن ای اے فاکس سے کم ہوسکتا ہے. High Usage Scenarios پروٹوٹائپنگ یا عادی استعمال کے لئے، کلاؤڈ APIs عام طور پر زیادہ اقتصادی ہیں. Low Usage Scenarios : صحت، مالیات، یا قانونی شعبوں کے لئے، مقامی تنصیب کے مطابق فائدہ اکثر استعمال حجم کے برعکس اخراجات کی وضاحت کرتا ہے. Regulated Industries شیرین نقطہ اکثر ایک ہائبرڈ نقطہ نظر ہے: حساس ڈیٹا پروسیسنگ کے لئے مقامی ماڈل استعمال کریں اور کلاؤڈ APIز غیر حساس خصوصیات کے لئے جو تازہ ترین ماڈل کی صلاحیتوں سے فائدہ اٹھاتے ہیں. جب مقامی vs. کلاؤڈ کا انتخاب کریں: مقامی: حساس اعداد و شمار، مطابقت کی ضروریات، پیشہ ورانہ لاگت کلاؤڈ: تیزی سے پروٹوٹائپنگ، مقیاس کی ضروریات، تازہ ترین ماڈل