Your AI Chatbot Just Leaked Customer Data to OpenAI. Here’s How it Happened and How to Prevent it

Do you know that LLM service providers can see the interactions that your AI agents have when you use their APIs? This may be common knowledge to those who are technical and knows how APIs work, but non-technical people may not have any idea that this goes on behind the scene.

To get started, what is an API? An API also known as Application Programming Interface is a way for two software components to communicate with each other using a set of definitions and protocols. In the case of LLMs, it allows your query, tools, and functions to interact with the provider’s model.

To illustrate what I mean, I built a simple agent that works with my command line, used the observability tool I built for my agents to monitor the interactions. Here’s what actually gets sent to OpenAI when you use their API with an AI agent framework. This isn’t just a theory but a real trace from a simple conversation…

\

In the images attached, you can see my system prompts and some logs that I added for the purpose of this demonstration. Then below is contents of the trace from my tool:

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 

You can see the following:

• My system prompts and agent configurations
• The conversation content
• Framework being used (CrewAI)
• Model choice (gpt-3.5-turbo)
• Token usage and performance metrics

This isn’t only about personal or sensitive information being parsed through the pipeline, but also your business strategy and IP: how you’ve designed your agents, your prompting strategies, your workflow architecture, etc.

This isn’t just exclusive to OpenAI, this is what all other LLM providers see when you use their APIs. If you are non-technical and building in a regulated industry, this is what you need to know so as to plan accordingly on how your AI agents will function in production. It’s not bad to use the APIs to build out your proof of concept for testing, but you need to be careful on what kind of data goes through it and make sure that PIIs (Personal Identifiable Information) do not pass through it.

How to use these APIs responsibly

Before using third party APIs in your application, make sure to read their privacy policy and terms of use on how they use your data. Some third party train with your data to improve their LLMs, some annonymize and train, others don’t at all.

Next is to make sure that whatever data you are going to use with the LLMs do not have sensitive information like credit cards, social security numbers, anything and everything that will and can be used to identify a person. This is done by classifying your data with clear policies on what can and cannot go through the APIs, also train your team to recognize sensitive data patterns that is within your company data.

Keep Your Data Local with Self-Hosted Models

If you are wondering how this is possible or how it works, your answer is Ollama. What is Ollama? Ollama is an open-source platform that lets you run large language models (LLMs) locally on your own machine: Windows, macOS, or Linux: without depending on cloud services. This means that all your data, interactions and services are within your environment: no external API calls, no data leaving your environment.

Ollama supports a wide range of high-quality open-source models:

• Llama 2/3: Meta’s flagship models, excellent for general conversations and reasoning
• Mistral: Fast, efficient models that punch above their weight
• CodeLlama: Specialized for programming tasks and code generation
• Gemma: Google’s open models optimized for safety and performance
• Phi: Microsoft’s compact but capable models
• Qwen: Strong multilingual capabilities

Most of these models come in different sizes (7B, 13B, 70B parameters), giving you the free rein to choose based on your available hardware and performance needs.

To run these models within Ollama, your hardware is dependent on the size of model you are working with.

• Small models (7B): 8–16GB RAM, can run on most modern laptops
• Medium models (13B): 16–32GB RAM, desktop or server recommended
• Large models (70B): 64GB+ RAM, enterprise-grade hardware required
• GPU acceleration: Optional but dramatically improves speed — NVIDIA GPUs with 8GB+ VRAM recommended

Using local models come with a trade-off between privacy and convenience and I will be highlighting some of them below:

Local Models (Ollama):

• ✅ Complete data privacy — nothing leaves your network
• ✅ No per-token costs after initial setup
• ✅ Works offline, no internet dependency
• ❌ Requires technical setup and maintenance
• ❌ Limited to open-source models (may not match GPT-4 quality)
• ❌ Hardware investment and electricity costs

Cloud APIs (OpenAI, etc.):

• ✅ Latest, most powerful models
• ✅ No infrastructure to manage
• ✅ Instant scaling and availability
• ❌ Data travels through third-party systems
• ❌ Ongoing per-token costs
• ❌ Dependent on internet and provider uptime

In production environment, these models (Ollama and custom) can be containerized for easy deployment to the cloud and an API generated for its use: this API will belong to you/your company, then used for your business. This approach lets you deploy across multiple servers, integrate with Kubernetes, and maintain the same scalability benefits you would get from cloud APIs.

The economics when it comes to cost considerations for local models is dependent on your usage pattern.

High Usage Scenarios: If you’re processing thousands of requests daily, local models often become cost-effective within months. A $5,000 server running 24/7 might cost less than your monthly OpenAI bill.

Low Usage Scenarios: For prototyping or occasional use, cloud APIs are usually more economical.

Regulated Industries: For healthcare, finance, or legal sectors, the compliance benefits of local deployment often justify the costs regardless of usage volume.

The sweet spot is often a hybrid approach: use local models for sensitive data processing and cloud APIs for non-sensitive features that benefit from the latest model capabilities.

When to choose local vs. cloud:

• Local: sensitive data, compliance requirements, predictable costs
• Cloud: rapid prototyping, scaling needs, latest models

\