क्या आप जानते हैं कि एलएलएम सेवा प्रदाता उन बातचीतों को देख सकते हैं जो आपके एआई एजेंट आपके एपीआई का उपयोग करते समय करते हैं? यह उन लोगों के लिए सामान्य ज्ञान हो सकता है जो तकनीकी हैं और जानते हैं कि एपीआई कैसे काम करते हैं, लेकिन गैर तकनीकी लोगों को कोई विचार नहीं हो सकता है कि यह मंच के पीछे चल रहा है। शुरू करने के लिए, एक एपीआई क्या है? एक एपीआई, एप्लिकेशन प्रोग्रामिंग इंटरफेस के रूप में भी जाना जाता है, दो सॉफ्टवेयर घटक को परिभाषाओं और प्रोटोकॉल के एक सेट का उपयोग करके एक दूसरे के साथ संवाद करने का एक तरीका है. एलएलएम के मामले में, यह आपके पूछताछ, उपकरणों और कार्यों को प्रदाता के मॉडल के साथ बातचीत करने की अनुमति देता है. मेरे मतलब को दर्शाने के लिए, मैंने एक सरल एजेंट बनाया जो मेरे कमांड लाइन के साथ काम करता है, मेरे एजेंटों के लिए बनाए गए निरीक्षण उपकरण का उपयोग करके बातचीत की निगरानी करने के लिए. यहाँ यह है कि जब आप एक एआई एजेंट फ्रेमवर्क के साथ उनके एपीआई का उपयोग करते हैं तो वास्तव में ओपनएआई को क्या भेजा जाता है. यह सिर्फ एक सिद्धांत नहीं है, बल्कि एक सरल बातचीत से एक वास्तविक निशान है... जोड़े गए छवियों में, आप मेरे सिस्टम पंप और कुछ लॉग देख सकते हैं जो मैंने इस प्रदर्शन के उद्देश्य के लिए जोड़ा है. फिर नीचे मेरे उपकरण से ट्रैक की सामग्री है: 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 आप निम्न देख सकते हैं: My System Prompts और एजेंट कॉन्फ़िगरेशन बातचीत की सामग्री उपयोग किए जाने वाले फ्रेमवर्क (CrewAI) मॉडल विकल्प (gpt-3.5-turbo) टोकन उपयोग और प्रदर्शन मीट्रिक्स यह न केवल व्यक्तिगत या संवेदनशील जानकारी के बारे में है जो पाइपलाइन के माध्यम से विश्लेषण की जाती है, बल्कि आपकी व्यावसायिक रणनीति और आईपी के बारे में भी है: आपने अपने एजेंटों को कैसे डिजाइन किया है, आपकी प्रोत्साहन रणनीतियां, आपकी कार्य प्रवाह वास्तुकला, आदि। यह केवल ओपनएआई के लिए विशेष नहीं है, यह वह है जो सभी अन्य एलएलएम प्रदाता देखते हैं जब आप अपने एपीआई का उपयोग करते हैं. यदि आप गैर तकनीकी हैं और एक विनियमित उद्योग में निर्माण करते हैं, तो यह जानने की जरूरत है ताकि आप इसके अनुरूप योजना बना सकें कि आपके एआई एजेंट उत्पादन में कैसे काम करेंगे. परीक्षण के लिए अपने अवधारणा सबूत का निर्माण करने के लिए एपीआई का उपयोग करना बुरा नहीं है, लेकिन आपको यह सुनिश्चित करने की आवश्यकता है कि किन डेटा के माध्यम से यह गुजरता है और यह सुनिश्चित करें कि पीआईआई (व्यक्तिगत पहचान योग्य जानकारी) इसके माध्यम से नहीं गुजरता है। इन एपीआई का जिम्मेदार तरीके से उपयोग कैसे करें अपने आवेदन में तीसरे पक्ष के एपीआई का उपयोग करने से पहले, अपने डेटा का उपयोग करने के तरीके के बारे में उनकी गोपनीयता नीति और उपयोग की शर्तों को पढ़ने के लिए सुनिश्चित करें। अगला यह सुनिश्चित करना है कि जो भी डेटा आप एलएलएम के साथ उपयोग करने जा रहे हैं, उसमें क्रेडिट कार्ड, सामाजिक सुरक्षा नंबर, किसी भी चीज और सब कुछ जैसे संवेदनशील जानकारी नहीं है जो किसी व्यक्ति की पहचान करने के लिए इस्तेमाल किया जाएगा और किया जा सकता है। अपने डेटा को स्वयं होस्ट किए गए मॉडल के साथ स्थानीय रखें यदि आप सोच रहे हैं कि यह कैसे संभव है या यह कैसे काम करता है, तो आपका जवाब ओलामा है. ओलामा क्या है? ओलामा एक ओपन सोर्स प्लेटफॉर्म है जो आपको अपने स्वयं के मशीन पर स्थानीय रूप से बड़े भाषा मॉडल (एलएलएम) चलाने की अनुमति देता है: विंडोज, मैकओएस, या लिनक्स: क्लाउड सेवाओं पर निर्भर किए बिना इसका मतलब है कि आपके सभी डेटा, बातचीत और सेवाएं आपके पर्यावरण के भीतर हैं: कोई बाहरी एपीआई कॉल नहीं करता है, कोई डेटा आपके पर्यावरण को छोड़ देता है। ओलामा उच्च गुणवत्ता वाले ओपन सोर्स मॉडल की एक विस्तृत श्रृंखला का समर्थन करता है: Llama 2/3: मेटा के प्रमुख मॉडल, सामान्य बातचीत और तर्क के लिए उत्कृष्ट मिस्ट्रा: तेज़, कुशल मॉडल जो अपना वजन बढ़ाते हैं CodeLlama: प्रोग्रामिंग कार्यों और कोड उत्पन्न करने के लिए विशेषज्ञता Gemma: गूगल के खुले मॉडल सुरक्षा और प्रदर्शन के लिए अनुकूलित Phi: माइक्रोसॉफ्ट की कॉम्पैक्ट लेकिन सक्षम मॉडल Qwen: मजबूत बहुभाषी क्षमता इनमें से अधिकांश मॉडल विभिन्न आकार (7B, 13B, 70B पैरामीटर) में आते हैं, जो आपको आपके उपलब्ध हार्डवेयर और प्रदर्शन आवश्यकताओं के आधार पर चुनने के लिए स्वतंत्रता प्रदान करते हैं। Ollama के भीतर इन मॉडल को चलाने के लिए, आपका हार्डवेयर आपके साथ काम कर रहे मॉडल के आकार पर निर्भर करता है। छोटे मॉडल (7B): 8-16GB रैम, अधिकांश आधुनिक लैपटॉप पर चल सकता है मध्यम मॉडल (13B): 16-32GB रैम, डेस्कटॉप या सर्वर की सिफारिश की जाती है बड़े मॉडल (70B): 64GB + रैम, उद्यम स्तर के हार्डवेयर की आवश्यकता होती है GPU अधिग्रहण: वैकल्पिक लेकिन गति में काफी सुधार – 8GB + VRAM के साथ NVIDIA GPUs की सिफारिश की जाती है स्थानीय मॉडल का उपयोग करना गोपनीयता और सुविधा के बीच एक संतुलन के साथ आता है और मैं नीचे उनमें से कुछ को उजागर करूंगा: Local Models (Ollama): ✅ पूर्ण डेटा गोपनीयता - आपके नेटवर्क से कुछ भी नहीं छोड़ता है ✅ प्रारंभिक स्थापना के बाद प्रति टोकन लागत नहीं ऑफ़लाइन काम करता है, इंटरनेट पर निर्भरता नहीं तकनीकी स्थापना और रखरखाव की आवश्यकता है 🔸 ओपन-सॉर्ड मॉडल पर सीमित (जीपीटी-4 गुणवत्ता से मेल नहीं आ सकता है) हार्डवेयर निवेश और बिजली लागत Cloud APIs (OpenAI, etc.): ✅ नवीनतम, सबसे शक्तिशाली मॉडल प्रबंधन करने के लिए कोई सुविधा नहीं है त्वरित स्केलिंग और उपलब्धता डेटा तीसरे पक्ष के सिस्टम के माध्यम से यात्रा करता है वर्तमान में टोक्यो लागत इंटरनेट पर निर्भरता और प्रदाता अपटाइम उत्पादन वातावरण में, इन मॉडल (ओलामा और कस्टम) को आसानी से क्लाउड में वितरित करने और इसके उपयोग के लिए उत्पन्न एपीआई के लिए कंटेनर किया जा सकता है: यह एपीआई आपके / आपकी कंपनी का होगा, फिर आपके व्यवसाय के लिए उपयोग किया जाएगा। स्थानीय मॉडल के लिए लागत विचारों के मामले में अर्थव्यवस्था आपके उपयोग पैटर्न पर निर्भर करती है। : यदि आप प्रतिदिन हजारों अनुरोधों को संसाधित कर रहे हैं, तो स्थानीय मॉडल अक्सर महीनों के भीतर लागत प्रभावी हो जाते हैं। High Usage Scenarios : प्रोटोटाइपिंग या कभी-कभी उपयोग के लिए, क्लाउड एपीआई आमतौर पर अधिक आर्थिक होते हैं। Low Usage Scenarios : स्वास्थ्य देखभाल, वित्त या कानूनी क्षेत्रों के लिए, स्थानीय तैनाती के अनुपालन लाभ अक्सर उपयोग की मात्रा के बावजूद लागत को उचित बनाते हैं। Regulated Industries मीठा बिंदु अक्सर एक हाइब्रिड दृष्टिकोण है: संवेदनशील डेटा प्रसंस्करण के लिए स्थानीय मॉडल का उपयोग करें और गैर-संवेदनशील सुविधाओं के लिए क्लाउड एपीआई जो नवीनतम मॉडल क्षमताओं से लाभ उठाते हैं। जब स्थानीय vs. क्लाउड का चयन करें: स्थानीय: संवेदनशील डेटा, अनुपालन आवश्यकताएं, पूर्वानुमानित लागत क्लाउड: त्वरित प्रोटोटाइपिंग, स्केलिंग आवश्यकताएं, नवीनतम मॉडल