Detect Greeting Questions | Input : Greeting detection prompt with input question
Output: Classification output
| ServiceName- Information about the application in the resource SpanName - Internal function name gen_ai.completion.0.finish_reason - gen_ai.completion.0.role - gen_ai.openai.system_fingerprint - gen_ai.request.max_tokens -The maximum number of response tokens requested gen_ai.request.model - The model requested (e.g. gpt-4 , claude , etc.) gen_ai.request.temperature gen_ai.system - The vendor of the LLM (e.g. OpenAI, Anthropic, etc.) gen_ai.usage.completion_tokens - The number of tokens used for the completion response gen_ai.usage.prompt_tokens - The number of tokens used for the prompt in the request llm.request.type - The type of request (e.g. completion , chat , etc.) llm.usage.total_tokens - The total number of tokens used
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| Output : Content Safety Check Output
| ServiceName - Information about the application in the resource SpanName - Internal function name
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| Output : Vector embeddings of the user query
| ServiceName - Information about the application in the resource SpanName - Internal function name gen_ai.request.model - The model requested (e.g. gpt-4 , claude , etc.) gen_ai.response.model - The model actually used (e.g. gpt-4-0613 , etc.) gen_ai.system - The vendor of the LLM (e.g. OpenAI, Anthropic, etc.) gen_ai.usage.prompt_tokens -The number of tokens used for the prompt in the request llm.headers - The headers used for the request llm.request.type - The type of request (e.g. completion , chat , etc.) llm.usage.total_tokens - The total number of tokens used
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| Output : Similar embeddings from the vector store
| ServiceName - Information about the application in the resource SpanName - Internal function name
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| Output : Reranked similar embeddings using Cohere reranker
| ServiceName - Information about the application in the resource SpanName - Internal function name
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| Input : Prompt, user query and the reranked context Output : Response from the LLM
| ServiceName - Information about the application in the resource SpanName - Internal function name gen_ai.completion.0.finish_reason - gen_ai.completion.0.role - gen_ai.openai.api_version - gen_ai.request.max_tokens -The maximum number of response tokens requested gen_ai.request.model - The model requested (e.g. gpt-4 , claude , etc.) gen_ai.request.temperature - gen_ai.response.model - The model actually used (e.g. gpt-4-0613 , etc.) gen_ai.system - The vendor of the LLM (e.g. OpenAI, Anthropic, etc.) gen_ai.usage.completion_tokens - The number of tokens used for the completion response gen_ai.usage.prompt_tokens - The number of tokens used for the prompt in the request llm.request.type - The type of request (e.g. completion , chat , etc.) llm.usage.total_tokens - The total number of tokens used
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| Input : Follow up question generation prompt, user query and LLM generated answer to the user query Output : Followup questions
| ServiceName - Information about the application in the resource SpanName - Internal function name gen_ai.completion.0.finish_reason - gen_ai.completion.0.role - gen_ai.openai.system_fingerprint gen_ai.openai.api_version - gen_ai.request.max_tokens -The maximum number of response tokens requested gen_ai.request.model -The model actually used (e.g. gpt-4-0613 , etc.) gen_ai.request.temperature - gen_ai.system -The vendor of the LLM (e.g. OpenAI, Anthropic, etc.) gen_ai.usage.completion_tokens -The number of tokens used for the completion response gen_ai.usage.prompt_tokens -The number of tokens used for the prompt in the request llm.request.type - The type of request (e.g. completion , chat , etc.)
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| Input : Prompt, user question, agent thoughts and actions Output: Response to the agent action
| ServiceName - Information about the application in the resource SpanName - Internal function name gen_ai.request.max_tokens - The maximum number of response tokens requested gen_ai.request.model -The model requested (e.g. gpt-4 , claude , etc.) gen_ai.request.temperature gen_ai.system-he vendor of the LLM (e.g. OpenAI, Anthropic, etc.) gen_ai.usage.completion_tokens -The number of tokens used for the completion response gen_ai.usage.prompt_tokens -The number of tokens used for the prompt in the request llm.request.type - The type of request (e.g. completion , chat , etc.) llm.usage.total_tokens - The total number of tokens used
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| Input : Prompt with user query
Output: Response from LLM
| ServiceName - Information about the application in the resource SpanName - Internal function name gen_ai.request.max_tokens - The maximum number of response tokens requested gen_ai.request.model -The model requested (e.g. gpt-4 , claude , etc.) gen_ai.request.temperature gen_ai.system-he vendor of the LLM (e.g. OpenAI, Anthropic, etc.) gen_ai.usage.completion_tokens -The number of tokens used for the completion response gen_ai.usage.prompt_tokens -The number of tokens used for the prompt in the request llm.request.type - The type of request (e.g. completion , chat , etc.) llm.usage.total_tokens - The total number of tokens used
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