{
    "query": "what is the title of my documents/",
    "namespace": "7e4bf311-7ec6-4453-99dd-0c967dfb3e4f",
    "messages": [
        {
            "role": "assistant",
            "content": "\ud83e\udd16\u2728 Hello, I am Simon, your personal assistant! \ud83c\udf1f How can I assist you today? Let's work together to answer your questions, overcome challenges, and achieve your goals! Just ask, and I am here for you.\n\nwhat is the title of my documents/\n\n FOR ADDITIONAL CONTEXT:\n\nKnowledgebase name: Test Documents\nKnowledgebase files:\ntest doc.docx\nKnowledgebases crawlers:\n"
        },
        {
            "role": "user",
            "content": "what is the title of my documents/"
        },
        {
            "role": "assistant",
            "content": ""
        }
    ],
    "stream": true,
    "language_level": "",
    "chat_channel": "kios:197:1727756844113",
    "language": "German",
    "tone": "neutral",
    "writing_style": "standard",
    "model": "gpt-4o-mini-2024-07-18",
    "knowledgebase": "ki-dev-large",
    "seed": 1,
    "client_id": 1727756844113,
    "all_context": false,
    "follow_up_for": null,
    "knowledgebase_files_count": 1,
    "override_command": null,
    "disable_clarity_check": false,
    "custom_primer": "",
    "logging": true,
    "query_route": ""
}


INITIALIZATION
Knowledgebase: ki-dev-large
Base Query: what is the title of my documents/
Model: gpt-4o-mini-2024-07-18
**Elapsed Time: 0.00 seconds**
ROUTING
Query type: list
**Elapsed Time: 1.77 seconds**
RAG PARAMETERS
Max Context To Include: 100
Lowest Score to Consider: 0.1
==================================================
**Elapsed Time: 0.14 seconds**
==================================================


VECTOR SEARCH ALGORITHM TO USE 
Use MMR search?: True
Use Similarity search?: False
==================================================
**Elapsed Time: 0.10 seconds**
==================================================


VECTOR SEARCH DONE 
==================================================
**Elapsed Time: 0.83 seconds**
==================================================


PRIMER 
Primer: 
            You are Simon, a highly intelligent personal assistant in a system called KIOS. You are a chatbot that
            can read knowledgebases through the "CONTEXT" that is included in the user's chat message.

        
            Your role is to act as an expert at summarization and analysis.

            In your responses to enterprise users, prioritize clarity, trustworthiness, and appropriate formality.

            Be honest by admitting when a topic falls outside your scope of knowledge, and suggest
            alternative avenues for obtaining information when necessary.

            Make effective use of chat history to avoid redundancy and enhance response relevance, continuously
            adapting to integrate all necessary details in your interactions.

            Use as much tokens as possible to provide a detailed response.
        
**Elapsed Time: 0.18 seconds**
FINAL QUERY 
Final Query: CONTEXT: ##########
File: test%20doc.docx

Page: 1

Context: test
##########

"""QUERY: what is the title of my documents/"""

Consider the chat history for relevant information. Use all information included. If query is already asked in the history double check the correctness of your answer and maybe correct your previous mistake. Use as much tokens as needed but at the same time be as efficient as possible.

Important: Take a look at the QUERY and only the QUERY. Please try always to answer the query question. If the client ask for a formatting structure follow his advise.But if the questions is vague or unclear ask a follow-up question based on the context.


Final Files Sources: test%20doc.docx - Page 1
==================================================
**Elapsed Time: 0.44 seconds**
==================================================


FINAL ANSWER 
Answer: [Answer was streamed to client]
==================================================
**Elapsed Time: 0.39 seconds**
==================================================