{
    "query": "You are a super intelligent assistant. Please answer all my questions precisely and comprehensively.\n\nThrough our system KIOS you have a Knowledge Base named crawl-2 with all the informations that the user requests. In this knowledge base are following Documents \n\nThis is the initial message to start the chat. Based on the following summary/context you should formulate an initial message greeting the user with the following user name [Gender] [Vorname] [Surname] tell them that you are the AI Chatbot Simon using the Large Language Model [Used Model] to answer all questions.\n\nFormulate the initial message in the Usersettings Language German\n\nPlease use the following context to suggest some questions or topics to chat about this knowledge base. List at least 3-10 possible topics or suggestions up and use emojis. The chat should be professional and in business terms.  At the end ask an open question what the user would like to check on the list. Please keep the wildcards incased in brackets and make it easy to replace the wildcards. \n\n The context provided is a series of code snippets from different files related to a project using Pinecone.io and OpenAI. \n\n**File: docs-pinecone-io-examples-sample-apps-namespace-notes-built-with-44594.txt**\n\nThis file focuses on embedding text chunks using the OpenAI text-embedding-3-small model. It also discusses RAG document management, which involves storing multiple documents within a namespace by prefixing chunk IDs with a document ID. This allows for targeted retrieval and deletion of specific documents.\n\n**File: docs-pinecone-io-examples-sample-apps-namespace-notes-project-structure-44597.txt**\n\nThis file is similar to the previous one, providing code snippets for embedding text chunks and managing RAG documents. It reiterates the importance of id prefixing for document management.\n\n**File: docs-pinecone-io-examples-sample-apps-namespace-notes-further-optimizations-for-the-rag-pipeline-44536.txt**\n\nThis file focuses on further optimizations for the RAG pipeline. It includes code snippets for embedding text chunks and managing RAG documents, but it also highlights the use of pagination for retrieving chunks from the namespace.\n\n**File: docs-pinecone-io-examples-sample-apps-namespace-notes-43975.txt**\n\nThis file is similar to the previous ones, providing code snippets for embedding text chunks and managing RAG documents. It emphasizes the use of id prefixing for document management.\n\n**File: docs-pinecone-io-examples-sample-apps-namespace-notes-create-a-pinecone-serverless-index-44622.txt**\n\nThis file focuses on creating a serverless Pinecone index. It includes code snippets for embedding text chunks and managing RAG documents, but it also highlights the use of a function called `getContext` to retrieve context from a previous message.\n\n**File: docs-pinecone-io-examples-sample-apps-namespace-notes-get-your-api-key-44621.txt**\n\nThis file focuses on retrieving an API key for Pinecone. It includes code snippets for embedding text chunks and managing RAG documents, but it also highlights the use of a function called `getContext` to retrieve context from a previous message. It also includes a code snippet for deleting documents from a namespace.\n\n**File: docs-pinecone-io-examples-sample-apps-namespace-notes-start-the-project-44524.txt**\n\nThis file focuses on starting a project using Pinecone. It includes code snippets for embedding text chunks and managing RAG documents, but it also highlights the use of a function called `getContext` to retrieve context from a previous message. It also includes a code snippet for deleting documents from a namespace.\n\n**File: docs-pinecone-io-examples-sample-apps-namespace-notes-simple-multi-tenant-rag-methodology-44526.txt**\n\nThis file focuses on a simple multi-tenant RAG methodology. It includes code snippets for embedding text chunks and managing RAG documents, but it also highlights the use of a function called `getContext` to retrieve context from a previous message. It also includes a code snippet for deleting documents from a namespace.\n\n**File: docs-pinecone-io-examples-sample-apps-namespace-notes-troubleshooting-44601.txt**\n\nThis file focuses on troubleshooting issues related to the project. It includes code snippets for embedding text chunks and managing RAG documents, but it also highlights the use of a function called `getContext` to retrieve context from a previous message. It also includes a code snippet for deleting documents from a namespace.\n\n**File: docs-pinecone-io-examples-sample-apps-namespace-notes-run-the-sample-app-44523.txt**\n\nThis file focuses on running the sample application. It includes code snippets for embedding text chunks and managing RAG documents, but it also highlights the use of a function called `getContext` to retrieve context from a previous message. It also includes a code snippet for deleting documents from a namespace.\n\nOverall, the context provided is a collection of code snippets and explanations related to a project using Pinecone.io and OpenAI for building a RAG system. The files cover various aspects of the project, including embedding text chunks, managing RAG documents, creating a serverless index, retrieving API keys, and troubleshooting issues.\n",
    "namespace": "c90e0ae7-9210-468a-a35c-5c9def9500d6",
    "messages": [],
    "stream": false,
    "language_level": "",
    "chat_channel": "",
    "language": "German",
    "tone": "neutral",
    "writing_style": "standard",
    "model": "gemini-1.5-flash",
    "knowledgebase": "ki-dev-large",
    "seed": 0,
    "client_id": 0,
    "all_context": true,
    "follow_up_for": null,
    "knowledgebase_files_count": 0,
    "override_command": "",
    "disable_clarity_check": true,
    "custom_primer": "",
    "logging": true,
    "query_route": ""
}


INITIALIZATION
Knowledgebase: ki-dev-large
Base Query: You are a super intelligent assistant. Please answer all my questions precisely and comprehensively.

Through our system KIOS you have a Knowledge Base named crawl-2 with all the informations that the user requests. In this knowledge base are following Documents 

This is the initial message to start the chat. Based on the following summary/context you should formulate an initial message greeting the user with the following user name [Gender] [Vorname] [Surname] tell them that you are the AI Chatbot Simon using the Large Language Model [Used Model] to answer all questions.

Formulate the initial message in the Usersettings Language German

Please use the following context to suggest some questions or topics to chat about this knowledge base. List at least 3-10 possible topics or suggestions up and use emojis. The chat should be professional and in business terms.  At the end ask an open question what the user would like to check on the list. Please keep the wildcards incased in brackets and make it easy to replace the wildcards. 

 The context provided is a series of code snippets from different files related to a project using Pinecone.io and OpenAI. 

**File: docs-pinecone-io-examples-sample-apps-namespace-notes-built-with-44594.txt**

This file focuses on embedding text chunks using the OpenAI text-embedding-3-small model. It also discusses RAG document management, which involves storing multiple documents within a namespace by prefixing chunk IDs with a document ID. This allows for targeted retrieval and deletion of specific documents.

**File: docs-pinecone-io-examples-sample-apps-namespace-notes-project-structure-44597.txt**

This file is similar to the previous one, providing code snippets for embedding text chunks and managing RAG documents. It reiterates the importance of id prefixing for document management.

**File: docs-pinecone-io-examples-sample-apps-namespace-notes-further-optimizations-for-the-rag-pipeline-44536.txt**

This file focuses on further optimizations for the RAG pipeline. It includes code snippets for embedding text chunks and managing RAG documents, but it also highlights the use of pagination for retrieving chunks from the namespace.

**File: docs-pinecone-io-examples-sample-apps-namespace-notes-43975.txt**

This file is similar to the previous ones, providing code snippets for embedding text chunks and managing RAG documents. It emphasizes the use of id prefixing for document management.

**File: docs-pinecone-io-examples-sample-apps-namespace-notes-create-a-pinecone-serverless-index-44622.txt**

This file focuses on creating a serverless Pinecone index. It includes code snippets for embedding text chunks and managing RAG documents, but it also highlights the use of a function called `getContext` to retrieve context from a previous message.

**File: docs-pinecone-io-examples-sample-apps-namespace-notes-get-your-api-key-44621.txt**

This file focuses on retrieving an API key for Pinecone. It includes code snippets for embedding text chunks and managing RAG documents, but it also highlights the use of a function called `getContext` to retrieve context from a previous message. It also includes a code snippet for deleting documents from a namespace.

**File: docs-pinecone-io-examples-sample-apps-namespace-notes-start-the-project-44524.txt**

This file focuses on starting a project using Pinecone. It includes code snippets for embedding text chunks and managing RAG documents, but it also highlights the use of a function called `getContext` to retrieve context from a previous message. It also includes a code snippet for deleting documents from a namespace.

**File: docs-pinecone-io-examples-sample-apps-namespace-notes-simple-multi-tenant-rag-methodology-44526.txt**

This file focuses on a simple multi-tenant RAG methodology. It includes code snippets for embedding text chunks and managing RAG documents, but it also highlights the use of a function called `getContext` to retrieve context from a previous message. It also includes a code snippet for deleting documents from a namespace.

**File: docs-pinecone-io-examples-sample-apps-namespace-notes-troubleshooting-44601.txt**

This file focuses on troubleshooting issues related to the project. It includes code snippets for embedding text chunks and managing RAG documents, but it also highlights the use of a function called `getContext` to retrieve context from a previous message. It also includes a code snippet for deleting documents from a namespace.

**File: docs-pinecone-io-examples-sample-apps-namespace-notes-run-the-sample-app-44523.txt**

This file focuses on running the sample application. It includes code snippets for embedding text chunks and managing RAG documents, but it also highlights the use of a function called `getContext` to retrieve context from a previous message. It also includes a code snippet for deleting documents from a namespace.

Overall, the context provided is a collection of code snippets and explanations related to a project using Pinecone.io and OpenAI for building a RAG system. The files cover various aspects of the project, including embedding text chunks, managing RAG documents, creating a serverless index, retrieving API keys, and troubleshooting issues.

Model: gemini-1.5-flash
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