Add Request Context feature: allow to override settings at runtime

[dluc]

Motivation and Context (Why the change? What's the scenario?)

Several settings of the solution are hard coded by design, and others can be configured but require a service restart to be changed.

This PR introduces a Context object that is passed during ingestion and search/ask. The context object is optional and can contain custom key-values accessible to handlers and search clients.

During web requests, the context is accessible also via dependency injection in those scenarios where a method signature doesn't support IContext, see RequestContextProvider. During ingestion, the context is accessible through the DataPipeline instance.

The context allows to override the following settings during a request/during the upload a document, without the need to change the code or change the configuration:

• custom_partitioning_max_tokens_per_paragraph_int: the max size of paragraphs while partitioning a file during the upload
• custom_partitioning_overlapping_tokens_int: overlapping tokens while partitioning a file
• custom_rag_empty_answer_str: the answer returned by Ask when no answer can be found
• custom_rag_prompt_str and custom_rag_fact_template_str: prompt used for RAG, including how facts are injected
• custom_rag_max_tokens_int: max number of tokens to generate with the RAG prompt
• custom_rag_temperature_float: temperature used with the RAG prompt
• custom_rag_nucleus_sampling_float: nucleus sampling used with the RAG prompt
• custom_summary_prompt_str: prompt used to summarize content
• custom_summary_target_token_size_int: size of the summary to generate (best effort)
• custom_summary_overlapping_tokens_int: overlapping tokens while generating summaries

Other keys can be used e.g. when working with custom handlers and custom classes. The RAG {{$facts}} template is now configurable and can include tags and metadata:

• {{$content}}: text from memory, i.e. chunk of text extracted from the source
• {{$source}}: name of the source file, or URL of the web page, where the content originated.
• {{$relevance}}: relevance score of the current chunk of text
• {{$memoryId}}: ID of the memory record
• {{$tags}}: list of tags, excluding reserved/internal ones
• {{$tag[X]}}: tag X value(s), replaced with "-" if the value is empty
• {{$meta[X]}}: value of memory record payload X field (memory payload is also known as metadata), replaced with "-" if the value is empty

The PR includes a few examples.

Sample syntax:

var context = new RequestContext();

context.SetArg("custom_summary_prompt_str", "Summarize this: {{$input}}. Summary: ");

context.SetArg("custom_summary_overlapping_tokens_int", 0);

await memory.ImportDocumentAsync(
    new Document("doc1").AddFile("file4-KM-Readme.pdf"),
    steps: Constants.PipelineOnlySummary,
    context: context);

var context = new RequestContext();

context.SetArg("custom_rag_fact_template_str", "=== Last update: {{$meta[last_update]}} ===\n{{$content}}\n");

context.SetArg("custom_rag_prompt_str", """
                                        Facts:
                                        {{$facts}}
                                        ======
                                        Given only the timestamped facts above, provide a very short answer, include the relevant dates in brackets.
                                        If you don't have sufficient information, reply with '{{$notFound}}'.
                                        Question: {{$input}}
                                        Answer:
                                        """);

var answer = await s_memory.AskAsync("What's Kernel Memory?", context: context);