Updated README for deprecations

Author: jamesbraza

README.md

@@ -362,7 +362,9 @@ from paperqa import Settings, ask
 
 answer_response = ask(
     "What is PaperQA2?",
-    settings=Settings(temperature=0.5, paper_directory="my_papers"),
+    settings=Settings(
+        temperature=0.5, agent={"index": {"paper_directory": "my_papers"}}
+    ),
 )
 ```
 
@@ -374,7 +376,9 @@ from paperqa import Settings, agent_query
 
 answer_response = await agent_query(
     query="What is PaperQA2?",
-    settings=Settings(temperature=0.5, paper_directory="my_papers"),
+    settings=Settings(
+        temperature=0.5, agent={"index": {"paper_directory": "my_papers"}}
+    ),
 )
 ```
 
@@ -469,7 +473,7 @@ from paperqa import Settings, ask
 answer_response = ask(
     "What is PaperQA2?",
     settings=Settings(
-        llm="gpt-4o-mini", summary_llm="gpt-4o-mini", paper_directory="my_papers"
+        llm="gpt-4o-mini", summary_llm="gpt-4o-mini", agent={"index": {"paper_directory": "my_papers"}}
     ),
 )
 ```
@@ -796,9 +800,9 @@ for ... in my_docs:
 Indexes will be placed in the [home directory][home dir] by default.
 This can be controlled via the `PQA_HOME` environment variable.
 
-Indexes are made by reading files in the `Settings.paper_directory`.
+Indexes are made by reading files in the `IndexSettings.paper_directory`.
 By default, we recursively read from subdirectories of the paper directory,
-unless disabled using `Settings.index_recursively`.
+unless disabled using `IndexSettings.recurse_subdirectories`.
 The paper directory is not modified in any way, it's just read from.
 
 [home dir]: https://docs.python.org/3/library/pathlib.html#pathlib.Path.home
@@ -824,7 +828,7 @@ which also works when called on `DocDetails`.
 ### Reusing Index
 
 The local search indexes are built based on a hash of the current `Settings` object.
-So make sure you properly specify the `paper_directory` to your `Settings` object.
+So make sure you properly specify the `paper_directory` to your `IndexSettings` object.
 In general, it's advisable to:
 
 1. Pre-build an index given a folder of papers (can take several minutes)
@@ -839,7 +843,7 @@ from paperqa.agents.search import get_directory_index
 
 
 async def amain(folder_of_papers: str | os.PathLike) -> None:
-    settings = Settings(paper_directory=folder_of_papers)
+    settings = Settings(agent={"index": {"paper_directory": folder_of_papers}})
 
     # 1. Build the index. Note an index name is autogenerated when unspecified
     built_index = await get_directory_index(settings=settings)
@@ -939,17 +943,13 @@ will return much faster than the first query and we'll be certain the authors ma
 | `answer.group_contexts_by_question`          | `False`                                | Groups the final contexts by the underlying `gather_evidence` question in the final context prompt.                           |
 | `answer.evidence_relevance_score_cutoff`     | `1`                                    | Cutoff evidence relevance score to include in the answer context (inclusive)                                                  |
 | `answer.skip_evidence_citation_strip`        | `False`                                | Skip removal of citations from the `gather_evidence` contexts                                                                 |
-| `parsing.chunk_size`                         | `5000`                                 | Characters per chunk (0 for no chunking).                                                                                     |
 | `parsing.page_size_limit`                    | `1,280,000`                            | Character limit per page.                                                                                                     |
-| `parsing.pdfs_use_block_parsing`             | `False`                                | Opt-in flag for block-based PDF parsing over text-based PDF parsing.                                                          |
 | `parsing.use_doc_details`                    | `True`                                 | Whether to get metadata details for docs.                                                                                     |
-| `parsing.overlap`                            | `250`                                  | Characters to overlap chunks.                                                                                                 |
 | `parsing.reader_config`                      | `dict`                                 | Optional keyword arguments for the document reader.                                                                           |
 | `parsing.multimodal`                         | `True`                                 | Control to parse both text and media from applicable documents, as well as potentially enriching them with text descriptions. |
 | `parsing.defer_embedding`                    | `False`                                | Whether to defer embedding until summarization.                                                                               |
 | `parsing.parse_pdf`                          | `paperqa_pypdf.parse_pdf_to_pages`     | Function to parse PDF files.                                                                                                  |
 | `parsing.configure_pdf_parser`               | No-op                                  | Callable to configure the PDF parser within `parse_pdf`, useful for behaviors such as enabling logging.                       |
-| `parsing.chunking_algorithm`                 | `ChunkingOptions.SIMPLE_OVERLAP`       | Algorithm for chunking.                                                                                                       |
 | `parsing.doc_filters`                        | `None`                                 | Optional filters for allowed documents.                                                                                       |
 | `parsing.use_human_readable_clinical_trials` | `False`                                | Parse clinical trial JSONs into readable text.                                                                                |
 | `parsing.enrichment_llm`                     | `"gpt-4o-2024-11-20"`                  | LLM for media enrichment.                                                                                                     |
@@ -976,7 +976,6 @@ will return much faster than the first query and we'll be certain the authors ma
 | `agent.return_paper_metadata`                | `False`                                | Whether to include paper title/year in search tool results.                                                                   |
 | `agent.search_count`                         | `8`                                    | Search count.                                                                                                                 |
 | `agent.timeout`                              | `500.0`                                | Timeout on agent execution (seconds).                                                                                         |
-| `agent.should_pre_search`                    | `False`                                | Whether to run search tool before invoking agent.                                                                             |
 | `agent.tool_names`                           | `None`                                 | Optional override on tools to provide the agent.                                                                              |
 | `agent.max_timesteps`                        | `None`                                 | Optional upper limit on environment steps.                                                                                    |
 | `agent.index.name`                           | `None`                                 | Optional name of the index.                                                                                                   |