Replace llama-index with a local Document dataclass

The whole dependency existed for one shallow use: llama_index.core.Document
as a text+metadata+doc_id carrier in add_context_to_nodes (plus one test).
The contextual-nodes pickle stores our own ChunkRecord objects with
primitive metadata, so existing HF artifacts are unaffected. Drops ~100
packages from the lockfile and removes one of the two openai<3 pins.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>

data/scraping_scripts/add_context_to_nodes.py

@@ -6,7 +6,8 @@ import random
 import re
 import time
 from collections import deque
-from typing import List
+from dataclasses import dataclass
+from typing import Any, List
 
 import tiktoken
 from dotenv import load_dotenv
@@ -14,7 +15,6 @@ from google import genai
 from google.genai import types
 from google.genai.errors import APIError
 from jinja2 import Template
-from llama_index.core import Document
 from pydantic import BaseModel, Field
 from tenacity import retry, retry_if_exception, stop_after_attempt
 from tqdm.asyncio import tqdm
@@ -27,6 +27,27 @@ from app.chroma_rag import (
 
 load_dotenv(".env")
 
+
+@dataclass
+class Document:
+    """Text + metadata carrier for one JSONL source document.
+
+    Replaces llama_index.core.Document, the only thing this repo used
+    llama-index for. Metadata is copied at construction so trimming a document
+    in process_chunk cannot mutate another holder's dict.
+    """
+
+    text: str
+    metadata: dict[str, Any]
+    doc_id: str = ""
+
+    def __post_init__(self) -> None:
+        self.metadata = dict(self.metadata)
+
+    def get_content(self) -> str:
+        return self.text
+
+
 CONTEXT_MODEL = os.getenv("GEMINI_CONTEXT_MODEL", "gemini-3.1-flash-lite")
 CONTEXT_MAX_OUTPUT_TOKENS = 1000
 CONTEXT_TPM_LIMIT = int(os.getenv("GEMINI_CONTEXT_TPM_LIMIT", "30000000"))
@@ -41,7 +62,7 @@ RETRYABLE_GENAI_STATUS_CODES = {408, 429, 500, 502, 503, 504}
 # detect docs whose content changed in place (doc_ids are path-based and stable
 # across edits, so id membership alone cannot catch this). update_docs_workflow
 # keeps its own copy of this constant so it does not have to import this
-# (Gemini/tiktoken/llama_index-heavy) module; tests assert the two stay in sync.
+# (Gemini/tiktoken-heavy) module; tests assert the two stay in sync.
 DOC_CONTENT_HASH_METADATA_KEY = "doc_content_hash"
 _genai_client: genai.Client | None = None
 _token_encoding = tiktoken.get_encoding("cl100k_base")
@@ -106,21 +127,7 @@ def create_docs(input_file: str) -> List[Document]:
                 Document(
                     doc_id=data["doc_id"],
                     text=data["content"],
-                    metadata=metadata,  # type: ignore
-                    excluded_llm_metadata_keys=[
-                        "title",
-                        "tokens",
-                        "retrieve_doc",
-                        "source",
-                        "content_hash",
-                    ],
-                    excluded_embed_metadata_keys=[
-                        "url",
-                        "tokens",
-                        "retrieve_doc",
-                        "source",
-                        "content_hash",
-                    ],
+                    metadata=metadata,
                 )
             )
     return documents

data/scraping_scripts/update_docs_workflow.py

@@ -138,7 +138,7 @@ LLMS_TXT_SOURCES = list(LLMS_TXT_SOURCE_KEYS)
 # Node-metadata key stamped by add_context_to_nodes.process_chunk with the
 # source document's JSONL ``content_hash``. Deliberately duplicated here (not
 # imported) so this module keeps its light import footprint —
-# add_context_to_nodes pulls in Gemini/tiktoken/llama_index, which this
+# add_context_to_nodes pulls in Gemini/tiktoken, which this
 # module's importers and tests should not need.
 # tests/test_incremental_context.py asserts the two constants stay in sync.
 DOC_CONTENT_HASH_METADATA_KEY = "doc_content_hash"
@@ -396,7 +396,7 @@ def merge_contextual_nodes(
 
 def _add_context_for_new_docs(temp_file: str, reprocessed_doc_ids: Set[str]) -> None:
     """Generate context for the docs in ``temp_file`` and merge into the PKL."""
-    # Imported lazily: pulls in Gemini/tiktoken/llama_index, which the rest of
+    # Imported lazily: pulls in Gemini/tiktoken, which the rest of
     # this module (and its importers/tests) should not need.
     import asyncio
 

pyproject.toml

@@ -17,7 +17,6 @@ dependencies = [
     "langchain-deepseek>=1.1.0",
     "langchain-google-genai",
     "langchain-openai",
-    "llama-index",
     "nbconvert",
     "nbformat",
     "openai",

tests/test_chroma_rag.py

@@ -9,9 +9,8 @@ from unittest.mock import ANY, Mock, patch
 
 import chromadb
 import tiktoken
-from data.scraping_scripts.add_context_to_nodes import process
+from data.scraping_scripts.add_context_to_nodes import Document, process
 from data.scraping_scripts.create_vector_stores import write_retrieval_artifacts
-from llama_index.core import Document
 from app.chroma_rag import (
     BM25Index,
     ChunkRecord,

uv.lock

@@ -27,7 +27,6 @@ dependencies = [
     { name = "langchain-deepseek" },
     { name = "langchain-google-genai" },
     { name = "langchain-openai" },
-    { name = "llama-index" },
     { name = "nbconvert" },
     { name = "nbformat" },
     { name = "openai" },
@@ -67,7 +66,6 @@ requires-dist = [
     { name = "langchain-deepseek", specifier = ">=1.1.0" },
     { name = "langchain-google-genai" },
     { name = "langchain-openai" },
-    { name = "llama-index" },
     { name = "nbconvert" },
     { name = "nbformat" },
     { name = "openai" },
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 [[package]]
 name = "typing-inspection"
 version = "0.4.4"