Index

_

__init__() (src.embed.EmbeddingConfig method), [1], [2], [3] (src.embed.EmbeddingModel method), [1], [2], [3] (src.embed.EmbeddingPipeline method), [1], [2], [3] (src.embed.FAISSIndex method), [1], [2], [3] (src.ingest.ChunkMetadata method), [1], [2], [3], [4] (src.ingest.DocumentChunk method), [1], [2], [3], [4] (src.ingest.DocumentIngester method), [1], [2], [3], [4] (src.ingest.PDFProcessor method), [1], [2], [3], [4] (src.ingest.TextChunker method), [1], [2], [3], [4] (src.ingest.TextCleaner method), [1], [2], [3], [4] (src.llm.BaseLLM method), [1], [2], [3] (src.llm.LLMConfig method), [1], [2], [3] (src.llm.LLMInterface method), [1], [2], [3] (src.llm.LLMResponse method), [1], [2], [3] (src.query.QueryEngine method), [1], [2], [3], [4] (src.query.QueryProcessor method), [1], [2], [3], [4] (src.query.QueryResult method), [1], [2], [3], [4] (src.utils.ProgressTracker method), [1], [2]

A

add_embeddings() (src.embed.FAISSIndex method), [1], [2], [3]

answer (src.llm.LLMResponse attribute), [1], [2], [3]

B

backend (src.llm.LLMConfig attribute), [1], [2], [3]

BaseLLM (class in src.llm), [1], [2], [3] batch_process() (in module src.utils), [1], [2]

C

chunk_end (src.ingest.ChunkMetadata attribute), [1], [2], [3], [4] chunk_index (src.ingest.ChunkMetadata attribute), [1], [2], [3], [4] chunk_size (src.ingest.ChunkMetadata attribute), [1], [2], [3], [4] chunk_start (src.ingest.ChunkMetadata attribute), [1], [2], [3], [4] chunk_text() (src.ingest.TextChunker method), [1], [2], [3], [4] ChunkMetadata (class in src.ingest), [1], [2], [3], [4]

chunks (src.query.QueryResult attribute), [1], [2], [3], [4] clean_text() (src.ingest.TextCleaner method), [1], [2], [3], [4] context_window (src.llm.LLMConfig attribute), [1], [2], [3] create_cache_directory() (in module src.utils), [1], [2] create_embeddings_from_chunks() (src.embed.EmbeddingPipeline method), [1], [2], [3] create_embeddings_from_chunks_file() (in module src.embed), [1], [2], [3] create_llm_interface() (in module src.llm), [1], [2], [3]

D

device (src.embed.EmbeddingConfig attribute), [1], [2], [3]

DocumentChunk (class in src.ingest), [1], [2], [3], [4] DocumentIngester (class in src.ingest), [1], [2], [3], [4]

E

EmbeddingConfig (class in src.embed), [1], [2], [3] EmbeddingModel (class in src.embed), [1], [2], [3]

EmbeddingPipeline (class in src.embed), [1], [2], [3] extract_text() (src.ingest.PDFProcessor method), [1], [2], [3], [4]

F

FAISSIndex (class in src.embed), [1], [2], [3] file_name (src.ingest.ChunkMetadata attribute), [1], [2], [3], [4] finish() (src.utils.ProgressTracker method), [1], [2]

format_llm_response() (in module src.llm), [1], [2], [3] format_prompt() (src.llm.LLMInterface method), [1], [2], [3] format_query_output() (in module src.query), [1], [2], [3], [4] format_results() (src.query.QueryProcessor method), [1], [2], [3], [4]

G

generate() (src.llm.BaseLLM method), [1], [2], [3] (src.llm.LlamaCppLLM method), [1], [2], [3] (src.llm.OpenAILLM method), [1], [2], [3] (src.llm.TransformersLLM method), [1], [2], [3] generate_answer() (src.llm.LLMInterface method), [1], [2], [3] generate_answer_from_query() (in module src.llm), [1], [2], [3] generate_embeddings() (src.embed.EmbeddingModel method), [1], [2], [3] generate_single_embedding() (src.embed.EmbeddingModel method), [1], [2], [3]

generation_time_ms (src.llm.LLMResponse attribute), [1], [2], [3] get_chunk_by_index() (src.embed.FAISSIndex method), [1], [2], [3] get_index_stats() (src.embed.EmbeddingPipeline method), [1], [2], [3] (src.query.QueryEngine method), [1], [2], [3], [4] get_logger() (in module src.utils), [1], [2] get_model_info() (src.llm.LLMInterface method), [1], [2], [3] get_relevant_context() (src.query.QueryProcessor method), [1], [2], [3], [4] get_system_info() (in module src.utils), [1], [2] get_total_embeddings() (src.embed.FAISSIndex method), [1], [2], [3]

I

ingest_documents() (in module src.ingest), [1], [2], [3], [4] (src.ingest.DocumentIngester method), [1], [2], [3], [4]

L

LlamaCppLLM (class in src.llm), [1], [2], [3] LLMConfig (class in src.llm), [1], [2], [3] LLMInterface (class in src.llm), [1], [2], [3] LLMResponse (class in src.llm), [1], [2], [3] load_config() (in module main)

load_embedding_pipeline() (in module src.embed), [1], [2], [3] load_index() (src.embed.EmbeddingPipeline method), [1], [2], [3] (src.embed.FAISSIndex method), [1], [2], [3] log_memory_usage() (in module src.utils), [1], [2] log_performance() (in module src.utils), [1], [2] log_system_info() (in module src.utils), [1], [2]

M

main module main() (in module main) max_tokens (src.llm.LLMConfig attribute), [1], [2], [3] merge_config_with_args() (in module main) metadata (src.ingest.DocumentChunk attribute), [1], [2], [3], [4] model_name (src.embed.EmbeddingConfig attribute), [1], [2], [3] model_path (src.llm.LLMConfig attribute), [1], [2], [3]

model_used (src.llm.LLMResponse attribute), [1], [2], [3] module main src src.embed, [1], [2], [3] src.ingest, [1], [2], [3], [4] src.llm, [1], [2], [3] src.query, [1], [2], [3], [4] src.utils, [1], [2]

N

normalize_embeddings (src.embed.EmbeddingConfig attribute), [1], [2], [3]

O

OpenAILLM (class in src.llm), [1], [2], [3]

optimize_memory() (in module src.utils), [1], [2]

P

page_number (src.ingest.ChunkMetadata attribute), [1], [2], [3], [4] PDFProcessor (class in src.ingest), [1], [2], [3], [4] process_query() (in module src.query), [1], [2], [3], [4] (src.query.QueryProcessor method), [1], [2], [3], [4]

ProgressTracker (class in src.utils), [1], [2] prompt_tokens (src.llm.LLMResponse attribute), [1], [2], [3]

Q

query (src.query.QueryResult attribute), [1], [2], [3], [4] QueryEngine (class in src.query), [1], [2], [3], [4]

QueryProcessor (class in src.query), [1], [2], [3], [4] QueryResult (class in src.query), [1], [2], [3], [4]

R

repeat_penalty (src.llm.LLMConfig attribute), [1], [2], [3]

response_tokens (src.llm.LLMResponse attribute), [1], [2], [3]

S

save_chunks() (src.ingest.DocumentIngester method), [1], [2], [3], [4] save_index() (src.embed.EmbeddingPipeline method), [1], [2], [3] (src.embed.FAISSIndex method), [1], [2], [3] search() (src.embed.FAISSIndex method), [1], [2], [3] (src.query.QueryEngine method), [1], [2], [3], [4] search_similar_chunks() (src.embed.EmbeddingPipeline method), [1], [2], [3] search_time_ms (src.query.QueryResult attribute), [1], [2], [3], [4] setup_logging() (in module src.utils), [1], [2] similarities (src.query.QueryResult attribute), [1], [2], [3], [4] similarity_threshold (src.embed.EmbeddingConfig attribute), [1], [2], [3] src module

src.embed module, [1], [2], [3] src.ingest module, [1], [2], [3], [4] src.llm module, [1], [2], [3] src.query module, [1], [2], [3], [4] src.utils module, [1], [2]

T

temperature (src.llm.LLMConfig attribute), [1], [2], [3] text (src.ingest.DocumentChunk attribute), [1], [2], [3], [4] text_length (src.ingest.ChunkMetadata attribute), [1], [2], [3], [4] TextChunker (class in src.ingest), [1], [2], [3], [4]

TextCleaner (class in src.ingest), [1], [2], [3], [4] top_k (src.embed.EmbeddingConfig attribute), [1], [2], [3] top_p (src.llm.LLMConfig attribute), [1], [2], [3] total_chunks_searched (src.query.QueryResult attribute), [1], [2], [3], [4] TransformersLLM (class in src.llm), [1], [2], [3]

U

update() (src.utils.ProgressTracker method), [1], [2]

V

validate_index() (src.query.QueryEngine method), [1], [2], [3], [4]

validate_ingest_args() (in module main) validate_query_args() (in module main)