From 023e54e15736787224cf08007e2c8b26addc3c87 Mon Sep 17 00:00:00 2001 From: Danyil Date: Thu, 20 Jul 2023 16:36:03 +0200 Subject: [PATCH 01/16] skip header row for rdf requests --- aikg/utils/rdf.py | 4 ---- 1 file changed, 4 deletions(-) diff --git a/aikg/utils/rdf.py b/aikg/utils/rdf.py index d8f04d0..5b631de 100644 --- a/aikg/utils/rdf.py +++ b/aikg/utils/rdf.py @@ -147,10 +147,6 @@ def get_subjects_docs( ) docs = [] - # Skipping header row - if isinstance(kg, SPARQLWrapper): - results = results[1:] - for sub, label, comment in results: if comment is None: comment = "" From e3ded236f17b53f0be9d1a2a192224f7066e281e Mon Sep 17 00:00:00 2001 From: cmdoret Date: Mon, 22 Jan 2024 13:07:06 +0100 Subject: [PATCH 02/16] fix: update chromadb.API -> chromadb.ClientApi --- aikg/flows/chroma_build.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/aikg/flows/chroma_build.py b/aikg/flows/chroma_build.py index 44be035..d3fe0bf 100644 --- a/aikg/flows/chroma_build.py +++ b/aikg/flows/chroma_build.py @@ -30,7 +30,7 @@ from typing_extensions import Annotated import uuid -from chromadb.api import API, Collection +from chromadb.api import ClientAPI, Collection from dotenv import load_dotenv from langchain.schema import Document from more_itertools import chunked @@ -53,7 +53,7 @@ def init_chromadb( collection_name: str, embedding_model: str, persist_directory: str, -) -> Tuple[API, Collection]: +) -> Tuple[ClientAPI, Collection]: """Prepare chromadb client.""" client = akchroma.setup_client(host, port, persist_directory=persist_directory) coll = akchroma.setup_collection(client, collection_name, embedding_model) From 14185eb2e89f700e34821748b77bc0e9c311cb2d Mon Sep 17 00:00:00 2001 From: cmdoret Date: Mon, 22 Jan 2024 13:07:16 +0100 Subject: [PATCH 03/16] chore: update dep versions --- poetry.lock | 5638 +++++++++++++++++++++++++++--------------------- pyproject.toml | 4 +- 2 files changed, 3148 insertions(+), 2494 deletions(-) diff --git a/poetry.lock 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b/aikg/utils/chroma.py index dfdea1e..c461689 100644 --- a/aikg/utils/chroma.py +++ b/aikg/utils/chroma.py @@ -17,10 +17,10 @@ import chromadb from chromadb.config import Settings -from chromadb.api import API, Collection +from chromadb.api import ClientAPI, Collection -def setup_client(host: str, port: int, persist_directory: str = ".chroma") -> API: +def setup_client(host: str, port: int, persist_directory: str = ".chroma") -> ClientAPI: """Prepare chromadb client. 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Subject: [PATCH 05/16] feat(examples-draft): first draft to provide examples to prompt --- aikg/config/chroma.py | 3 + aikg/flows/chroma_examples.py | 154 ++++++++++++++++++++++++++++++++++ aikg/server.py | 18 +++- aikg/utils/chat.py | 17 ++++ 4 files changed, 191 insertions(+), 1 deletion(-) create mode 100644 aikg/flows/chroma_examples.py diff --git a/aikg/config/chroma.py b/aikg/config/chroma.py index ea919fd..f23a7cf 100644 --- a/aikg/config/chroma.py +++ b/aikg/config/chroma.py @@ -31,6 +31,8 @@ class ChromaConfig(BaseModel): The port of the ChromaDB server. collection_name: The name of the ChromaDB collection to store the index in. + collection_examples: + The name of the ChromaDB collection to store examples in. embedding_model_id: The HuggingFace ID of the embedding model to use. batch_size: @@ -42,6 +44,7 @@ class ChromaConfig(BaseModel): host: str = os.environ.get("CHROMA_HOST", "127.0.0.1") port: int = int(os.environ.get("CHROMA_PORT", "8000")) collection_name: str = os.environ.get("CHROMA_COLLECTION", "test") + collection_examples: str = os.environ.get("CHROMA_COLLECTION", "examples") batch_size: int = int(os.environ.get("CHROMA_BATCH_SIZE", "50")) embedding_model: str = os.environ.get("CHROMA_MODEL", "all-mpnet-base-v2") persist_directory: str = os.environ.get("CHROMA_PERSIST_DIR", ".chroma/") diff --git a/aikg/flows/chroma_examples.py b/aikg/flows/chroma_examples.py new file mode 100644 index 0000000..50fe312 --- /dev/null +++ b/aikg/flows/chroma_examples.py @@ -0,0 +1,154 @@ +# kg-llm-interface +# Copyright 2023 - Swiss Data Science Center (SDSC) +# A partnership between École Polytechnique Fédérale de Lausanne (EPFL) and +# Eidgenössische Technische Hochschule Zürich (ETHZ). +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +"""This flow builds a ChromaDB vector index from RDF data in a SPARQL endpoint. + +For each subject in the target graph, a document is generated. The document consists of: +* A human readable body made up of the annotations (rdfs:comment, rdf:label) associated with the subject. +* Triples with the subject attached as metadata. + +The documents are then stored in a vector database. The embedding is computed using the document body, +and triples included as metadata. The index is persisted to disk and can be subsequently loaded into memory +for querying.""" + +from pathlib import Path +from typing import Optional, Tuple +from typing_extensions import Annotated +import uuid + +from chromadb.api import ClientAPI, Collection +from dotenv import load_dotenv +from langchain.schema import Document +from more_itertools import chunked +from prefect import flow, task +from prefect import get_run_logger +from rdflib import ConjunctiveGraph, Graph +from SPARQLWrapper import SPARQLWrapper +import typer + +from aikg.config import ChromaConfig, SparqlConfig +from aikg.config.common import parse_yaml_config +import aikg.utils.rdf as akrdf +import aikg.utils.chroma as akchroma + + +@task +def init_chromadb( + host: str, + port: int, + collection_name: str, + embedding_model: str, + persist_directory: str, +) -> Tuple[ClientAPI, Collection]: + """Prepare chromadb client.""" + client = akchroma.setup_client(host, port, persist_directory=persist_directory) + coll = akchroma.setup_collection(client, collection_name, embedding_model) + + return client, coll + + +@task +def index_batch(batch: list[Document]): + """Sends a batch of document for indexing in the vector store""" + coll.add( + ids=[str(uuid.uuid4()) for _ in batch], + documents=[doc.page_content for doc in batch], + metadatas=[doc.metadata for doc in batch], + ) + + +@flow +def chroma_build_flow( + chroma_cfg: ChromaConfig = ChromaConfig(), + # sparql_cfg: SparqlConfig = SparqlConfig(), + # graph: Optional[str] = None, +): + """Build a ChromaDB vector index from RDF data in a SPARQL endpoint. + + Parameters + ---------- + chroma_cfg: + ChromaDB configuration. + """ + load_dotenv() + logger = get_run_logger() + logger.info("INFO Started") + # Connect to external resources + global coll + client, coll = init_chromadb( + chroma_cfg.host, + chroma_cfg.port, + chroma_cfg.collection_name, + chroma_cfg.embedding_model, + chroma_cfg.persist_directory, + ) + kg = akrdf.setup_kg( + sparql_cfg.endpoint, + user=sparql_cfg.user, + password=sparql_cfg.password, + ) + + # Create subject documents + docs = sparql_to_documents( + kg, + graph=graph, + ) + + # Vectorize and index documents by batches to reduce overhead + logger.info(f"Indexing by batches of {chroma_cfg.batch_size} items") + embed_counter = 0 + for batch in chunked(docs, chroma_cfg.batch_size): + embed_counter += len(batch) + index_batch(batch) + logger.info(f"Indexed {embed_counter} items.") + + +def cli( + chroma_cfg_path: Annotated[ + Optional[Path], + typer.Option(default=None, help="YAML file with Chroma client configuration."), + ] = None, + sparql_cfg_path: Annotated[ + Optional[Path], + typer.Option( + default=None, help="YAML file with SPARQL endpoint configuration." + ), + ] = None, + graph: Annotated[ + Optional[str], + typer.Option( + default=None, + help="URI of named graph from which to select triples to embed. If not set, the default graph is used.", + ), + ] = None, +): + """Command line wrapper for RDF to ChromaDB index flow.""" + chroma_cfg = ( + parse_yaml_config(chroma_cfg_path, ChromaConfig) + if chroma_cfg_path + else ChromaConfig() + ) + sparql_cfg = ( + parse_yaml_config(sparql_cfg_path, SparqlConfig) + if sparql_cfg_path + else SparqlConfig() + ) + chroma_build_flow(chroma_cfg, sparql_cfg, graph=graph) + + +if __name__ == "__main__": + typer.run(cli) diff --git a/aikg/server.py b/aikg/server.py index 2cb8500..a283874 100644 --- a/aikg/server.py +++ b/aikg/server.py @@ -32,7 +32,7 @@ from aikg.config import ChatConfig, ChromaConfig, SparqlConfig from aikg.config.common import parse_yaml_config from aikg.models import Conversation, Message -from aikg.utils.chat import generate_answer, generate_sparql +from aikg.utils.chat import generate_answer, generate_examples, generate_sparql from aikg.utils.llm import setup_llm_chain, setup_llm from aikg.utils.chroma import setup_collection, setup_client from aikg.utils.rdf import setup_kg, query_kg @@ -58,6 +58,11 @@ chroma_config.collection_name, chroma_config.embedding_model, ) +collection_examples = setup_collection( + client, + chroma_config.collection_examples, + chroma_config.embedding_model, +) llm = setup_llm(chat_config.model_id, chat_config.max_new_tokens) # For now, both chains share the same model to spare memory answer_chain = setup_llm_chain(llm, chat_config.answer_template) @@ -91,6 +96,17 @@ async def ask(question: str) -> Message: return Message(text=answer, sender="AI", time=datetime.now()) +@app.get("/examples/") +async def ask(question: str) -> Message: + """Generate examples from question + and return examples to prompt.""" + ... + examples = generate_examples(question, collection_examples, sparql_chain) + # results = query_kg(kg, query) + # answer = generate_answer(question, query, results, answer_chain) + return Message(text=examples, sender="AI", time=datetime.now()) + + @app.get("/sparql/") async def sparql(question: str) -> Message: """Generate and return sparql query from question.""" diff --git a/aikg/utils/chat.py b/aikg/utils/chat.py index 2da8179..0ff6122 100644 --- a/aikg/utils/chat.py +++ b/aikg/utils/chat.py @@ -71,6 +71,23 @@ def generate_sparql( return query +def generate_examples( + question: str, + collection: Collection, + limit: int = 5, +) -> str: + """Retrieve k-nearest examples from the vector store and return them.""" + + # Retrieve documents and triples from top k subjects + examples = collection.query(query_texts=question, n_results=limit) + # Extract triples and concatenate as a ntriples string + # triples = "\n".join([res.get("triples", "") for res in results["metadatas"][0]]) + # Convert to turtle for better readability and fewer tokens + # triples = Graph().parse(data=triples).serialize(format="turtle") + # query = llm_chain.run(question_str=question, context_str=triples) + return examples + + def generate_answer( question: str, query: str, From 8745471346796d917fba159b4e32958b251b7c7d Mon Sep 17 00:00:00 2001 From: Stefan Milosavljevic Date: Thu, 25 Jan 2024 11:20:44 +0100 Subject: [PATCH 06/16] feat(few-shot): implemented chromadb setup for examples questions and corresponding queries --- aikg/config/chroma.py | 2 +- aikg/flows/chroma_examples.py | 64 ++++++++++++----------------------- aikg/utils/chat.py | 35 ++++++++++++++----- aikg/utils/io.py | 28 +++++++++++++++ 4 files changed, 77 insertions(+), 52 deletions(-) diff --git a/aikg/config/chroma.py b/aikg/config/chroma.py index f23a7cf..f173bc0 100644 --- a/aikg/config/chroma.py +++ b/aikg/config/chroma.py @@ -43,7 +43,7 @@ class ChromaConfig(BaseModel): host: str = os.environ.get("CHROMA_HOST", "127.0.0.1") port: int = int(os.environ.get("CHROMA_PORT", "8000")) - collection_name: str = os.environ.get("CHROMA_COLLECTION", "test") + collection_name: str = os.environ.get("CHROMA_COLLECTION", "schema") collection_examples: str = os.environ.get("CHROMA_COLLECTION", "examples") batch_size: int = int(os.environ.get("CHROMA_BATCH_SIZE", "50")) embedding_model: str = os.environ.get("CHROMA_MODEL", "all-mpnet-base-v2") diff --git a/aikg/flows/chroma_examples.py b/aikg/flows/chroma_examples.py index 50fe312..804fa66 100644 --- a/aikg/flows/chroma_examples.py +++ b/aikg/flows/chroma_examples.py @@ -15,14 +15,14 @@ # See the License for the specific language governing permissions and # limitations under the License. -"""This flow builds a ChromaDB vector index from RDF data in a SPARQL endpoint. +"""This flow builds a ChromaDB vector index from examples including questions and corresponding SPARQL queries. For each subject in the target graph, a document is generated. The document consists of: -* A human readable body made up of the annotations (rdfs:comment, rdf:label) associated with the subject. -* Triples with the subject attached as metadata. +* A human readable body made up of human readable questions +* SPARQL queries attached as metadata. -The documents are then stored in a vector database. The embedding is computed using the document body, -and triples included as metadata. The index is persisted to disk and can be subsequently loaded into memory +The documents are then stored in a vector database. The embedding is computed using the document body (questions), +and SPAQRL queries included as metadata. The index is persisted to disk and can be subsequently loaded into memory for querying.""" from pathlib import Path @@ -36,13 +36,11 @@ from more_itertools import chunked from prefect import flow, task from prefect import get_run_logger -from rdflib import ConjunctiveGraph, Graph -from SPARQLWrapper import SPARQLWrapper import typer -from aikg.config import ChromaConfig, SparqlConfig +from aikg.config import ChromaConfig from aikg.config.common import parse_yaml_config -import aikg.utils.rdf as akrdf +import aikg.utils.io as akio import aikg.utils.chroma as akchroma @@ -72,12 +70,11 @@ def index_batch(batch: list[Document]): @flow -def chroma_build_flow( +def chroma_build_examples_flow( + chroma_input_dir: Path, chroma_cfg: ChromaConfig = ChromaConfig(), - # sparql_cfg: SparqlConfig = SparqlConfig(), - # graph: Optional[str] = None, ): - """Build a ChromaDB vector index from RDF data in a SPARQL endpoint. + """Build a ChromaDB vector index from examples. Parameters ---------- @@ -92,20 +89,14 @@ def chroma_build_flow( client, coll = init_chromadb( chroma_cfg.host, chroma_cfg.port, - chroma_cfg.collection_name, + chroma_cfg.collection_examples, chroma_cfg.embedding_model, chroma_cfg.persist_directory, ) - kg = akrdf.setup_kg( - sparql_cfg.endpoint, - user=sparql_cfg.user, - password=sparql_cfg.password, - ) # Create subject documents - docs = sparql_to_documents( - kg, - graph=graph, + docs = akio.get_sparql_examples( + input_path=chroma_input_dir, ) # Vectorize and index documents by batches to reduce overhead @@ -118,36 +109,25 @@ def chroma_build_flow( def cli( + chroma_input_dir: Annotated[ + Path, + typer.Argument( + default=None, + help="Path to directory with example SPARQL queries", + ), + ], chroma_cfg_path: Annotated[ Optional[Path], typer.Option(default=None, help="YAML file with Chroma client configuration."), ] = None, - sparql_cfg_path: Annotated[ - Optional[Path], - typer.Option( - default=None, help="YAML file with SPARQL endpoint configuration." - ), - ] = None, - graph: Annotated[ - Optional[str], - typer.Option( - default=None, - help="URI of named graph from which to select triples to embed. If not set, the default graph is used.", - ), - ] = None, ): - """Command line wrapper for RDF to ChromaDB index flow.""" + """Command line wrapper for SPARQL examples to ChromaDB index flow.""" chroma_cfg = ( parse_yaml_config(chroma_cfg_path, ChromaConfig) if chroma_cfg_path else ChromaConfig() ) - sparql_cfg = ( - parse_yaml_config(sparql_cfg_path, SparqlConfig) - if sparql_cfg_path - else SparqlConfig() - ) - chroma_build_flow(chroma_cfg, sparql_cfg, graph=graph) + chroma_build_examples_flow(chroma_input_dir, chroma_cfg) if __name__ == "__main__": diff --git a/aikg/utils/chat.py b/aikg/utils/chat.py index 0ff6122..a9c8a95 100644 --- a/aikg/utils/chat.py +++ b/aikg/utils/chat.py @@ -56,7 +56,11 @@ def post_process_answer(answer: str) -> str: def generate_sparql( - question: str, collection: Collection, llm_chain: LLMChain, limit: int = 5 + question: str, + examples: str, + collection: Collection, + llm_chain: LLMChain, + limit: int = 5, ) -> str: """Retrieve k-nearest documents from the vector store and synthesize SPARQL query.""" @@ -67,7 +71,12 @@ def generate_sparql( triples = "\n".join([res.get("triples", "") for res in results["metadatas"][0]]) # Convert to turtle for better readability and fewer tokens triples = Graph().parse(data=triples).serialize(format="turtle") - query = llm_chain.run(question_str=question, context_str=triples) + print(question) + print(triples) + print(examples) + query = llm_chain.run( + question_str=question, context_str=triples, examples_str=examples + ) return query @@ -76,16 +85,24 @@ def generate_examples( collection: Collection, limit: int = 5, ) -> str: - """Retrieve k-nearest examples from the vector store and return them.""" + """Retrieve k-nearest questions from the examples in the vector store and return them + together with their correponding query.""" # Retrieve documents and triples from top k subjects examples = collection.query(query_texts=question, n_results=limit) - # Extract triples and concatenate as a ntriples string - # triples = "\n".join([res.get("triples", "") for res in results["metadatas"][0]]) - # Convert to turtle for better readability and fewer tokens - # triples = Graph().parse(data=triples).serialize(format="turtle") - # query = llm_chain.run(question_str=question, context_str=triples) - return examples + # Extract relevant information from dict + example_docs = examples["documents"][0] + example_meta = examples["metadatas"][0] + # + example_prompt = "" + for doc, meta in zip(example_docs, example_meta): + example_prompt += f""" + Question: + {doc} + Query: + {meta['query']} + """ + return example_prompt def generate_answer( diff --git a/aikg/utils/io.py b/aikg/utils/io.py index b29bdc5..645ebe1 100644 --- a/aikg/utils/io.py +++ b/aikg/utils/io.py @@ -16,7 +16,10 @@ # limitations under the License. import requests +import os from pathlib import Path +from typing import List +from langchain.schema import Document from tqdm import tqdm @@ -31,3 +34,28 @@ def download_file(url: str, output_path: str | Path): for chunk in tqdm(response.iter_content(chunk_size=8192)): if chunk: f.write(chunk) + + +def get_sparql_examples(input_path: str | Path) -> List[Document]: + """ + Load SPARQL example query files with first line being the question (starting with #) + and the remaining lines being the query. We reformat this content into a document + where the page content is the question and the query is attached as metadata + """ + # loop through example files from the input and create a doc with all examples + examples_docs = [] + for file_name in os.listdir(input_path): + file_path = os.path.join(input_path, file_name) + with open(file_path) as f: + examples_temp = [] + examples_temp.append(f.read()) + # Splitting the file content into lines + lines = examples_temp[0].split("\n") + # Extracting the question (removing '#' from the first line) + question = lines[0].strip()[1:] + # Extracting the SPARQL query from the remaining lines + sparql_query = "\n".join(lines[1:]) + examples_docs.append( + Document(page_content=question, metadata={"query": sparql_query}) + ) + return examples_docs From ed14f6e768c39679ab48bec9c8d30fe81af059e3 Mon Sep 17 00:00:00 2001 From: supermaxiste Date: Mon, 5 Feb 2024 13:18:04 +0100 Subject: [PATCH 07/16] fix: example env variable name Co-authored-by: Cyril Matthey-Doret --- aikg/config/chroma.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/aikg/config/chroma.py b/aikg/config/chroma.py index f173bc0..acf7c3a 100644 --- a/aikg/config/chroma.py +++ b/aikg/config/chroma.py @@ -44,7 +44,7 @@ class ChromaConfig(BaseModel): host: str = os.environ.get("CHROMA_HOST", "127.0.0.1") port: int = int(os.environ.get("CHROMA_PORT", "8000")) collection_name: str = os.environ.get("CHROMA_COLLECTION", "schema") - collection_examples: str = os.environ.get("CHROMA_COLLECTION", "examples") + collection_examples: str = os.environ.get("CHROMA_EXAMPLES", "examples") batch_size: int = int(os.environ.get("CHROMA_BATCH_SIZE", "50")) embedding_model: str = os.environ.get("CHROMA_MODEL", "all-mpnet-base-v2") persist_directory: str = os.environ.get("CHROMA_PERSIST_DIR", ".chroma/") From 4b3cf6a6f7bb2a9dfdcc2db6f11b38498931ae61 Mon Sep 17 00:00:00 2001 From: supermaxiste Date: Mon, 5 Feb 2024 13:18:28 +0100 Subject: [PATCH 08/16] suggestion(style): emphasis on pairs Co-authored-by: Cyril Matthey-Doret --- aikg/flows/chroma_examples.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/aikg/flows/chroma_examples.py b/aikg/flows/chroma_examples.py index 804fa66..40996fc 100644 --- a/aikg/flows/chroma_examples.py +++ b/aikg/flows/chroma_examples.py @@ -15,7 +15,7 @@ # See the License for the specific language governing permissions and # limitations under the License. -"""This flow builds a ChromaDB vector index from examples including questions and corresponding SPARQL queries. +"""This flow builds a ChromaDB vector index from examples consisting of pairs of questions and SPARQL queries. For each subject in the target graph, a document is generated. The document consists of: * A human readable body made up of human readable questions From 6b361238b0af307f58725a4b91f89bf84d759804 Mon Sep 17 00:00:00 2001 From: supermaxiste Date: Mon, 5 Feb 2024 13:24:51 +0100 Subject: [PATCH 09/16] fix: add document input dir parameter Co-authored-by: Cyril Matthey-Doret --- aikg/flows/chroma_examples.py | 2 ++ 1 file changed, 2 insertions(+) diff --git a/aikg/flows/chroma_examples.py b/aikg/flows/chroma_examples.py index 40996fc..ef02dbe 100644 --- a/aikg/flows/chroma_examples.py +++ b/aikg/flows/chroma_examples.py @@ -78,6 +78,8 @@ def chroma_build_examples_flow( Parameters ---------- + chroma_input_dir: + Directory containing files with example question-query pairs. The files should be in sparql format, with the first line being the question as a comment. chroma_cfg: ChromaDB configuration. """ From 9cea0b1c90ed485f8e782d22ca08d1611e8966cb Mon Sep 17 00:00:00 2001 From: supermaxiste Date: Mon, 5 Feb 2024 13:30:23 +0100 Subject: [PATCH 10/16] feat: add path validation options to chroma input_dir Co-authored-by: Cyril Matthey-Doret --- aikg/flows/chroma_examples.py | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/aikg/flows/chroma_examples.py b/aikg/flows/chroma_examples.py index ef02dbe..a72382a 100644 --- a/aikg/flows/chroma_examples.py +++ b/aikg/flows/chroma_examples.py @@ -114,8 +114,10 @@ def cli( chroma_input_dir: Annotated[ Path, typer.Argument( - default=None, help="Path to directory with example SPARQL queries", + exists=True, + file_okay=False, + dir_okay=True, ), ], chroma_cfg_path: Annotated[ From 8130850abb92f822c61c1095b12084abb09b449e Mon Sep 17 00:00:00 2001 From: supermaxiste Date: Mon, 5 Feb 2024 13:30:45 +0100 Subject: [PATCH 11/16] chore: remove commented code Co-authored-by: Cyril Matthey-Doret --- aikg/server.py | 2 -- 1 file changed, 2 deletions(-) diff --git a/aikg/server.py b/aikg/server.py index a283874..5add0f8 100644 --- a/aikg/server.py +++ b/aikg/server.py @@ -102,8 +102,6 @@ async def ask(question: str) -> Message: and return examples to prompt.""" ... examples = generate_examples(question, collection_examples, sparql_chain) - # results = query_kg(kg, query) - # answer = generate_answer(question, query, results, answer_chain) return Message(text=examples, sender="AI", time=datetime.now()) From 074176f865746ff615e0c1e771ac7a8b61d46037 Mon Sep 17 00:00:00 2001 From: supermaxiste Date: Mon, 5 Feb 2024 13:31:06 +0100 Subject: [PATCH 12/16] fix: drop debugging print statement Co-authored-by: Cyril Matthey-Doret --- aikg/utils/chat.py | 3 --- 1 file changed, 3 deletions(-) diff --git a/aikg/utils/chat.py b/aikg/utils/chat.py index a9c8a95..e1bd35e 100644 --- a/aikg/utils/chat.py +++ b/aikg/utils/chat.py @@ -71,9 +71,6 @@ def generate_sparql( triples = "\n".join([res.get("triples", "") for res in results["metadatas"][0]]) # Convert to turtle for better readability and fewer tokens triples = Graph().parse(data=triples).serialize(format="turtle") - print(question) - print(triples) - print(examples) query = llm_chain.run( question_str=question, context_str=triples, examples_str=examples ) From 537a9af78ce608b283f44f740633db4d95efe94c Mon Sep 17 00:00:00 2001 From: Stefan Milosavljevic Date: Mon, 5 Feb 2024 14:35:55 +0100 Subject: [PATCH 13/16] refactor: make parser for examples more flexible --- aikg/flows/chroma_examples.py | 22 ++++++++++++++----- aikg/utils/io.py | 41 ++++++++++++++++------------------- 2 files changed, 36 insertions(+), 27 deletions(-) diff --git a/aikg/flows/chroma_examples.py b/aikg/flows/chroma_examples.py index a72382a..52f85bd 100644 --- a/aikg/flows/chroma_examples.py +++ b/aikg/flows/chroma_examples.py @@ -29,6 +29,7 @@ from typing import Optional, Tuple from typing_extensions import Annotated import uuid +import os from chromadb.api import ClientAPI, Collection from dotenv import load_dotenv @@ -69,6 +70,16 @@ def index_batch(batch: list[Document]): ) +@task +def get_sparql_examples(dir: Path) -> list[Document]: + # find files + files = [] + for file_name in os.listdir(dir): + files.append(os.path.join(dir, file_name)) + # provide each file as text stream to be parsed + return [akio.parse_sparql_example(open(ex)) for ex in files] + + @flow def chroma_build_examples_flow( chroma_input_dir: Path, @@ -97,16 +108,17 @@ def chroma_build_examples_flow( ) # Create subject documents - docs = akio.get_sparql_examples( - input_path=chroma_input_dir, + docs = get_sparql_examples( + dir=chroma_input_dir, ) # Vectorize and index documents by batches to reduce overhead logger.info(f"Indexing by batches of {chroma_cfg.batch_size} items") embed_counter = 0 - for batch in chunked(docs, chroma_cfg.batch_size): - embed_counter += len(batch) - index_batch(batch) + for doc in docs: + for batch in chunked(doc, chroma_cfg.batch_size): + embed_counter += len(batch) + index_batch(batch) logger.info(f"Indexed {embed_counter} items.") diff --git a/aikg/utils/io.py b/aikg/utils/io.py index 645ebe1..693d5eb 100644 --- a/aikg/utils/io.py +++ b/aikg/utils/io.py @@ -18,9 +18,8 @@ import requests import os from pathlib import Path -from typing import List +from typing import List, TextIO from langchain.schema import Document - from tqdm import tqdm @@ -36,26 +35,24 @@ def download_file(url: str, output_path: str | Path): f.write(chunk) -def get_sparql_examples(input_path: str | Path) -> List[Document]: +def parse_sparql_example(example: TextIO) -> List[Document]: """ - Load SPARQL example query files with first line being the question (starting with #) - and the remaining lines being the query. We reformat this content into a document + Parse a text stream as input with first line being a question (starting with #) + and the remaining lines being a (SPARQL) query. We reformat this content into a document where the page content is the question and the query is attached as metadata """ - # loop through example files from the input and create a doc with all examples - examples_docs = [] - for file_name in os.listdir(input_path): - file_path = os.path.join(input_path, file_name) - with open(file_path) as f: - examples_temp = [] - examples_temp.append(f.read()) - # Splitting the file content into lines - lines = examples_temp[0].split("\n") - # Extracting the question (removing '#' from the first line) - question = lines[0].strip()[1:] - # Extracting the SPARQL query from the remaining lines - sparql_query = "\n".join(lines[1:]) - examples_docs.append( - Document(page_content=question, metadata={"query": sparql_query}) - ) - return examples_docs + # Create temp variable to process text stream + example_temp = [] + example_temp.append(example.read()) + # Splitting the file content into lines + lines = example_temp[0].split("\n") + # Extracting the question (removing '#' from the first line) + question = lines[0].strip()[1:] + # Extracting the SPARQL query from the remaining lines + sparql_query = "\n".join(lines[1:]) + # Create example document for the output + example_doc = [] + example_doc.append( + Document(page_content=question, metadata={"query": sparql_query}) + ) + return example_doc From 60a9afac539b0ece9425d8d78c9077b6043f2f54 Mon Sep 17 00:00:00 2001 From: Stefan Milosavljevic Date: Mon, 19 Feb 2024 09:23:52 +0100 Subject: [PATCH 14/16] fix(examples): examples optional and improved looping --- aikg/config/chat.py | 1 + aikg/flows/chroma_examples.py | 11 +++++------ aikg/utils/chat.py | 4 ++-- 3 files changed, 8 insertions(+), 8 deletions(-) diff --git a/aikg/config/chat.py b/aikg/config/chat.py index aabb415..eea9f8f 100644 --- a/aikg/config/chat.py +++ b/aikg/config/chat.py @@ -62,6 +62,7 @@ class ChatConfig(BaseModel): When generating sparql: * Never enclose the sparql in back-quotes +{examples_str} Use the following format: diff --git a/aikg/flows/chroma_examples.py b/aikg/flows/chroma_examples.py index 52f85bd..8adf1a3 100644 --- a/aikg/flows/chroma_examples.py +++ b/aikg/flows/chroma_examples.py @@ -18,8 +18,8 @@ """This flow builds a ChromaDB vector index from examples consisting of pairs of questions and SPARQL queries. For each subject in the target graph, a document is generated. The document consists of: -* A human readable body made up of human readable questions -* SPARQL queries attached as metadata. +* A human readable question (document body) +* A corresponding SPARQL query (document metadata) The documents are then stored in a vector database. The embedding is computed using the document body (questions), and SPAQRL queries included as metadata. The index is persisted to disk and can be subsequently loaded into memory @@ -115,10 +115,9 @@ def chroma_build_examples_flow( # Vectorize and index documents by batches to reduce overhead logger.info(f"Indexing by batches of {chroma_cfg.batch_size} items") embed_counter = 0 - for doc in docs: - for batch in chunked(doc, chroma_cfg.batch_size): - embed_counter += len(batch) - index_batch(batch) + for batch in chunked(docs, 2): + embed_counter += len(batch) + index_batch(batch) logger.info(f"Indexed {embed_counter} items.") diff --git a/aikg/utils/chat.py b/aikg/utils/chat.py index e1bd35e..f0de767 100644 --- a/aikg/utils/chat.py +++ b/aikg/utils/chat.py @@ -57,9 +57,9 @@ def post_process_answer(answer: str) -> str: def generate_sparql( question: str, - examples: str, collection: Collection, llm_chain: LLMChain, + examples: str = "", limit: int = 5, ) -> str: """Retrieve k-nearest documents from the vector store and synthesize @@ -91,7 +91,7 @@ def generate_examples( example_docs = examples["documents"][0] example_meta = examples["metadatas"][0] # - example_prompt = "" + example_prompt = "Examples: \n\n" for doc, meta in zip(example_docs, example_meta): example_prompt += f""" Question: From c25f6dfdb28abb4d84277f03bd0edd1a4f36e18a Mon Sep 17 00:00:00 2001 From: Stefan Milosavljevic Date: Mon, 19 Feb 2024 09:39:15 +0100 Subject: [PATCH 15/16] fix(loop): restored chunk loop and added internal loop --- aikg/flows/chroma_examples.py | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/aikg/flows/chroma_examples.py b/aikg/flows/chroma_examples.py index 8adf1a3..1b48bbc 100644 --- a/aikg/flows/chroma_examples.py +++ b/aikg/flows/chroma_examples.py @@ -115,9 +115,10 @@ def chroma_build_examples_flow( # Vectorize and index documents by batches to reduce overhead logger.info(f"Indexing by batches of {chroma_cfg.batch_size} items") embed_counter = 0 - for batch in chunked(docs, 2): + for batch in chunked(docs, chroma_cfg.batch_size): embed_counter += len(batch) - index_batch(batch) + for doc in batch: + index_batch(doc) logger.info(f"Indexed {embed_counter} items.") From 23d98c8468a756cdfba429b4179a346472ae0cbf Mon Sep 17 00:00:00 2001 From: Stefan Milosavljevic Date: Wed, 28 Feb 2024 14:46:00 +0100 Subject: [PATCH 16/16] fix: get_sparql_example returns a doc instead of a list with doc --- aikg/flows/chroma_examples.py | 3 +-- aikg/utils/io.py | 5 +---- 2 files changed, 2 insertions(+), 6 deletions(-) diff --git a/aikg/flows/chroma_examples.py b/aikg/flows/chroma_examples.py index 1b48bbc..7111956 100644 --- a/aikg/flows/chroma_examples.py +++ b/aikg/flows/chroma_examples.py @@ -117,8 +117,7 @@ def chroma_build_examples_flow( embed_counter = 0 for batch in chunked(docs, chroma_cfg.batch_size): embed_counter += len(batch) - for doc in batch: - index_batch(doc) + index_batch(docs) logger.info(f"Indexed {embed_counter} items.") diff --git a/aikg/utils/io.py b/aikg/utils/io.py index 693d5eb..ccf23d1 100644 --- a/aikg/utils/io.py +++ b/aikg/utils/io.py @@ -51,8 +51,5 @@ def parse_sparql_example(example: TextIO) -> List[Document]: # Extracting the SPARQL query from the remaining lines sparql_query = "\n".join(lines[1:]) # Create example document for the output - example_doc = [] - example_doc.append( - Document(page_content=question, metadata={"query": sparql_query}) - ) + example_doc = Document(page_content=question, metadata={"query": sparql_query}) return example_doc