Add support for kdbai

medirag/index/kdbai.py

@@ -0,0 +1,63 @@
+from llama_index.core import VectorStoreIndex, StorageContext, Settings, load_index_from_storage
+from llama_index.core.node_parser import SentenceSplitter, SemanticSplitterNodeParser
+from llama_index.embeddings.huggingface import HuggingFaceEmbedding
+from llama_index.vector_stores.kdbai import KDBAIVectorStore
+import kdbai_client as kdbai
+import os
+
+
+class DailyMedIndexer:
+    def __init__(self, model_name="nuvocare/WikiMedical_sent_biobert"):
+        self.model_name = model_name
+        self._initialize_embedding_model()
+        self.session = kdbai.Session(api_key=os.getenv('KDBAI_API_KEY'),
+                                     endpoint=os.getenv('KDBAI_ENDPOINT'))
+        self.vector_store = KDBAIVectorStore(self.session.table("daily_med"))
+        self.vector_store_index = None
+
+    def _initialize_embedding_model(self):
+        # Initialize the embedding model
+        embed_model = HuggingFaceEmbedding(model_name=self.model_name)
+        Settings.embed_model = embed_model
+
+    def load_index(self, documents=None):
+        """
+        Load the index from existing storage or create a new one from provided documents.
+        """
+        self._initialize_embedding_model()
+
+        if documents:
+            return self._build_index_from_documents(documents)
+        else:
+            return self._load_existing_index()
+
+    def _build_index_from_documents(self, documents):
+        print("Building index from documents...")
+
+        storage_context = StorageContext.from_defaults(vector_store=self.vector_store)
+        chunk = SemanticSplitterNodeParser(buffer_size=1, breakpoint_percentile_threshold=95,
+                                           embed_model=Settings.embed_model)
+        self.vector_store_index = VectorStoreIndex.from_documents(
+            documents,
+            storage_context=storage_context,
+            transformations=[chunk]
+        )
+        return self.vector_store_index
+
+    def _load_existing_index(self):
+        try:
+            print("Loading index from storage context...")
+            self.vector_store_index = VectorStoreIndex.from_vector_store(self.vector_store)
+            return self.vector_store_index
+        except Exception as e:
+            raise ValueError(f"Failed to load index from storage context: {e}")
+
+    def retrieve(self, query, top_k=3):
+        """
+        Retrieve the top-k results based on the query.
+        """
+        if not self.vector_store_index:
+            raise ValueError("Vector store is not initialized. Please index documents first.")
+
+        retriever = self.vector_store_index.as_retriever(similarity_top_k=top_k)
+        return retriever.retrieve(query)

misc/create_kdbai_table.py

@@ -0,0 +1,29 @@
+import os
+
+from dotenv import load_dotenv
+
+load_dotenv()
+
+import kdbai_client as kdbai
+
+session = kdbai.Session(api_key=os.getenv('KDBAI_API_KEY'), endpoint=os.getenv('KDBAI_ENDPOINT'))
+
+schema = dict(
+    columns=[
+        dict(name="document_id", pytype="bytes"),
+        dict(name="text", pytype="bytes"),
+        dict(
+            name="embedding",
+            vectorIndex=dict(type="flat", metric="L2", dims=768),
+        ),
+    ]
+)
+
+KDBAI_TABLE_NAME = "daily_med"
+
+# First ensure the table does not already exist
+if KDBAI_TABLE_NAME in session.list():
+    session.table(KDBAI_TABLE_NAME).drop()
+
+# Create the table
+table = session.create_table(KDBAI_TABLE_NAME, schema)

poetry.lock

@@ -1561,6 +1561,25 @@ files = [
     {file = "jsonpointer-3.0.0.tar.gz", hash = "sha256:2b2d729f2091522d61c3b31f82e11870f60b68f43fbc705cb76bf4b832af59ef"},
 ]
 
+[[package]]
+name = "kdbai-client"
+version = "1.2.4"
+description = "KDB.AI Client for Python"
+optional = false
+python-versions = "<4.0,>=3.8"
+files = [
+    {file = "kdbai_client-1.2.4-py3-none-any.whl", hash = "sha256:cf5043e2d0033186a25bce566901db96d98053d764f01d2d0b32d03b188e5584"},
+]
+
+[package.dependencies]
+pandas = ">=1.5.0"
+pykx = ">=2.1.1,<3.0.0"
+requests = "*"
+
+[package.extras]
+lint = ["mypy", "mypy-gitlab-code-quality"]
+test = ["pytest (>=7.3.2,<8.0.0)", "pytest-cov (>=4.0.0,<5.0.0)", "pytest-mock"]
+
 [[package]]
 name = "kiwisolver"
 version = "1.4.5"
@@ -1676,19 +1695,19 @@ files = [
 
 [[package]]
 name = "langchain"
-version = "0.2.14"
+version = "0.2.15"
 description = "Building applications with LLMs through composability"
 optional = false
 python-versions = "<4.0,>=3.8.1"
 files = [
-    {file = "langchain-0.2.14-py3-none-any.whl", hash = "sha256:eed76194ee7d9c081037a3df7868d4de90e0410b51fc1ca933a8379e464bf40c"},
-    {file = "langchain-0.2.14.tar.gz", hash = "sha256:dc2aa5a58882054fb5d043c39ab8332ebd055f88f17839da68e1c7fd0a4fefe2"},
+    {file = "langchain-0.2.15-py3-none-any.whl", hash = "sha256:9e6231441870aaa8523be24a5785ccccfdde759a7e27dd082b6ec80f68e49dec"},
+    {file = "langchain-0.2.15.tar.gz", hash = "sha256:f613ce7594be34f9bac687134a56f6e8274951907b798dbd037aefc95df78953"},
 ]
 
 [package.dependencies]
 aiohttp = ">=3.8.3,<4.0.0"
 async-timeout = {version = ">=4.0.0,<5.0.0", markers = "python_version < \"3.11\""}
-langchain-core = ">=0.2.32,<0.3.0"
+langchain-core = ">=0.2.35,<0.3.0"
 langchain-text-splitters = ">=0.2.0,<0.3.0"
 langsmith = ">=0.1.17,<0.2.0"
 numpy = [
@@ -1703,13 +1722,13 @@ tenacity = ">=8.1.0,<8.4.0 || >8.4.0,<9.0.0"
 
 [[package]]
 name = "langchain-core"
-version = "0.2.35"
+version = "0.2.36"
 description = "Building applications with LLMs through composability"
 optional = false
 python-versions = "<4.0,>=3.8.1"
 files = [
-    {file = "langchain_core-0.2.35-py3-none-any.whl", hash = "sha256:e994fb8598e919842205824836a584243c1fb7f44268f6f14921c529667c4e6e"},
-    {file = "langchain_core-0.2.35.tar.gz", hash = "sha256:da8f51355a4a285345c41a3232fd0f1cc3a33726eb7b3557b753ffabfeb68b3f"},
+    {file = "langchain_core-0.2.36-py3-none-any.whl", hash = "sha256:eabce6e7538cb9dc60db4bc1eb584bbb91a5e7e02a96d5b65b4a6ab151081b6d"},
+    {file = "langchain_core-0.2.36.tar.gz", hash = "sha256:56f2367070e8afc43922bba1d046035a144b4e732a5474676403bd0eb33d85f2"},
 ]
 
 [package.dependencies]
@@ -1740,13 +1759,13 @@ langchain-core = ">=0.2.10,<0.3.0"
 
 [[package]]
 name = "langsmith"
-version = "0.1.105"
+version = "0.1.106"
 description = "Client library to connect to the LangSmith LLM Tracing and Evaluation Platform."
 optional = false
 python-versions = "<4.0,>=3.8.1"
 files = [
-    {file = "langsmith-0.1.105-py3-none-any.whl", hash = "sha256:a0098d0bc60ee79792109b0c1fef8252e21fd2dc424f4d902b8d9eb75160438b"},
-    {file = "langsmith-0.1.105.tar.gz", hash = "sha256:a8717ef90f3f740c202aa6878da89d4581ff28998336b48b831a92b855c460c3"},
+    {file = "langsmith-0.1.106-py3-none-any.whl", hash = "sha256:a418161c98de72ee2c6eea6667c6217814b67db4b9a3a024788013384216ff35"},
+    {file = "langsmith-0.1.106.tar.gz", hash = "sha256:64a890a05640d64692f5515ebb444b0457332a9cf9e7605c4651de6737a7d3a0"},
 ]
 
 [package.dependencies]
@@ -1776,13 +1795,13 @@ openai = ">=1.14.0"
 
 [[package]]
 name = "llama-index-core"
-version = "0.11.1"
+version = "0.11.2"
 description = "Interface between LLMs and your data"
 optional = false
 python-versions = "<4.0,>=3.8.1"
 files = [
-    {file = "llama_index_core-0.11.1-py3-none-any.whl", hash = "sha256:7d86c72be272c13f2c8fd5c62f27aba08a38e23cc5d28e02509d69909859102d"},
-    {file = "llama_index_core-0.11.1.tar.gz", hash = "sha256:5c8b5cb1313866ff38ce91bea53a72519a52c9dabc0ca9d5c8b63aa8d3b2dd23"},
+    {file = "llama_index_core-0.11.2-py3-none-any.whl", hash = "sha256:6c55667c4943ba197199e21e9b0e4641449f5e5dca662b0c91f5306f8c114e4f"},
+    {file = "llama_index_core-0.11.2.tar.gz", hash = "sha256:eec37976fe3b1baa3bb31bd3c5f6ea821555c7065ac6a55b71b5601a7e097977"},
 ]
 
 [package.dependencies]
@@ -1824,6 +1843,21 @@ huggingface-hub = {version = ">=0.19.0", extras = ["inference"]}
 llama-index-core = ">=0.11.0,<0.12.0"
 sentence-transformers = ">=2.6.1"
 
+[[package]]
+name = "llama-index-embeddings-openai"
+version = "0.2.3"
+description = "llama-index embeddings openai integration"
+optional = false
+python-versions = "<4.0,>=3.8.1"
+files = [
+    {file = "llama_index_embeddings_openai-0.2.3-py3-none-any.whl", hash = "sha256:be7d2aad0884e54d291af786b23d2feb7770cd1c3950f0de1fd5e36c60d83c06"},
+    {file = "llama_index_embeddings_openai-0.2.3.tar.gz", hash = "sha256:2f7adef6b61fd4f1bea487166ff9a5ff063227686b7dbb5d2227e46450a7ec4c"},
+]
+
+[package.dependencies]
+llama-index-core = ">=0.11.0,<0.12.0"
+openai = ">=1.1.0"
+
 [[package]]
 name = "llama-index-llms-openai"
 version = "0.2.0"
@@ -1889,6 +1923,23 @@ files = [
 [package.dependencies]
 llama-index-core = ">=0.11.0,<0.12.0"
 
+[[package]]
+name = "llama-index-vector-stores-kdbai"
+version = "0.3.1"
+description = "llama-index vector_stores kdbai integration"
+optional = false
+python-versions = "<4.0,>=3.8.1"
+files = [
+    {file = "llama_index_vector_stores_kdbai-0.3.1-py3-none-any.whl", hash = "sha256:cb3f6fb793337d2b5bf0a83a7c2e242f92210d5dba20335bc16b0d9f6862df83"},
+    {file = "llama_index_vector_stores_kdbai-0.3.1.tar.gz", hash = "sha256:06067e5fda5330f2527f448981592dbeaf14cd1895a44b04a760efc70fa5f8cf"},
+]
+
+[package.dependencies]
+kdbai-client = ">=1.1.0"
+llama-index-core = ">=0.11.0,<0.12.0"
+pandas = "*"
+pykx = ">=2.1.1,<3.0.0"
+
 [[package]]
 name = "lxml"
 version = "5.3.0"
@@ -2861,76 +2912,71 @@ files = [
 
 [[package]]
 name = "pandas"
-version = "2.2.2"
+version = "2.1.4"
 description = "Powerful data structures for data analysis, time series, and statistics"
 optional = false
 python-versions = ">=3.9"
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 ]
 
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 python-dateutil = ">=2.8.2"
 pytz = ">=2020.1"
-tzdata = ">=2022.7"
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 test = ["hypothesis (>=6.46.1)", "pytest (>=7.3.2)", "pytest-xdist (>=2.2.0)"]
-xml = ["lxml (>=4.9.2)"]
+xml = ["lxml (>=4.8.0)"]
 
 [[package]]
 name = "parso"
@@ -3371,6 +3417,59 @@ files = [
 [package.extras]
 windows-terminal = ["colorama (>=0.4.6)"]
 
+[[package]]
+name = "pykx"
+version = "2.5.3"
+description = "An interface between Python and q"
+optional = false
+python-versions = ">=3.7"
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+
+[package.dependencies]
+numpy = [
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+    {version = ">=1.23,<2.0", markers = "python_version == \"3.11\""},
+    {version = ">=1.26,<2.0", markers = "python_version == \"3.12\""},
+]
+pandas = ">=1.2,<2.2.0"
+pytz = ">=2022.1"
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+
+[package.extras]
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+beta = ["dill (>=0.2.0)"]
+dashboards = ["ast2json (>=0.3,<1.0)"]
+debug = ["find-libpython (>=0.2,<1.0)"]
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+lint = ["flake8 (==4.0.1)", "flake8-bugbear (==22.1.11)", "flake8-colors (==0.1.9)", "flake8-docstrings (==1.6.0)", "flake8-import-order (==0.18.1)", "pep8-naming (==0.12.1)", "pyproject-flake8 (==0.0.1a2)"]
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+streamlit = ["streamlit (>=1.28,<2.0)"]
+test = ["Cython (>=3.0.0,<3.1.0)", "coverage[toml] (==6.3.2)", "plotly (==5.10.0)", "psutil (==5.9.5)", "pytest (==7.1.2)", "pytest-asyncio (==0.18.3)", "pytest-benchmark (==3.4.1)", "pytest-cov (==3.0.0)", "pytest-monitor (==1.6.5)", "pytest-order (==1.1.0)", "pytest-randomly (==3.11.0)", "pytest-timeout (>=2.0.0)", "pytest-xdist (==2.5.0)"]
+
 [[package]]
 name = "pyparsing"
 version = "3.1.4"
@@ -4440,6 +4539,17 @@ dev = ["tokenizers[testing]"]
 docs = ["setuptools-rust", "sphinx", "sphinx-rtd-theme"]
 testing = ["black (==22.3)", "datasets", "numpy", "pytest", "requests", "ruff"]
 
+[[package]]
+name = "toml"
+version = "0.10.2"
+description = "Python Library for Tom's Obvious, Minimal Language"
+optional = false
+python-versions = ">=2.6, !=3.0.*, !=3.1.*, !=3.2.*"
+files = [
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+    {file = "toml-0.10.2.tar.gz", hash = "sha256:b3bda1d108d5dd99f4a20d24d9c348e91c4db7ab1b749200bded2f839ccbe68f"},
+]
+
 [[package]]
 name = "tomli"
 version = "2.0.1"
@@ -5260,4 +5370,4 @@ multidict = ">=4.0"
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.10,<3.13"
-content-hash = "45accb38e74b5646d74896c8545504072d577c8a87b71d379753672353e613be"
+content-hash = "5b9906edba328df0ad2bee1ebaeae3dd1bf5f8a9c0b52a6ab026e9fbe87105cb"

pyproject.toml

@@ -7,27 +7,30 @@ readme = "README.md"
 
 [tool.poetry.dependencies]
 python = ">=3.10,<3.13"
-llama-index-core = ">=0.11.1"
+llama-index-core = ">=0.11.2"
 llama-index-readers-file = ">=0.2.0"
 llama-index-vector-stores-faiss = ">=0.2.1"
 llama-index-utils-workflow = ">=0.2.0"
 llama-index-embeddings-huggingface = ">=0.3.1"
 llama-index-llms-openai = ">=0.2.0"
-beautifulsoup4 = "^4.12.3"
-lxml = "^5.3.0"
-langchain = ">=0.2.14"
-faiss-cpu = "^1.8.0.post1"
-sentence-transformers = "^3.0.1"
-tqdm = "^4.66.5"
-transformers = "^4.44.2"
-torch = "^2.4.0"
+llama-index-agent-openai = ">=0.3.0"
+llama-index-vector-stores-kdbai = ">=0.3.1"
+llama-index-embeddings-openai = ">=0.2.3"
+beautifulsoup4 = ">=4.12.3"
+lxml = ">=5.3.0"
+langchain = ">=0.2.15"
+faiss-cpu = ">=1.8.0.post1"
+sentence-transformers = ">=3.0.1"
+tqdm = ">=4.66.5"
+transformers = ">=4.44.2"
+torch = ">=2.4.0"
 nltk = ">=3.9.1"
-dspy-ai = "^2.4.13"
-python-dotenv = "^1.0.1"
-accelerate = "^0.33.0"
-gradio = "^4.42.0"
-pydantic = "^2.8.2"
-llama-index-agent-openai = "^0.3.0"
+dspy-ai = ">=2.4.13"
+python-dotenv = ">=1.0.1"
+accelerate = ">=0.33.0"
+gradio = ">=4.42.0"
+pydantic = ">=2.8.2"
+kdbai-client = ">=1.2.4"
 
 
 

requirements.txt

@@ -54,18 +54,21 @@ joblib==1.4.2 ; python_version >= "3.10" and python_version < "3.13"
 jsonpatch==1.33 ; python_version >= "3.10" and python_version < "3.13"
 jsonpickle==3.2.2 ; python_version >= "3.10" and python_version < "3.13"
 jsonpointer==3.0.0 ; python_version >= "3.10" and python_version < "3.13"
+kdbai-client==1.2.4 ; python_version >= "3.10" and python_version < "3.13"
 kiwisolver==1.4.5 ; python_version >= "3.10" and python_version < "3.13"
-langchain-core==0.2.35 ; python_version >= "3.10" and python_version < "3.13"
+langchain-core==0.2.36 ; python_version >= "3.10" and python_version < "3.13"
 langchain-text-splitters==0.2.2 ; python_version >= "3.10" and python_version < "3.13"
-langchain==0.2.14 ; python_version >= "3.10" and python_version < "3.13"
-langsmith==0.1.105 ; python_version >= "3.10" and python_version < "3.13"
+langchain==0.2.15 ; python_version >= "3.10" and python_version < "3.13"
+langsmith==0.1.106 ; python_version >= "3.10" and python_version < "3.13"
 llama-index-agent-openai==0.3.0 ; python_version >= "3.10" and python_version < "3.13"
-llama-index-core==0.11.1 ; python_version >= "3.10" and python_version < "3.13"
+llama-index-core==0.11.2 ; python_version >= "3.10" and python_version < "3.13"
 llama-index-embeddings-huggingface==0.3.1 ; python_version >= "3.10" and python_version < "3.13"
+llama-index-embeddings-openai==0.2.3 ; python_version >= "3.10" and python_version < "3.13"
 llama-index-llms-openai==0.2.0 ; python_version >= "3.10" and python_version < "3.13"
 llama-index-readers-file==0.2.0 ; python_version >= "3.10" and python_version < "3.13"
 llama-index-utils-workflow==0.2.0 ; python_version >= "3.10" and python_version < "3.13"
 llama-index-vector-stores-faiss==0.2.1 ; python_version >= "3.10" and python_version < "3.13"
+llama-index-vector-stores-kdbai==0.3.1 ; python_version >= "3.10" and python_version < "3.13"
 lxml==5.3.0 ; python_version >= "3.10" and python_version < "3.13"
 mako==1.3.5 ; python_version >= "3.10" and python_version < "3.13"
 markdown-it-py==3.0.0 ; python_version >= "3.10" and python_version < "3.13" and sys_platform != "emscripten"
@@ -99,7 +102,7 @@ openai==1.42.0 ; python_version >= "3.10" and python_version < "3.13"
 optuna==3.6.1 ; python_version >= "3.10" and python_version < "3.13"
 orjson==3.10.7 ; python_version >= "3.10" and python_version < "3.13"
 packaging==24.1 ; python_version >= "3.10" and python_version < "3.13"
-pandas==2.2.2 ; python_version >= "3.10" and python_version < "3.13"
+pandas==2.1.4 ; python_version >= "3.10" and python_version < "3.13"
 parso==0.8.4 ; python_version >= "3.10" and python_version < "3.13"
 pexpect==4.9.0 ; python_version >= "3.10" and python_version < "3.13" and (sys_platform != "win32" and sys_platform != "emscripten")
 pillow==10.4.0 ; python_version >= "3.10" and python_version < "3.13"
@@ -112,6 +115,7 @@ pydantic-core==2.20.1 ; python_version >= "3.10" and python_version < "3.13"
 pydantic==2.8.2 ; python_version >= "3.10" and python_version < "3.13"
 pydub==0.25.1 ; python_version >= "3.10" and python_version < "3.13"
 pygments==2.18.0 ; python_version >= "3.10" and python_version < "3.13"
+pykx==2.5.3 ; python_version >= "3.10" and python_version < "3.13"
 pyparsing==3.1.4 ; python_version >= "3.10" and python_version < "3.13"
 pypdf==4.3.1 ; python_version >= "3.10" and python_version < "3.13"
 python-dateutil==2.9.0.post0 ; python_version >= "3.10" and python_version < "3.13"
@@ -144,6 +148,7 @@ tenacity==8.5.0 ; python_version >= "3.10" and python_version < "3.13"
 threadpoolctl==3.5.0 ; python_version >= "3.10" and python_version < "3.13"
 tiktoken==0.7.0 ; python_version >= "3.10" and python_version < "3.13"
 tokenizers==0.19.1 ; python_version >= "3.10" and python_version < "3.13"
+toml==0.10.2 ; python_version >= "3.10" and python_version < "3.13"
 tomlkit==0.12.0 ; python_version >= "3.10" and python_version < "3.13"
 torch==2.4.0 ; python_version >= "3.10" and python_version < "3.13"
 tqdm==4.66.5 ; python_version >= "3.10" and python_version < "3.13"