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angry-meow
commited on
Commit
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31f9732
1
Parent(s):
7f24de7
Few new models
Browse files- .gitignore +1 -0
- __pycache__/constants.cpython-311.pyc +0 -0
- __pycache__/models.cpython-311.pyc +0 -0
- load_existing_docs.py +19 -28
- models.py +24 -5
- tuning/requirements.in +14 -0
- tuning/requirements.txt +412 -0
- tuning/tuning_embeddings_sandbox.ipynb +0 -0
.gitignore
CHANGED
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.env
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.env
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/__pycache__
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__pycache__/constants.cpython-311.pyc
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Binary files a/__pycache__/constants.cpython-311.pyc and b/__pycache__/constants.cpython-311.pyc differ
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__pycache__/models.cpython-311.pyc
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Binary files a/__pycache__/models.cpython-311.pyc and b/__pycache__/models.cpython-311.pyc differ
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load_existing_docs.py
CHANGED
@@ -6,12 +6,7 @@ from langchain_community.document_loaders import PyPDFLoader, UnstructuredURLLoa
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from qdrant_client.http.models import VectorParams
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import pymupdf
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import requests
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-
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#qdrant = QdrantVectorStore.from_existing_collection(
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# embedding=models.basic_embeddings,
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# collection_name="kai_test_documents",
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# url=constants.QDRANT_ENDPOINT,
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#)
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def extract_links_from_pdf(pdf_path):
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links = []
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#print(len(documents))
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semantic_split_docs = models.semanticChunker.split_documents(documents)
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#
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#
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#
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#
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#
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#
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#
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#chunk them
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#semantic_split_docs = models.semanticChunker.split_documents(all_documents)
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-
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-
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#add them to the existing qdrant client
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collection_name = "
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collections = models.qdrant_client.get_collections()
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collection_names = [collection.name for collection in collections.collections]
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if collection_name not in collection_names:
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models.qdrant_client.create_collection(
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collection_name=collection_name,
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vectors_config=VectorParams(size=
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)
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qdrant_vector_store = QdrantVectorStore(
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client=models.qdrant_client,
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collection_name=collection_name,
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embedding=models.
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)
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qdrant_vector_store.add_documents(
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from qdrant_client.http.models import VectorParams
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import pymupdf
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import requests
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from transformers import AutoTokenizer
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def extract_links_from_pdf(pdf_path):
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links = []
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#print(len(documents))
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#semantic_split_docs = models.semanticChunker.split_documents(documents)
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semantic_tuned_split_docs = models.semanticChunker_tuned.split_documents(documents)
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#RCTS_split_docs = models.RCTS.split_documents(documents)
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#print(len(semantic_split_docs))
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print(len(semantic_tuned_split_docs))
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#tokenizer = models.tuned_embeddings.client.tokenizer
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#
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#token_sizes = [len(tokenizer.encode(chunk)) for chunk in semantic_tuned_split_docs]
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# Display the token sizes
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#for idx, size in enumerate(token_sizes):
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# print(f"Chunk {idx + 1}: {size} tokens")
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#
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#exit()
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#add them to the existing qdrant client
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collection_name = "docs_from_ripped_urls_semantic_tuned"
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collections = models.qdrant_client.get_collections()
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collection_names = [collection.name for collection in collections.collections]
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if collection_name not in collection_names:
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models.qdrant_client.create_collection(
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collection_name=collection_name,
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vectors_config=VectorParams(size=1024, distance="Cosine")
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)
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qdrant_vector_store = QdrantVectorStore(
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client=models.qdrant_client,
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collection_name=collection_name,
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embedding=models.tuned_embeddings
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)
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qdrant_vector_store.add_documents(semantic_tuned_split_docs)
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models.py
CHANGED
@@ -5,9 +5,11 @@ from langchain.callbacks.tracers import LangChainTracer
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from langchain_huggingface.embeddings import HuggingFaceEmbeddings
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from langchain_experimental.text_splitter import SemanticChunker
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from langchain_openai.embeddings import OpenAIEmbeddings
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from
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from qdrant_client import QdrantClient
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from langchain_text_splitters import RecursiveCharacterTextSplitter
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import constants
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import os
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@@ -66,10 +68,8 @@ gpt4o_mini = ChatOpenAI(
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)
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basic_embeddings = HuggingFaceEmbeddings(model_name="snowflake/snowflake-arctic-embed-l")
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-
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-
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# query_instruction="Represent the query for retrieval: "
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#)
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te3_small = OpenAIEmbeddings(api_key=constants.OPENAI_API_KEY, model="text-embedding-3-small")
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breakpoint_threshold_type="percentile"
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)
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RCTS = RecursiveCharacterTextSplitter(
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# Set a really small chunk size, just to show.
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chunk_size=500,
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chunk_overlap=25,
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length_function=len,
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)
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from langchain_huggingface.embeddings import HuggingFaceEmbeddings
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from langchain_experimental.text_splitter import SemanticChunker
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from langchain_openai.embeddings import OpenAIEmbeddings
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from langchain_qdrant import QdrantVectorStore, Qdrant
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from langchain.retrievers.contextual_compression import ContextualCompressionRetriever
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from qdrant_client import QdrantClient
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from langchain_text_splitters import RecursiveCharacterTextSplitter
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from langchain_cohere import CohereRerank
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import constants
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import os
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)
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basic_embeddings = HuggingFaceEmbeddings(model_name="snowflake/snowflake-arctic-embed-l")
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tuned_embeddings = HuggingFaceEmbeddings(model_name="CoExperiences/snowflake-l-marketing-tuned")
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te3_small = OpenAIEmbeddings(api_key=constants.OPENAI_API_KEY, model="text-embedding-3-small")
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breakpoint_threshold_type="percentile"
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)
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semanticChunker_tuned = SemanticChunker(
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tuned_embeddings,
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breakpoint_threshold_type="percentile",
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breakpoint_threshold_amount=85
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)
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RCTS = RecursiveCharacterTextSplitter(
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# Set a really small chunk size, just to show.
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chunk_size=500,
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chunk_overlap=25,
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length_function=len,
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)
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semantic_tuned_Qdrant_vs = QdrantVectorStore(
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client=qdrant_client,
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collection_name="docs_from_ripped_urls_semantic_tuned",
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embedding=tuned_embeddings
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)
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semantic_tuned_retriever = semantic_tuned_Qdrant_vs.as_retriever(search_kwargs={"k" : 10})
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#compression
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compressor = CohereRerank(model="rerank-english-v3.0")
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compression_retriever = ContextualCompressionRetriever(
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base_compressor=compressor, base_retriever=semantic_tuned_retriever
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)
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tuning/requirements.in
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@@ -0,0 +1,14 @@
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langchain_openai
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langchain_huggingface
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langchain_core==0.2.38
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langchain
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langchain_community
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langchain-text-splitters
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faiss-cpu
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unstructured==0.15.7
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python-pptx==1.0.2
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nltk==3.9.1
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pyarrow
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sentence_transformers
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datasets
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ragas
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tuning/requirements.txt
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1 |
+
#
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2 |
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# This file is autogenerated by pip-compile with Python 3.11
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3 |
+
# by the following command:
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4 |
+
#
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5 |
+
# pip-compile requirements.in
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6 |
+
#
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7 |
+
aiohappyeyeballs==2.4.3
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8 |
+
# via aiohttp
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9 |
+
aiohttp==3.10.10
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10 |
+
# via
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11 |
+
# datasets
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12 |
+
# fsspec
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13 |
+
# langchain
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14 |
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# langchain-community
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15 |
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aiosignal==1.3.1
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16 |
+
# via aiohttp
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17 |
+
annotated-types==0.7.0
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18 |
+
# via pydantic
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19 |
+
anyio==4.6.2.post1
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20 |
+
# via
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21 |
+
# httpx
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22 |
+
# openai
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23 |
+
appdirs==1.4.4
|
24 |
+
# via ragas
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25 |
+
attrs==24.2.0
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26 |
+
# via aiohttp
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27 |
+
backoff==2.2.1
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28 |
+
# via unstructured
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29 |
+
beautifulsoup4==4.12.3
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30 |
+
# via unstructured
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31 |
+
certifi==2024.8.30
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32 |
+
# via
|
33 |
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# httpcore
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34 |
+
# httpx
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35 |
+
# requests
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36 |
+
cffi==1.17.1
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37 |
+
# via cryptography
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38 |
+
chardet==5.2.0
|
39 |
+
# via unstructured
|
40 |
+
charset-normalizer==3.4.0
|
41 |
+
# via requests
|
42 |
+
click==8.1.7
|
43 |
+
# via nltk
|
44 |
+
cryptography==43.0.1
|
45 |
+
# via unstructured-client
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46 |
+
dataclasses-json==0.6.7
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47 |
+
# via
|
48 |
+
# langchain-community
|
49 |
+
# unstructured
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50 |
+
datasets==3.0.1
|
51 |
+
# via
|
52 |
+
# -r requirements.in
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53 |
+
# ragas
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54 |
+
dill==0.3.8
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55 |
+
# via
|
56 |
+
# datasets
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57 |
+
# multiprocess
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58 |
+
distro==1.9.0
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59 |
+
# via openai
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60 |
+
emoji==2.14.0
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61 |
+
# via unstructured
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62 |
+
eval-type-backport==0.2.0
|
63 |
+
# via unstructured-client
|
64 |
+
faiss-cpu==1.9.0
|
65 |
+
# via -r requirements.in
|
66 |
+
filelock==3.16.1
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67 |
+
# via
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68 |
+
# datasets
|
69 |
+
# huggingface-hub
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70 |
+
# torch
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71 |
+
# transformers
|
72 |
+
# triton
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73 |
+
filetype==1.2.0
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74 |
+
# via unstructured
|
75 |
+
frozenlist==1.4.1
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76 |
+
# via
|
77 |
+
# aiohttp
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78 |
+
# aiosignal
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79 |
+
fsspec[http]==2024.6.1
|
80 |
+
# via
|
81 |
+
# datasets
|
82 |
+
# huggingface-hub
|
83 |
+
# torch
|
84 |
+
greenlet==3.1.1
|
85 |
+
# via sqlalchemy
|
86 |
+
h11==0.14.0
|
87 |
+
# via httpcore
|
88 |
+
httpcore==1.0.6
|
89 |
+
# via httpx
|
90 |
+
httpx==0.27.2
|
91 |
+
# via
|
92 |
+
# langsmith
|
93 |
+
# openai
|
94 |
+
# unstructured-client
|
95 |
+
huggingface-hub==0.26.0
|
96 |
+
# via
|
97 |
+
# datasets
|
98 |
+
# langchain-huggingface
|
99 |
+
# sentence-transformers
|
100 |
+
# tokenizers
|
101 |
+
# transformers
|
102 |
+
idna==3.10
|
103 |
+
# via
|
104 |
+
# anyio
|
105 |
+
# httpx
|
106 |
+
# requests
|
107 |
+
# yarl
|
108 |
+
jinja2==3.1.4
|
109 |
+
# via torch
|
110 |
+
jiter==0.6.1
|
111 |
+
# via openai
|
112 |
+
joblib==1.4.2
|
113 |
+
# via
|
114 |
+
# nltk
|
115 |
+
# scikit-learn
|
116 |
+
jsonpatch==1.33
|
117 |
+
# via langchain-core
|
118 |
+
jsonpath-python==1.0.6
|
119 |
+
# via unstructured-client
|
120 |
+
jsonpointer==3.0.0
|
121 |
+
# via jsonpatch
|
122 |
+
langchain==0.2.16
|
123 |
+
# via
|
124 |
+
# -r requirements.in
|
125 |
+
# langchain-community
|
126 |
+
# ragas
|
127 |
+
langchain-community==0.2.16
|
128 |
+
# via
|
129 |
+
# -r requirements.in
|
130 |
+
# ragas
|
131 |
+
langchain-core==0.2.38
|
132 |
+
# via
|
133 |
+
# -r requirements.in
|
134 |
+
# langchain
|
135 |
+
# langchain-community
|
136 |
+
# langchain-huggingface
|
137 |
+
# langchain-openai
|
138 |
+
# langchain-text-splitters
|
139 |
+
# ragas
|
140 |
+
langchain-huggingface==0.0.3
|
141 |
+
# via -r requirements.in
|
142 |
+
langchain-openai==0.1.23
|
143 |
+
# via
|
144 |
+
# -r requirements.in
|
145 |
+
# ragas
|
146 |
+
langchain-text-splitters==0.2.4
|
147 |
+
# via
|
148 |
+
# -r requirements.in
|
149 |
+
# langchain
|
150 |
+
langdetect==1.0.9
|
151 |
+
# via unstructured
|
152 |
+
langsmith==0.1.136
|
153 |
+
# via
|
154 |
+
# langchain
|
155 |
+
# langchain-community
|
156 |
+
# langchain-core
|
157 |
+
lxml==5.3.0
|
158 |
+
# via
|
159 |
+
# python-pptx
|
160 |
+
# unstructured
|
161 |
+
markupsafe==3.0.2
|
162 |
+
# via jinja2
|
163 |
+
marshmallow==3.23.0
|
164 |
+
# via dataclasses-json
|
165 |
+
mpmath==1.3.0
|
166 |
+
# via sympy
|
167 |
+
multidict==6.1.0
|
168 |
+
# via
|
169 |
+
# aiohttp
|
170 |
+
# yarl
|
171 |
+
multiprocess==0.70.16
|
172 |
+
# via datasets
|
173 |
+
mypy-extensions==1.0.0
|
174 |
+
# via typing-inspect
|
175 |
+
nest-asyncio==1.6.0
|
176 |
+
# via
|
177 |
+
# ragas
|
178 |
+
# unstructured-client
|
179 |
+
networkx==3.4.1
|
180 |
+
# via torch
|
181 |
+
nltk==3.9.1
|
182 |
+
# via
|
183 |
+
# -r requirements.in
|
184 |
+
# unstructured
|
185 |
+
numpy==1.26.4
|
186 |
+
# via
|
187 |
+
# datasets
|
188 |
+
# faiss-cpu
|
189 |
+
# langchain
|
190 |
+
# langchain-community
|
191 |
+
# pandas
|
192 |
+
# pyarrow
|
193 |
+
# ragas
|
194 |
+
# scikit-learn
|
195 |
+
# scipy
|
196 |
+
# transformers
|
197 |
+
# unstructured
|
198 |
+
nvidia-cublas-cu12==12.4.5.8
|
199 |
+
# via
|
200 |
+
# nvidia-cudnn-cu12
|
201 |
+
# nvidia-cusolver-cu12
|
202 |
+
# torch
|
203 |
+
nvidia-cuda-cupti-cu12==12.4.127
|
204 |
+
# via torch
|
205 |
+
nvidia-cuda-nvrtc-cu12==12.4.127
|
206 |
+
# via torch
|
207 |
+
nvidia-cuda-runtime-cu12==12.4.127
|
208 |
+
# via torch
|
209 |
+
nvidia-cudnn-cu12==9.1.0.70
|
210 |
+
# via torch
|
211 |
+
nvidia-cufft-cu12==11.2.1.3
|
212 |
+
# via torch
|
213 |
+
nvidia-curand-cu12==10.3.5.147
|
214 |
+
# via torch
|
215 |
+
nvidia-cusolver-cu12==11.6.1.9
|
216 |
+
# via torch
|
217 |
+
nvidia-cusparse-cu12==12.3.1.170
|
218 |
+
# via
|
219 |
+
# nvidia-cusolver-cu12
|
220 |
+
# torch
|
221 |
+
nvidia-nccl-cu12==2.21.5
|
222 |
+
# via torch
|
223 |
+
nvidia-nvjitlink-cu12==12.4.127
|
224 |
+
# via
|
225 |
+
# nvidia-cusolver-cu12
|
226 |
+
# nvidia-cusparse-cu12
|
227 |
+
# torch
|
228 |
+
nvidia-nvtx-cu12==12.4.127
|
229 |
+
# via torch
|
230 |
+
openai==1.52.0
|
231 |
+
# via
|
232 |
+
# langchain-openai
|
233 |
+
# ragas
|
234 |
+
orjson==3.10.7
|
235 |
+
# via langsmith
|
236 |
+
packaging==24.1
|
237 |
+
# via
|
238 |
+
# datasets
|
239 |
+
# faiss-cpu
|
240 |
+
# huggingface-hub
|
241 |
+
# langchain-core
|
242 |
+
# marshmallow
|
243 |
+
# transformers
|
244 |
+
pandas==2.2.3
|
245 |
+
# via datasets
|
246 |
+
pillow==11.0.0
|
247 |
+
# via
|
248 |
+
# python-pptx
|
249 |
+
# sentence-transformers
|
250 |
+
propcache==0.2.0
|
251 |
+
# via yarl
|
252 |
+
psutil==6.1.0
|
253 |
+
# via unstructured
|
254 |
+
pyarrow==17.0.0
|
255 |
+
# via
|
256 |
+
# -r requirements.in
|
257 |
+
# datasets
|
258 |
+
pycparser==2.22
|
259 |
+
# via cffi
|
260 |
+
pydantic==2.9.2
|
261 |
+
# via
|
262 |
+
# langchain
|
263 |
+
# langchain-core
|
264 |
+
# langsmith
|
265 |
+
# openai
|
266 |
+
# ragas
|
267 |
+
# unstructured-client
|
268 |
+
pydantic-core==2.23.4
|
269 |
+
# via pydantic
|
270 |
+
pypdf==5.0.1
|
271 |
+
# via unstructured-client
|
272 |
+
pysbd==0.3.4
|
273 |
+
# via ragas
|
274 |
+
python-dateutil==2.8.2
|
275 |
+
# via
|
276 |
+
# pandas
|
277 |
+
# unstructured-client
|
278 |
+
python-iso639==2024.4.27
|
279 |
+
# via unstructured
|
280 |
+
python-magic==0.4.27
|
281 |
+
# via unstructured
|
282 |
+
python-pptx==1.0.2
|
283 |
+
# via -r requirements.in
|
284 |
+
pytz==2024.2
|
285 |
+
# via pandas
|
286 |
+
pyyaml==6.0.2
|
287 |
+
# via
|
288 |
+
# datasets
|
289 |
+
# huggingface-hub
|
290 |
+
# langchain
|
291 |
+
# langchain-community
|
292 |
+
# langchain-core
|
293 |
+
# transformers
|
294 |
+
ragas==0.2.1
|
295 |
+
# via -r requirements.in
|
296 |
+
rapidfuzz==3.10.0
|
297 |
+
# via unstructured
|
298 |
+
regex==2024.9.11
|
299 |
+
# via
|
300 |
+
# nltk
|
301 |
+
# tiktoken
|
302 |
+
# transformers
|
303 |
+
requests==2.32.3
|
304 |
+
# via
|
305 |
+
# datasets
|
306 |
+
# huggingface-hub
|
307 |
+
# langchain
|
308 |
+
# langchain-community
|
309 |
+
# langsmith
|
310 |
+
# requests-toolbelt
|
311 |
+
# tiktoken
|
312 |
+
# transformers
|
313 |
+
# unstructured
|
314 |
+
requests-toolbelt==1.0.0
|
315 |
+
# via
|
316 |
+
# langsmith
|
317 |
+
# unstructured-client
|
318 |
+
safetensors==0.4.5
|
319 |
+
# via transformers
|
320 |
+
scikit-learn==1.5.2
|
321 |
+
# via sentence-transformers
|
322 |
+
scipy==1.14.1
|
323 |
+
# via
|
324 |
+
# scikit-learn
|
325 |
+
# sentence-transformers
|
326 |
+
sentence-transformers==3.2.0
|
327 |
+
# via
|
328 |
+
# -r requirements.in
|
329 |
+
# langchain-huggingface
|
330 |
+
six==1.16.0
|
331 |
+
# via
|
332 |
+
# langdetect
|
333 |
+
# python-dateutil
|
334 |
+
sniffio==1.3.1
|
335 |
+
# via
|
336 |
+
# anyio
|
337 |
+
# httpx
|
338 |
+
# openai
|
339 |
+
soupsieve==2.6
|
340 |
+
# via beautifulsoup4
|
341 |
+
sqlalchemy==2.0.36
|
342 |
+
# via
|
343 |
+
# langchain
|
344 |
+
# langchain-community
|
345 |
+
sympy==1.13.1
|
346 |
+
# via torch
|
347 |
+
tabulate==0.9.0
|
348 |
+
# via unstructured
|
349 |
+
tenacity==8.5.0
|
350 |
+
# via
|
351 |
+
# langchain
|
352 |
+
# langchain-community
|
353 |
+
# langchain-core
|
354 |
+
threadpoolctl==3.5.0
|
355 |
+
# via scikit-learn
|
356 |
+
tiktoken==0.8.0
|
357 |
+
# via
|
358 |
+
# langchain-openai
|
359 |
+
# ragas
|
360 |
+
tokenizers==0.20.1
|
361 |
+
# via
|
362 |
+
# langchain-huggingface
|
363 |
+
# transformers
|
364 |
+
torch==2.5.0
|
365 |
+
# via sentence-transformers
|
366 |
+
tqdm==4.66.5
|
367 |
+
# via
|
368 |
+
# datasets
|
369 |
+
# huggingface-hub
|
370 |
+
# nltk
|
371 |
+
# openai
|
372 |
+
# sentence-transformers
|
373 |
+
# transformers
|
374 |
+
# unstructured
|
375 |
+
transformers==4.45.2
|
376 |
+
# via
|
377 |
+
# langchain-huggingface
|
378 |
+
# sentence-transformers
|
379 |
+
triton==3.1.0
|
380 |
+
# via torch
|
381 |
+
typing-extensions==4.12.2
|
382 |
+
# via
|
383 |
+
# huggingface-hub
|
384 |
+
# langchain-core
|
385 |
+
# openai
|
386 |
+
# pydantic
|
387 |
+
# pydantic-core
|
388 |
+
# python-pptx
|
389 |
+
# sqlalchemy
|
390 |
+
# torch
|
391 |
+
# typing-inspect
|
392 |
+
# unstructured
|
393 |
+
typing-inspect==0.9.0
|
394 |
+
# via
|
395 |
+
# dataclasses-json
|
396 |
+
# unstructured-client
|
397 |
+
tzdata==2024.2
|
398 |
+
# via pandas
|
399 |
+
unstructured==0.15.7
|
400 |
+
# via -r requirements.in
|
401 |
+
unstructured-client==0.26.1
|
402 |
+
# via unstructured
|
403 |
+
urllib3==2.2.3
|
404 |
+
# via requests
|
405 |
+
wrapt==1.16.0
|
406 |
+
# via unstructured
|
407 |
+
xlsxwriter==3.2.0
|
408 |
+
# via python-pptx
|
409 |
+
xxhash==3.5.0
|
410 |
+
# via datasets
|
411 |
+
yarl==1.15.4
|
412 |
+
# via aiohttp
|
tuning/tuning_embeddings_sandbox.ipynb
ADDED
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|
|