Spaces:
Build error
Build error
Add supabase vector store
Browse files- agent.py +39 -3
- pyproject.toml +3 -0
- uv.lock +624 -27
agent.py
CHANGED
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@@ -5,7 +5,12 @@ from langgraph.prebuilt import tools_condition
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from langgraph.prebuilt import ToolNode
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from langchain_google_genai import ChatGoogleGenerativeAI
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from langchain_core.messages import SystemMessage, HumanMessage
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-
from
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from tools.math_tools import add, subtract, multiply, divide, modulus, power, sqrt
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from tools.search_tools import search_wikipedia, web_search
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from tools.image_video_tools import query_image
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@@ -25,6 +30,22 @@ def build_graph():
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llm_with_tools = llm.bind_tools(tools)
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def assistant(state: MessagesState):
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"""Assistant node for invoking the LLM."""
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messages = state["messages"]
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@@ -33,12 +54,27 @@ def build_graph():
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messages = [SystemMessage(content="You are a helpful AI assistant. Use the available tools to answer questions accurately. When providing your final answer, use the format: FINAL ANSWER: [your answer]")] + messages
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response = llm_with_tools.invoke(messages)
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return {"messages": [response]}
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builder = StateGraph(MessagesState)
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-
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builder.add_node("assistant", assistant)
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builder.add_node("tools", ToolNode(tools))
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-
builder.add_edge(START, "
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builder.add_conditional_edges(
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"assistant",
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tools_condition,
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from langgraph.prebuilt import ToolNode
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from langchain_google_genai import ChatGoogleGenerativeAI
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from langchain_core.messages import SystemMessage, HumanMessage
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from langchain_huggingface import HuggingFaceEmbeddings
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from langchain_community.vectorstores import SupabaseVectorStore
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from supabase.client import Client, create_client
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from tools.math_tools import add, subtract, multiply, divide, modulus, power, sqrt
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from tools.search_tools import search_wikipedia, web_search
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from tools.image_video_tools import query_image
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llm_with_tools = llm.bind_tools(tools)
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embeddings = HuggingFaceEmbeddings(model_name="sentence-transformers/all-mpnet-base-v2") # dim=768
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supabase: Client = create_client(
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os.environ.get("SUPABASE_URL"),
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os.environ.get("SUPABASE_SERVICE_KEY"))
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vector_store = SupabaseVectorStore(
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client=supabase,
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embedding= embeddings,
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table_name="documents",
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query_name="match_documents_langchain",
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)
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create_retriever_tool = create_retriever_tool(
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retriever=vector_store.as_retriever(),
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name="Question Search",
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description="A tool to retrieve similar questions from a vector store.",
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)
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def assistant(state: MessagesState):
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"""Assistant node for invoking the LLM."""
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messages = state["messages"]
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messages = [SystemMessage(content="You are a helpful AI assistant. Use the available tools to answer questions accurately. When providing your final answer, use the format: FINAL ANSWER: [your answer]")] + messages
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response = llm_with_tools.invoke(messages)
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return {"messages": [response]}
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def retriever(state: MessagesState):
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"""Retriever node"""
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# Add system message if not present
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if not any(isinstance(m, SystemMessage) for m in messages):
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messages = [SystemMessage(content="You are a helpful AI assistant. Use the available tools to answer questions accurately. When providing your final answer, use the format: FINAL ANSWER: [your answer]")] + messages
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similar_question = vector_store.similarity_search(state["messages"][0].content)
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example_msg = HumanMessage(
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content=f"Here I provide a similar question and answer for reference: \n\n{similar_question[0].page_content}",
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)
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return {"messages": state["messages"] + [example_msg]}
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builder = StateGraph(MessagesState)
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builder.add_node("retriever", retriever)
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builder.add_node("assistant", assistant)
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builder.add_node("tools", ToolNode(tools))
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builder.add_edge(START, "retriever")
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builder.add_edge("retriever", "assistant")
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builder.add_conditional_edges(
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"assistant",
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tools_condition,
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pyproject.toml
CHANGED
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@@ -10,8 +10,11 @@ dependencies = [
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"langchain-community>=0.3.23",
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"langchain-core>=0.3.59",
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"langchain-google-genai>=2.1.4",
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"langgraph>=0.4.3",
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"pandas>=2.2.3",
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"requests>=2.32.3",
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"wikipedia>=1.4.0",
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]
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"langchain-community>=0.3.23",
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"langchain-core>=0.3.59",
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"langchain-google-genai>=2.1.4",
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"langchain-huggingface>=0.2.0",
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"langgraph>=0.4.3",
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"pandas>=2.2.3",
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"requests>=2.32.3",
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"supabase>=2.15.1",
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"torch==2.2.2",
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"wikipedia>=1.4.0",
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]
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uv.lock
CHANGED
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@@ -291,6 +291,18 @@ wheels = [
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{ url = "https://files.pythonhosted.org/packages/c3/be/d0d44e092656fe7a06b55e6103cbce807cdbdee17884a5367c68c9860853/dataclasses_json-0.6.7-py3-none-any.whl", hash = "sha256:0dbf33f26c8d5305befd61b39d2b3414e8a407bedc2834dea9b8d642666fb40a", size = 28686 },
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]
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[[package]]
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name = "dotenv"
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version = "0.9.9"
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@@ -353,9 +365,12 @@ dependencies = [
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{ name = "langchain-community" },
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{ name = "langchain-core" },
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{ name = "langchain-google-genai" },
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{ name = "langgraph" },
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{ name = "pandas" },
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{ name = "requests" },
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{ name = "wikipedia" },
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]
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@@ -366,9 +381,12 @@ requires-dist = [
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{ name = "langchain-community", specifier = ">=0.3.23" },
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{ name = "langchain-core", specifier = ">=0.3.59" },
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{ name = "langchain-google-genai", specifier = ">=2.1.4" },
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{ name = "langgraph", specifier = ">=0.4.3" },
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{ name = "pandas", specifier = ">=2.2.3" },
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{ name = "requests", specifier = ">=2.32.3" },
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{ name = "wikipedia", specifier = ">=1.4.0" },
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]
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@@ -504,6 +522,21 @@ wheels = [
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{ url = "https://files.pythonhosted.org/packages/86/f1/62a193f0227cf15a920390abe675f386dec35f7ae3ffe6da582d3ade42c7/googleapis_common_protos-1.70.0-py3-none-any.whl", hash = "sha256:b8bfcca8c25a2bb253e0e0b0adaf8c00773e5e6af6fd92397576680b807e0fd8", size = 294530 },
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[[package]]
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name = "gradio"
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version = "5.29.0"
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{ url = "https://files.pythonhosted.org/packages/04/4b/29cac41a4d98d144bf5f6d33995617b185d14b22401f75ca86f384e87ff1/h11-0.16.0-py3-none-any.whl", hash = "sha256:63cf8bbe7522de3bf65932fda1d9c2772064ffb3dae62d55932da54b31cb6c86", size = 37515 },
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[[package]]
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name = "hf-xet"
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version = "1.1.0"
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{ url = "https://files.pythonhosted.org/packages/53/d6/cb32842cbf1cf5a154b41fa918a2fd86003af9bca227a2397cd7f312a8a6/hf_xet-1.1.0-cp37-abi3-win_amd64.whl", hash = "sha256:73153eab9abf3d6973b21e94a67ccba5d595c3e12feb8c0bf50be02964e7f126", size = 4204376 },
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[[package]]
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name = "httpcore"
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version = "1.0.9"
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{ url = "https://files.pythonhosted.org/packages/2a/39/e50c7c3a983047577ee07d2a9e53faf5a69493943ec3f6a384bdc792deb2/httpx-0.28.1-py3-none-any.whl", hash = "sha256:d909fcccc110f8c7faf814ca82a9a4d816bc5a6dbfea25d6591d6985b8ba59ad", size = 73517 },
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[[package]]
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name = "httpx-sse"
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version = "0.4.0"
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{ url = "https://files.pythonhosted.org/packages/3a/bf/6002da17ec1c7a47bedeb216812929665927c70b6e7500b3c7bf36f01bdd/huggingface_hub-0.31.1-py3-none-any.whl", hash = "sha256:43f73124819b48b42d140cbc0d7a2e6bd15b2853b1b9d728d4d55ad1750cac5b", size = 484265 },
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[[package]]
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name = "idna"
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version = "3.10"
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{ url = "https://files.pythonhosted.org/packages/76/c6/c88e154df9c4e1a2a66ccf0005a88dfb2650c1dffb6f5ce603dfbd452ce3/idna-3.10-py3-none-any.whl", hash = "sha256:946d195a0d259cbba61165e88e65941f16e9b36ea6ddb97f00452bae8b1287d3", size = 70442 },
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[[package]]
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name = "jinja2"
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version = "3.1.6"
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{ url = "https://files.pythonhosted.org/packages/62/a1/3d680cbfd5f4b8f15abc1d571870c5fc3e594bb582bc3b64ea099db13e56/jinja2-3.1.6-py3-none-any.whl", hash = "sha256:85ece4451f492d0c13c5dd7c13a64681a86afae63a5f347908daf103ce6d2f67", size = 134899 },
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[[package]]
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name = "jsonpatch"
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version = "1.33"
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{ url = "https://files.pythonhosted.org/packages/07/12/2be71bebbc23e4a499c50df567017110e4d382a045422647c8e6b1040541/langchain_google_genai-2.1.4-py3-none-any.whl", hash = "sha256:a3fa3cf7fe9c1de77280f42fbdd22cfcc5fbeb0d60cd5be7a0e6c50a74f5ce73", size = 44313 },
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[[package]]
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name = "langchain-text-splitters"
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version = "0.3.8"
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{ url = "https://files.pythonhosted.org/packages/b3/38/89ba8ad64ae25be8de66a6d463314cf1eb366222074cfda9ee839c56a4b4/mdurl-0.1.2-py3-none-any.whl", hash = "sha256:84008a41e51615a49fc9966191ff91509e3c40b939176e643fd50a5c2196b8f8", size = 9979 },
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]
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[[package]]
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name = "multidict"
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version = "6.4.3"
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{ url = "https://files.pythonhosted.org/packages/79/7b/2c79738432f5c924bef5071f933bcc9efd0473bac3b4aa584a6f7c1c8df8/mypy_extensions-1.1.0-py3-none-any.whl", hash = "sha256:1be4cccdb0f2482337c4743e60421de3a356cd97508abadd57d47403e94f5505", size = 4963 },
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[[package]]
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name = "numpy"
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version = "2.2.5"
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{ url = "https://files.pythonhosted.org/packages/63/be/b85e4aa4bf42c6502851b971f1c326d583fcc68227385f92089cf50a7b45/numpy-2.2.5-cp313-cp313t-win_amd64.whl", hash = "sha256:d403c84991b5ad291d3809bace5e85f4bbf44a04bdc9a88ed2bb1807b3360bb8", size = 12750096 },
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[[package]]
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name = "orjson"
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version = "3.10.18"
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[[package]]
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| 1257 |
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| 1522 |
[[package]]
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| 1523 |
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| 1611 |
[[package]]
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| 1620 |
[[package]]
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| 1697 |
[[package]]
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| 1706 |
[[package]]
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[[package]]
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