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Running
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Update app.py
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app.py
CHANGED
@@ -3,39 +3,26 @@ import re
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import gradio as gr
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from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig
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import torch
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You can build with this endpoint using🔮DeepSeekMath📉 available here : [deepseek-ai/deepseek-math-7b-instruct](https://huggingface.co/deepseek-ai/deepseek-math-7b-instruct). We're using 🤖[introspector/unimath](https://huggingface.co/datasets/introspector/unimath) for cool examples, check it out below ! The demo is still a work in progress and we're looking forward to build downstream tasks that showcase outstanding mathematical reasoning. Have any ideas ? join us below !
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You can also use 🔮DeepSeekMath📉 by cloning this space. Simply click here: <a style="display:inline-block" href="https://huggingface.co/spaces/Tonic/Math?duplicate=true"><img src="https://img.shields.io/badge/-Duplicate%20Space-blue?labelColor=white&style=flat&logo=data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABAAAAAQCAYAAAAf8/9hAAAAAXNSR0IArs4c6QAAAP5JREFUOE+lk7FqAkEURY+ltunEgFXS2sZGIbXfEPdLlnxJyDdYB62sbbUKpLbVNhyYFzbrrA74YJlh9r079973psed0cvUD4A+4HoCjsA85X0Dfn/RBLBgBDxnQPfAEJgBY+A9gALA4tcbamSzS4xq4FOQAJgCDwV2CPKV8tZAJcAjMMkUe1vX+U+SMhfAJEHasQIWmXNN3abzDwHUrgcRGmYcgKe0bxrblHEB4E/pndMazNpSZGcsZdBlYJcEL9Afo75molJyM2FxmPgmgPqlWNLGfwZGG6UiyEvLzHYDmoPkDDiNm9JR9uboiONcBXrpY1qmgs21x1QwyZcpvxt9NS09PlsPAAAAAElFTkSuQmCC&logoWidth=14" alt="Duplicate Space"></a></h3>
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Join us : 🌟TeamTonic🌟 is always making cool demos! Join our active builder's 🛠️community 👻 [![Join us on Discord](https://img.shields.io/discord/1109943800132010065?label=Discord&logo=discord&style=flat-square)](https://discord.gg/GWpVpekp) On 🤗Huggingface: [TeamTonic](https://huggingface.co/TeamTonic) & [MultiTransformer](https://huggingface.co/MultiTransformer) Math with [introspector](https://huggingface.co/introspector) On 🌐Github: [Tonic-AI](https://github.com/tonic-ai) & contribute to🌟 [SciTonic](https://github.com/Tonic-AI/scitonic)🤗Big thanks to Yuvi Sharma and all the folks at huggingface for the community grant 🤗
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"""
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LEAN4_DEFAULT_HEADER = """import Mathlib
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import Aesop
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set_option maxHeartbeats 0
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open BigOperators Real Nat Topology Rat
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"""
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additional_info_prompt = "Explain the above using mathematics, print entire answer in latex format:"
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def format_prompt(
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```lean4
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{LEAN4_DEFAULT_HEADER}
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{question}
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{additional_info}
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"""
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unimath1 = """Goal:
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X : UU
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Y : UU
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P : UU
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X0 : X × Y → P
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x : X
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============================
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(Y → P)
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DEBUG:Going to execute:
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PTRDEBUGTAC<coq-core.plugins.ltac::intro@1> $1
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DEBUG LTAC Evaluated term: yp
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TcDebug (0) > NONE??? LtacNotationCall (no location),/mnt/data1/2024/01/05/UniMath/UniMath/Foundations/PartA.v:234
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"""
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# source : unimath/unimath/batch2/data08
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unimath2 = """Goal:
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R : ring M : module R
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============================
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(islinear (idfun M))
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DEBUG:Going to execute:
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PTRDEBUGTACapply pathsinv0; trivial
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Level 0: Backtrace:
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Proof is not complete.
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Level 0: Backtrace:
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Proof is not complete.
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TcDebug (0) > NONE??? LtacNotationCall (no location),/mnt/data1/2024/01/05/UniMath/UniMath/MoreFoundations/Tactics.veasy:19, Tactics (UniMath.MoreFoundations),/mnt/data1/2024/01/05/UniMath/UniMath/Algebra/Modules/Examples.v:27
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"""
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# source : unimath/unimath/batch2/data_22/BATCH122007
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unimath3 = """Goal:
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X : UU i : nat b : hProptoType (i < S i) x : Vector X (S i) r : i = i
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============================
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(pr1 lastelement = pr1 (i,, b))
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DEBUG:Going to execute:
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PTRDEBUGTACsimpl
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DEBUG LTAC Evaluated term: isinjstntonat
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TcDebug (0) > /mnt/data1/2024/01/05/UniMath/UniMath/Combinatorics/FiniteSequences.v:114
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"""
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# source : unimath/unimath/batch2/data_12/BATCH112026
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unimath4 = """Goal:
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X : dcpo CX : continuous_dcpo_struct X x : pr1hSet X y : pr1hSet X
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============================
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(x ⊑ y
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DEBUG:Going to execute:
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PTRDEBUGTACsimple refine (p _ _ _) ||
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simple refine (p _ _ _ _) ||
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simple refine (p _ _ _ _ _) ||
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simple refine (p _ _ _ _ _ _) ||
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simple refine (p _ _ _ _ _ _ _) ||
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simple refine (p _ _ _ _ _ _ _ _) ||
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simple refine (p _ _ _ _ _ _ _ _ _) ||
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simple refine (p _ _ _ _ _ _ _ _ _ _) ||
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simple refine (p _ _ _ _ _ _ _ _ _ _ _) ||
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simple refine (p _ _ _ _ _ _ _ _ _ _ _ _) ||
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simple refine (p _ _ _ _ _ _ _ _ _ _ _ _ _) ||
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simple refine
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(p _ _ _ _ _ _ _ _ _ _ _ _ _ _) || simple
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refine (p _ _ _ _ _ _ _ _ _ _ _ _ _ _ _)
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Level 0: Backtrace:
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In environment
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X : dcpo
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CX : continuous_dcpo_struct X
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x, y : X
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The term "weqimplimpl ?f ?g" has type "isaprop ?X → isaprop ?Y → ?X ≃ ?Y"
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while it is expected to have type
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"x ⊑ y ≃ (∀ i : approximating_family CX x, approximating_family CX x i ⊑ y)".
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Level 0: Backtrace:
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In environment
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X : dcpo
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CX : continuous_dcpo_struct X
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x, y : X
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The term "weqimplimpl ?f ?g" has type "isaprop ?X → isaprop ?Y → ?X ≃ ?Y"
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while it is expected to have type
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"x ⊑ y ≃ (∀ i : approximating_family CX x, approximating_family CX x i ⊑ y)".
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TcDebug (0) > NONE??? LtacNotationCall (no location),/mnt/data1/2024/01/05/UniMath/UniMath/Foundations/Init.vsimple_rapply:174, Init (UniMath.Foundations),/mnt/data1/2024/01/05/UniMath/UniMath/Foundations/Init.v??? LtacNotationCall:189, Init (UniMath.Foundations),/mnt/data1/2024/01/05/UniMath/UniMath/OrderTheory/DCPOs/Basis/Continuous.v:166
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"""
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# source : unimath/unimath/batch2/data_42/BATCH142042
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examples = [
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[unimath1, additional_info_prompt, 1200],
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model_name = "Goedel-LM/Goedel-Prover-SFT"
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tokenizer = AutoTokenizer.from_pretrained(model_name)
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model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
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# model.generation_config = GenerationConfig.from_pretrained(model_name)
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# model.generation_config.pad_token_id = model.generation_config.eos_token_id
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# Set generation config
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model.generation_config = GenerationConfig.from_pretrained(model_name)
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model.generation_config.bos_token_id = 100000
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model.generation_config.eos_token_id = 100001
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def parse_full_answer(answer):
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"""Parses the assistant's answer, excluding any text before 'Assistant :'."""
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match = re.search(r"Assistant\s*:\s*(.*)", answer, re.DOTALL)
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return match.group(1).strip() if match else "No assistant answer found."
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def parse_final_answer(answer):
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"""Extracts the final answer enclosed within \boxed{}."""
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match = re.search(r"\\boxed\{([^}]+)\}", answer)
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return match.group(1) if match else "No final answer found."
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@spaces.GPU
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def solve_math_problem(question,
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# Format the prompt using Lean4 structure
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prompt = format_prompt(question,
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input_ids = tokenizer(prompt, return_tensors="pt").input_ids.to(model.device)
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outputs = model.generate(
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result = tokenizer.decode(outputs[0], skip_special_tokens=True)
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def main():
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iface = gr.Interface(
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You can also use 🔮Goedel Prover📉 by cloning this space. Simply click here: <a style="display:inline-block" href="https://huggingface.co/spaces/Tonic/Math?duplicate=true"><img src="https://img.shields.io/badge/-Duplicate%20Space-blue?labelColor=white&style=flat&logo=data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABAAAAAQCAYAAAAf8/9hAAAAAXNSR0IArs4c6QAAAP5JREFUOE+lk7FqAkEURY+ltunEgFXS2sZGIbXfEPdLlnxJyDdYB62sbbUKpLbVNhyYFzbrrA74YJlh9r079973psed0cvUD4A+4HoCjsA85X0Dfn/RBLBgBDxnQPfAEJgBY+A9gALA4tcbamSzS4xq4FOQAJgCDwV2CPKV8tZAJcAjMMkUe1vX+U+SMhfAJEHasQIWmXNN3abzDwHUrgcRGmYcgKe0bxrblHEB4E/pndMazNpSZGcsZdBlYJcEL9Afo75molJyM2FxmPgmgPqlWNLGfwZGG6UiyEvLzHYDmoPkDDiNm9JR9uboiONcBXrpY1qmgs21x1QwyZcpvxt9NS09PlsPAAAAAElFTkSuQmCC&logoWidth=14" alt="Duplicate Space"></a></h3>
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Join us : 🌟TeamTonic🌟 is always making cool demos! Join our active builder's 🛠️community 👻 [![Join us on Discord](https://img.shields.io/discord/1109943800132010065?label=Discord&logo=discord&style=flat-square)](https://discord.gg/GWpVpekp) On 🤗Huggingface: [TeamTonic](https://huggingface.co/TeamTonic) & [MultiTransformer](https://huggingface.co/MultiTransformer) Math with [introspector](https://huggingface.co/introspector) On 🌐Github: [Tonic-AI](https://github.com/tonic-ai) & contribute to🌟 [SciTonic](https://github.com/Tonic-AI/scitonic)🤗Big thanks to Yuvi Sharma and all the folks at huggingface for the community grant 🤗
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""",
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fn=solve_math_problem,
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outputs=[
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gr.
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gr.
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],
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inputs=[
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gr.Textbox(label="🤔Enter your
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gr.Textbox(value=additional_info_prompt, label="🪜Optional
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gr.Slider(minimum=150, maximum=
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],
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examples=examples
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)
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iface.launch()
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if __name__ == "__main__":
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main()
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import gradio as gr
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from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig
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import torch
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import json
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LEAN4_DEFAULT_HEADER = "import Mathlib\nimport Aesop\n\nset_option maxHeartbeats 0\n\nopen BigOperators Real Nat Topology Rat\n\n"
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title = """# 🙋🏻♂️Welcome to🌟Tonic's🔮Goedel Prover📉
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You can build with this endpoint using🔮Goedel-Prover-SFT📉 available here : [Goedel-LM/Goedel-Prover-SFT](https://huggingface.co/Goedel-LM/Goedel-Prover-SFT)."""
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def format_prompt(formal_statement, informal_prefix=""):
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"""Format the input according to the Lean4 structure"""
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return f"Complete the following Lean 4 code with explanatory comments preceding each line of code:\n\n```lean4\n{LEAN4_DEFAULT_HEADER}{informal_prefix}{formal_statement}"
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def extract_code(response):
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"""Extract code between lean4 code blocks"""
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try:
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return re.search(r'```lean4\n(.*?)\n```', response, re.DOTALL).group(1)
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except:
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return "None"
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# Example problems
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unimath1 = """Goal:
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X : UU
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Y : UU
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P : UU
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X0 : X × Y → P
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x : X
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============================
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(Y → P)"""
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unimath2 = """Goal:
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R : ring M : module R
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(islinear (idfun M))"""
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unimath3 = """Goal:
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X : UU i : nat b : hProptoType (i < S i) x : Vector X (S i) r : i = i
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(pr1 lastelement = pr1 (i,, b))"""
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unimath4 = """Goal:
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X : dcpo CX : continuous_dcpo_struct X x : pr1hSet X y : pr1hSet X
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============================
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(x ⊑ y ≃ (∀ i : approximating_family CX x, approximating_family CX x i ⊑ y))"""
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additional_info_prompt = "/-Explain using mathematics-/"
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examples = [
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[unimath1, additional_info_prompt, 1200],
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model_name = "Goedel-LM/Goedel-Prover-SFT"
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tokenizer = AutoTokenizer.from_pretrained(model_name)
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model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
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# Set generation config
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model.generation_config = GenerationConfig.from_pretrained(model_name)
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model.generation_config.bos_token_id = 100000
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model.generation_config.eos_token_id = 100001
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@spaces.GPU
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def solve_math_problem(question, informal_prefix, max_tokens):
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# Format the prompt using Lean4 structure
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prompt = format_prompt(question, informal_prefix)
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input_ids = tokenizer(prompt, return_tensors="pt").input_ids.to(model.device)
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outputs = model.generate(
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input_ids,
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max_length=max_tokens + input_ids.shape[1],
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pad_token_id=model.generation_config.pad_token_id,
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temperature=1.0,
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top_p=0.95,
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)
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result = tokenizer.decode(outputs[0], skip_special_tokens=True)
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# Extract the full code from the response
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full_code = extract_code(prompt + result)
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# Create output dictionary similar to reference code
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output_data = {
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"model_input": prompt,
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"model_output": result,
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"full_code": full_code
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}
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return json.dumps(output_data, indent=2), full_code
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def main():
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iface = gr.Interface(
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You can also use 🔮Goedel Prover📉 by cloning this space. Simply click here: <a style="display:inline-block" href="https://huggingface.co/spaces/Tonic/Math?duplicate=true"><img src="https://img.shields.io/badge/-Duplicate%20Space-blue?labelColor=white&style=flat&logo=data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABAAAAAQCAYAAAAf8/9hAAAAAXNSR0IArs4c6QAAAP5JREFUOE+lk7FqAkEURY+ltunEgFXS2sZGIbXfEPdLlnxJyDdYB62sbbUKpLbVNhyYFzbrrA74YJlh9r079973psed0cvUD4A+4HoCjsA85X0Dfn/RBLBgBDxnQPfAEJgBY+A9gALA4tcbamSzS4xq4FOQAJgCDwV2CPKV8tZAJcAjMMkUe1vX+U+SMhfAJEHasQIWmXNN3abzDwHUrgcRGmYcgKe0bxrblHEB4E/pndMazNpSZGcsZdBlYJcEL9Afo75molJyM2FxmPgmgPqlWNLGfwZGG6UiyEvLzHYDmoPkDDiNm9JR9uboiONcBXrpY1qmgs21x1QwyZcpvxt9NS09PlsPAAAAAElFTkSuQmCC&logoWidth=14" alt="Duplicate Space"></a></h3>
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Join us : 🌟TeamTonic🌟 is always making cool demos! Join our active builder's 🛠️community 👻 [![Join us on Discord](https://img.shields.io/discord/1109943800132010065?label=Discord&logo=discord&style=flat-square)](https://discord.gg/GWpVpekp) On 🤗Huggingface: [TeamTonic](https://huggingface.co/TeamTonic) & [MultiTransformer](https://huggingface.co/MultiTransformer) Math with [introspector](https://huggingface.co/introspector) On 🌐Github: [Tonic-AI](https://github.com/tonic-ai) & contribute to🌟 [SciTonic](https://github.com/Tonic-AI/scitonic)🤗Big thanks to Yuvi Sharma and all the folks at huggingface for the community grant 🤗
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104 |
""",
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|
105 |
fn=solve_math_problem,
|
106 |
outputs=[
|
107 |
+
gr.JSON(label="Full Output"),
|
108 |
+
gr.Code(label="Extracted Lean4 Code", language="lean")
|
109 |
],
|
110 |
inputs=[
|
111 |
+
gr.Textbox(label="🤔Enter your Lean4 formal statement", lines=7),
|
112 |
+
gr.Textbox(value=additional_info_prompt, label="🪜Optional informal prefix"),
|
113 |
+
gr.Slider(minimum=150, maximum=2048, value=650, label="🪙Max Tokens")
|
114 |
],
|
115 |
examples=examples
|
116 |
)
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|
|
118 |
iface.launch()
|
119 |
|
120 |
if __name__ == "__main__":
|
121 |
+
main()
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