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Diego Carpintero
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Parent(s):
3b3351d
add description
Browse files
app.py
CHANGED
@@ -5,26 +5,25 @@ from minerva import Minerva
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from formatter import AutoGenFormatter
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title = "Minerva:
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description = """
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Submission for RBI Berkeley, CS294/194-196, LLM Agents (Diego Carpintero)
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"""
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inputs = gr.components.Image()
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outputs = [
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@@ -32,7 +31,7 @@ outputs = [
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gr.HTML(label="Agentic Workflow (Streaming)")
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]
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examples = "examples"
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example_labels = ["EN:Gift:Social", "ES:Banking:Social", "EN:Billing:SMS", "EN:Multifactor:Email", "EN:CustomerService:Twitter"]
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model = Minerva()
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formatter = AutoGenFormatter()
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from formatter import AutoGenFormatter
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title = "Minerva: LLM Agents for Scam Protection"
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description = """
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π¦ Minerva uses LLM Agents to analyze screenshots for potential scams. </br>
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π’ It provides the analysis in the language of the extracted text.</br></br>
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π <b>Try out one of the examples to perform a scam analysis. </b></br>
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βοΈ The Agentic Workflow is streamed for demonstration purposes. </br></br>
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π΅ LLM Agents coordinated as an AutoGen Team in a RoundRobin fashion: </br>
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- *OCR Specialist* </br>
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- *Link Checker* </br>
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- *Content Analyst* </br>
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- *Decision Maker* </br>
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- *Summary Specialist* </br>
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- *Language Translation Specialist* </br></br>
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π§βπ»οΈ https://github.com/dcarpintero/minerva </br>
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π Submission for RBI Berkeley, CS294/194-196, LLM Agents (Diego Carpintero)</br></br>
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β₯οΈ Built with AutoGen 0.4.0 and OpenAI.
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"""
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inputs = gr.components.Image()
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outputs = [
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gr.HTML(label="Agentic Workflow (Streaming)")
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]
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examples = "examples"
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example_labels = ["EN:Gift:Social", "ES:Banking:Social", "EN:Billing:SMS", "EN:Multifactor:Email", "EN:CustomerService:Twitter", "00:Landscape.HAM"]
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model = Minerva()
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formatter = AutoGenFormatter()
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