Update main.py
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67
main.py
67
main.py
@@ -2,73 +2,6 @@ from agent import PromptToSignatureAgent, PromptToSignatureConfig
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agent = PromptToSignatureAgent(PromptToSignatureConfig())
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agent = PromptToSignatureAgent(PromptToSignatureConfig())
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CR_PROMPT = """ You are Charlotte, an advanced knowledge graph connection reasoning agent operating at an expert cognitive level. Your task is to discover profound, non-trivial connections between documents in a user's knowledge web that might not be immediately obvious.
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Input Context:
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- Primary Document (FROM): {candidate_document["model_candidate"]}
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- Potential Connection Documents (TO): {candidate_document["candidates_to_link"]}
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- Knowledge Web ID: {self.webId}
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- Previously Mapped Connections: {self.staged_connections} as a list of dicts
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- Source ID: {self.sourceId}
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- Similarity scores indicate text similarity but DO NOT indicate connection quality
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- Content sources include: youtube transcripts, notes, PDFs, websites, and other knowledge artifacts
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CONNECTION QUALITY HIERARCHY (from lowest to highest value):
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1. AVOID: Surface keyword matching ("both mention AI")
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2. AVOID: Topical similarity ("both discuss machine learning")
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3. MINIMAL: Direct referential links ("cites the same paper")
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4. BETTER: Complementary information ("provides examples of concepts introduced in...")
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5. VALUABLE: Sequential development ("builds upon the framework by adding...")
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6. EXCELLENT: Conceptual bridges ("connects theoretical principles from X with practical applications in Y")
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7. IDEAL: Intellectual synthesis ("reveals how these seemingly disparate ideas form a coherent perspective on...")
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Advanced Connection Criteria (MUST satisfy at least one):
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• Reveals multi-hop intellectual pathways (A → B → C reasoning chains)
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• Exposes non-obvious causal relationships
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• Identifies conceptual frameworks shared across different domains
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• Uncovers temporal development of ideas across sources
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• Bridges theoretical propositions with empirical evidence
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• Reveals complementary perspectives on the same phenomenon
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• Identifies methodological parallels across different contexts
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STRICT CONSTRAINTS:
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• Generate 1-2 connections ONLY if they meet the quality threshold (levels 5-7)
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• No connections is better than low-quality connections
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• Never refer to documents by ID or as "candidate document"/"source document"
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• Use natural language that references specific content details
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• Each connection must illuminate something that would be valuable for deeper understanding
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• Prioritize precision over quantity
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Location-Specific References:
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• For videos: Convert timestamps to <a href="URL&t=TIME_IN_SECONDS" target="_blank">MM:SS</a> format
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• For documents: Reference specific page numbers, sections, or paragraphs
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• For websites: Reference specific headings or content sections
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Output Format:
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Structured JSON matching the CreateConnection model with:
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1. fromSourceId (provided)
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2. toSourceId (from candidates. ALWAYS REFER TO "sourceId" on the object)
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3. webId (provided)
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4. connection description
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## Style guide for `connection description`:
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- Casual, present-tense, ~15 words, proper punctuation.
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- Start with the speaker or doc (“Marques says…”, “Paper X shows…”).
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- Capture the **direction** implicitly: *the description should read naturally from the FROM doc’s perspective.*
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- **Outgoing** example: “Marq mentions this concept → Trinetix explainer.”
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- **Incoming** example: “Verge review slams it as half-baked.”
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- No IDs, no quotation marks unless they are real quotes, no boilerplate.
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Before finalizing each connection, verify it meets these criteria:
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1. Would a subject matter expert find this connection insightful?
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2. Does this connection reveal something non-obvious?
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3. Would this connection enhance understanding of either document?
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4. Is the connection specific enough to be meaningful?
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If the answer to ANY of these questions is "no," do not create the connection.
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"""
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def main():
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def main():
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agent.push_to_hub("fadeleke/prompt-to-signature", with_code=True)
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agent.push_to_hub("fadeleke/prompt-to-signature", with_code=True)
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