saksham
1a4c80958f
FastAPI + Celery + Next.js + Postgres/Redis app with company monitoring, source collection, LLM-based change analysis, enrichment, and account security (Turnstile, escalating lockout, email verification).
118 lines
4.0 KiB
Python
118 lines
4.0 KiB
Python
"""Renders a ReportContent (structured, from the LLM) into the Markdown
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document the API/UI serve alongside the JSON - see spec section 6G for the
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16-section layout this follows.
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"""
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from __future__ import annotations
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from app.prompts.report_generation import Finding, InferredProject, ReportContent
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def _render_findings(findings: list[Finding]) -> str:
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if not findings:
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return "_No findings for this section from the current evidence._\n"
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lines = []
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for f in findings:
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lines.append(f"- **{f.headline}** _(confidence: {f.confidence.value.replace('_', ' ')})_")
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lines.append(f" {f.summary}")
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if f.date:
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lines.append(f" _Date: {f.date}_")
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return "\n".join(lines) + "\n"
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def _render_projects(projects: list[InferredProject]) -> str:
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if not projects:
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return "_No inferred strategic projects from the current evidence._\n"
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lines = []
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for p in projects:
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lines.append(
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f"- **{p.project_name}** _({p.status.value.replace('_', ' ')}, confidence {p.confidence:.0%})_"
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)
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lines.append(f" {p.summary}")
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if p.alternative_explanations:
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lines.append(f" Alternative explanations: {'; '.join(p.alternative_explanations)}")
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return "\n".join(lines) + "\n"
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def _render_list(items: list[str]) -> str:
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if not items:
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return "_None noted._\n"
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return "\n".join(f"- {item}" for item in items) + "\n"
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def render_report_markdown(
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content: ReportContent,
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*,
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company_name: str,
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generated_at: str,
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model_provider: str,
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model_name: str,
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sources: list[dict],
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) -> str:
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parts = [
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f"# Competitive Intelligence Report: {company_name}",
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f"_Generated {generated_at} · {model_provider}/{model_name}_",
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"",
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"## 1. Executive Summary",
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content.executive_summary,
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"",
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"## 2. Company Overview",
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content.company_overview,
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"",
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"## 3. Products and Service Landscape",
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_render_findings(content.products_and_services),
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"## 4. Recent Developments",
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_render_findings(content.recent_developments),
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"## 5. Strategic Initiatives",
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_render_findings(content.strategic_initiatives),
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"## 6. Key Project Signals",
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_render_projects(content.key_inferred_projects),
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"## 7. Competitive Positioning",
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content.market_positioning,
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"",
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content.competitor_comparison,
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"",
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"## 8. SWOT Analysis",
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"**Strengths**",
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_render_list(content.swot.strengths),
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"**Weaknesses**",
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_render_list(content.swot.weaknesses),
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"**Opportunities**",
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_render_list(content.swot.opportunities),
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"**Threats**",
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_render_list(content.swot.threats),
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"## 9. Hiring Signals",
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_render_findings(content.hiring_signals),
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"## 10. Product and Technology Signals",
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_render_findings(content.technology_signals + content.patent_signals),
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"## 11. Customer Sentiment",
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content.customer_sentiment,
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"",
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"## 12. Financial and Regulatory Signals",
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_render_findings(content.financial_signals + content.regulatory_and_legal_signals),
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"## 13. Risks and Opportunities",
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"**Risks**",
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_render_list(content.risks),
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"**Opportunities**",
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_render_list(content.opportunities),
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"## 14. Important Unknowns",
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_render_list(content.unknowns_and_missing_data),
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"## 15. Sources",
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_render_sources(sources),
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"## 16. Methodology and Limitations",
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content.methodology,
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"",
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content.limitations,
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]
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return "\n".join(str(p) for p in parts)
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def _render_sources(sources: list[dict]) -> str:
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if not sources:
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return "_No sources recorded for this report._\n"
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lines = [
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f"- [{s.get('title') or s.get('url')}]({s.get('url')}) — retrieved {s.get('retrieved_date')}"
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for s in sources
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]
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return "\n".join(lines) + "\n"
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