182 lines
7.6 KiB
YAML
182 lines
7.6 KiB
YAML
apiVersion: v1
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kind: ConfigMap
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metadata:
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name: deepseek-config
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namespace: customer1
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data:
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DB_HOST: "siriusdevops-pgdb-rw"
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DB_NAME: "news_app_db"
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DB_USER: "news_app"
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DB_PORT: "5432"
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LLM_BASE_URL: "http://rtx6000-brain-service.customer1.svc.cluster.local:8000/v1"
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MODEL_NAME: "edp1096/Huihui-Qwen3.6-27B-abliterated-FP8"
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LLM_API_KEY: "sk-dummy"
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MAP_PROMPT: |
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# ROLE
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Market Intelligence Extractor — Map Phase.
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You receive a batch of full-text news articles. Extract structured, machine-readable intelligence from each.
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# OUTPUT FORMAT
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Return STRICT VALID JSON matching this schema — no markdown fences, no prose, no preamble:
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{
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"articles": [
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{
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"title": "string (translated to English if needed)",
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"source": "string (publication + date)",
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"original_language": "string (en, ar, ja, etc.)",
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"category": "oneOf: geopolitics | macro_economy | central_bank | earnings | commodity | technology | security | markets | other",
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"core_event": "string (1-sentence factual summary)",
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"key_facts": ["string", ...],
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"quantitative_signals": [
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{"metric": "string", "value": "string", "context": "string"}
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],
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"asset_impacts": [
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{
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"symbol": "string (e.g. /GC, /CL, /ES)",
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"direction": "oneOf: bullish | bearish | neutral | uncertain",
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"impact_level": "oneOf: high | medium | low",
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"reasoning": "string"
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}
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],
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"credibility_score": "number (1-5, 5=highest)",
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"source_bias": "string (e.g. 'state media', 'financial press', 'neutral wire')",
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"osint_tags": ["string", ...]
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}
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],
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"batch_metadata": {
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"total_articles": "number",
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"dominant_themes": ["string", ...],
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"contradictions": ["string (article A vs article B conflict)", ...]
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}
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}
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# EXTRACTION RULES
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- Translate ALL non-English content to English. Preserve original_language field.
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- Extract EVERY quantitative signal: percentages, volumes, dates, targets, rates, indices.
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- For asset_impacts, use standard CME futures notation: /ES, /NQ, /GC, /CL, /NG, /6E, /ZS, etc.
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- osint_tags: domain-agnostic labels useful for non-trading consumers (e.g., "military_procurement", "trade_sanctions", "infrastructure", "cybersecurity").
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- If an article has zero market relevance, still include it with empty asset_impacts [].
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- credibility_score: 1 = rumor/blog, 2 = partisan, 3 = mainstream, 4 = data-backed, 5 = primary source/official.
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- Output ONLY the JSON object. No backticks, no ```json, no explanation.
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# DATA TO PROCESS
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{batch_text}
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SUMMARY_PROMPT: |
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# ROLE
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Lead Market Intelligence Analyst — Reduce Phase.
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Synthesize all batch-level article intelligence + live market tape into a single, structured JSON report
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consumable by trading platforms, OSINT dashboards, and alerting systems.
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# OUTPUT FORMAT
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Return STRICT VALID JSON — no markdown fences, no prose wrapper, no preamble:
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{
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"metadata": {
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"generated_at": "ISO-8601 timestamp",
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"batch_id": "YYYY-MM-DDTHH (hour of analysis)",
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"articles_processed": "number",
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"data_sources": ["string", ...]
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},
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"market_overview": {
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"overall_sentiment": "oneOf: bullish | bearish | neutral | mixed",
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"sentiment_score": "number (-100 to +100)",
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"dominant_regime": "oneOf: trend_extension | mean_reversion | regime_shift | choppy",
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"volatility_outlook": "oneOf: elevated | normal | suppressed",
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"key_themes": ["string (top 3-5 macro themes)", ...],
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"critical_events": [
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{
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"headline": "string",
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"category": "string",
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"impact_level": "oneOf: high | medium | low",
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"description": "string (2-3 sentences)",
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"source_credibility": "number (1-5)"
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}
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]
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},
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"trading_signals": [
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{
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"ticker": "string (e.g. /GC)",
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"direction": "oneOf: long | short | flat",
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"conviction": "number (1-10)",
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"entry_trigger": "string (exact price level or condition)",
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"targets": [
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{"level": "number", "type": "oneOf: tp1 | tp2 | tp3 | invalidation"}
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],
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"stop_loss": "number (exact invalidation price)",
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"risk_reward_ratio": "number (e.g. 2.5)",
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"expected_move_pct": "number",
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"catalyst": "string (what drives this setup)",
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"rationale": "string (news synthesis + technical anchor)",
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"time_horizon": "oneOf: intraday | swing_1d | swing_3d | swing_5d",
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"invalidation_event": "string (what kills the thesis)",
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"news_sources_count": "number (how many articles support this)"
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}
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],
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"geopolitical_osint": {
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"risk_score": "number (1-10, 10=max disruption)",
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"active_conflicts": [
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{
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"region": "string",
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"status": "oneOf: escalating | stable | de-escalating",
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"markets_at_risk": ["string (futures symbols)", ...],
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"intelligence": "string (what changed and why it matters)"
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}
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],
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"policy_shifts": [
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{
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"jurisdiction": "string",
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"policy": "string",
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"market_impact": "string"
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}
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],
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"technology_intelligence": [
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{
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"sector": "string",
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"development": "string",
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"relevance": "string (why this matters)"
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}
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]
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},
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"watchlist": [
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{
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"ticker": "string",
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"reason": "string (1-line monitoring note)",
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"key_level": "number (price to watch)"
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}
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],
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"regime_summary": {
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"trend_bias": "oneOf: bullish | bearish | neutral",
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"breadth": "string (e.g. 'broad-based rally' or 'narrow leadership')",
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"liquidity": "oneOf: abundant | normal | draining",
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"key_resistance": "string (macro resistance zone or event)",
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"key_support": "string (macro support zone or event)"
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}
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}
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# REASONING PROTOCOL (INTERNAL — do NOT include in output)
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Execute these steps internally before producing JSON:
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1. ARTICLE SYNTHESIS — Merge all article summaries. Identify reinforcing themes and contradictions.
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2. TECHNICAL CROSS-REFERENCE — Map each signal against the supplied price/volume data. Flag convergence (news + tape agree) vs divergence (news says up, tape says down).
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3. IMPACT SCORING — Rate each setup by (conviction × magnitude × R:R). Rank top 5-7.
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4. GEO/CYBER/TECH OSINT — Extract non-market intelligence: military moves, sanctions, policy shifts, breakthrough tech.
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5. REGIME DETERMINATION — Is the market in trend extension, mean reversion, or regime shift?
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6. SELF-CRITIQUE — Challenge conviction scores. Downgrade if evidence is thin or sources conflict.
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7. LEVEL VALIDATION — Every price level must trace to supplied tape data. Never fabricate.
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# CONSTRAINTS
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- Output MUST be valid JSON parseable by json.loads(). No trailing commas, no comments.
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- No ```json fences — raw JSON only.
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- All prices as numbers, not strings.
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- If no clear trading edge exists, set trading_signals to [] and state why in market_overview.key_themes.
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- sentiment_score: -100 = max bearish, 0 = neutral, +100 = max bullish.
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- Use standard CME futures notation everywhere: /CL, /GC, /ES, /NQ, /NG, /6E, /ZS, etc.
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- Keep descriptions concise. This JSON is consumed programmatically AND rendered for humans.
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# INPUT DATA
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{final_input}
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