--- title: "Batch forecast multiple prediction market questions concurrently" method: POST path: "/predict/batch" tags: ["Inference"] --- # Batch forecast multiple prediction market questions concurrently `POST /predict/batch` ## Request - Base URL: `https://foresea.ink` (the document declares no server; this is the origin it was published from) - URL: `https://foresea.ink/predict/batch` - Auth: none declared Submit up to 25 forecasting questions and receive concurrent structured predictions. ## Request body - BatchPredictRequest - `items` PredictRequest[], required: List of forecasting requests (max 25) - `question` string, required: The forecasting question to evaluate. It should ask about a future or otherwise resolvable event, option, quantity, or date. - `description` string: Extended background context that clarifies what the question is asking. - `resolution_criteria` string: Full venue conditions and measurement source used to resolve the forecast. - `categories` string[]: Topic tags (e.g. `['Economics', 'United States']`). - `news_articles` NewsArticle[]: Pre-fetched venue or caller news articles to preserve as evidence. When `attach_evidence` is true, fresh retrieved news is merged with them. - `title` string, nullable: Article headline. - `summary` string, nullable: Short human-written summary. - `summary_llm` string, nullable: LLM-generated summary. - `text` string, nullable: Full article body text. - `source` string, nullable: Publisher name (e.g. Reuters). - `credibility` object, nullable: Credibility score breakdown. - `frs` object, nullable: Future-Resolution Statement metadata. - `url` string, nullable: Canonical article URL. - `authors` unknown - `publish_date` string, nullable: ISO 8601 publish timestamp. - `keywords` unknown - `relevance_score` number, nullable: Cosine similarity to the question (0–1). - `search_query` string, nullable: Query used to retrieve this article. - `variant` string: Prompt variant that controls the reasoning instruction style. See the variant table in the Overview section. - `attach_evidence` boolean: If `true`, fetch live evidence and merge it with any supplied articles. - `evidence_top_k` integer: Maximum number of evidence articles to retrieve (1–100). - `evidence_detail` string: Evidence detail level in the model prompt. Use `summary` for scheduled multi-model runs to keep prompts bounded; default `full` preserves the interactive API behaviour. - `created_time` string, nullable: ISO 8601 question creation time. - `publish_time` string, nullable: ISO 8601 question publish time. - `resolve_time` string, nullable: ISO 8601 resolution deadline. - `days_open` integer, nullable: Days the question has been open. - `history` object[]: Prior conversation turns for multi-turn context, oldest first. Each item is `{"role": "user"|"assistant", "content": "..."}`. - `conversation_steer` string: Optional per-conversation steering instruction for tone, emphasis, or analytical stance. It cannot override safety rules or response contracts. - `question_type` string, nullable: Question type: `binary`, `multiple_choice`, `numeric`, or `date`. Set this explicitly for API clients; auto-detected from the question when omitted. - `options` string[]: Candidate answers for `multiple_choice` questions (optional; the model can infer them). - `market_platform` string, nullable: Prediction market venue, e.g. `Polymarket`, `Kalshi`, `Manifold`, or `Metaculus`. - `market_url` string, nullable: URL for the prediction market being analyzed. Must start with `http://` or `https://`. - `market_outcome` string, nullable: Outcome whose market-implied probability is provided. Defaults to `Yes` for binary markets; set this to `No` or to a multiple-choice option label when needed. - `market_ident` string, nullable: Venue market id (Polymarket slug / Kalshi ticker). Lets Foresea fetch live odds when `market_probability` is omitted. - `market_probability` number, nullable: Current market-implied probability for `market_outcome`. Use 0-1, or pass a percentage from 0-100 and Foresea will normalize it. When omitted but the market is identifiable (`market_url` or `market_platform`+`market_ident`), Foresea fetches the current live odds. - `market_volume` number, nullable: 24-hour trading volume in USD. Populated automatically from live odds when the market is identifiable. - `market_liquidity` number, nullable: Total open interest / liquidity in USD. Populated automatically from live odds. - `market_price_change_24h` number, nullable: Price change in the last 24 hours (in probability points, -1..1). Populated automatically from live odds. - `market_bid` number, nullable: Current best bid (YES) in probability units (0..1). Kalshi only; Polymarket uses the mid price. - `market_ask` number, nullable: Current best ask (YES) in probability units (0..1). Kalshi only. - `market_last_trade_price` number, nullable: Last actual trade price (0..1). More reliable than resting bid/ask in thin markets. Populated automatically. - `market_price_change_7d` number, nullable: 7-day price change in probability points (-1..1). Reveals slow drift that 24h misses. Populated automatically. - `market_resolution_source` string, nullable: Who resolves the market (e.g. UMA oracle, Kalshi team). Affects how much to trust the market price. - `market_no_sub_title` string, nullable: What the NO outcome represents (Kalshi). Useful when the question wording is ambiguous. - `market_expected_expiration_time` string, nullable: When the venue expects to settle (Kalshi). May differ from trading close date. - `market_floor_strike` unknown - `market_cap_strike` unknown - `market_price_history` object[], nullable: Recent price points for this market, newest first. Each entry: {ts: ISO timestamp, probability: float 0..1, volume?: float, liquidity?: float, bid?: float, ask?: float}. Up to 8 entries. Shown to the model as market-trajectory context so it can detect price and tradability changes that the current price alone would hide. - `forecast_history` object[], nullable: Prior Foresea forecast snapshots for the same market, newest first. Used by scheduled re-forecasts so repeat forecasts are stateful updates, not independent stateless calls. - `openrouter_api_key` string, nullable: User-supplied OpenRouter API key. When set, this request is routed through OpenRouter using `openrouter_model` instead of the server's default provider. - `openrouter_model` string, nullable: OpenRouter model ID (e.g. `openai/gpt-4o`, `anthropic/claude-3.5-sonnet`). - `model` string, nullable: Optional alternate server-hosted model to forecast with, from the SCADS allowlist (for example `gpt-oss-120b`, `scads-alias-reasoning`, `kimi-k2.7-code`). Uses the server's own key — no BYOK needed. Powers the multi-model paper-trading comparison. - `provider_base_url` string, nullable: Optional OpenAI-compatible chat-completions endpoint (e.g. `https://api.openai.com/v1/chat/completions`). When set with `openrouter_api_key` + `openrouter_model`, the request goes to your own endpoint instead of OpenRouter. Must be public HTTPS. - `chat_mode` boolean: When `true`, skips the forecast output template entirely. The model responds in plain natural language with no structured JSON. - `effort_tier` 'simple' | 'standard' | 'deep', nullable: How much reasoning effort the model call uses, when the provider supports it (best-effort; unsupported providers ignore it). Set explicitly to override; left unset, no reasoning-effort hint is sent. - `max_tokens` integer, nullable: Optional per-request generation cap. The server still clamps this to its configured model limit. - `ollama_base_url` string, nullable: Base URL of an Ollama instance, e.g. `http://localhost:11434`. No API key required. Cloud-metadata hosts are blocked; for foresea.ink the instance must be reachable from the server. - `concurrency_limit` integer: Max concurrent model calls ## Response `200` Successful Response - BatchPredictResponse - `results` PredictResponse[], required - `question_type` string: Detected type: `binary`, `multiple_choice`, `numeric`, or `date`. - `predicted_answer` string, nullable: Headline answer: Yes/No, the top option, or the median estimate. - `confidence` number, nullable: Confidence in the headline answer (binary/MC). Null for numeric. - `model_probability` number, nullable: Explicit model probability for conversational forecasts, when one was provided. - `options` OptionProb[]: Per-option probabilities for `multiple_choice`. - `label` string, required: The option text. - `probability` number, required: Probability assigned to this option (0–1). - `range_forecast` RangeForecast: A numeric or date estimate expressed as percentile bounds. - `p10` string, nullable: 10th-percentile (low) estimate. - `p50` string, nullable: 50th-percentile (median) estimate. - `p90` string, nullable: 90th-percentile (high) estimate. - `unit` string, nullable: Unit of the estimate, e.g. 'USD', '%', 'people'. - `rationale` string, nullable: 2–4 sentence explanation of the prediction. - `model_rationale` string, nullable: Raw rationale as returned by the model (may differ from `rationale` after post-processing). - `variant` string, required: Prompt variant used for this prediction. - `model_key` string, required: Model identifier (e.g. `gpt-oss-120b`). - `served_model_name` string, nullable: Exact upstream model name that served the response, if reported by the provider. - `evidence_sources` EvidenceSource[]: Deduplicated citations used as evidence. - `source` string, required: Publisher name. - `title` string, nullable: Article headline. - `url` string, nullable: Article URL. - `publish_date` string, nullable: ISO 8601 publish date. - `relevance_score` number, nullable: Relevance to the question (0–1). - `evidence_articles` NewsArticle[]: Full evidence articles passed to the model. - `title` string, nullable: Article headline. - `summary` string, nullable: Short human-written summary. - `summary_llm` string, nullable: LLM-generated summary. - `text` string, nullable: Full article body text. - `source` string, nullable: Publisher name (e.g. Reuters). - `credibility` object, nullable: Credibility score breakdown. - `frs` object, nullable: Future-Resolution Statement metadata. - `url` string, nullable: Canonical article URL. - `authors` unknown - `publish_date` string, nullable: ISO 8601 publish timestamp. - `keywords` unknown - `relevance_score` number, nullable: Cosine similarity to the question (0–1). - `search_query` string, nullable: Query used to retrieve this article. - `evidence_error` string, nullable: Non-null if evidence retrieval failed (prediction still returned). - `market_analysis` MarketAnalysis: Deterministic comparison between Foresea's forecast and a market price. - `platform` string, nullable: Prediction market venue supplied by the caller. - `market_url` string, nullable: Prediction market URL supplied by the caller. - `outcome` string, required: Outcome being compared against the market price. - `market_probability` number, required: Market-implied probability for the outcome. - `model_probability` number, nullable: Foresea probability for the same outcome (recalibrated from the live track record when warranted). - `model_probability_raw` number, nullable: Raw model probability before live calibration (only set when calibration was applied). - `edge` number, nullable: Model probability minus market probability. - `stance` string, required: `model_above_market`, `model_below_market`, `in_line`, or `not_comparable`. - `summary` string, required: Short human-readable market comparison. - `complexity` string, nullable: Model's own self-reported difficulty for this question: `low` or `high`. - `bull_factors` object[], nullable: Decomposed factors favoring the YES / upside outcome. - `bear_factors` object[], nullable: Decomposed counter-factors favoring the NO / downside outcome. - `key_catalysts` object[], nullable: Key upcoming events/dates that could trigger thesis revision. - `total` integer, required - `successful` integer, required - `failed` integer, required - `elapsed_ms` number, required ## Other responses - `422`: Validation Error --- [API](https://skmtc.dev/foresea/apis/foresea-intelligence-api.md) · [All operations](https://skmtc.dev/foresea/apis/foresea-intelligence-api/llms.txt) · [OpenAPI document](https://skmtc.dev/foresea/apis/foresea-intelligence-api/revisions/b03e49f4385d?raw)