47 lines
4.5 KiB
JSON
47 lines
4.5 KiB
JSON
{
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"generate_cypher.predict": {
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"traces": [],
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"train": [],
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"demos": [],
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"signature": {
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"instructions": "text\nTask: Given (1) a natural-language question and (2) a Neo4j schema description, output exactly ONE Cypher query that answers the question.\n\nINPUTS\n- question: the user request in natural language.\n- neo4j_schema: schema info given either as:\n (a) JSON-like dict describing node labels, relationship types, directions, and properties, OR\n (b) a textual summary listing node labels with properties and a list of allowed relationships as {start, type, end}, plus any relationship properties.\n\nABSOLUTE REQUIREMENTS (must follow)\n1) Output ONLY the Cypher query text.\n - No reasoning, no explanations, no markdown/code fences, no headings, no extra characters.\n2) Use ONLY labels, relationship types, directions, and properties that appear in neo4j_schema.\n - Do NOT invent labels/properties/relationships.\n - If the question asks for something not representable, produce the closest possible query using only the schema.\n3) Respect relationship direction exactly as specified.\n - If schema says Article -[:PUBLISHED_IN]-> Journal, do not reverse it.\n - In JSON-like schemas, relationship direction may be expressed as \"in\" or \"out\" under a node\u2019s \"relationships\"; interpret it relative to that node.\n4) Return ONLY what the question asks for.\n - If it asks for \u201ctitle values\u201d, return a.title (not whole nodes).\n - If it asks for counts, return counts with clear aliases.\n - Use DISTINCT when the question implies uniqueness.\n5) Produce exactly one valid Cypher statement.\n\nQUERY CONSTRUCTION RULES / COMMON PITFALLS TO AVOID\nA) Filtering on relationship properties:\n - Put relationship property predicates on the relationship pattern or in WHERE, using correct Cypher syntax.\n - Example: MATCH (a)-[r:PUBLISHED_IN]->(j) WHERE r.meta = '220'\n - IMPORTANT: use Cypher string literals with single quotes (e.g., '220'), not JSON-style quotes.\nB) \u201cFirst N\u201d / \u201cN items\u201d semantics:\n - If the question requests \u201cfirst 3\u201d or \u201c20 Article\u201d, include LIMIT N.\n - If \u201cfirst\u201d implies ordering but no explicit sort key is given in schema/question, you may use LIMIT without ORDER BY.\n - Do NOT return more columns than asked just to justify \u201cfirst\u201d.\nC) Aggregations and grouping:\n - When returning both a field and a count, group by the non-aggregated field via WITH/RETURN.\n - Apply HAVING-like filters using WITH ... WHERE (e.g., cities with >1 student).\n - Example pattern:\n MATCH (s:Student)\n WITH s.city_code AS city, count(*) AS student_count\n WHERE student_count > 1\n RETURN city, student_count\nD) Date/time duration questions:\n - Use only functions that work with the property datatypes shown.\n - If begin/end are DATE_TIME, you may use duration/between logic; prefer robust checks:\n - If asked \u201cexactly one month\u201d, check the full duration equals duration({months:1}) when possible, or use duration.between(f.begin, f.end) and compare appropriately.\n - Do not introduce alternative date properties that aren\u2019t requested unless necessary and present in schema.\nE) String matching:\n - For prefix constraints, use STARTS WITH.\n - For exact text match, use equality.\nF) Combining strings/properties:\n - Use `+` for concatenation and alias with AS as requested.\n\nOUTPUT\n- Exactly one Cypher query, and nothing else.",
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"fields": [
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{
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"prefix": "Question:",
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"description": "Question to model using a cypher statement. Use only the provided relationship types and properties in the schema."
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},
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{
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"prefix": "Neo 4 J Schema:",
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"description": "Current graph schema in Neo4j as a list of NODES and RELATIONSHIPS."
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},
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{
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"prefix": "Reasoning: Let's think step by step in order to",
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"description": "${reasoning}"
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},
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{
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"prefix": "Statement:",
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"description": "Cypher statement to query the graph database."
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}
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]
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},
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"lm": {
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"model": "openrouter/openai/gpt-4o",
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"model_type": "chat",
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"cache": true,
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"num_retries": 3,
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"finetuning_model": null,
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"launch_kwargs": {},
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"train_kwargs": {},
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"temperature": null,
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"max_tokens": 1024,
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"api_base": "https://openrouter.ai/api/v1"
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}
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},
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"metadata": {
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"dependency_versions": {
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"python": "3.13",
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"dspy": "3.0.4",
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"cloudpickle": "3.1"
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}
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}
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} |