backend: render AI import approval card instead of raw tool_code

Give previewImport a concrete object schema (was z.array(z.unknown())) so
Google Gemini can emit a real function call — an array-of-unknown serializes
to an empty JSON schema, which made Gemini print the call as a `tool_code`
text block instead of invoking the tool. Validation stays lenient in
execute() via patientInputSchema. Also strengthen the system prompt: never
print tool calls/JSON or re-list record fields; keep prose to one sentence.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
This commit is contained in:
Khalid Abdi
2026-06-27 21:32:58 +03:00
parent c82ba4b33e
commit b2ac27dda7
4 changed files with 102 additions and 6 deletions
+96 -4
View File
@@ -648,12 +648,104 @@ export function createChatTools(ctx: ToolContext) {
previewImport: tool({
description:
"Validate patient records parsed from an uploaded database export, as a dry run. Does NOT save anything. Call this when the clinician wants to import/migrate an existing patient database OR add a single patient; parse the file into our patient shape first. The clinician must approve before any data is written.",
// A concrete object schema (not z.unknown()): Google Gemini can only emit a
// real function call when the tool's parameters have a defined JSON schema.
// An array-of-unknown serializes to an empty schema, which makes Gemini
// print the call as `tool_code` text instead of invoking it. Validation
// stays lenient — execute() re-parses each record with patientInputSchema,
// which coerces gender words, bare-string lists, etc.
inputSchema: z.object({
records: z
.array(z.unknown())
.describe(
"Patient records mapped to temetro's shape (fileNumber, name, age, sex, vitals, labs, medications, problems, allergies, encounters).",
),
.array(
z.object({
fileNumber: z
.string()
.optional()
.describe(
"File number / MRN; digits only (leave blank to auto-generate)",
),
name: z.string().describe("Patient full name"),
age: z.number().optional().describe("Age in years"),
sex: z
.string()
.optional()
.describe("Sex — accepts Male/Female or M/F"),
status: z
.string()
.optional()
.describe("active, inpatient, or discharged"),
pcp: z.string().optional().describe("Primary care provider name"),
alerts: z
.array(z.string())
.optional()
.describe("Free-text clinical alerts"),
allergies: z
.array(
z.object({
substance: z.string().describe("Allergen, e.g. Penicillin"),
reaction: z.string().optional(),
severity: z
.string()
.optional()
.describe("mild, moderate, or severe"),
}),
)
.optional(),
medications: z
.array(
z.object({
name: z.string(),
dose: z.string().optional(),
frequency: z.string().optional(),
}),
)
.optional(),
problems: z
.array(
z.object({
label: z.string().describe("Problem / diagnosis"),
since: z.string().optional(),
}),
)
.optional(),
labs: z
.array(
z.object({
name: z.string(),
value: z.string(),
flag: z
.string()
.optional()
.describe("normal, high, low, or critical"),
takenAt: z
.string()
.optional()
.describe("Date, YYYY-MM-DD"),
}),
)
.optional(),
encounters: z
.array(
z.object({
date: z
.string()
.optional()
.describe("Visit date, YYYY-MM-DD"),
type: z
.string()
.optional()
.describe("Visit type / department"),
provider: z.string().optional(),
summary: z
.string()
.optional()
.describe("Diagnosis / treatment / notes combined"),
}),
)
.optional(),
}),
)
.describe("Patient records parsed from the upload, mapped to temetro's shape"),
}),
execute: async ({ records }) => {
step(`Validating ${records.length} record(s)`);