# POST /api/chat-contract

Ask natural language questions about a specific contract. The QVAC AI engine answers based on the contract text and optionally the prior audit analysis.

***

## Request

```http
POST /api/chat-contract
Content-Type: application/json
```

**Body:**

```typescript
{
  contractText: string,          // Required — full contract text
  userQuestion: string,          // Required — the user's question
  analysisResult?: object,       // Optional — prior ContractReviewResult (improves answers)
  model?: string,                // Optional — QVAC tier: "fast" | "smart" | "best"
  lang?: "en" | "id"             // Optional — response language (default: "id")
}
```

***

## Response

```typescript
// 200 OK
{
  success: true,
  data: {
    answer: string              // Plain text answer from AI
  }
}
```

***

## Example

```bash
curl -X POST http://localhost:3000/api/chat-contract \
  -H "Content-Type: application/json" \
  -d '{
    "contractText": "PERJANJIAN JASA IT\n...",
    "userQuestion": "Apakah ada klausul penalti jika proyek terlambat?",
    "lang": "id"
  }'
```

```json
{
  "success": true,
  "data": {
    "answer": "Berdasarkan kontrak, klausul penalti keterlambatan terdapat di Pasal 9 ayat 2. Disebutkan bahwa kontraktor dikenakan denda 0.1% per hari keterlambatan dari nilai kontrak, maksimal 5%. Namun perlu diperhatikan bahwa klausul ini hanya berlaku untuk kontraktor — tidak ada penalti setara untuk keterlambatan pembayaran dari klien."
  }
}
```

***

## Suggested Questions

* "Apakah ada klausul yang merugikan kontraktor?"
* "Berapa total nilai kontrak dan jadwal pembayarannya?"
* "Apa kewajiban saya di Pasal 4?"
* "Apakah hak kekayaan intelektual sudah diatur dengan jelas?"
* "Does this contract comply with Indonesian labor law?"

***

## Notes

* Passing `analysisResult` from a prior `/api/audit` call significantly improves answer quality, as the AI has the context of the full analysis
* The AI answers in the same language as the `lang` parameter
* Responses are plain text (not JSON within the answer)
* All inference runs locally via QVAC SDK (`chatContract` function in `app/lib/contractAgent.ts`)


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://contractguard-ai.gitbook.io/contractguard-ai-docs/api-reference/chat-contract.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.