feat: structured output (#17877)

api/core/llm_generator/llm_generator.py

@@ -10,6 +10,7 @@ from core.llm_generator.prompts import (
     GENERATOR_QA_PROMPT,
     JAVASCRIPT_CODE_GENERATOR_PROMPT_TEMPLATE,
     PYTHON_CODE_GENERATOR_PROMPT_TEMPLATE,
+    SYSTEM_STRUCTURED_OUTPUT_GENERATE,
     WORKFLOW_RULE_CONFIG_PROMPT_GENERATE_TEMPLATE,
 )
 from core.model_manager import ModelManager
@@ -340,3 +341,37 @@ class LLMGenerator:
 
         answer = cast(str, response.message.content)
         return answer.strip()
+
+    @classmethod
+    def generate_structured_output(cls, tenant_id: str, instruction: str, model_config: dict):
+        model_manager = ModelManager()
+        model_instance = model_manager.get_model_instance(
+            tenant_id=tenant_id,
+            model_type=ModelType.LLM,
+            provider=model_config.get("provider", ""),
+            model=model_config.get("name", ""),
+        )
+
+        prompt_messages = [
+            SystemPromptMessage(content=SYSTEM_STRUCTURED_OUTPUT_GENERATE),
+            UserPromptMessage(content=instruction),
+        ]
+        model_parameters = model_config.get("model_parameters", {})
+
+        try:
+            response = cast(
+                LLMResult,
+                model_instance.invoke_llm(
+                    prompt_messages=list(prompt_messages), model_parameters=model_parameters, stream=False
+                ),
+            )
+
+            generated_json_schema = cast(str, response.message.content)
+            return {"output": generated_json_schema, "error": ""}
+
+        except InvokeError as e:
+            error = str(e)
+            return {"output": "", "error": f"Failed to generate JSON Schema. Error: {error}"}
+        except Exception as e:
+            logging.exception(f"Failed to invoke LLM model, model: {model_config.get('name')}")
+            return {"output": "", "error": f"An unexpected error occurred: {str(e)}"}

api/core/llm_generator/prompts.py

@@ -220,3 +220,110 @@ Here is the task description: {{INPUT_TEXT}}
 
 You just need to generate the output
 """  # noqa: E501
+
+SYSTEM_STRUCTURED_OUTPUT_GENERATE = """
+Your task is to convert simple user descriptions into properly formatted JSON Schema definitions. When a user describes data fields they need, generate a complete, valid JSON Schema that accurately represents those fields with appropriate types and requirements.
+
+## Instructions:
+
+1. Analyze the user's description of their data needs
+2. Identify each property that should be included in the schema
+3. Determine the appropriate data type for each property
+4. Decide which properties should be required
+5. Generate a complete JSON Schema with proper syntax
+6. Include appropriate constraints when specified (min/max values, patterns, formats)
+7. Provide ONLY the JSON Schema without any additional explanations, comments, or markdown formatting.
+8. DO NOT use markdown code blocks (``` or ``` json). Return the raw JSON Schema directly.
+
+## Examples:
+
+### Example 1:
+**User Input:** I need name and age
+**JSON Schema Output:**
+{
+  "type": "object",
+  "properties": {
+    "name": { "type": "string" },
+    "age": { "type": "number" }
+  },
+  "required": ["name", "age"]
+}
+
+### Example 2:
+**User Input:** I want to store information about books including title, author, publication year and optional page count
+**JSON Schema Output:**
+{
+  "type": "object",
+  "properties": {
+    "title": { "type": "string" },
+    "author": { "type": "string" },
+    "publicationYear": { "type": "integer" },
+    "pageCount": { "type": "integer" }
+  },
+  "required": ["title", "author", "publicationYear"]
+}
+
+### Example 3:
+**User Input:** Create a schema for user profiles with email, password, and age (must be at least 18)
+**JSON Schema Output:**
+{
+  "type": "object",
+  "properties": {
+    "email": { 
+      "type": "string",
+      "format": "email"
+    },
+    "password": { 
+      "type": "string",
+      "minLength": 8
+    },
+    "age": { 
+      "type": "integer",
+      "minimum": 18
+    }
+  },
+  "required": ["email", "password", "age"]
+}
+
+### Example 4:
+**User Input:** I need album schema, the ablum has songs, and each song has name, duration, and artist.
+**JSON Schema Output:**
+{
+    "type": "object",
+    "properties": {
+        "properties": {
+            "songs": {
+                "type": "array",
+                "items": {
+                    "type": "object",
+                    "properties": {
+                        "name": {
+                            "type": "string"
+                        },
+                        "id": {
+                            "type": "string"
+                        },
+                        "duration": {
+                            "type": "string"
+                        },
+                        "aritst": {
+                            "type": "string"
+                        }
+                    },
+                    "required": [
+                        "name",
+                        "id",
+                        "duration",
+                        "aritst"
+                    ]
+                }
+            }
+        }
+    },
+    "required": [
+        "songs"
+    ]
+}
+
+Now, generate a JSON Schema based on my description
+"""  # noqa: E501