init,llm gateway & import_analyse

app/models.py

@@ -0,0 +1,92 @@
+from __future__ import annotations
+
+from enum import Enum
+from typing import Any, List, Optional
+
+from pydantic import BaseModel, Field
+
+
+class LLMRole(str, Enum):
+    USER = "user"
+    ASSISTANT = "assistant"
+    SYSTEM = "system"
+
+
+class LLMMessage(BaseModel):
+    role: LLMRole = Field(..., description="Message author role.")
+    content: str = Field(..., description="Plain text content of the message.")
+
+
+class LLMProvider(str, Enum):
+    OPENAI = "openai"
+    ANTHROPIC = "anthropic"
+    OPENROUTER = "openrouter"
+    GEMINI = "gemini"
+    QWEN = "qwen"
+    DEEPSEEK = "deepseek"
+
+
+class LLMRequest(BaseModel):
+    provider: LLMProvider = Field(..., description="Target LLM provider identifier.")
+    model: str = Field(..., description="Model name understood by the provider.")
+    messages: List[LLMMessage] = Field(..., description="Ordered chat messages.")
+    temperature: Optional[float] = Field(
+        0.7, description="Sampling temperature when supported."
+    )
+    top_p: Optional[float] = Field(
+        None, description="Top-p nucleus sampling when supported."
+    )
+    max_tokens: Optional[int] = Field(
+        None, description="Maximum tokens to generate when supported."
+    )
+    stream: Optional[bool] = Field(
+        False, description="Enable provider streaming if both sides support it."
+    )
+    extra_params: Optional[dict[str, Any]] = Field(
+        None, description="Provider-specific parameters to merge into the payload."
+    )
+
+
+class LLMChoice(BaseModel):
+    index: int
+    message: LLMMessage
+
+
+class LLMResponse(BaseModel):
+    provider: LLMProvider
+    model: str
+    choices: List[LLMChoice]
+    raw: Optional[dict[str, Any]] = Field(
+        None, description="Raw provider response for debugging."
+    )
+
+
+class DataImportAnalysisRequest(BaseModel):
+    import_record_id: str = Field(..., description="Unique identifier for this import run.")
+    example_data: str = Field(
+        ...,
+        max_length=30_000,
+        description="Sample rows from the import payload. Limited to 30k characters.",
+    )
+    table_headers: List[str] = Field(
+        ...,
+        min_length=1,
+        description="Ordered list of table headers associated with the data.",
+    )
+    llm_model: str = Field(
+        ...,
+        description="Model identifier. Accepts 'provider:model' format or plain model name.",
+    )
+    temperature: Optional[float] = Field(
+        None,
+        description="Optional override for LLM temperature when generating recognition output.",
+    )
+    max_tokens: Optional[int] = Field(
+        None,
+        description="Optional override for maximum tokens generated during recognition.",
+    )
+
+
+class DataImportAnalysisResponse(BaseModel):
+    import_record_id: str
+    llm_response: LLMResponse