Add AGENTS.md documentation for AI agent guidance

2026-02-23 09:59:52 -05:00
commit 2e2b817435
21 changed files with 2513 additions and 0 deletions
--- a/app/routers/embeddings.py
+++ b/app/routers/embeddings.py
@@ -0,0 +1,114 @@
+"""Embeddings endpoint router."""
+
+from typing import Union
+from fastapi import APIRouter, HTTPException, Request
+from app.models.openai_models import (
+    EmbeddingRequest,
+    EmbeddingResponse,
+    ErrorResponse,
+    ErrorDetail,
+)
+from app.services.watsonx_service import watsonx_service
+from app.utils.transformers import transform_watsonx_to_openai_embeddings
+from app.config import settings
+import logging
+
+logger = logging.getLogger(__name__)
+
+router = APIRouter()
+
+
+@router.post(
+    "/v1/embeddings",
+    response_model=Union[EmbeddingResponse, ErrorResponse],
+    responses={
+        200: {"model": EmbeddingResponse},
+        400: {"model": ErrorResponse},
+        401: {"model": ErrorResponse},
+        500: {"model": ErrorResponse},
+    },
+)
+async def create_embeddings(
+    request: EmbeddingRequest,
+    http_request: Request,
+):
+    """Create embeddings using OpenAI-compatible API.
+    
+    This endpoint accepts OpenAI-formatted embedding requests and translates
+    them to watsonx.ai embeddings API calls.
+    """
+    try:
+        # Map model name if needed
+        watsonx_model = settings.map_model(request.model)
+        logger.info(f"Embeddings request: {request.model} -> {watsonx_model}")
+        
+        # Handle input (can be string or list)
+        if isinstance(request.input, str):
+            inputs = [request.input]
+        elif isinstance(request.input, list):
+            if len(request.input) == 0:
+                raise HTTPException(
+                    status_code=400,
+                    detail={
+                        "error": {
+                            "message": "Input cannot be empty",
+                            "type": "invalid_request_error",
+                            "code": "invalid_input",
+                        }
+                    },
+                )
+            # Handle list of strings or list of token IDs
+            if isinstance(request.input[0], str):
+                inputs = request.input
+            else:
+                # Token IDs not supported yet
+                raise HTTPException(
+                    status_code=400,
+                    detail={
+                        "error": {
+                            "message": "Token ID input not supported",
+                            "type": "invalid_request_error",
+                            "code": "unsupported_input_type",
+                        }
+                    },
+                )
+        else:
+            raise HTTPException(
+                status_code=400,
+                detail={
+                    "error": {
+                        "message": "Invalid input type",
+                        "type": "invalid_request_error",
+                        "code": "invalid_input_type",
+                    }
+                },
+            )
+        
+        # Call watsonx embeddings
+        watsonx_response = await watsonx_service.embeddings(
+            model_id=watsonx_model,
+            inputs=inputs,
+        )
+        
+        # Transform response
+        openai_response = transform_watsonx_to_openai_embeddings(
+            watsonx_response,
+            request.model,
+        )
+        
+        return openai_response
+        
+    except HTTPException:
+        raise
+    except Exception as e:
+        logger.error(f"Error in embeddings: {str(e)}", exc_info=True)
+        raise HTTPException(
+            status_code=500,
+            detail={
+                "error": {
+                    "message": str(e),
+                    "type": "internal_error",
+                    "code": "internal_error",
+                }
+            },
+        )