feat: Add v2 prompt endpoints for continue-conversation and search

Implements v2 versions of prompt generation endpoints:
- POST /v2/projects/{project_id}/prompt/continue-conversation
- POST /v2/projects/{project_id}/prompt/search

These endpoints use v2 dependencies (ContextServiceV2Dep, SearchServiceV2Dep,
EntityServiceV2Dep, EntityRepositoryV2Dep) for consistent ID-based operations.

Includes comprehensive test suite with 7 test cases covering success paths,
error handling, and v2 path validation.

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

Author: jope-bm

src/basic_memory/api/app.py

@@ -27,6 +27,7 @@
     search_router as v2_search,
     resource_router as v2_resource,
     directory_router as v2_directory,
+    prompt_router as v2_prompt,
 )
 from basic_memory.config import ConfigManager
 from basic_memory.services.initialization import initialize_file_sync, initialize_app
@@ -90,6 +91,7 @@ async def lifespan(app: FastAPI):  # pragma: no cover
 app.include_router(v2_search, prefix="/v2/projects/{project_id}")
 app.include_router(v2_resource, prefix="/v2/projects/{project_id}")
 app.include_router(v2_directory, prefix="/v2/projects/{project_id}")
+app.include_router(v2_prompt, prefix="/v2/projects/{project_id}")
 app.include_router(v2_project, prefix="/v2")
 
 # Project resource router works across projects

src/basic_memory/api/v2/__init__.py

@@ -19,6 +19,7 @@
     resource_router,
     search_router,
     directory_router,
+    prompt_router,
 )
 
 __all__ = [
@@ -28,4 +29,5 @@
     "resource_router",
     "search_router",
     "directory_router",
+    "prompt_router",
 ]

src/basic_memory/api/v2/routers/__init__.py

@@ -6,6 +6,7 @@
 from basic_memory.api.v2.routers.search_router import router as search_router
 from basic_memory.api.v2.routers.resource_router import router as resource_router
 from basic_memory.api.v2.routers.directory_router import router as directory_router
+from basic_memory.api.v2.routers.prompt_router import router as prompt_router
 
 __all__ = [
     "knowledge_router",
@@ -14,4 +15,5 @@
     "search_router",
     "resource_router",
     "directory_router",
+    "prompt_router",
 ]

src/basic_memory/api/v2/routers/prompt_router.py

@@ -0,0 +1,270 @@
+"""V2 Prompt Router - ID-based prompt generation operations.
+
+This router uses v2 dependencies for consistent project ID handling.
+Prompt endpoints are action-based (not resource-based), so they don't
+have entity IDs in URLs - they generate formatted prompts from queries.
+"""
+
+from datetime import datetime, timezone
+from fastapi import APIRouter, HTTPException, status
+from loguru import logger
+
+from basic_memory.api.routers.utils import to_graph_context, to_search_results
+from basic_memory.api.template_loader import template_loader
+from basic_memory.schemas.base import parse_timeframe
+from basic_memory.deps import (
+    ContextServiceV2Dep,
+    EntityRepositoryV2Dep,
+    SearchServiceV2Dep,
+    EntityServiceV2Dep,
+    ProjectIdPathDep,
+)
+from basic_memory.schemas.prompt import (
+    ContinueConversationRequest,
+    SearchPromptRequest,
+    PromptResponse,
+    PromptMetadata,
+)
+from basic_memory.schemas.search import SearchItemType, SearchQuery
+
+router = APIRouter(prefix="/prompt", tags=["prompt-v2"])
+
+
+@router.post("/continue-conversation", response_model=PromptResponse)
+async def continue_conversation(
+    project_id: ProjectIdPathDep,
+    search_service: SearchServiceV2Dep,
+    entity_service: EntityServiceV2Dep,
+    context_service: ContextServiceV2Dep,
+    entity_repository: EntityRepositoryV2Dep,
+    request: ContinueConversationRequest,
+) -> PromptResponse:
+    """Generate a prompt for continuing a conversation.
+
+    This endpoint takes a topic and/or timeframe and generates a prompt with
+    relevant context from the knowledge base.
+
+    Args:
+        project_id: Validated numeric project ID from URL path
+        request: The request parameters
+
+    Returns:
+        Formatted continuation prompt with context
+    """
+    logger.info(
+        f"V2 Generating continue conversation prompt for project {project_id}, "
+        f"topic: {request.topic}, timeframe: {request.timeframe}"
+    )
+
+    since = parse_timeframe(request.timeframe) if request.timeframe else None
+
+    # Initialize search results
+    search_results = []
+
+    # Get data needed for template
+    if request.topic:
+        query = SearchQuery(text=request.topic, after_date=request.timeframe)
+        results = await search_service.search(query, limit=request.search_items_limit)
+        search_results = await to_search_results(entity_service, results)
+
+        # Build context from results
+        all_hierarchical_results = []
+        for result in search_results:
+            if hasattr(result, "permalink") and result.permalink:
+                # Get hierarchical context using the new dataclass-based approach
+                context_result = await context_service.build_context(
+                    result.permalink,
+                    depth=request.depth,
+                    since=since,
+                    max_related=request.related_items_limit,
+                    include_observations=True,  # Include observations for entities
+                )
+
+                # Process results into the schema format
+                graph_context = await to_graph_context(
+                    context_result, entity_repository=entity_repository
+                )
+
+                # Add results to our collection (limit to top results for each permalink)
+                if graph_context.results:
+                    all_hierarchical_results.extend(graph_context.results[:3])
+
+        # Limit to a reasonable number of total results
+        all_hierarchical_results = all_hierarchical_results[:10]
+
+        template_context = {
+            "topic": request.topic,
+            "timeframe": request.timeframe,
+            "hierarchical_results": all_hierarchical_results,
+            "has_results": len(all_hierarchical_results) > 0,
+        }
+    else:
+        # If no topic, get recent activity
+        context_result = await context_service.build_context(
+            types=[SearchItemType.ENTITY],
+            depth=request.depth,
+            since=since,
+            max_related=request.related_items_limit,
+            include_observations=True,
+        )
+        recent_context = await to_graph_context(context_result, entity_repository=entity_repository)
+
+        hierarchical_results = recent_context.results[:5]  # Limit to top 5 recent items
+
+        template_context = {
+            "topic": f"Recent Activity from ({request.timeframe})",
+            "timeframe": request.timeframe,
+            "hierarchical_results": hierarchical_results,
+            "has_results": len(hierarchical_results) > 0,
+        }
+
+    try:
+        # Render template
+        rendered_prompt = await template_loader.render(
+            "prompts/continue_conversation.hbs", template_context
+        )
+
+        # Calculate metadata
+        # Count items of different types
+        observation_count = 0
+        relation_count = 0
+        entity_count = 0
+
+        # Get the hierarchical results from the template context
+        hierarchical_results_for_count = template_context.get("hierarchical_results", [])
+
+        # For topic-based search
+        if request.topic:
+            for item in hierarchical_results_for_count:
+                if hasattr(item, "observations"):
+                    observation_count += len(item.observations) if item.observations else 0
+
+                if hasattr(item, "related_results"):
+                    for related in item.related_results or []:
+                        if hasattr(related, "type"):
+                            if related.type == "relation":
+                                relation_count += 1
+                            elif related.type == "entity":  # pragma: no cover
+                                entity_count += 1  # pragma: no cover
+        # For recent activity
+        else:
+            for item in hierarchical_results_for_count:
+                if hasattr(item, "observations"):
+                    observation_count += len(item.observations) if item.observations else 0
+
+                if hasattr(item, "related_results"):
+                    for related in item.related_results or []:
+                        if hasattr(related, "type"):
+                            if related.type == "relation":
+                                relation_count += 1
+                            elif related.type == "entity":  # pragma: no cover
+                                entity_count += 1  # pragma: no cover
+
+        # Build metadata
+        metadata = {
+            "query": request.topic,
+            "timeframe": request.timeframe,
+            "search_count": len(search_results)
+            if request.topic
+            else 0,  # Original search results count
+            "context_count": len(hierarchical_results_for_count),
+            "observation_count": observation_count,
+            "relation_count": relation_count,
+            "total_items": (
+                len(hierarchical_results_for_count)
+                + observation_count
+                + relation_count
+                + entity_count
+            ),
+            "search_limit": request.search_items_limit,
+            "context_depth": request.depth,
+            "related_limit": request.related_items_limit,
+            "generated_at": datetime.now(timezone.utc).isoformat(),
+        }
+
+        prompt_metadata = PromptMetadata(**metadata)
+
+        return PromptResponse(
+            prompt=rendered_prompt, context=template_context, metadata=prompt_metadata
+        )
+    except Exception as e:
+        logger.error(f"Error rendering continue conversation template: {e}")
+        raise HTTPException(
+            status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
+            detail=f"Error rendering prompt template: {str(e)}",
+        )
+
+
+@router.post("/search", response_model=PromptResponse)
+async def search_prompt(
+    project_id: ProjectIdPathDep,
+    search_service: SearchServiceV2Dep,
+    entity_service: EntityServiceV2Dep,
+    request: SearchPromptRequest,
+    page: int = 1,
+    page_size: int = 10,
+) -> PromptResponse:
+    """Generate a prompt for search results.
+
+    This endpoint takes a search query and formats the results into a helpful
+    prompt with context and suggestions.
+
+    Args:
+        project_id: Validated numeric project ID from URL path
+        request: The search parameters
+        page: The page number for pagination
+        page_size: The number of results per page, defaults to 10
+
+    Returns:
+        Formatted search results prompt with context
+    """
+    logger.info(
+        f"V2 Generating search prompt for project {project_id}, "
+        f"query: {request.query}, timeframe: {request.timeframe}"
+    )
+
+    limit = page_size
+    offset = (page - 1) * page_size
+
+    query = SearchQuery(text=request.query, after_date=request.timeframe)
+    results = await search_service.search(query, limit=limit, offset=offset)
+    search_results = await to_search_results(entity_service, results)
+
+    template_context = {
+        "query": request.query,
+        "timeframe": request.timeframe,
+        "results": search_results,
+        "has_results": len(search_results) > 0,
+        "result_count": len(search_results),
+    }
+
+    try:
+        # Render template
+        rendered_prompt = await template_loader.render("prompts/search.hbs", template_context)
+
+        # Build metadata
+        metadata = {
+            "query": request.query,
+            "timeframe": request.timeframe,
+            "search_count": len(search_results),
+            "context_count": len(search_results),
+            "observation_count": 0,  # Search results don't include observations
+            "relation_count": 0,  # Search results don't include relations
+            "total_items": len(search_results),
+            "search_limit": limit,
+            "context_depth": 0,  # No context depth for basic search
+            "related_limit": 0,  # No related items for basic search
+            "generated_at": datetime.now(timezone.utc).isoformat(),
+        }
+
+        prompt_metadata = PromptMetadata(**metadata)
+
+        return PromptResponse(
+            prompt=rendered_prompt, context=template_context, metadata=prompt_metadata
+        )
+    except Exception as e:
+        logger.error(f"Error rendering search template: {e}")
+        raise HTTPException(
+            status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
+            detail=f"Error rendering prompt template: {str(e)}",
+        )