feat: add freshrss openclaw pipeline and clean repo

src/summary_mcp/server.py

@@ -1,4 +1,9 @@
-from __future__ import annotations
+from __future__ import annotations
+
+import json
+import tempfile
+from datetime import date
+from pathlib import Path
 
 from mcp.server.fastmcp import FastMCP
 
@@ -9,6 +14,7 @@ from summary_mcp.models.filtering import FilterContext, FilterInput
 from summary_mcp.models.item import Item
 from summary_mcp.models.llm_result import LlmSummaryResult
 from summary_mcp.models.summary_io import ExtractionInput
+from summary_mcp.workflows import run_freshrss_pipeline
 
 
 mcp = FastMCP(name="content-extract-mcp")
@@ -30,9 +36,7 @@ def extract_url_content(url: str, language_hint: str | None = None) -> dict:
 def extract_item_content(item: dict) -> dict:
     """Extract structured article content from a normalized item object."""
     parsed_item = Item.model_validate(item)
-    result = extract_content(
-        ExtractionInput(item=parsed_item)
-    )
+    result = extract_content(ExtractionInput(item=parsed_item))
     return result.model_dump(mode="json")
 
 
@@ -61,6 +65,66 @@ def filter_summary_result(
     return decision.model_dump(mode="json")
 
 
+@mcp.tool()
+def run_freshrss_openclaw_pipeline(
+    limit: int = 5,
+    mark_read: bool = False,
+    include_read: bool = False,
+    debug_artifacts: bool = False,
+    continuation: str | None = None,
+    timeout_seconds: float = 60.0,
+    max_retries: int = 2,
+    stream_id: str = "user/-/state/com.google/reading-list",
+    api_base_url: str | None = None,
+    username: str | None = None,
+    api_password: str | None = None,
+    llm_api_key: str | None = None,
+    llm_model: str | None = None,
+    llm_api_url: str | None = None,
+    context: dict | None = None,
+    run_id: str | None = None,
+    date_value: str | None = None,
+    output_dir: str | None = None,
+    include_item_reports: bool = False,
+) -> dict:
+    """Run the full FreshRSS -> extract -> LLM -> filter -> OpenClaw payload pipeline."""
+    temp_context_path: Path | None = None
+
+    try:
+        if context is not None:
+            with tempfile.NamedTemporaryFile("w", encoding="utf-8", suffix=".json", delete=False) as handle:
+                json.dump(context, handle, ensure_ascii=False, indent=2)
+                temp_context_path = Path(handle.name)
+
+        result = run_freshrss_pipeline(
+            api_base_url=api_base_url,
+            username=username,
+            api_password=api_password,
+            stream_id=stream_id,
+            limit=limit,
+            continuation=continuation,
+            include_read=include_read,
+            mark_read=mark_read,
+            debug_artifacts=debug_artifacts,
+            context_path=temp_context_path,
+            max_retries=max_retries,
+            timeout_seconds=timeout_seconds,
+            llm_api_key=llm_api_key,
+            llm_model=llm_model,
+            llm_api_url=llm_api_url,
+            run_id=run_id,
+            delivery_date=date.fromisoformat(date_value) if date_value else None,
+            output_dir=Path(output_dir) if output_dir else None,
+        )
+    finally:
+        if temp_context_path and temp_context_path.exists():
+            temp_context_path.unlink()
+
+    if not include_item_reports:
+        result = {key: value for key, value in result.items() if key != "items"}
+    return result
+
+
 def main() -> None:
     mcp.run()