Feat: debug extractor... (#10294)

### What problem does this PR solve?

### Type of change

- [x] New Feature (non-breaking change which adds functionality)

agent/canvas.py

@@ -153,6 +153,16 @@ class Graph:
     def get_tenant_id(self):
         return self._tenant_id
 
+    def get_variable_value(self, exp: str) -> Any:
+        exp = exp.strip("{").strip("}").strip(" ").strip("{").strip("}")
+        if exp.find("@") < 0:
+            return self.globals[exp]
+        cpn_id, var_nm = exp.split("@")
+        cpn = self.get_component(cpn_id)
+        if not cpn:
+            raise Exception(f"Can't find variable: '{cpn_id}@{var_nm}'")
+        return cpn["obj"].output(var_nm)
+
 
 class Canvas(Graph):
 
@@ -406,16 +416,6 @@ class Canvas(Graph):
             return False
         return True
 
-    def get_variable_value(self, exp: str) -> Any:
-        exp = exp.strip("{").strip("}").strip(" ").strip("{").strip("}")
-        if exp.find("@") < 0:
-            return self.globals[exp]
-        cpn_id, var_nm = exp.split("@")
-        cpn = self.get_component(cpn_id)
-        if not cpn:
-            raise Exception(f"Can't find variable: '{cpn_id}@{var_nm}'")
-        return cpn["obj"].output(var_nm)
-
     def get_history(self, window_size):
         convs = []
         if window_size <= 0:

agent/component/llm.py

@@ -102,6 +102,8 @@ class LLM(ComponentBase):
 
     def get_input_elements(self) -> dict[str, Any]:
         res = self.get_input_elements_from_text(self._param.sys_prompt)
+        if isinstance(self._param.prompts, str):
+            self._param.prompts = [{"role": "user", "content": self._param.prompts}]
         for prompt in self._param.prompts:
             d = self.get_input_elements_from_text(prompt["content"])
             res.update(d)
@@ -114,6 +116,8 @@ class LLM(ComponentBase):
         self._param.sys_prompt += txt
 
     def _sys_prompt_and_msg(self, msg, args):
+        if isinstance(self._param.prompts, str):
+            self._param.prompts = [{"role": "user", "content": self._param.prompts}]
         for p in self._param.prompts:
             if msg and msg[-1]["role"] == p["role"]:
                 continue

rag/flow/extractor/extractor.py

@@ -14,9 +14,10 @@
 #  limitations under the License.
 import random
 from agent.component.llm import LLMParam, LLM
+from rag.flow.base import ProcessBase, ProcessParamBase
 
 
-class ExtractorParam(LLMParam):
+class ExtractorParam(ProcessParamBase, LLMParam):
     def __init__(self):
         super().__init__()
         self.field_name = ""
@@ -26,7 +27,7 @@ class ExtractorParam(LLMParam):
         self.check_empty(self.field_name, "Result Destination")
 
 
-class Extractor(LLM):
+class Extractor(ProcessBase, LLM):
     component_name = "Extractor"
 
     async def _invoke(self, **kwargs):

rag/flow/extractor/schema.py

@@ -30,7 +30,7 @@ class ExtractorFromUpstream(BaseModel):
     json_result: list[dict[str, Any]] | None = Field(default=None, alias="json")
     markdown_result: str | None = Field(default=None, alias="markdown")
     text_result: str | None = Field(default=None, alias="text")
-    html_result: list[str] | None = Field(default=None, alias="html")
+    html_result: str | None = Field(default=None, alias="html")
 
     model_config = ConfigDict(populate_by_name=True, extra="forbid")
 

rag/flow/hierarchical_merger/schema.py

@@ -29,7 +29,7 @@ class HierarchicalMergerFromUpstream(BaseModel):
     json_result: list[dict[str, Any]] | None = Field(default=None, alias="json")
     markdown_result: str | None = Field(default=None, alias="markdown")
     text_result: str | None = Field(default=None, alias="text")
-    html_result: list[str] | None = Field(default=None, alias="html")
+    html_result: str | None = Field(default=None, alias="html")
 
     model_config = ConfigDict(populate_by_name=True, extra="forbid")
 

rag/flow/pipeline.py

@@ -143,6 +143,10 @@ class Pipeline(Graph):
             async def invoke():
                 nonlocal last_cpn, cpn_obj
                 await cpn_obj.invoke(**last_cpn.output())
+                #if inspect.iscoroutinefunction(cpn_obj.invoke):
+                #    await cpn_obj.invoke(**last_cpn.output())
+                #else:
+                #    cpn_obj.invoke(**last_cpn.output())
 
             async with trio.open_nursery() as nursery:
                 nursery.start_soon(invoke)

rag/flow/splitter/schema.py

@@ -30,7 +30,7 @@ class SplitterFromUpstream(BaseModel):
     json_result: list[dict[str, Any]] | None = Field(default=None, alias="json")
     markdown_result: str | None = Field(default=None, alias="markdown")
     text_result: str | None = Field(default=None, alias="text")
-    html_result: list[str] | None = Field(default=None, alias="html")
+    html_result: str | None = Field(default=None, alias="html")
 
     model_config = ConfigDict(populate_by_name=True, extra="forbid")
 

rag/flow/tokenizer/schema.py

@@ -31,7 +31,7 @@ class TokenizerFromUpstream(BaseModel):
     json_result: list[dict[str, Any]] | None = Field(default=None, alias="json")
     markdown_result: str | None = Field(default=None, alias="markdown")
     text_result: str | None = Field(default=None, alias="text")
-    html_result: list[str] | None = Field(default=None, alias="html")
+    html_result: str | None = Field(default=None, alias="html")
 
     model_config = ConfigDict(populate_by_name=True, extra="forbid")
 

rag/flow/tokenizer/tokenizer.py

@@ -119,7 +119,7 @@ class Tokenizer(ProcessBase):
                     if ck.get("questions"):
                         ck["question_tks"] = rag_tokenizer.tokenize("\n".join(ck["questions"]))
                     if ck.get("keywords"):
-                        ck["important_tks"] = rag_tokenizer.tokenize("\n".join(ck["keywords"]))
+                        ck["important_tks"] = rag_tokenizer.tokenize(",".join(ck["keywords"]))
                     if ck.get("summary"):
                         ck["content_ltks"] = rag_tokenizer.tokenize(ck["summary"])
                         ck["content_sm_ltks"] = rag_tokenizer.fine_grained_tokenize(ck["content_ltks"])

rag/svr/task_executor.py

@@ -222,10 +222,9 @@ async def collect():
         return None, None
 
     canceled = False
-    if msg.get("doc_id", "") == GRAPH_RAPTOR_FAKE_DOC_ID:
+    if msg.get("doc_id", "") in [GRAPH_RAPTOR_FAKE_DOC_ID, CANVAS_DEBUG_DOC_ID]:
         task = msg
         if task["task_type"] in ["graphrag", "raptor"] and msg.get("doc_ids", []):
-            print(f"hack {msg['doc_ids']=}=",flush=True)
             task = TaskService.get_task(msg["id"], msg["doc_ids"])
             task["doc_ids"] = msg["doc_ids"]
     else: