stash: add tracing implementation scaffold in the api

api/core/ops/weave_trace/entities/weave_trace_entity.py

@@ -1,6 +1,9 @@
-from pydantic import BaseModel, Field
+from pydantic import BaseModel, Field, field_validator
+from pydantic_core.core_schema import ValidationInfo
 from typing import Any, Union, Optional, List, Dict
 
+from core.ops.utils import replace_text_with_content
+
 class WeaveTokenUsage(BaseModel):
     input_tokens: Optional[int] = None
     output_tokens: Optional[int] = None
@@ -12,9 +15,75 @@ class WeaveMultiModel(BaseModel):
 
 
 class WeaveTraceModel(WeaveTokenUsage, WeaveMultiModel):
+    id: str = Field(..., description="ID of the trace")
+    op: str = Field(..., description="Name of the operation")
     inputs: Optional[Union[str, Dict[str, Any], List, None]] = Field(None, description="Inputs of the trace")
+    outputs: Optional[Union[str, Dict[str, Any], List, None]] = Field(None, description="Outputs of the trace")
     attributes: Optional[Union[str, Dict[str, Any], List, None]] = Field(None, description="Metadata and attributes associated with trace")
+    exception: Optional[str] = Field(None, description="Exception message of the trace")
 
-class WeaveTraceUpdateModel(BaseModel):
+    @field_validator("inputs", "outputs")
-    run_id: str = Field(..., description="ID of the run")
+    @classmethod
-    outputs: Optional[Union[str, Dict[str, Any], List, None]] = Field(None, description="Outputs of the trace")
+    def ensure_dict(cls, v, info: ValidationInfo):
+        field_name = info.field_name
+        values = info.data
+        if v == {} or v is None:
+            return v
+        usage_metadata = {
+            "input_tokens": values.get("input_tokens", 0),
+            "output_tokens": values.get("output_tokens", 0),
+            "total_tokens": values.get("total_tokens", 0),
+        }
+        file_list = values.get("file_list", [])
+        if isinstance(v, str):
+            if field_name == "inputs":
+                return {
+                    "messages": {
+                        "role": "user",
+                        "content": v,
+                        "usage_metadata": usage_metadata,
+                        "file_list": file_list,
+                    },
+                }
+            elif field_name == "outputs":
+                return {
+                    "choices": {
+                        "role": "ai",
+                        "content": v,
+                        "usage_metadata": usage_metadata,
+                        "file_list": file_list,
+                    },
+                }
+        elif isinstance(v, list):
+            data = {}
+            if len(v) > 0 and isinstance(v[0], dict):
+                # rename text to content
+                v = replace_text_with_content(data=v)
+                if field_name == "inputs":
+                    data = {
+                        "messages": v,
+                    }
+                elif field_name == "outputs":
+                    data = {
+                        "choices": {
+                            "role": "ai",
+                            "content": v,
+                            "usage_metadata": usage_metadata,
+                            "file_list": file_list,
+                        },
+                    }
+                return data
+            else:
+                return {
+                    "choices": {
+                        "role": "ai" if field_name == "outputs" else "user",
+                        "content": str(v),
+                        "usage_metadata": usage_metadata,
+                        "file_list": file_list,
+                    },
+                }
+        if isinstance(v, dict):
+            v["usage_metadata"] = usage_metadata
+            v["file_list"] = file_list
+            return v
+        return v

api/core/ops/weave_trace/weave_trace.py

@@ -25,6 +25,7 @@ from models.model import EndUser, MessageFile
 from models.workflow import WorkflowNodeExecution
 import weave
 import wandb
+from core.ops.weave_trace.entities.weave_trace_entity import WeaveTraceModel
 
 logger = logging.getLogger(__name__)
 
@@ -42,9 +43,100 @@ class WeaveDataTrace(BaseTraceInstance):
         self.file_base_url = os.getenv("FILES_URL", "http://127.0.0.1:5001")
         self.calls = {}
 
+    def get_project_url(self,):
+        try:
+            project_url = f"https://wandb.ai/{self.weave_client._project_id()}"
+            return project_url
+        except Exception as e:
+            logger.debug(f"Weave get run url failed: {str(e)}")
+            raise ValueError(f"Weave get run url failed: {str(e)}")
+
 
     def trace(self, trace_info: BaseTraceInfo):
+        logger.debug(f"Trace info: {trace_info}")
+        print("Trace info: ", trace_info)
+        if isinstance(trace_info, WorkflowTraceInfo):
+            # self.workflow_trace(trace_info)
+            print("Workflow trace: ", trace_info)
+            pass
+        if isinstance(trace_info, MessageTraceInfo):
+            self.message_trace(trace_info)
+        if isinstance(trace_info, ModerationTraceInfo):
+            print("Moderation trace: ", trace_info)
+            pass
+            # self.moderation_trace(trace_info)
+        if isinstance(trace_info, SuggestedQuestionTraceInfo):
+            print("Suggested question trace: ", trace_info)
+            pass
+            # self.suggested_question_trace(trace_info)
+        if isinstance(trace_info, DatasetRetrievalTraceInfo):
+            print("Dataset retrieval trace: ", trace_info)
+            pass
+            # self.dataset_retrieval_trace(trace_info)
+        if isinstance(trace_info, ToolTraceInfo):
+            print("Tool trace: ", trace_info)
             pass
+            # self.tool_trace(trace_info)
+        if isinstance(trace_info, GenerateNameTraceInfo):
+            print("Generate name trace: ", trace_info)
+            pass
+            # self.generate_name_trace(trace_info)
+
+    def message_trace(self, trace_info: MessageTraceInfo):
+        # get message file data
+        file_list = cast(list[str], trace_info.file_list) or []
+        message_file_data: Optional[MessageFile] = trace_info.message_file_data
+        file_url = f"{self.file_base_url}/{message_file_data.url}" if message_file_data else ""
+        file_list.append(file_url)
+        metadata = trace_info.metadata
+        message_data = trace_info.message_data
+        if message_data is None:
+            return
+        message_id = message_data.id
+
+        user_id = message_data.from_account_id
+        metadata["user_id"] = user_id
+
+        if message_data.from_end_user_id:
+            end_user_data: Optional[EndUser] = (
+                db.session.query(EndUser).filter(EndUser.id == message_data.from_end_user_id).first()
+            )
+            if end_user_data is not None:
+                end_user_id = end_user_data.session_id
+                metadata["end_user_id"] = end_user_id
+
+        metadata["message_id"] = message_id
+        metadata["start_time"]=trace_info.start_time
+        metadata["end_time"]=trace_info.end_time
+        metadata["tags"] = ["message", str(trace_info.conversation_mode)]
+        message_run = WeaveTraceModel(
+            id=message_id,
+            op=str(TraceTaskName.MESSAGE_TRACE.value),
+            input_tokens=trace_info.message_tokens,
+            output_tokens=trace_info.answer_tokens,
+            total_tokens=trace_info.total_tokens,
+            inputs=trace_info.inputs,
+            outputs=trace_info.outputs,
+            exception=trace_info.error,
+            file_list=file_list,
+            attributes=metadata
+        )
+        self.add_run(message_run)
+
+        # create llm run parented to message run
+        llm_run = WeaveTraceModel(
+            id=str(uuid.uuid4()),
+            input_tokens=trace_info.message_tokens,
+            output_tokens=trace_info.answer_tokens,
+            total_tokens=trace_info.total_tokens,
+            op="llm",
+            inputs=trace_info.inputs,
+            outputs=trace_info.outputs,
+            attributes=metadata,
+        )
+        self.add_run(llm_run, parent_run_id=message_id,)
+        self.update_run(llm_run)
+        self.update_run(message_run)
 
     def api_check(self):
         try:
@@ -58,15 +150,15 @@ class WeaveDataTrace(BaseTraceInstance):
             logger.debug(f"Weave API check failed: {str(e)}")
             raise ValueError(f"Weave API check failed: {str(e)}")
 
-    def add_run(self, run_data: dict, parent_run_id: Optional[str] = None):
+    def add_run(self, run_data: WeaveTraceModel, parent_run_id: Optional[str] = None):
-        call = self.weave_client.create_call(op=run_data["name"], inputs=run_data["inputs"])
+        call = self.weave_client.create_call(op=run_data.op, inputs=run_data.inputs,  attributes=run_data.attributes)
-        self.calls[run_data["id"]] = call
+        self.calls[run_data.id] = call
         if parent_run_id:
-            self.calls[run_data["id"]].parent_id = parent_run_id
+            self.calls[run_data.id].parent_id = parent_run_id
 
-    def update_run(self, run_data: dict):
+    def update_run(self, run_data: WeaveTraceModel):
-        call = self.calls.get(run_data["id"])
+        call = self.calls.get(run_data.id)
         if call:
-            self.weave_client.finish_call(call, output=run_data["outputs"])
+            self.weave_client.finish_call(call=call, output=run_data.outputs, exception=run_data.exception)
         else:
             raise ValueError(f"Call with id {run_data['id']} not found")

api/services/ops_service.py

@@ -67,7 +67,14 @@ class OpsService:
                 new_decrypt_tracing_config.update({"project_url": project_url})
             except Exception:
                 new_decrypt_tracing_config.update({"project_url": "https://www.comet.com/opik/"})
-
+        if tracing_provider == "weave" and (
+            "project_url" not in decrypt_tracing_config or not decrypt_tracing_config.get("project_url")
+        ):
+            try:
+                project_url = OpsTraceManager.get_trace_config_project_url(decrypt_tracing_config, tracing_provider)
+                new_decrypt_tracing_config.update({"project_url": project_url})
+            except Exception:
+                new_decrypt_tracing_config.update({"project_url": "https://wandb.ai/"})
         trace_config_data.tracing_config = new_decrypt_tracing_config
         return trace_config_data.to_dict()