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255 lines
9.1 KiB
Python
255 lines
9.1 KiB
Python
"""A Tracer implementation that records to LangChain endpoint."""
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from __future__ import annotations
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import logging
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import os
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from typing import Any, Dict, List, Optional, Union
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from uuid import UUID, uuid4
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import requests
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from langchain.callbacks.tracers.base import BaseTracer
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from langchain.callbacks.tracers.schemas import (
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ChainRun,
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LLMRun,
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RunCreate,
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ToolRun,
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TracerSession,
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TracerSessionBase,
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TracerSessionV2,
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TracerSessionV2Create,
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)
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from langchain.utils import raise_for_status_with_text
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def _get_headers() -> Dict[str, Any]:
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"""Get the headers for the LangChain API."""
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headers: Dict[str, Any] = {"Content-Type": "application/json"}
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if os.getenv("LANGCHAIN_API_KEY"):
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headers["x-api-key"] = os.getenv("LANGCHAIN_API_KEY")
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return headers
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def _get_endpoint() -> str:
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return os.getenv("LANGCHAIN_ENDPOINT", "http://localhost:8000")
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class LangChainTracer(BaseTracer):
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"""An implementation of the SharedTracer that POSTS to the langchain endpoint."""
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def __init__(self, **kwargs: Any) -> None:
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"""Initialize the LangChain tracer."""
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super().__init__(**kwargs)
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self._endpoint = _get_endpoint()
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self._headers = _get_headers()
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def _persist_run(self, run: Union[LLMRun, ChainRun, ToolRun]) -> None:
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"""Persist a run."""
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if isinstance(run, LLMRun):
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endpoint = f"{self._endpoint}/llm-runs"
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elif isinstance(run, ChainRun):
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endpoint = f"{self._endpoint}/chain-runs"
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else:
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endpoint = f"{self._endpoint}/tool-runs"
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try:
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response = requests.post(
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endpoint,
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data=run.json(),
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headers=self._headers,
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)
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raise_for_status_with_text(response)
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except Exception as e:
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logging.warning(f"Failed to persist run: {e}")
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def _persist_session(
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self, session_create: TracerSessionBase
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) -> Union[TracerSession, TracerSessionV2]:
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"""Persist a session."""
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try:
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r = requests.post(
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f"{self._endpoint}/sessions",
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data=session_create.json(),
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headers=self._headers,
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)
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session = TracerSession(id=r.json()["id"], **session_create.dict())
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except Exception as e:
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logging.warning(f"Failed to create session, using default session: {e}")
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session = TracerSession(id=1, **session_create.dict())
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return session
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def _load_session(self, session_name: Optional[str] = None) -> TracerSession:
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"""Load a session from the tracer."""
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try:
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url = f"{self._endpoint}/sessions"
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if session_name:
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url += f"?name={session_name}"
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r = requests.get(url, headers=self._headers)
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tracer_session = TracerSession(**r.json()[0])
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except Exception as e:
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session_type = "default" if not session_name else session_name
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logging.warning(
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f"Failed to load {session_type} session, using empty session: {e}"
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)
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tracer_session = TracerSession(id=1)
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self.session = tracer_session
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return tracer_session
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def load_session(self, session_name: str) -> Union[TracerSession, TracerSessionV2]:
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"""Load a session with the given name from the tracer."""
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return self._load_session(session_name)
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def load_default_session(self) -> Union[TracerSession, TracerSessionV2]:
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"""Load the default tracing session and set it as the Tracer's session."""
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return self._load_session("default")
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def _get_tenant_id() -> Optional[str]:
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"""Get the tenant ID for the LangChain API."""
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tenant_id: Optional[str] = os.getenv("LANGCHAIN_TENANT_ID")
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if tenant_id:
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return tenant_id
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endpoint = _get_endpoint()
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headers = _get_headers()
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response = requests.get(endpoint + "/tenants", headers=headers)
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raise_for_status_with_text(response)
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tenants: List[Dict[str, Any]] = response.json()
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if not tenants:
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raise ValueError(f"No tenants found for URL {endpoint}")
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return tenants[0]["id"]
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class LangChainTracerV2(LangChainTracer):
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"""An implementation of the SharedTracer that POSTS to the langchain endpoint."""
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def __init__(self, example_id: Optional[UUID] = None, **kwargs: Any) -> None:
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"""Initialize the LangChain tracer."""
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super().__init__(**kwargs)
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self._endpoint = _get_endpoint()
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self._headers = _get_headers()
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self.tenant_id = _get_tenant_id()
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self.example_id = example_id
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def _get_session_create(
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self, name: Optional[str] = None, **kwargs: Any
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) -> TracerSessionBase:
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return TracerSessionV2Create(name=name, extra=kwargs, tenant_id=self.tenant_id)
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def _persist_session(self, session_create: TracerSessionBase) -> TracerSessionV2:
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"""Persist a session."""
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session: Optional[TracerSessionV2] = None
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try:
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r = requests.post(
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f"{self._endpoint}/sessions",
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data=session_create.json(),
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headers=self._headers,
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)
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raise_for_status_with_text(r)
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creation_args = session_create.dict()
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if "id" in creation_args:
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del creation_args["id"]
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return TracerSessionV2(id=r.json()["id"], **creation_args)
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except Exception as e:
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if session_create.name is not None:
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try:
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return self.load_session(session_create.name)
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except Exception:
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pass
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logging.warning(
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f"Failed to create session {session_create.name},"
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f" using empty session: {e}"
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)
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session = TracerSessionV2(id=uuid4(), **session_create.dict())
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return session
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def _get_default_query_params(self) -> Dict[str, Any]:
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"""Get the query params for the LangChain API."""
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return {"tenant_id": self.tenant_id}
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def load_session(self, session_name: str) -> TracerSessionV2:
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"""Load a session with the given name from the tracer."""
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try:
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url = f"{self._endpoint}/sessions"
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params = {"tenant_id": self.tenant_id}
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if session_name:
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params["name"] = session_name
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r = requests.get(url, headers=self._headers, params=params)
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raise_for_status_with_text(r)
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tracer_session = TracerSessionV2(**r.json()[0])
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except Exception as e:
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session_type = "default" if not session_name else session_name
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logging.warning(
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f"Failed to load {session_type} session, using empty session: {e}"
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)
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tracer_session = TracerSessionV2(id=uuid4(), tenant_id=self.tenant_id)
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self.session = tracer_session
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return tracer_session
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def load_default_session(self) -> TracerSessionV2:
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"""Load the default tracing session and set it as the Tracer's session."""
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return self.load_session("default")
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def _convert_run(self, run: Union[LLMRun, ChainRun, ToolRun]) -> RunCreate:
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"""Convert a run to a Run."""
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session = self.session or self.load_default_session()
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inputs: Dict[str, Any] = {}
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outputs: Optional[Dict[str, Any]] = None
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child_runs: List[Union[LLMRun, ChainRun, ToolRun]] = []
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if isinstance(run, LLMRun):
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run_type = "llm"
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inputs = {"prompts": run.prompts}
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outputs = run.response.dict() if run.response else {}
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child_runs = []
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elif isinstance(run, ChainRun):
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run_type = "chain"
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inputs = run.inputs
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outputs = run.outputs
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child_runs = [
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*run.child_llm_runs,
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*run.child_chain_runs,
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*run.child_tool_runs,
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]
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else:
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run_type = "tool"
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inputs = {"input": run.tool_input}
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outputs = {"output": run.output} if run.output else {}
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child_runs = [
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*run.child_llm_runs,
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*run.child_chain_runs,
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*run.child_tool_runs,
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]
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return RunCreate(
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id=run.uuid,
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name=run.serialized.get("name"),
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start_time=run.start_time,
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end_time=run.end_time,
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extra=run.extra or {},
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error=run.error,
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execution_order=run.execution_order,
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serialized=run.serialized,
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inputs=inputs,
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outputs=outputs,
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session_id=session.id,
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run_type=run_type,
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reference_example_id=self.example_id,
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child_runs=[self._convert_run(child) for child in child_runs],
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)
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def _persist_run(self, run: Union[LLMRun, ChainRun, ToolRun]) -> None:
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"""Persist a run."""
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run_create = self._convert_run(run)
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try:
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response = requests.post(
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f"{self._endpoint}/runs",
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data=run_create.json(),
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headers=self._headers,
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)
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raise_for_status_with_text(response)
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except Exception as e:
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logging.warning(f"Failed to persist run: {e}")
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