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Add possibility to pass on_artifacts for a specific conversation (#12687)

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Possibility to pass on_artifacts to a conversation. It can be then
achieved by adding this way:

```python
result = agent.run(
    input=message.text,
    metadata={
        "on_artifact": CALLBACK_FUNCTION
    },
)
```
This commit is contained in:
Jakub Novák 2023-11-06 16:29:47 +01:00 committed by GitHub
parent 0378662e1d
commit ada3d2cbd1
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1 changed files with 15 additions and 2 deletions
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17
libs/langchain/langchain/tools/e2b_data_analysis/tool.py
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@ -9,6 +9,7 @@ from typing import IO, TYPE_CHECKING, Any, Callable, List, Optional, Type
from langchain.callbacks.manager import (
AsyncCallbackManagerForToolRun,
CallbackManager,
CallbackManagerForToolRun,
)
from langchain.pydantic_v1 import BaseModel, Field, PrivateAttr
@ -151,14 +152,26 @@ class E2BDataAnalysisTool(BaseTool):
return "\n".join(lines)
def _run(
self, python_code: str, run_manager: Optional[CallbackManagerForToolRun] = None
self,
python_code: str,
run_manager: Optional[CallbackManagerForToolRun] = None,
callbacks: Optional[CallbackManager] = None,
) -> str:
python_code = add_last_line_print(python_code)
stdout, stderr, _ = self.session.run_python(python_code)
if callbacks is not None:
on_artifact = getattr(callbacks.metadata, "on_artifact", None)
else:
on_artifact = None
stdout, stderr, artifacts = self.session.run_python(
python_code, on_artifact=on_artifact
)
out = {
"stdout": stdout,
"stderr": stderr,
"artifacts": list(map(lambda artifact: artifact.name, artifacts)),
}
return json.dumps(out)