mirror of
https://github.com/hwchase17/langchain.git
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72 lines
2.5 KiB
Python
72 lines
2.5 KiB
Python
from __future__ import annotations
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import json
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from typing import Any, cast
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from langchain_core.messages import content as types
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def _convert_from_v1_to_groq(
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content: list[types.ContentBlock],
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model_provider: str | None,
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) -> tuple[list[dict[str, Any] | str], dict]:
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new_content: list = []
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new_additional_kwargs: dict = {}
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for i, block in enumerate(content):
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if block["type"] == "text":
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new_content.append({"text": block.get("text", ""), "type": "text"})
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elif (
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block["type"] == "reasoning"
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and (reasoning := block.get("reasoning"))
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and model_provider == "groq"
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):
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new_additional_kwargs["reasoning_content"] = reasoning
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elif block["type"] == "server_tool_call" and model_provider == "groq":
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new_block = {}
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if "args" in block:
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new_block["arguments"] = json.dumps(block["args"])
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if idx := block.get("extras", {}).get("index"):
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new_block["index"] = idx
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if block.get("name") == "web_search":
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new_block["type"] = "search"
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elif block.get("name") == "code_interpreter":
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new_block["type"] = "python"
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else:
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new_block["type"] = ""
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if i < len(content) - 1 and content[i + 1]["type"] == "server_tool_result":
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result = cast("types.ServerToolResult", content[i + 1])
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for k, v in result.get("extras", {}).items():
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new_block[k] = v # noqa: PERF403
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if "output" in result:
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new_block["output"] = result["output"]
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if "executed_tools" not in new_additional_kwargs:
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new_additional_kwargs["executed_tools"] = []
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new_additional_kwargs["executed_tools"].append(new_block)
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elif block["type"] == "server_tool_result":
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continue
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elif (
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block["type"] == "non_standard"
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and "value" in block
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and model_provider == "groq"
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):
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new_content.append(block["value"])
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else:
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new_content.append(block)
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# For consistency with v0 payloads, we cast single text blocks to str
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if (
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len(new_content) == 1
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and isinstance(new_content[0], dict)
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and new_content[0].get("type") == "text"
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and (text_content := new_content[0].get("text"))
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and isinstance(text_content, str)
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):
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return text_content, new_additional_kwargs
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return new_content, new_additional_kwargs
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