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- from __future__ import annotations
- import re
- import json
- import asyncio
- import time
- from pathlib import Path
- from typing import Optional, Callable, AsyncIterator
- from ..typing import Messages
- from ..providers.helper import filter_none
- from ..providers.asyncio import to_async_iterator
- from ..providers.response import Reasoning
- from ..providers.types import ProviderType
- from ..cookies import get_cookies_dir
- from .web_search import do_search, get_search_message
- from .files import read_bucket, get_bucket_dir
- from .. import debug
- BUCKET_INSTRUCTIONS = """
- Instruction: Make sure to add the sources of cites using [[domain]](Url) notation after the reference. Example: [[a-z0-9.]](http://example.com)
- """
- def validate_arguments(data: dict) -> dict:
- if "arguments" in data:
- if isinstance(data["arguments"], str):
- data["arguments"] = json.loads(data["arguments"])
- if not isinstance(data["arguments"], dict):
- raise ValueError("Tool function arguments must be a dictionary or a json string")
- else:
- return filter_none(**data["arguments"])
- else:
- return {}
- def get_api_key_file(cls) -> Path:
- return Path(get_cookies_dir()) / f"api_key_{cls.parent if hasattr(cls, 'parent') else cls.__name__}.json"
- async def async_iter_run_tools(provider: ProviderType, model: str, messages, tool_calls: Optional[list] = None, **kwargs):
- # Handle web_search from kwargs
- web_search = kwargs.get('web_search')
- if web_search:
- try:
- messages = messages.copy()
- web_search = web_search if isinstance(web_search, str) and web_search != "true" else None
- messages[-1]["content"] = await do_search(messages[-1]["content"], web_search)
- except Exception as e:
- debug.log(f"Couldn't do web search: {e.__class__.__name__}: {e}")
- # Keep web_search in kwargs for provider native support
- pass
- # Read api_key from config file
- if getattr(provider, "needs_auth", False) and "api_key" not in kwargs:
- auth_file = get_api_key_file(provider)
- if auth_file.exists():
- with auth_file.open("r") as f:
- auth_result = json.load(f)
- if "api_key" in auth_result:
- kwargs["api_key"] = auth_result["api_key"]
- if tool_calls is not None:
- for tool in tool_calls:
- if tool.get("type") == "function":
- if tool.get("function", {}).get("name") == "search_tool":
- tool["function"]["arguments"] = validate_arguments(tool["function"])
- messages = messages.copy()
- messages[-1]["content"] = await do_search(
- messages[-1]["content"],
- **tool["function"]["arguments"]
- )
- elif tool.get("function", {}).get("name") == "continue":
- last_line = messages[-1]["content"].strip().splitlines()[-1]
- content = f"Carry on from this point:\n{last_line}"
- messages.append({"role": "user", "content": content})
- elif tool.get("function", {}).get("name") == "bucket_tool":
- def on_bucket(match):
- return "".join(read_bucket(get_bucket_dir(match.group(1))))
- has_bucket = False
- for message in messages:
- if "content" in message and isinstance(message["content"], str):
- new_message_content = re.sub(r'{"bucket_id":"([^"]*)"}', on_bucket, message["content"])
- if new_message_content != message["content"]:
- has_bucket = True
- message["content"] = new_message_content
- if has_bucket and isinstance(messages[-1]["content"], str):
- messages[-1]["content"] += BUCKET_INSTRUCTIONS
- create_function = provider.get_async_create_function()
- response = to_async_iterator(create_function(model=model, messages=messages, **kwargs))
- async for chunk in response:
- yield chunk
- def iter_run_tools(
- iter_callback: Callable,
- model: str,
- messages: Messages,
- provider: Optional[str] = None,
- tool_calls: Optional[list] = None,
- **kwargs
- ) -> AsyncIterator:
- # Handle web_search from kwargs
- web_search = kwargs.get('web_search')
- if web_search:
- try:
- messages = messages.copy()
- web_search = web_search if isinstance(web_search, str) and web_search != "true" else None
- messages[-1]["content"] = asyncio.run(do_search(messages[-1]["content"], web_search))
- except Exception as e:
- debug.log(f"Couldn't do web search: {e.__class__.__name__}: {e}")
- # Keep web_search in kwargs for provider native support
- pass
- # Read api_key from config file
- if provider is not None and provider.needs_auth and "api_key" not in kwargs:
- auth_file = get_api_key_file(provider)
- if auth_file.exists():
- with auth_file.open("r") as f:
- auth_result = json.load(f)
- if "api_key" in auth_result:
- kwargs["api_key"] = auth_result["api_key"]
- if tool_calls is not None:
- for tool in tool_calls:
- if tool.get("type") == "function":
- if tool.get("function", {}).get("name") == "search_tool":
- tool["function"]["arguments"] = validate_arguments(tool["function"])
- messages[-1]["content"] = get_search_message(
- messages[-1]["content"],
- raise_search_exceptions=True,
- **tool["function"]["arguments"]
- )
- elif tool.get("function", {}).get("name") == "continue_tool":
- if provider not in ("OpenaiAccount", "HuggingFace"):
- last_line = messages[-1]["content"].strip().splitlines()[-1]
- content = f"Carry on from this point:\n{last_line}"
- messages.append({"role": "user", "content": content})
- else:
- # Enable provider native continue
- if "action" not in kwargs:
- kwargs["action"] = "continue"
- elif tool.get("function", {}).get("name") == "bucket_tool":
- def on_bucket(match):
- return "".join(read_bucket(get_bucket_dir(match.group(1))))
- has_bucket = False
- for message in messages:
- if "content" in message and isinstance(message["content"], str):
- new_message_content = re.sub(r'{"bucket_id":"([^"]*)"}', on_bucket, message["content"])
- if new_message_content != message["content"]:
- has_bucket = True
- message["content"] = new_message_content
- if has_bucket and isinstance(messages[-1]["content"], str):
- messages[-1]["content"] += BUCKET_INSTRUCTIONS
- is_thinking = 0
- for chunk in iter_callback(model=model, messages=messages, provider=provider, **kwargs):
- if not isinstance(chunk, str):
- yield chunk
- continue
- if "<think>" in chunk:
- chunk = chunk.split("<think>", 1)
- yield chunk[0]
- yield Reasoning(is_thinking="<think>")
- yield Reasoning(chunk[1])
- yield Reasoning(None, "Is thinking...")
- is_thinking = time.time()
- if "</think>" in chunk:
- chunk = chunk.split("</think>", 1)
- yield Reasoning(chunk[0])
- yield Reasoning(is_thinking="</think>")
- yield Reasoning(None, f"Finished in {round(time.time()-is_thinking, 2)} seconds")
- yield chunk[1]
- is_thinking = 0
- elif is_thinking:
- yield Reasoning(chunk)
- else:
- yield chunk
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