diff --git a/en/.doctrees/agentscope.agents.doctree b/en/.doctrees/agentscope.agents.doctree index 45cfeda88..d725a8403 100644 Binary files a/en/.doctrees/agentscope.agents.doctree and b/en/.doctrees/agentscope.agents.doctree differ diff --git a/en/.doctrees/agentscope.agents.react_agent.doctree b/en/.doctrees/agentscope.agents.react_agent.doctree index 886e8d441..6f9865ed6 100644 Binary files a/en/.doctrees/agentscope.agents.react_agent.doctree and b/en/.doctrees/agentscope.agents.react_agent.doctree differ diff --git a/en/.doctrees/agentscope.parsers.doctree b/en/.doctrees/agentscope.parsers.doctree index 0565aa35b..a993298e7 100644 Binary files a/en/.doctrees/agentscope.parsers.doctree and b/en/.doctrees/agentscope.parsers.doctree differ diff --git a/en/.doctrees/agentscope.parsers.regex_tagged_content_parser.doctree b/en/.doctrees/agentscope.parsers.regex_tagged_content_parser.doctree new file mode 100644 index 000000000..23c7ee0f7 Binary files /dev/null and b/en/.doctrees/agentscope.parsers.regex_tagged_content_parser.doctree differ diff --git a/en/.doctrees/environment.pickle b/en/.doctrees/environment.pickle index e6723bbdb..7a16ae36e 100644 Binary files a/en/.doctrees/environment.pickle and b/en/.doctrees/environment.pickle differ diff --git a/en/.doctrees/index.doctree b/en/.doctrees/index.doctree index 9e5741c78..e0181662e 100644 Binary files a/en/.doctrees/index.doctree and b/en/.doctrees/index.doctree differ diff --git a/en/.doctrees/tutorial/203-parser.doctree b/en/.doctrees/tutorial/203-parser.doctree index 02410bc86..d57e26f41 100644 Binary files a/en/.doctrees/tutorial/203-parser.doctree and b/en/.doctrees/tutorial/203-parser.doctree differ diff --git a/en/_modules/agentscope/agents/react_agent.html b/en/_modules/agentscope/agents/react_agent.html index e7a63f569..daffd0ee8 100644 --- a/en/_modules/agentscope/agents/react_agent.html +++ b/en/_modules/agentscope/agents/react_agent.html @@ -119,16 +119,15 @@

Source code for agentscope.agents.react_agent

and act iteratively to solve problems. More details can be found in the paper https://arxiv.org/abs/2210.03629. """ -from typing import Any, Optional, Union, Sequence - -from loguru import logger +from typing import Optional, Union, Sequence from agentscope.exception import ResponseParsingError, FunctionCallError from agentscope.agents import AgentBase from agentscope.message import Msg -from agentscope.parsers import MarkdownJsonDictParser +from agentscope.parsers.regex_tagged_content_parser import ( + RegexTaggedContentParser, +) from agentscope.service import ServiceToolkit -from agentscope.service.service_toolkit import ServiceFunction INSTRUCTION_PROMPT = """## What You Should Do: 1. First, analyze the current situation, and determine your goal. @@ -162,11 +161,10 @@

Source code for agentscope.agents.react_agent

self, name: str, model_config_name: str, - service_toolkit: ServiceToolkit = None, + service_toolkit: ServiceToolkit, sys_prompt: str = "You're a helpful assistant. Your name is {name}.", max_iters: int = 10, verbose: bool = True, - **kwargs: Any, ) -> None: """Initialize the ReAct agent with the given name, model config name and tools. @@ -194,39 +192,6 @@

Source code for agentscope.agents.react_agent

model_config_name=model_config_name, ) - # TODO: To compatible with the old version, which will be deprecated - # soon - if "tools" in kwargs: - logger.warning( - "The argument `tools` will be deprecated soon. " - "Please use `service_toolkit` instead. Example refers to " - "https://github.com/modelscope/agentscope/blob/main/" - "examples/conversation_with_react_agent/code/" - "conversation_with_react_agent.py", - ) - - service_funcs = {} - for func, json_schema in kwargs["tools"]: - name = json_schema["function"]["name"] - service_funcs[name] = ServiceFunction( - name=name, - original_func=func, - processed_func=func, - json_schema=json_schema, - ) - - if service_toolkit is None: - service_toolkit = ServiceToolkit() - service_toolkit.service_funcs = service_funcs - else: - service_toolkit.service_funcs.update(service_funcs) - - elif service_toolkit is None: - raise ValueError( - "The argument `service_toolkit` is required to initialize " - "the ReActAgent.", - ) - self.service_toolkit = service_toolkit self.verbose = verbose self.max_iters = max_iters @@ -249,15 +214,22 @@

Source code for agentscope.agents.react_agent

self.memory.add(Msg("system", self.sys_prompt, role="system")) # Initialize a parser object to formulate the response from the model - self.parser = MarkdownJsonDictParser( - content_hint={ - "thought": "what you thought", - "speak": "what you speak", - "function": service_toolkit.tools_calling_format, - }, - required_keys=["thought", "speak", "function"], - # Only print the speak field when verbose is False - keys_to_content=True if self.verbose else "speak", + self.parser = RegexTaggedContentParser( + format_instruction="""Respond with specific tags as outlined below: + +- When calling tool functions, note the "arg_name" should be replaced with the actual argument name: +<thought>what you thought</thought> +<function>the function name you want to call</function> +<arg_name>the value of the argument</arg_name> +<arg_name>the value of the argument</arg_name> + +- When you want to generate a final response: +<thought>what you thought</thought> +<response>what you respond</response> +...""", # noqa + try_parse_json=True, + required_keys=["thought"], + keys_to_content="response", )
@@ -290,41 +262,38 @@

Source code for agentscope.agents.react_agent

try: raw_response = self.model(prompt) + # Print out the text generated by llm in non-/streaming mode if self.verbose: # To be compatible with streaming and non-streaming mode self.speak(raw_response.stream or raw_response.text) res = self.parser.parse(raw_response) - # Record the response in memory - self.memory.add( - Msg( - self.name, - self.parser.to_memory(res.parsed), - "assistant", - ), - ) - - # Print out the response - msg_returned = Msg( - self.name, - self.parser.to_content(res.parsed), - "assistant", - ) - - if not self.verbose: - self.speak(msg_returned) + # Record the raw text into memory to avoid that LLMs learn + # from the previous response format + self.memory.add(Msg(self.name, res.text, "assistant")) # Skip the next steps if no need to call tools # The parsed field is a dictionary - arg_function = res.parsed["function"] + arg_function = res.parsed.get("function", "") if ( isinstance(arg_function, str) and arg_function in ["[]", ""] or isinstance(arg_function, list) and len(arg_function) == 0 ): - # Only the speak field is exposed to users or other agents + # Only the response field is exposed to users or other + # agents + msg_returned = Msg( + self.name, + res.parsed.get("response", res.text), + "assistant", + ) + + if not self.verbose: + # Print out the returned message + self.speak(msg_returned) + return msg_returned # Only catch the response parsing error and expose runtime @@ -349,6 +318,20 @@

Source code for agentscope.agents.react_agent

# Parse, check and execute the tool functions in service toolkit try: + # Reorganize the parsed response to the required format of the + # service toolkit + res.parsed["function"] = [ + { + "name": res.parsed["function"], + "arguments": { + k: v + for k, v in res.parsed.items() + if k not in ["speak", "thought", "function"] + }, + }, + ] + + # Execute the function execute_results = self.service_toolkit.parse_and_call_func( res.parsed["function"], ) diff --git a/en/_modules/agentscope/parsers/regex_tagged_content_parser.html b/en/_modules/agentscope/parsers/regex_tagged_content_parser.html new file mode 100644 index 000000000..4c94cbddd --- /dev/null +++ b/en/_modules/agentscope/parsers/regex_tagged_content_parser.html @@ -0,0 +1,325 @@ + + + + + + + agentscope.parsers.regex_tagged_content_parser — AgentScope documentation + + + + + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+
    +
  • + + +
  • +
  • +
+
+
+
+
+ +

Source code for agentscope.parsers.regex_tagged_content_parser

+# -*- coding: utf-8 -*-
+"""The parser for dynamic tagged content"""
+import json
+import re
+from typing import Union, Sequence, Optional, List
+
+from loguru import logger
+
+from ..exception import TagNotFoundError
+from ..models import ModelResponse
+from ..parsers import ParserBase
+from ..parsers.parser_base import DictFilterMixin
+
+
+
+[docs] +class RegexTaggedContentParser(ParserBase, DictFilterMixin): + """A regex tagged content parser, which extracts tagged content according + to the provided regex pattern. Different from other parsers, this parser + allows to extract multiple tagged content without knowing the keys in + advance. The parsed result will be a dictionary within the parsed field of + the model response. + + Compared with other parsers, this parser is more flexible and can be used + in dynamic scenarios where + - the keys are not known in advance + - the number of the tagged content is not fixed + + Note: Without knowing the keys in advance, it's hard to prepare a format + instruction template for different scenarios. Therefore, we ask the user + to provide the format instruction in the constructor. Of course, the user + can construct and manage the prompt by themselves optionally. + + Example: + By default, the parser use a regex pattern to extract tagged content + with the following format: + ``` + <{name1}>{content1}</{name1}> + <{name2}>{content2}</{name2}> + ``` + The parser will extract the content as the following dictionary: + ``` + { + "name1": content1, + "name2": content2, + } + ``` + """ + +
+[docs] + def __init__( + self, + tagged_content_pattern: str = r"<(?P<name>[^>]+)>" + r"(?P<content>.*?)" + r"</\1?>", + format_instruction: Optional[str] = None, + try_parse_json: bool = True, + required_keys: Optional[List[str]] = None, + keys_to_memory: Union[str, bool, Sequence[str]] = True, + keys_to_content: Union[str, bool, Sequence[str]] = True, + keys_to_metadata: Union[str, bool, Sequence[str]] = False, + ) -> None: + """Initialize the regex tagged content parser. + + Args: + tagged_content_pattern (`Optional[str]`, defaults to + `"<(?P<name>[^>]+)>(?P<content>.*?)</\1?>"`): + The regex pattern to extract tagged content. The pattern should + contain two named groups: `name` and `content`. The `name` + group is used as the key of the tagged content, and the + `content` group is used as the value. + format_instruction (`Optional[str]`, defaults to `None`): + The instruction for the format of the tagged content, which + will be attached to the end of the prompt messages to remind + the LLM to follow the format. + try_parse_json (`bool`, defaults to `True`): + Whether to try to parse the tagged content as JSON. Note + the parsing function won't raise exceptions. + required_keys (`Optional[List[str]]`, defaults to `None`): + The keys that are required in the tagged content. + keys_to_memory (`Union[str, bool, Sequence[str]]`, + defaults to `True`): + The keys to save to memory. + keys_to_content (`Union[str, bool, Sequence[str]]`, + defaults to `True`): + The keys to save to content. + keys_to_metadata (`Union[str, bool, Sequence[str]]`, + defaults to `False`): + The key or keys to be filtered in `to_metadata` method. If + it's + - `False`, `None` will be returned in the `to_metadata` method + - `str`, the corresponding value will be returned + - `List[str]`, a filtered dictionary will be returned + - `True`, the whole dictionary will be returned + """ + + DictFilterMixin.__init__( + self, + keys_to_memory=keys_to_memory, + keys_to_content=keys_to_content, + keys_to_metadata=keys_to_metadata, + ) + + assert ( + "<name>" in tagged_content_pattern + ), "The tagged content pattern should contain a named group 'name'." + assert ( + "<content>" in tagged_content_pattern + ), "The tagged content pattern should contain a named group 'content'." + + self.tagged_content_pattern = tagged_content_pattern + self._format_instruction = format_instruction + self.try_parse_json = try_parse_json + self.required_keys = required_keys or []
+ + + @property + def format_instruction(self) -> str: + """The format instruction for the tagged content.""" + if self._format_instruction is None: + raise ValueError( + "The format instruction is not provided. Please provide it in " + "the constructor of the parser.", + ) + return self._format_instruction + +
+[docs] + def parse(self, response: ModelResponse) -> ModelResponse: + """Parse the response text by the regex pattern, and return a dict of + the content in the parsed field of the response. + + Args: + response (`ModelResponse`): + The response to be parsed. + + Returns: + `ModelResponse`: The response with the parsed field as the parsed + result. + """ + assert response.text is not None, "The response text is None." + + matches = re.finditer( + self.tagged_content_pattern, + response.text, + flags=re.DOTALL, + ) + + results = {} + for match in matches: + results[match.group("name")] = match.group("content") + + keys_missing = [ + key for key in self.required_keys if key not in results + ] + + if len(keys_missing) > 0: + raise TagNotFoundError( + f"Failed to find tags: {', '.join(keys_missing)}", + response.text, + ) + + if self.try_parse_json: + keys_failed = [] + for key in results: + try: + results[key] = json.loads(results[key]) + except json.JSONDecodeError: + keys_failed.append(key) + + logger.debug( + f'Failed to parse JSON for keys: {", ".join(keys_failed)}', + ) + + response.parsed = results + return response
+
+ +
+ +
+
+
+ +
+ +
+

© Copyright 2024, Alibaba Tongyi Lab.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
+
+
+
+
+ + + + \ No newline at end of file diff --git a/en/_modules/agentscope/service/service_toolkit.html b/en/_modules/agentscope/service/service_toolkit.html index a7a3e81d5..f9162e8ce 100644 --- a/en/_modules/agentscope/service/service_toolkit.html +++ b/en/_modules/agentscope/service/service_toolkit.html @@ -504,17 +504,9 @@

Source code for agentscope.service.service_toolkit

All modules for which code is available
  • agentscope.parsers.code_block_parser
  • agentscope.parsers.json_object_parser
  • agentscope.parsers.parser_base
  • +
  • agentscope.parsers.regex_tagged_content_parser
  • agentscope.parsers.tagged_content_parser
  • agentscope.pipelines.functional
  • agentscope.pipelines.pipeline
  • diff --git a/en/_sources/agentscope.parsers.regex_tagged_content_parser.rst.txt b/en/_sources/agentscope.parsers.regex_tagged_content_parser.rst.txt new file mode 100644 index 000000000..34d77e4cf --- /dev/null +++ b/en/_sources/agentscope.parsers.regex_tagged_content_parser.rst.txt @@ -0,0 +1,7 @@ +agentscope.parsers.regex\_tagged\_content\_parser module +======================================================== + +.. automodule:: agentscope.parsers.regex_tagged_content_parser + :members: + :undoc-members: + :show-inheritance: diff --git a/en/_sources/agentscope.parsers.rst.txt b/en/_sources/agentscope.parsers.rst.txt index 9ddffdc95..c5fdb5530 100644 --- a/en/_sources/agentscope.parsers.rst.txt +++ b/en/_sources/agentscope.parsers.rst.txt @@ -10,6 +10,7 @@ Submodules agentscope.parsers.code_block_parser agentscope.parsers.json_object_parser agentscope.parsers.parser_base + agentscope.parsers.regex_tagged_content_parser agentscope.parsers.tagged_content_parser Module contents diff --git a/en/_sources/tutorial/203-parser.md.txt b/en/_sources/tutorial/203-parser.md.txt index bb2fae98e..5bbf46dd7 100644 --- a/en/_sources/tutorial/203-parser.md.txt +++ b/en/_sources/tutorial/203-parser.md.txt @@ -65,13 +65,15 @@ You should generate python code in a fenced code block as follows AgentScope provides multiple built-in parsers, and developers can choose according to their needs. -| Target Format | Parser Class | Description | -| --- | --- |------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| -| String | `MarkdownCodeBlockParser` | Requires LLM to generate specified text within a Markdown code block marked by ```. The result is a string. | -| Dictionary | `MarkdownJsonDictParser` | Requires LLM to produce a specified dictionary within the code block marked by \```json and \```. The result is a Python dictionary. | -| | `MultiTaggedContentParser` | Requires LLM to generate specified content within multiple tags. Contents from different tags will be parsed into a single Python dictionary with different key-value pairs. | +| Target Format | Parser Class | Description | +|---------------------------|----------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| +| String | `MarkdownCodeBlockParser` | Requires LLM to generate specified text within a Markdown code block marked by ```. The result is a string. | +| Dictionary | `MarkdownJsonDictParser` | Requires LLM to produce a specified dictionary within the code block marked by \```json and \```. The result is a Python dictionary. | +| | `MultiTaggedContentParser` | Requires LLM to generate specified content within multiple tags. Contents from different tags will be parsed into a single Python dictionary with different key-value pairs. | +| | `RegexTaggedContentParser` | For uncertain tag names and quantities, allows users to modify regular expressions, and the return result is a dictionary. | | JSON / Python Object Type | `MarkdownJsonObjectParser` | Requires LLM to produce specified content within the code block marked by \```json and \```. The result will be converted into a Python object via json.loads. | + > **NOTE**: Compared to `MarkdownJsonDictParser`, `MultiTaggedContentParser` is more suitable for weak LLMs and when the required format is too complex. > For example, when LLM is required to generate Python code, if the code is returned directly within a dictionary, LLM needs to be aware of escaping characters (\t, \n, ...), and the differences between double and single quotes when calling `json.loads` > @@ -263,12 +265,34 @@ In AgentScope, we achieve post-processing by calling the `to_content`, `to_memor > None > ``` +#### Parsers -Next we will introduce two parsers for dictionary type. +For dictionary type return values, AgentScope provides multiple parsers for developers to choose from according to their needs. -#### MarkdownJsonDictParser +##### RegexTaggedContentParser -##### Initialization & Format Instruction Template +###### Initialization + +`RegexTaggedContentParser` is designed for scenarios where 1) the tag name is uncertain, and 2) the number of tags is uncertain. +In this case, the parser cannot provide a general response format instruction, so developers need to provide the corresponding response format instruction (`format_instruction`) when initializing. +Of course, the developers can handle the prompt engineering by themselves optionally. + +```python +from agentscope.parsers import RegexTaggedContentParser + +parser = RegexTaggedContentParser( + format_instruction="""Respond with specific tags as outlined below +what you thought +what you speak +""", + try_parse_json=True, # Try to parse the content of the tag as JSON object + required_keys=["thought", "speak"] # Required keys in the returned dictionary +) +``` + +##### MarkdownJsonDictParser + +###### Initialization & Format Instruction Template - `MarkdownJsonDictParser` requires LLM to generate dictionary within a code block fenced by \```json and \``` tags. @@ -303,7 +327,7 @@ This parameter can be a string or a dictionary. For dictionary, it will be autom ``` ```` -##### Validation +###### Validation The `content_hint` parameter in `MarkdownJsonDictParser` also supports type validation based on Pydantic. When initializing, you can set `content_hint` to a Pydantic model class, and AgentScope will modify the `instruction_format` attribute based on this class. Besides, Pydantic will be used to validate the dictionary returned by LLM during parsing. @@ -346,11 +370,11 @@ parser.parser(""" """) ```` -#### MultiTaggedContentParser +##### MultiTaggedContentParser `MultiTaggedContentParser` asks LLM to generate specific content within multiple tag pairs. The content from different tag pairs will be parsed into a single Python dictionary. Its usage is similar to `MarkdownJsonDictParser`, but the initialization method is different, and it is more suitable for weak LLMs or complex return content. -##### Initialization & Format Instruction Template +###### Initialization & Format Instruction Template Within `MultiTaggedContentParser`, each tag pair will be specified by as `TaggedContent` object, which contains - Tag name (`name`), the key value in the returned dictionary @@ -393,7 +417,7 @@ Respond with specific tags as outlined below, and the content between [FINISH_DI [FINISH_DISCUSSION]true/false, whether the discussion is finished[/FINISH_DISCUSSION] ``` -##### Parse Function +###### Parse Function - `MultiTaggedContentParser`'s parsing result is a dictionary, whose keys are the value of `name` in the `TaggedContent` objects. The following is an example of parsing the LLM response in the werewolf game: diff --git a/en/agentscope.agents.html b/en/agentscope.agents.html index 14f68435a..83c44825d 100644 --- a/en/agentscope.agents.html +++ b/en/agentscope.agents.html @@ -744,7 +744,7 @@

    Submodules
    -__init__(name: str, model_config_name: str, service_toolkit: ServiceToolkit | None = None, sys_prompt: str = "You're a helpful assistant. Your name is {name}.", max_iters: int = 10, verbose: bool = True, **kwargs: Any) None[source]
    +__init__(name: str, model_config_name: str, service_toolkit: ServiceToolkit, sys_prompt: str = "You're a helpful assistant. Your name is {name}.", max_iters: int = 10, verbose: bool = True) None[source]

    Initialize the ReAct agent with the given name, model config name and tools.

    diff --git a/en/agentscope.agents.react_agent.html b/en/agentscope.agents.react_agent.html index bb7d2b516..feba5efae 100644 --- a/en/agentscope.agents.react_agent.html +++ b/en/agentscope.agents.react_agent.html @@ -137,7 +137,7 @@ their own needs.

    -__init__(name: str, model_config_name: str, service_toolkit: ServiceToolkit | None = None, sys_prompt: str = "You're a helpful assistant. Your name is {name}.", max_iters: int = 10, verbose: bool = True, **kwargs: Any) None[source]
    +__init__(name: str, model_config_name: str, service_toolkit: ServiceToolkit, sys_prompt: str = "You're a helpful assistant. Your name is {name}.", max_iters: int = 10, verbose: bool = True) None[source]

    Initialize the ReAct agent with the given name, model config name and tools.

    diff --git a/en/agentscope.html b/en/agentscope.html index bc49eafd1..4a5bb6f2d 100644 --- a/en/agentscope.html +++ b/en/agentscope.html @@ -472,6 +472,10 @@

    SubpackagesDictFilterMixin +
  • agentscope.parsers.regex_tagged_content_parser module +
  • agentscope.parsers.tagged_content_parser module
  • +
  • RegexTaggedContentParser +
  • diff --git a/en/agentscope.parsers.html b/en/agentscope.parsers.html index 558971c09..32aa2492d 100644 --- a/en/agentscope.parsers.html +++ b/en/agentscope.parsers.html @@ -176,6 +176,15 @@

    Submodulesagentscope.parsers.regex_tagged_content_parser module +
  • agentscope.parsers.tagged_content_parser module
    • TaggedContent
      • TaggedContent.__init__()
      • @@ -613,6 +622,114 @@

        Submodules +
        +class agentscope.parsers.RegexTaggedContentParser(tagged_content_pattern: str = '<(?P<name>[^>]+)>(?P<content>.*?)</\\1?>', format_instruction: str | None = None, try_parse_json: bool = True, required_keys: List[str] | None = None, keys_to_memory: str | bool | Sequence[str] = True, keys_to_content: str | bool | Sequence[str] = True, keys_to_metadata: str | bool | Sequence[str] = False)[source]
        +

        Bases: ParserBase, DictFilterMixin

        +

        A regex tagged content parser, which extracts tagged content according +to the provided regex pattern. Different from other parsers, this parser +allows to extract multiple tagged content without knowing the keys in +advance. The parsed result will be a dictionary within the parsed field of +the model response.

        +

        Compared with other parsers, this parser is more flexible and can be used +in dynamic scenarios where +- the keys are not known in advance +- the number of the tagged content is not fixed

        +

        Note: Without knowing the keys in advance, it’s hard to prepare a format +instruction template for different scenarios. Therefore, we ask the user +to provide the format instruction in the constructor. Of course, the user +can construct and manage the prompt by themselves optionally.

        +

        Example

        +

        By default, the parser use a regex pattern to extract tagged content +with the following format: +` +<{name1}>{content1}</{name1}> +<{name2}>{content2}</{name2}> +` +The parser will extract the content as the following dictionary: +``` +{

        +
        +

        “name1”: content1, +“name2”: content2,

        +
        +
        +

        }

        +
        +
        +__init__(tagged_content_pattern: str = '<(?P<name>[^>]+)>(?P<content>.*?)</\\1?>', format_instruction: str | None = None, try_parse_json: bool = True, required_keys: List[str] | None = None, keys_to_memory: str | bool | Sequence[str] = True, keys_to_content: str | bool | Sequence[str] = True, keys_to_metadata: str | bool | Sequence[str] = False) None[source]
        +

        Initialize the regex tagged content parser.

        +
        +
        Parameters:
        +
          +
        • (Optional[str] (tagged_content_pattern)

        • +
        • to (defaults)

        • +
        • `"<

          The regex pattern to extract tagged content. The pattern should +contain two named groups: name and content. The name +group is used as the key of the tagged content, and the +content group is used as the value.

          +

        • +
        • format_instruction (Optional[str], defaults to None) – The instruction for the format of the tagged content, which +will be attached to the end of the prompt messages to remind +the LLM to follow the format.

        • +
        • try_parse_json (bool, defaults to True) – Whether to try to parse the tagged content as JSON. Note +the parsing function won’t raise exceptions.

        • +
        • required_keys (Optional[List[str]], defaults to None) – The keys that are required in the tagged content.

        • +
        • (`Union[str (keys_to_memory) –

        • +
        • bool

        • +
        • Sequence[str]]`

        • +
        +
        +
        +

        :param : +:param defaults to True): The keys to save to memory. +:param keys_to_content (Union[str: +:param bool: +:param Sequence[str]]: +:param : +:param defaults to True): The keys to save to content. +:param keys_to_metadata (Union[str: +:param bool: +:param Sequence[str]]: +:param : +:param defaults to False): The key or keys to be filtered in to_metadata method. If

        +
        +

        it’s +- False, None will be returned in the to_metadata method +- str, the corresponding value will be returned +- List[str], a filtered dictionary will be returned +- True, the whole dictionary will be returned

        +
        +
        + +
        +
        +property format_instruction: str
        +

        The format instruction for the tagged content.

        +
        + +
        +
        +parse(response: ModelResponse) ModelResponse[source]
        +

        Parse the response text by the regex pattern, and return a dict of +the content in the parsed field of the response.

        +
        +
        Parameters:
        +

        response (ModelResponse) – The response to be parsed.

        +
        +
        Returns:
        +

        The response with the parsed field as the parsed +result.

        +
        +
        Return type:
        +

        ModelResponse

        +
        +
        +
        + +
        +

  • + diff --git a/en/agentscope.parsers.parser_base.html b/en/agentscope.parsers.parser_base.html index 80714c165..c1aacd12b 100644 --- a/en/agentscope.parsers.parser_base.html +++ b/en/agentscope.parsers.parser_base.html @@ -23,7 +23,7 @@ - + @@ -204,7 +204,7 @@


    diff --git a/en/agentscope.parsers.regex_tagged_content_parser.html b/en/agentscope.parsers.regex_tagged_content_parser.html new file mode 100644 index 000000000..36a405765 --- /dev/null +++ b/en/agentscope.parsers.regex_tagged_content_parser.html @@ -0,0 +1,267 @@ + + + + + + + + agentscope.parsers.regex_tagged_content_parser module — AgentScope documentation + + + + + + + + + + + + + + + + + + + + +
    + + +
    + +
    +
    +
    + +
    +
    +
    +
    + +
    +

    agentscope.parsers.regex_tagged_content_parser module

    +

    The parser for dynamic tagged content

    +
    +
    +class agentscope.parsers.regex_tagged_content_parser.RegexTaggedContentParser(tagged_content_pattern: str = '<(?P<name>[^>]+)>(?P<content>.*?)</\\1?>', format_instruction: str | None = None, try_parse_json: bool = True, required_keys: List[str] | None = None, keys_to_memory: str | bool | Sequence[str] = True, keys_to_content: str | bool | Sequence[str] = True, keys_to_metadata: str | bool | Sequence[str] = False)[source]
    +

    Bases: ParserBase, DictFilterMixin

    +

    A regex tagged content parser, which extracts tagged content according +to the provided regex pattern. Different from other parsers, this parser +allows to extract multiple tagged content without knowing the keys in +advance. The parsed result will be a dictionary within the parsed field of +the model response.

    +

    Compared with other parsers, this parser is more flexible and can be used +in dynamic scenarios where +- the keys are not known in advance +- the number of the tagged content is not fixed

    +

    Note: Without knowing the keys in advance, it’s hard to prepare a format +instruction template for different scenarios. Therefore, we ask the user +to provide the format instruction in the constructor. Of course, the user +can construct and manage the prompt by themselves optionally.

    +

    Example

    +

    By default, the parser use a regex pattern to extract tagged content +with the following format: +` +<{name1}>{content1}</{name1}> +<{name2}>{content2}</{name2}> +` +The parser will extract the content as the following dictionary: +``` +{

    +
    +

    “name1”: content1, +“name2”: content2,

    +
    +
    +

    }

    +
    +
    +__init__(tagged_content_pattern: str = '<(?P<name>[^>]+)>(?P<content>.*?)</\\1?>', format_instruction: str | None = None, try_parse_json: bool = True, required_keys: List[str] | None = None, keys_to_memory: str | bool | Sequence[str] = True, keys_to_content: str | bool | Sequence[str] = True, keys_to_metadata: str | bool | Sequence[str] = False) None[source]
    +

    Initialize the regex tagged content parser.

    +
    +
    Parameters:
    +
      +
    • (Optional[str] (tagged_content_pattern)

    • +
    • to (defaults)

    • +
    • `"<

      The regex pattern to extract tagged content. The pattern should +contain two named groups: name and content. The name +group is used as the key of the tagged content, and the +content group is used as the value.

      +

    • +
    • format_instruction (Optional[str], defaults to None) – The instruction for the format of the tagged content, which +will be attached to the end of the prompt messages to remind +the LLM to follow the format.

    • +
    • try_parse_json (bool, defaults to True) – Whether to try to parse the tagged content as JSON. Note +the parsing function won’t raise exceptions.

    • +
    • required_keys (Optional[List[str]], defaults to None) – The keys that are required in the tagged content.

    • +
    • (`Union[str (keys_to_memory) –

    • +
    • bool

    • +
    • Sequence[str]]`

    • +
    +
    +
    +

    :param : +:param defaults to True): The keys to save to memory. +:param keys_to_content (Union[str: +:param bool: +:param Sequence[str]]: +:param : +:param defaults to True): The keys to save to content. +:param keys_to_metadata (Union[str: +:param bool: +:param Sequence[str]]: +:param : +:param defaults to False): The key or keys to be filtered in to_metadata method. If

    +
    +

    it’s +- False, None will be returned in the to_metadata method +- str, the corresponding value will be returned +- List[str], a filtered dictionary will be returned +- True, the whole dictionary will be returned

    +
    +
    + +
    +
    +property format_instruction: str
    +

    The format instruction for the tagged content.

    +
    + +
    +
    +parse(response: ModelResponse) ModelResponse[source]
    +

    Parse the response text by the regex pattern, and return a dict of +the content in the parsed field of the response.

    +
    +
    Parameters:
    +

    response (ModelResponse) – The response to be parsed.

    +
    +
    Returns:
    +

    The response with the parsed field as the parsed +result.

    +
    +
    Return type:
    +

    ModelResponse

    +
    +
    +
    + +
    +
    + +
    + + +
    +
    + +
    +
    +
    +
    + + + + \ No newline at end of file diff --git a/en/agentscope.parsers.tagged_content_parser.html b/en/agentscope.parsers.tagged_content_parser.html index bad889e17..97fa6512d 100644 --- a/en/agentscope.parsers.tagged_content_parser.html +++ b/en/agentscope.parsers.tagged_content_parser.html @@ -24,7 +24,7 @@ - + @@ -288,7 +288,7 @@
    diff --git a/en/genindex.html b/en/genindex.html index a604aa41b..5c43dcc3c 100644 --- a/en/genindex.html +++ b/en/genindex.html @@ -273,6 +273,10 @@

    _

  • (agentscope.parsers.MultiTaggedContentParser method)
  • (agentscope.parsers.parser_base.DictFilterMixin method) +
  • +
  • (agentscope.parsers.regex_tagged_content_parser.RegexTaggedContentParser method) +
  • +
  • (agentscope.parsers.RegexTaggedContentParser method)
  • (agentscope.parsers.tagged_content_parser.MultiTaggedContentParser method)
  • @@ -726,6 +730,13 @@

    A

    +
  • + agentscope.parsers.regex_tagged_content_parser + +
  • @@ -798,6 +809,8 @@

    A

  • module
  • + +
    • agentscope.rpc.rpc_agent_client @@ -805,8 +818,6 @@

      A

    • module
    - -
    • agentscope.rpc.rpc_agent_pb2 @@ -1839,6 +1850,10 @@

      F

    • (agentscope.parsers.MarkdownJsonObjectParser property)
    • (agentscope.parsers.MultiTaggedContentParser attribute) +
    • +
    • (agentscope.parsers.regex_tagged_content_parser.RegexTaggedContentParser property) +
    • +
    • (agentscope.parsers.RegexTaggedContentParser property)
    • (agentscope.parsers.tagged_content_parser.MultiTaggedContentParser attribute)
    • @@ -2582,6 +2597,8 @@

      M

    • agentscope.parsers.json_object_parser
    • agentscope.parsers.parser_base +
    • +
    • agentscope.parsers.regex_tagged_content_parser
    • agentscope.parsers.tagged_content_parser
    • @@ -2976,6 +2993,10 @@

      P

    • (agentscope.parsers.parser_base.ParserBase method)
    • (agentscope.parsers.ParserBase method) +
    • +
    • (agentscope.parsers.regex_tagged_content_parser.RegexTaggedContentParser method) +
    • +
    • (agentscope.parsers.RegexTaggedContentParser method)
    • (agentscope.parsers.tagged_content_parser.MultiTaggedContentParser method)
    • @@ -3118,6 +3139,12 @@

      R

      +
    • RegexTaggedContentParser (class in agentscope.parsers) + +
    • register() (agentscope.utils.monitor.DummyMonitor method) diff --git a/en/objects.inv b/en/objects.inv index 65b32f6de..7f8ddc91e 100644 Binary files a/en/objects.inv and b/en/objects.inv differ diff --git a/en/py-modindex.html b/en/py-modindex.html index 7c38bb458..18585cac8 100644 --- a/en/py-modindex.html +++ b/en/py-modindex.html @@ -302,6 +302,11 @@

      Python Module Index

          agentscope.parsers.parser_base + + +     + agentscope.parsers.regex_tagged_content_parser +     diff --git a/en/searchindex.js b/en/searchindex.js index f6c58bc47..1f1966834 100644 --- a/en/searchindex.js +++ b/en/searchindex.js @@ -1 +1 @@ -Search.setIndex({"alltitles": {"(Optional) Setting up a local embedding model service": [[117, "optional-setting-up-a-local-embedding-model-service"]], "A Quick Introduction to RAG in AgentScope": [[117, null]], "About AgentScope": [[100, null]], "About Dashboard": [[115, "about-dashboard"]], "About Memory": [[111, "about-memory"]], "About Message": [[111, "about-message"]], "About PromptEngine Class": [[112, "about-promptengine-class"]], "About Service Toolkit": [[110, "about-service-toolkit"]], "About ServiceResponse": [[110, "about-serviceresponse"]], "About Workstation": [[115, "about-workstation"]], "Actor Model": [[114, "actor-model"]], "Adding and Deleting Participants": [[106, "adding-and-deleting-participants"]], "Advanced Usage": [[109, "advanced-usage"], [113, "advanced-usage"], [114, "advanced-usage"]], "Agent": [[100, "agent"], [105, null]], "Agent Server": [[114, "agent-server"]], "AgentScope API Reference": [[98, null]], "AgentScope Code Structure": [[100, "agentscope-code-structure"]], "AgentScope Documentation": [[98, null]], "AgentScope Studio": [[115, null]], "Background": [[108, "background"], [116, "background"]], "Basic Parameters": [[107, "basic-parameters"]], "Basic Usage": [[113, "basic-usage"]], "Broadcast message in MsgHub": [[106, "broadcast-message-in-msghub"]], "Build Model Service from Scratch": [[107, "build-model-service-from-scratch"]], "Build Your Application": [[115, "build-your-application"]], "Built-in Prompt Strategies": [[112, "built-in-prompt-strategies"]], "Built-in Service Functions": [[110, "built-in-service-functions"]], "Category": [[106, "category"]], "Challenges in Prompt Construction": [[112, "challenges-in-prompt-construction"]], "Check Your Application": [[115, "check-your-application"]], "Child Process Mode": [[114, "child-process-mode"]], "Code Review": [[119, "code-review"]], "Commit Your Changes": [[119, "commit-your-changes"]], "Configuration": [[107, "configuration"]], "Configuration Format": [[107, "configuration-format"]], "Contribute to AgentScope": [[119, null]], "Contribute to Codebase": [[119, "contribute-to-codebase"]], "Creat Your Own Model Wrapper": [[107, "creat-your-own-model-wrapper"]], "Create a New Branch": [[119, "create-a-new-branch"]], "Create a Virtual Environment": [[101, "create-a-virtual-environment"]], "Create new Service Function": [[110, "create-new-service-function"]], "Creating a MsgHub": [[106, "creating-a-msghub"]], "Customized Parser": [[108, "customized-parser"]], "Customizing Agents from the AgentPool": [[105, "customizing-agents-from-the-agentpool"]], "DashScope API": [[107, "dashscope-api"]], "DashScopeChatWrapper": [[112, "dashscopechatwrapper"]], "DashScopeMultiModalWrapper": [[112, "dashscopemultimodalwrapper"]], "Detailed Parameters": [[107, "detailed-parameters"]], "DialogAgent": [[105, "dialogagent"]], "Dictionary Type": [[108, "dictionary-type"]], "DingTalk (\u9489\u9489)": [[118, "dingtalk"]], "Discord": [[118, "discord"]], "Distribution": [[114, null]], "Example": [[110, "example"]], "Example: Werewolf Game": [[103, null]], "Explore Built-in Examples": [[115, "explore-built-in-examples"]], "Exploring the AgentPool": [[105, "exploring-the-agentpool"]], "ForLoopPipeline": [[106, "forlooppipeline"]], "Fork and Clone the Repository": [[119, "fork-and-clone-the-repository"]], "Format Instruction Template": [[108, "format-instruction-template"]], "Formatting Prompts in Dynamic Way": [[112, "formatting-prompts-in-dynamic-way"]], "Gemini API": [[107, "gemini-api"]], "GeminiChatWrapper": [[112, "geminichatwrapper"]], "Generation": [[116, "generation"]], "Generation with In Context Learning": [[116, "generation-with-in-context-learning"]], "Get Involved": [[120, null]], "Get a Monitor Instance": [[113, "get-a-monitor-instance"]], "Getting Involved": [[98, "getting-involved"], [121, "getting-involved"]], "Getting Started": [[103, "getting-started"]], "GitHub": [[118, "github"]], "Handling Quotas": [[113, "handling-quotas"]], "How is AgentScope designed?": [[100, "how-is-agentscope-designed"]], "How to create a Knowledge object": [[117, "how-to-create-a-knowledge-object"]], "How to use": [[110, "how-to-use"]], "How to use Service Functions": [[110, "how-to-use-service-functions"]], "How to use a Knowledge object": [[117, "how-to-use-a-knowledge-object"]], "IfElsePipeline": [[106, "ifelsepipeline"]], "Implement Werewolf Pipeline": [[103, "implement-werewolf-pipeline"]], "Implementation": [[114, "implementation"]], "Import Running Histories": [[115, "import-running-histories"]], "Import or Export Your Application": [[115, "import-or-export-your-application"]], "In Model Calling": [[109, "in-model-calling"]], "In Model Configuration": [[109, "in-model-configuration"]], "Independent Process Mode": [[114, "independent-process-mode"]], "Initialization": [[108, "initialization"], [112, "initialization"], [116, "initialization"], [116, "id1"]], "Initialization & Format Instruction Template": [[108, "initialization-format-instruction-template"], [108, "id1"], [108, "id3"]], "Install from Source": [[101, "install-from-source"]], "Install with Pip": [[101, "install-with-pip"]], "Installation": [[101, null]], "Installing AgentScope": [[101, "installing-agentscope"]], "JSON / Python Object Type": [[108, "json-python-object-type"]], "Joining AgentScope Community": [[118, null]], "Joining Prompt Components": [[112, "joining-prompt-components"]], "Key Concepts": [[100, "key-concepts"]], "Key Features of PromptEngine": [[112, "key-features-of-promptengine"]], "Knowledge": [[117, "knowledge"]], "Knowledge Bank": [[117, "knowledge-bank"]], "Leverage Pipeline and MsgHub": [[103, "leverage-pipeline-and-msghub"]], "LiteLLM Chat API": [[107, "litellm-chat-api"]], "LiteLLMChatWrapper": [[112, "litellmchatwrapper"]], "Logging": [[104, null], [104, "id1"]], "Logging a Chat Message": [[104, "logging-a-chat-message"]], "Logging a System information": [[104, "logging-a-system-information"]], "Making Changes": [[119, "making-changes"]], "Manage your agent server processes": [[114, "manage-your-agent-server-processes"]], "MarkdownCodeBlockParser": [[108, "markdowncodeblockparser"]], "MarkdownJsonDictParser": [[108, "markdownjsondictparser"]], "MarkdownJsonObjectParser": [[108, "markdownjsonobjectparser"]], "Memory": [[111, null]], "MemoryBase Class": [[111, "memorybase-class"]], "Message": [[100, "message"]], "MessageBase Class": [[111, "messagebase-class"]], "Model": [[107, null]], "Module contents": [[0, "module-agentscope"], [1, "module-agentscope.agents"], [15, "module-agentscope.memory"], [19, "module-agentscope.models"], [31, "module-agentscope.parsers"], [36, "module-agentscope.pipelines"], [39, "module-agentscope.prompt"], [40, "module-agentscope.rag"], [44, "module-agentscope.rpc"], [48, "module-agentscope.server"], [51, "module-agentscope.service"], [52, "module-agentscope.service.execute_code"], [55, "module-agentscope.service.file"], [59, "module-agentscope.service.multi_modality"], [62, "module-agentscope.service.retrieval"], [68, "module-agentscope.service.sql_query"], [72, "module-agentscope.service.text_processing"], [74, "module-agentscope.service.web"], [80, "module-agentscope.strategy"], [82, "module-agentscope.studio"], [83, "module-agentscope.utils"], [88, "module-agentscope.web"], [89, "module-agentscope.web.gradio"], [93, "module-agentscope.web.workstation"]], "Monitor": [[113, null]], "More about knowledge configurations": [[117, "more-about-knowledge-configurations"]], "More details inside LlamaIndexKnowledge": [[117, "more-details-inside-llamaindexknowledge"]], "Msg Class": [[111, "msg-class"]], "MsgHub": [[106, "msghub"]], "MultiTaggedContentParser": [[108, "multitaggedcontentparser"]], "Non-Vision Models": [[112, "non-vision-models"]], "Note": [[115, "note"]], "Ollama API": [[107, "ollama-api"]], "OllamaChatWrapper": [[112, "ollamachatwrapper"]], "OllamaGenerationWrapper": [[112, "ollamagenerationwrapper"]], "OpenAI API": [[107, "openai-api"]], "OpenAIChatWrapper": [[112, "openaichatwrapper"]], "Output List Type Prompt": [[112, "output-list-type-prompt"]], "Output String Type Prompt": [[112, "output-string-type-prompt"]], "Overview": [[108, "overview"]], "Parse Function": [[108, "parse-function"], [108, "id2"], [108, "id4"]], "Parser": [[103, "parser"]], "Parser Module": [[108, "parser-module"]], "Pipeline Combination": [[106, "pipeline-combination"]], "Pipeline and MsgHub": [[106, null]], "Pipelines": [[106, "pipelines"]], "PlaceHolder": [[114, "placeholder"]], "Post Request API": [[107, "post-request-api"]], "Printing in Streaming Mode": [[109, "printing-in-streaming-mode"]], "Prompt Engine (Will be deprecated in the future)": [[112, "prompt-engine-will-be-deprecated-in-the-future"]], "Prompt Engineering": [[112, null]], "Prompt Strategy": [[112, "prompt-strategy"], [112, "id1"], [112, "id2"], [112, "id3"], [112, "id4"], [112, "id5"], [112, "id6"], [112, "id7"]], "Quick Start": [[102, null], [115, "quick-start"]], "RAG agent": [[117, "rag-agent"]], "ReAct Agent and Tool Usage": [[108, "react-agent-and-tool-usage"]], "Register Running Application": [[115, "register-running-application"]], "Register a budget for an API": [[113, "register-a-budget-for-an-api"]], "Registering API Usage Metrics": [[113, "registering-api-usage-metrics"]], "Report Bugs and Ask For New Features?": [[119, "report-bugs-and-ask-for-new-features"]], "Resetting and Removing Metrics": [[113, "resetting-and-removing-metrics"]], "Response Parser": [[108, null]], "Retrieving Metrics": [[113, "retrieving-metrics"]], "Run Your Application": [[115, "run-your-application"]], "SequentialPipeline": [[106, "sequentialpipeline"]], "Service": [[100, "service"]], "Setting Up the Logger": [[104, "setting-up-the-logger"]], "Setup Streaming Mode": [[109, "setup-streaming-mode"]], "Start AgentScope Studio": [[115, "start-agentscope-studio"]], "Step 1: Convert your agent to its distributed version": [[114, "step-1-convert-your-agent-to-its-distributed-version"]], "Step 1: Prepare Model API and Set Model Configs": [[103, "step-1-prepare-model-api-and-set-model-configs"]], "Step 2: Define the Roles of Each Agent": [[103, "step-2-define-the-roles-of-each-agent"]], "Step 2: Orchestrate Distributed Application Flow": [[114, "step-2-orchestrate-distributed-application-flow"]], "Step 3: Initialize AgentScope and the Agents": [[103, "step-3-initialize-agentscope-and-the-agents"]], "Step 4: Set Up the Game Logic": [[103, "step-4-set-up-the-game-logic"]], "Step 5: Run the Application": [[103, "step-5-run-the-application"]], "Step1: Prepare Model": [[102, "step1-prepare-model"]], "Step2: Create Agents": [[102, "step2-create-agents"]], "Step3: Agent Conversation": [[102, "step3-agent-conversation"]], "Streaming": [[109, null]], "String Type": [[108, "string-type"]], "Submit a Pull Request": [[119, "submit-a-pull-request"]], "Submodules": [[0, "submodules"], [1, "submodules"], [15, "submodules"], [19, "submodules"], [31, "submodules"], [36, "submodules"], [40, "submodules"], [44, "submodules"], [48, "submodules"], [51, "submodules"], [52, "submodules"], [55, "submodules"], [59, "submodules"], [62, "submodules"], [68, "submodules"], [72, "submodules"], [74, "submodules"], [80, "submodules"], [83, "submodules"], [89, "submodules"], [93, "submodules"]], "Subpackages": [[0, "subpackages"], [51, "subpackages"], [88, "subpackages"]], "Supported Models": [[107, "supported-models"]], "SwitchPipeline": [[106, "switchpipeline"]], "System Prompt Comparer": [[116, "system-prompt-comparer"]], "System Prompt Generator": [[116, "system-prompt-generator"]], "System Prompt Optimization": [[116, null]], "System Prompt Optimizer": [[116, "system-prompt-optimizer"]], "Table of Contents": [[108, "table-of-contents"], [116, "table-of-contents"]], "TemporaryMemory": [[111, "temporarymemory"]], "Tool": [[110, null]], "Tutorial Navigator": [[98, "tutorial-navigator"], [121, "tutorial-navigator"]], "Typical Use Cases": [[108, "typical-use-cases"]], "Understanding AgentBase": [[105, "understanding-agentbase"]], "Understanding the Monitor in AgentScope": [[113, "understanding-the-monitor-in-agentscope"]], "Updating Metrics": [[113, "updating-metrics"]], "Usage": [[106, "usage"], [106, "id1"], [114, "usage"]], "UserAgent": [[105, "useragent"]], "Using Conda": [[101, "using-conda"]], "Using LlamaIndexKnowledge as an example": [[117, "using-llamaindexknowledge-as-an-example"]], "Using Virtualenv": [[101, "using-virtualenv"]], "Using prefix to Distinguish Metrics": [[113, "using-prefix-to-distinguish-metrics"]], "Using the Monitor": [[113, "using-the-monitor"]], "Validation": [[108, "validation"]], "Vision Models": [[112, "vision-models"]], "Welcome to AgentScope Tutorial": [[98, "welcome-to-agentscope-tutorial"], [121, null]], "WereWolf Game": [[108, "werewolf-game"]], "What is AgentScope?": [[100, "what-is-agentscope"]], "WhileLoopPipeline": [[106, "whilelooppipeline"]], "Why AgentScope?": [[100, "why-agentscope"]], "Workflow": [[100, "workflow"]], "ZhipuAI API": [[107, "zhipuai-api"]], "ZhipuAIChatWrapper": [[112, "zhipuaichatwrapper"]], "agentscope": [[99, null]], "agentscope package": [[0, null]], "agentscope.agents package": [[1, null]], "agentscope.agents.agent module": [[2, null]], "agentscope.agents.dialog_agent module": [[3, null]], "agentscope.agents.dict_dialog_agent module": [[4, null]], "agentscope.agents.operator module": [[5, null]], "agentscope.agents.rag_agent module": [[6, null]], "agentscope.agents.react_agent module": [[7, null]], "agentscope.agents.rpc_agent module": [[8, null]], "agentscope.agents.text_to_image_agent module": [[9, null]], "agentscope.agents.user_agent module": [[10, null]], "agentscope.constants module": [[11, null]], "agentscope.exception module": [[12, null]], "agentscope.file_manager module": [[13, null]], "agentscope.logging module": [[14, null]], "agentscope.memory package": [[15, null]], "agentscope.memory.memory module": [[16, null]], "agentscope.memory.temporary_memory module": [[17, null]], "agentscope.message module": [[18, null]], "agentscope.models package": [[19, null]], "agentscope.models.config module": [[20, null]], "agentscope.models.dashscope_model module": [[21, null]], "agentscope.models.gemini_model module": [[22, null]], "agentscope.models.litellm_model module": [[23, null]], "agentscope.models.model module": [[24, null]], "agentscope.models.ollama_model module": [[25, null]], "agentscope.models.openai_model module": [[26, null]], "agentscope.models.post_model module": [[27, null]], "agentscope.models.response module": [[28, null]], "agentscope.models.zhipu_model module": [[29, null]], "agentscope.msghub module": [[30, 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"agentscope.service.multi_modality.openai_services module", "agentscope.service.retrieval package", "agentscope.service.retrieval.retrieval_from_list module", "agentscope.service.retrieval.similarity module", "agentscope.service.service_response module", "agentscope.service.service_status module", "agentscope.service.service_toolkit module", "agentscope.service.sql_query package", "agentscope.service.sql_query.mongodb module", "agentscope.service.sql_query.mysql module", "agentscope.service.sql_query.sqlite module", "agentscope.service.text_processing package", "agentscope.service.text_processing.summarization module", "agentscope.service.web package", "agentscope.service.web.arxiv module", "agentscope.service.web.dblp module", "agentscope.service.web.download module", "agentscope.service.web.search module", "agentscope.service.web.web_digest module", "agentscope.strategy package", "agentscope.strategy.mixture_of_agent module", "agentscope.studio package", "agentscope.utils package", "agentscope.utils.common module", "agentscope.utils.monitor module", "agentscope.utils.token_utils module", "agentscope.utils.tools module", "agentscope.web package", "agentscope.web.gradio package", "agentscope.web.gradio.constants module", "agentscope.web.gradio.studio module", "agentscope.web.gradio.utils module", "agentscope.web.workstation package", "agentscope.web.workstation.workflow module", "agentscope.web.workstation.workflow_dag module", "agentscope.web.workstation.workflow_node module", "agentscope.web.workstation.workflow_utils module", "AgentScope Documentation", "agentscope", "About AgentScope", "Installation", "Quick Start", "Example: Werewolf Game", "Logging", "Agent", "Pipeline and MsgHub", "Model", "Response Parser", "Streaming", "Tool", "Memory", "Prompt Engineering", "Monitor", "Distribution", "AgentScope Studio", "System Prompt Optimization", "A Quick Introduction to RAG in AgentScope", "Joining AgentScope Community", "Contribute to AgentScope", "Get Involved", "Welcome to AgentScope Tutorial"], "titleterms": {"1": [104, 115], "2": [104, 115], "3": 104, "4": 104, "5": 104, "A": 118, "For": 120, "In": [110, 117], "Will": 113, "about": [101, 111, 112, 113, 116, 118], "actor": 115, "ad": 107, "advanc": [110, 114, 115], "agent": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 101, 103, 104, 106, 109, 115, 118], "agentbas": 106, "agentpool": 106, "agentscop": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 104, 114, 116, 118, 119, 120, 122], "an": [114, 118], "api": [99, 104, 108, 114], "applic": [104, 115, 116], "arxiv": 76, "ask": 120, "background": [109, 117], "bank": 118, "basic": [108, 114], "branch": 120, "broadcast": 107, "budget": 114, "bug": 120, "build": [108, 116], "built": [111, 113, 116], "call": 110, "case": 109, "categori": 107, "challeng": 113, "chang": 120, "chat": [105, 108], "check": 116, "child": 115, "class": [112, 113], "clone": 120, "code": [101, 120], "code_block_pars": 32, "codebas": 120, "combin": 107, "commit": 120, "common": [57, 85], "commun": 119, "compar": 117, "compon": 113, "concept": 101, "conda": 102, "config": [20, 104], "configur": [108, 110, 118], "constant": [11, 91], "construct": 113, "content": [0, 1, 15, 19, 31, 37, 40, 41, 45, 49, 52, 53, 56, 60, 63, 69, 73, 75, 81, 83, 84, 89, 90, 94, 109, 117], "context": 117, "contribut": 120, "convers": 103, "convert": 115, "cost": 115, "creat": [102, 103, 107, 108, 111, 118, 120], "custom": [106, 109], "dashboard": 116, "dashscop": 108, "dashscope_model": 21, "dashscope_servic": 61, "dashscopechatwrapp": 113, "dashscopemultimodalwrapp": 113, "dblp": 77, "defin": 104, "delet": 107, "deprec": 113, "design": 101, "detail": [108, 118], "dialog_ag": 3, "dialogag": 106, "dict_dialog_ag": 4, "dictionari": 109, "dingtalk": 119, "discord": 119, "distinguish": 114, "distribut": 115, "document": 99, "download": 78, "dynam": 113, "each": 104, "embed": 118, "engin": 113, "environ": 102, "exampl": [104, 111, 116, 118], "except": 12, "exec_python": 54, "exec_shel": 55, "execute_cod": [53, 54, 55], "explor": [106, 116], "export": 116, "featur": [113, 120], "file": [56, 57, 58, 59], "file_manag": 13, "flow": 115, "fork": 120, "forlooppipelin": 107, "format": [108, 109, 113], "from": [102, 106, 108], "function": [38, 109, 111], "futur": 113, "game": [104, 109], "gemini": 108, "gemini_model": 22, "geminichatwrapp": 113, "gener": 117, "get": [99, 104, 114, 121, 122], "github": 119, "gradio": [90, 91, 92, 93], "handl": 114, "histori": 116, "how": [101, 111, 118], "i": 101, "ifelsepipelin": 107, "implement": [104, 115], "import": 116, "independ": 115, "inform": 105, "initi": [104, 109, 113, 117], "insid": 118, "instal": 102, "instanc": 114, "instruct": 109, "introduct": 118, "involv": [99, 121, 122], "its": 115, "join": [113, 119], "json": [58, 109], "json_object_pars": 33, "kei": [101, 113], "knowledg": [42, 118], "knowledge_bank": 43, "launcher": 50, "learn": 117, "leverag": 104, "list": 113, "litellm": 108, "litellm_model": 23, "litellmchatwrapp": 113, "llama_index_knowledg": 44, "llamaindexknowledg": 118, "local": 118, "log": [14, 105], "logger": 105, "logic": 104, "lower": 115, "make": 120, "manag": 115, "markdowncodeblockpars": 109, "markdownjsondictpars": 109, "markdownjsonobjectpars": 109, "memori": [15, 16, 17, 112], "memorybas": 112, "messag": [18, 101, 105, 107, 112], "messagebas": 112, "metric": 114, "mixture_of_ag": 82, "mode": [110, 115], "model": [19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 103, 104, 108, 110, 113, 115, 118], "modul": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 109], "mongodb": 70, "monitor": [86, 114], "more": 118, "msg": 112, "msghub": [30, 104, 107], "multi_mod": [60, 61, 62], "multitaggedcontentpars": 109, "mysql": 71, "navig": [99, 122], "new": [111, 120], "non": 113, "note": 116, "object": [109, 118], "ollama": 108, "ollama_model": 25, "ollamachatwrapp": 113, "ollamagenerationwrapp": 113, "openai": 108, "openai_model": 26, "openai_servic": 62, "openaichatwrapp": 113, "oper": 5, "optim": 117, "option": 118, "orchestr": 115, "output": 113, "overview": 109, "own": 108, "packag": [0, 1, 15, 19, 31, 37, 40, 41, 45, 49, 52, 53, 56, 60, 63, 69, 73, 75, 81, 83, 84, 89, 90, 94], "paramet": 108, "pars": 109, "parser": [31, 32, 33, 34, 35, 36, 104, 109], "parser_bas": 34, "particip": 107, "pip": 102, "pipelin": [37, 38, 39, 104, 107], "placehold": 115, "post": 108, "post_model": 27, "prefix": 114, "prepar": [103, 104], "print": 110, "process": 115, "prompt": [40, 113, 117], "promptengin": 113, "pull": 120, "python": 109, "quick": [103, 116, 118], "quota": 114, "rag": [41, 42, 43, 44, 118], "rag_ag": 6, "react": 109, "react_ag": 7, "refer": 99, "regex_tagged_content_pars": 35, "regextaggedcontentpars": 109, "regist": [114, 116], "remov": 114, "report": 120, "repositori": 120, "request": [108, 120], "reset": 114, "respons": [28, 109], "retriev": [63, 64, 65, 114], "retrieval_from_list": 64, "review": 120, "role": 104, "rpc": [45, 46, 47, 48], "rpc_agent": 8, "rpc_agent_cli": 46, "rpc_agent_pb2": 47, "rpc_agent_pb2_grpc": 48, "run": [104, 116], "scratch": 108, "search": 79, "sequentialpipelin": 107, "server": [49, 50, 51, 115], "servic": [51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 101, 108, 111, 118], "service_respons": 66, "service_statu": 67, "service_toolkit": 68, "servicerespons": 111, "set": [104, 105, 118], "setup": 110, "similar": 65, "sourc": 102, "sql_queri": [69, 70, 71, 72], "sqlite": 72, "start": [103, 104, 116], "step": [104, 115], "step1": 103, "step2": 103, "step3": 103, "strategi": [81, 82, 113], "stream": 110, "string": [109, 113], "structur": 101, "studio": [83, 92, 116], "submit": 120, "submodul": [0, 1, 15, 19, 31, 37, 41, 45, 49, 52, 53, 56, 60, 63, 69, 73, 75, 81, 84, 90, 94], "subpackag": [0, 52, 89], "summar": 74, "support": 108, "switchpipelin": 107, "system": [105, 117], "tabl": [109, 117], "tagged_content_pars": 36, "templat": 109, "temporary_memori": 17, "temporarymemori": 112, "text": 59, "text_process": [73, 74], "text_to_image_ag": 9, "to_dist": 115, "token_util": 87, "tool": [88, 109, 111], "toolkit": 111, "tutori": [99, 122], "type": [109, 113], "typic": 109, "understand": [106, 114], "up": [104, 105, 118], "updat": 114, "us": [102, 109, 111, 114, 118], "usag": [107, 109, 110, 114, 115], "user_ag": 10, "userag": 106, "util": [84, 85, 86, 87, 88, 93], "valid": 109, "version": 115, "virtual": 102, "virtualenv": 102, "vision": 113, "wai": 113, "web": [75, 76, 77, 78, 79, 80, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98], "web_digest": 80, "welcom": [99, 122], "werewolf": [104, 109], "what": 101, "whilelooppipelin": 107, "why": 101, "workflow": [95, 101], "workflow_dag": 96, "workflow_nod": 97, "workflow_util": 98, "workstat": [94, 95, 96, 97, 98, 116], "wrapper": 108, "your": [108, 115, 116, 120], "zhipu_model": 29, "zhipuai": 108, "zhipuaichatwrapp": 113, "\u9489\u9489": 119}}) \ No newline at end of file diff --git a/en/tutorial/203-parser.html b/en/tutorial/203-parser.html index 186b21cc2..ab4899097 100644 --- a/en/tutorial/203-parser.html +++ b/en/tutorial/203-parser.html @@ -234,7 +234,11 @@

      Overview

      MultiTaggedContentParser

      Requires LLM to generate specified content within multiple tags. Contents from different tags will be parsed into a single Python dictionary with different key-value pairs.

      -

      JSON / Python Object Type

      +

      +

      RegexTaggedContentParser

      +

      For uncertain tag names and quantities, allows users to modify regular expressions, and the return result is a dictionary.

      + +

      JSON / Python Object Type

      MarkdownJsonObjectParser

      Requires LLM to produce specified content within the code block marked by ```json and ```. The result will be converted into a Python object via json.loads.

      @@ -440,11 +444,34 @@

      Dictionary Type +

      Parsers

      +

      For dictionary type return values, AgentScope provides multiple parsers for developers to choose from according to their needs.

      +
      +
      RegexTaggedContentParser
      +
      +
      Initialization
      +

      RegexTaggedContentParser is designed for scenarios where 1) the tag name is uncertain, and 2) the number of tags is uncertain. +In this case, the parser cannot provide a general response format instruction, so developers need to provide the corresponding response format instruction (format_instruction) when initializing. +Of course, the developers can handle the prompt engineering by themselves optionally.

      +
      from agentscope.parsers import RegexTaggedContentParser
      +
      +parser = RegexTaggedContentParser(
      +    format_instruction="""Respond with specific tags as outlined below
      +<thought>what you thought</thought>
      +<speak>what you speak</speak>
      +""",
      +    try_parse_json=True,                    # Try to parse the content of the tag as JSON object
      +    required_keys=["thought", "speak"]      # Required keys in the returned dictionary
      +)
      +
      +
      +
      +
      -

      MarkdownJsonDictParser

      +
      MarkdownJsonDictParser
      -
      Initialization & Format Instruction Template
      +
      Initialization & Format Instruction Template
      • MarkdownJsonDictParser requires LLM to generate dictionary within a code block fenced by ```json and ``` tags.

      • Except keys_to_content, keys_to_memory and keys_to_metadata, the content_hint parameter can be provided to give an example and explanation of the response result, that is, to remind LLM where and what kind of dictionary should be generated. @@ -480,7 +507,7 @@

        Initialization & Format Instruction Template -
        Validation
        +
        Validation

        The content_hint parameter in MarkdownJsonDictParser also supports type validation based on Pydantic. When initializing, you can set content_hint to a Pydantic model class, and AgentScope will modify the instruction_format attribute based on this class. Besides, Pydantic will be used to validate the dictionary returned by LLM during parsing.

        A simple example is as follows, where "..." can be filled with specific type validation rules, which can be referred to the Pydantic documentation.

        from pydantic import BaseModel, Field
        @@ -522,10 +549,10 @@ 
        Validation -

        MultiTaggedContentParser

        +
        MultiTaggedContentParser

        MultiTaggedContentParser asks LLM to generate specific content within multiple tag pairs. The content from different tag pairs will be parsed into a single Python dictionary. Its usage is similar to MarkdownJsonDictParser, but the initialization method is different, and it is more suitable for weak LLMs or complex return content.

        -
        -
        Initialization & Format Instruction Template
        +
        +
        Initialization & Format Instruction Template

        Within MultiTaggedContentParser, each tag pair will be specified by as TaggedContent object, which contains

        • Tag name (name), the key value in the returned dictionary

        • @@ -567,8 +594,8 @@
          Initialization & Format Instruction Template -
          Parse Function
          +
          +
          Parse Function
          • MultiTaggedContentParser’s parsing result is a dictionary, whose keys are the value of name in the TaggedContent objects. The following is an example of parsing the LLM response in the werewolf game:

          • @@ -595,13 +622,14 @@
            Parse Function
        +

        JSON / Python Object Type

        MarkdownJsonObjectParser

        MarkdownJsonObjectParser also uses the ```json and ``` tags in Markdown, but does not limit the content type. It can be a list, dictionary, number, string, etc., which can be parsed into a Python object via json.loads.

        -
        -
        Initialization & Format Instruction Template
        +
        +
        Initialization & Format Instruction Template
        from agentscope.parsers import MarkdownJsonObjectParser
         
         parser = MarkdownJsonObjectParser(
        @@ -618,8 +646,8 @@ 
        Initialization & Format Instruction Template -
        Parse Function
        +
        +
        Parse Function
        res = parser.parse(
             ModelResponse(
                 text="""Yes, here is the generated list
        diff --git a/zh_CN/.doctrees/agentscope.agents.doctree b/zh_CN/.doctrees/agentscope.agents.doctree
        index ad131a081..86d1a92a4 100644
        Binary files a/zh_CN/.doctrees/agentscope.agents.doctree and b/zh_CN/.doctrees/agentscope.agents.doctree differ
        diff --git a/zh_CN/.doctrees/agentscope.agents.react_agent.doctree b/zh_CN/.doctrees/agentscope.agents.react_agent.doctree
        index 993dfb829..616d88d4d 100644
        Binary files a/zh_CN/.doctrees/agentscope.agents.react_agent.doctree and b/zh_CN/.doctrees/agentscope.agents.react_agent.doctree differ
        diff --git a/zh_CN/.doctrees/agentscope.parsers.doctree b/zh_CN/.doctrees/agentscope.parsers.doctree
        index 1e17686a9..6c3625be6 100644
        Binary files a/zh_CN/.doctrees/agentscope.parsers.doctree and b/zh_CN/.doctrees/agentscope.parsers.doctree differ
        diff --git a/zh_CN/.doctrees/agentscope.parsers.regex_tagged_content_parser.doctree b/zh_CN/.doctrees/agentscope.parsers.regex_tagged_content_parser.doctree
        new file mode 100644
        index 000000000..1d17e772d
        Binary files /dev/null and b/zh_CN/.doctrees/agentscope.parsers.regex_tagged_content_parser.doctree differ
        diff --git a/zh_CN/.doctrees/environment.pickle b/zh_CN/.doctrees/environment.pickle
        index c83d3e8c1..b5ad6fe61 100644
        Binary files a/zh_CN/.doctrees/environment.pickle and b/zh_CN/.doctrees/environment.pickle differ
        diff --git a/zh_CN/.doctrees/index.doctree b/zh_CN/.doctrees/index.doctree
        index ff429be37..b43bef4ed 100644
        Binary files a/zh_CN/.doctrees/index.doctree and b/zh_CN/.doctrees/index.doctree differ
        diff --git a/zh_CN/.doctrees/tutorial/203-parser.doctree b/zh_CN/.doctrees/tutorial/203-parser.doctree
        index fd795d024..eb822efd4 100644
        Binary files a/zh_CN/.doctrees/tutorial/203-parser.doctree and b/zh_CN/.doctrees/tutorial/203-parser.doctree differ
        diff --git a/zh_CN/_modules/agentscope/agents/react_agent.html b/zh_CN/_modules/agentscope/agents/react_agent.html
        index 383e4cb87..e92adf738 100644
        --- a/zh_CN/_modules/agentscope/agents/react_agent.html
        +++ b/zh_CN/_modules/agentscope/agents/react_agent.html
        @@ -120,16 +120,15 @@ 

        agentscope.agents.react_agent 源代码

         and act iteratively to solve problems. More details can be found in the paper
         https://arxiv.org/abs/2210.03629.
         """
        -from typing import Any, Optional, Union, Sequence
        -
        -from loguru import logger
        +from typing import Optional, Union, Sequence
         
         from agentscope.exception import ResponseParsingError, FunctionCallError
         from agentscope.agents import AgentBase
         from agentscope.message import Msg
        -from agentscope.parsers import MarkdownJsonDictParser
        +from agentscope.parsers.regex_tagged_content_parser import (
        +    RegexTaggedContentParser,
        +)
         from agentscope.service import ServiceToolkit
        -from agentscope.service.service_toolkit import ServiceFunction
         
         INSTRUCTION_PROMPT = """## What You Should Do:
         1. First, analyze the current situation, and determine your goal.
        @@ -163,11 +162,10 @@ 

        agentscope.agents.react_agent 源代码

                 self,
                 name: str,
                 model_config_name: str,
        -        service_toolkit: ServiceToolkit = None,
        +        service_toolkit: ServiceToolkit,
                 sys_prompt: str = "You're a helpful assistant. Your name is {name}.",
                 max_iters: int = 10,
                 verbose: bool = True,
        -        **kwargs: Any,
             ) -> None:
                 """Initialize the ReAct agent with the given name, model config name
                 and tools.
        @@ -195,39 +193,6 @@ 

        agentscope.agents.react_agent 源代码

                     model_config_name=model_config_name,
                 )
         
        -        # TODO: To compatible with the old version, which will be deprecated
        -        #  soon
        -        if "tools" in kwargs:
        -            logger.warning(
        -                "The argument `tools` will be deprecated soon. "
        -                "Please use `service_toolkit` instead. Example refers to "
        -                "https://github.com/modelscope/agentscope/blob/main/"
        -                "examples/conversation_with_react_agent/code/"
        -                "conversation_with_react_agent.py",
        -            )
        -
        -            service_funcs = {}
        -            for func, json_schema in kwargs["tools"]:
        -                name = json_schema["function"]["name"]
        -                service_funcs[name] = ServiceFunction(
        -                    name=name,
        -                    original_func=func,
        -                    processed_func=func,
        -                    json_schema=json_schema,
        -                )
        -
        -            if service_toolkit is None:
        -                service_toolkit = ServiceToolkit()
        -                service_toolkit.service_funcs = service_funcs
        -            else:
        -                service_toolkit.service_funcs.update(service_funcs)
        -
        -        elif service_toolkit is None:
        -            raise ValueError(
        -                "The argument `service_toolkit` is required to initialize "
        -                "the ReActAgent.",
        -            )
        -
                 self.service_toolkit = service_toolkit
                 self.verbose = verbose
                 self.max_iters = max_iters
        @@ -250,15 +215,22 @@ 

        agentscope.agents.react_agent 源代码

                 self.memory.add(Msg("system", self.sys_prompt, role="system"))
         
                 # Initialize a parser object to formulate the response from the model
        -        self.parser = MarkdownJsonDictParser(
        -            content_hint={
        -                "thought": "what you thought",
        -                "speak": "what you speak",
        -                "function": service_toolkit.tools_calling_format,
        -            },
        -            required_keys=["thought", "speak", "function"],
        -            # Only print the speak field when verbose is False
        -            keys_to_content=True if self.verbose else "speak",
        +        self.parser = RegexTaggedContentParser(
        +            format_instruction="""Respond with specific tags as outlined below:
        +
        +- When calling tool functions, note the "arg_name" should be replaced with the actual argument name:
        +<thought>what you thought</thought>
        +<function>the function name you want to call</function>
        +<arg_name>the value of the argument</arg_name>
        +<arg_name>the value of the argument</arg_name>
        +
        +- When you want to generate a final response:
        +<thought>what you thought</thought>
        +<response>what you respond</response>
        +...""",  # noqa
        +            try_parse_json=True,
        +            required_keys=["thought"],
        +            keys_to_content="response",
                 )
        @@ -291,41 +263,38 @@

        agentscope.agents.react_agent 源代码

                     try:
                         raw_response = self.model(prompt)
         
        +                # Print out the text generated by llm in non-/streaming mode
                         if self.verbose:
                             # To be compatible with streaming and non-streaming mode
                             self.speak(raw_response.stream or raw_response.text)
         
                         res = self.parser.parse(raw_response)
         
        -                # Record the response in memory
        -                self.memory.add(
        -                    Msg(
        -                        self.name,
        -                        self.parser.to_memory(res.parsed),
        -                        "assistant",
        -                    ),
        -                )
        -
        -                # Print out the response
        -                msg_returned = Msg(
        -                    self.name,
        -                    self.parser.to_content(res.parsed),
        -                    "assistant",
        -                )
        -
        -                if not self.verbose:
        -                    self.speak(msg_returned)
        +                # Record the raw text into memory to avoid that LLMs learn
        +                # from the previous response format
        +                self.memory.add(Msg(self.name, res.text, "assistant"))
         
                         # Skip the next steps if no need to call tools
                         # The parsed field is a dictionary
        -                arg_function = res.parsed["function"]
        +                arg_function = res.parsed.get("function", "")
                         if (
                             isinstance(arg_function, str)
                             and arg_function in ["[]", ""]
                             or isinstance(arg_function, list)
                             and len(arg_function) == 0
                         ):
        -                    # Only the speak field is exposed to users or other agents
        +                    # Only the response field is exposed to users or other
        +                    # agents
        +                    msg_returned = Msg(
        +                        self.name,
        +                        res.parsed.get("response", res.text),
        +                        "assistant",
        +                    )
        +
        +                    if not self.verbose:
        +                        # Print out the returned message
        +                        self.speak(msg_returned)
        +
                             return msg_returned
         
                     # Only catch the response parsing error and expose runtime
        @@ -350,6 +319,20 @@ 

        agentscope.agents.react_agent 源代码

         
                     # Parse, check and execute the tool functions in service toolkit
                     try:
        +                # Reorganize the parsed response to the required format of the
        +                # service toolkit
        +                res.parsed["function"] = [
        +                    {
        +                        "name": res.parsed["function"],
        +                        "arguments": {
        +                            k: v
        +                            for k, v in res.parsed.items()
        +                            if k not in ["speak", "thought", "function"]
        +                        },
        +                    },
        +                ]
        +
        +                # Execute the function
                         execute_results = self.service_toolkit.parse_and_call_func(
                             res.parsed["function"],
                         )
        diff --git a/zh_CN/_modules/agentscope/parsers/regex_tagged_content_parser.html b/zh_CN/_modules/agentscope/parsers/regex_tagged_content_parser.html
        new file mode 100644
        index 000000000..f9036be70
        --- /dev/null
        +++ b/zh_CN/_modules/agentscope/parsers/regex_tagged_content_parser.html
        @@ -0,0 +1,326 @@
        +
        +
        +
        +
        +  
        +  
        +  agentscope.parsers.regex_tagged_content_parser — AgentScope  文档
        +      
        +      
        +      
        +
        +  
        +  
        +  
        +        
        +        
        +        
        +        
        +        
        +        
        +        
        +        
        +    
        +    
        +     
        +
        +
        + 
        +  
        +
      • | + 中文 +

    +
    +
    + + +
    + +
    +
    +
    +
      +
    • + + +
    • +
    • +
    +
    +
    +
    +
    + +

    agentscope.parsers.regex_tagged_content_parser 源代码

    +# -*- coding: utf-8 -*-
    +"""The parser for dynamic tagged content"""
    +import json
    +import re
    +from typing import Union, Sequence, Optional, List
    +
    +from loguru import logger
    +
    +from ..exception import TagNotFoundError
    +from ..models import ModelResponse
    +from ..parsers import ParserBase
    +from ..parsers.parser_base import DictFilterMixin
    +
    +
    +
    +[文档] +class RegexTaggedContentParser(ParserBase, DictFilterMixin): + """A regex tagged content parser, which extracts tagged content according + to the provided regex pattern. Different from other parsers, this parser + allows to extract multiple tagged content without knowing the keys in + advance. The parsed result will be a dictionary within the parsed field of + the model response. + + Compared with other parsers, this parser is more flexible and can be used + in dynamic scenarios where + - the keys are not known in advance + - the number of the tagged content is not fixed + + Note: Without knowing the keys in advance, it's hard to prepare a format + instruction template for different scenarios. Therefore, we ask the user + to provide the format instruction in the constructor. Of course, the user + can construct and manage the prompt by themselves optionally. + + Example: + By default, the parser use a regex pattern to extract tagged content + with the following format: + ``` + <{name1}>{content1}</{name1}> + <{name2}>{content2}</{name2}> + ``` + The parser will extract the content as the following dictionary: + ``` + { + "name1": content1, + "name2": content2, + } + ``` + """ + +
    +[文档] + def __init__( + self, + tagged_content_pattern: str = r"<(?P<name>[^>]+)>" + r"(?P<content>.*?)" + r"</\1?>", + format_instruction: Optional[str] = None, + try_parse_json: bool = True, + required_keys: Optional[List[str]] = None, + keys_to_memory: Union[str, bool, Sequence[str]] = True, + keys_to_content: Union[str, bool, Sequence[str]] = True, + keys_to_metadata: Union[str, bool, Sequence[str]] = False, + ) -> None: + """Initialize the regex tagged content parser. + + Args: + tagged_content_pattern (`Optional[str]`, defaults to + `"<(?P<name>[^>]+)>(?P<content>.*?)</\1?>"`): + The regex pattern to extract tagged content. The pattern should + contain two named groups: `name` and `content`. The `name` + group is used as the key of the tagged content, and the + `content` group is used as the value. + format_instruction (`Optional[str]`, defaults to `None`): + The instruction for the format of the tagged content, which + will be attached to the end of the prompt messages to remind + the LLM to follow the format. + try_parse_json (`bool`, defaults to `True`): + Whether to try to parse the tagged content as JSON. Note + the parsing function won't raise exceptions. + required_keys (`Optional[List[str]]`, defaults to `None`): + The keys that are required in the tagged content. + keys_to_memory (`Union[str, bool, Sequence[str]]`, + defaults to `True`): + The keys to save to memory. + keys_to_content (`Union[str, bool, Sequence[str]]`, + defaults to `True`): + The keys to save to content. + keys_to_metadata (`Union[str, bool, Sequence[str]]`, + defaults to `False`): + The key or keys to be filtered in `to_metadata` method. If + it's + - `False`, `None` will be returned in the `to_metadata` method + - `str`, the corresponding value will be returned + - `List[str]`, a filtered dictionary will be returned + - `True`, the whole dictionary will be returned + """ + + DictFilterMixin.__init__( + self, + keys_to_memory=keys_to_memory, + keys_to_content=keys_to_content, + keys_to_metadata=keys_to_metadata, + ) + + assert ( + "<name>" in tagged_content_pattern + ), "The tagged content pattern should contain a named group 'name'." + assert ( + "<content>" in tagged_content_pattern + ), "The tagged content pattern should contain a named group 'content'." + + self.tagged_content_pattern = tagged_content_pattern + self._format_instruction = format_instruction + self.try_parse_json = try_parse_json + self.required_keys = required_keys or []
    + + + @property + def format_instruction(self) -> str: + """The format instruction for the tagged content.""" + if self._format_instruction is None: + raise ValueError( + "The format instruction is not provided. Please provide it in " + "the constructor of the parser.", + ) + return self._format_instruction + +
    +[文档] + def parse(self, response: ModelResponse) -> ModelResponse: + """Parse the response text by the regex pattern, and return a dict of + the content in the parsed field of the response. + + Args: + response (`ModelResponse`): + The response to be parsed. + + Returns: + `ModelResponse`: The response with the parsed field as the parsed + result. + """ + assert response.text is not None, "The response text is None." + + matches = re.finditer( + self.tagged_content_pattern, + response.text, + flags=re.DOTALL, + ) + + results = {} + for match in matches: + results[match.group("name")] = match.group("content") + + keys_missing = [ + key for key in self.required_keys if key not in results + ] + + if len(keys_missing) > 0: + raise TagNotFoundError( + f"Failed to find tags: {', '.join(keys_missing)}", + response.text, + ) + + if self.try_parse_json: + keys_failed = [] + for key in results: + try: + results[key] = json.loads(results[key]) + except json.JSONDecodeError: + keys_failed.append(key) + + logger.debug( + f'Failed to parse JSON for keys: {", ".join(keys_failed)}', + ) + + response.parsed = results + return response
    +
    + +
    + +
    +
    + +
    +
    +
    + + + + + \ No newline at end of file diff --git a/zh_CN/_modules/agentscope/service/service_toolkit.html b/zh_CN/_modules/agentscope/service/service_toolkit.html index 55e467475..810e114f4 100644 --- a/zh_CN/_modules/agentscope/service/service_toolkit.html +++ b/zh_CN/_modules/agentscope/service/service_toolkit.html @@ -505,17 +505,9 @@

    agentscope.service.service_toolkit 源代码

    agentscope.service.service_toolkit 源代码
    代码可用的所有模块
     
  • agentscope.parsers.code_block_parser
  • agentscope.parsers.json_object_parser
  • agentscope.parsers.parser_base
  • +
  • agentscope.parsers.regex_tagged_content_parser
  • agentscope.parsers.tagged_content_parser
  • agentscope.pipelines.functional
  • agentscope.pipelines.pipeline
  • diff --git a/zh_CN/_sources/agentscope.parsers.regex_tagged_content_parser.rst.txt b/zh_CN/_sources/agentscope.parsers.regex_tagged_content_parser.rst.txt new file mode 100644 index 000000000..34d77e4cf --- /dev/null +++ b/zh_CN/_sources/agentscope.parsers.regex_tagged_content_parser.rst.txt @@ -0,0 +1,7 @@ +agentscope.parsers.regex\_tagged\_content\_parser module +======================================================== + +.. automodule:: agentscope.parsers.regex_tagged_content_parser + :members: + :undoc-members: + :show-inheritance: diff --git a/zh_CN/_sources/agentscope.parsers.rst.txt b/zh_CN/_sources/agentscope.parsers.rst.txt index 9ddffdc95..c5fdb5530 100644 --- a/zh_CN/_sources/agentscope.parsers.rst.txt +++ b/zh_CN/_sources/agentscope.parsers.rst.txt @@ -10,6 +10,7 @@ Submodules agentscope.parsers.code_block_parser agentscope.parsers.json_object_parser agentscope.parsers.parser_base + agentscope.parsers.regex_tagged_content_parser agentscope.parsers.tagged_content_parser Module contents diff --git a/zh_CN/_sources/tutorial/203-parser.md.txt b/zh_CN/_sources/tutorial/203-parser.md.txt index 8bad224e4..8ea13231c 100644 --- a/zh_CN/_sources/tutorial/203-parser.md.txt +++ b/zh_CN/_sources/tutorial/203-parser.md.txt @@ -12,13 +12,17 @@ - [初始化](#初始化) - [响应格式模版](#响应格式模版) - [解析函数](#解析函数) - - [字典类型](#字典dict类型) - - [MarkdownJsonDictParser](#markdownjsondictparser) - - [初始化 & 响应格式模版](#初始化--响应格式模版) - - [类型校验](#类型校验) - - [MultiTaggedContentParser](#multitaggedcontentparser) - - [初始化 & 响应格式模版](#初始化--响应格式模版-1) - - [解析函数](#解析函数-1) + - [字典类型](#字典类型) + - [关于 DictFilterMixin](#关于-dictfiltermixin) + - [解析器](#解析器) + - [RegexTaggedContentParser](#regextaggedcontentparser) + - [初始化](#初始化) + - [MarkdownJsonDictParser](#markdownjsondictparser) + - [初始化 & 响应格式模版](#初始化--响应格式模版) + - [类型校验](#类型校验) + - [MultiTaggedContentParser](#multitaggedcontentparser) + - [初始化 & 响应格式模版](#初始化--响应格式模版-1) + - [解析函数](#解析函数-1) - [JSON / Python 对象类型](#json--python-对象类型) - [MarkdownJsonObjectParser](#markdownjsonobjectparser) - [初始化 & 响应格式模版](#初始化--响应格式模版-2) @@ -72,6 +76,7 @@ AgentScope提供了多种不同解析器,开发者可以根据自己的需求 | 字符串(`str`)类型 | `MarkdownCodeBlockParser` | 要求 LLM 将指定的文本生成到Markdown中以 ``` 标识的代码块中,解析结果为字符串。 | | 字典(`dict`)类型 | `MarkdownJsonDictParser` | 要求 LLM 在 \```json 和 \``` 标识的代码块中产生指定内容的字典,解析结果为 Python 字典。 | | | `MultiTaggedContentParser` | 要求 LLM 在多个标签中产生指定内容,这些不同标签中的内容将一同被解析成一个 Python 字典,并填入不同的键值对中。 | +| | `RegexTaggedContentParser` | 适用于不确定标签名,不确定标签数量的场景。允许用户修改正则表达式,返回结果为字典。 | | JSON / Python对象类型 | `MarkdownJsonObjectParser` | 要求 LLM 在 \```json 和 \``` 标识的代码块中产生指定的内容,解析结果将通过 `json.loads` 转换成 Python 对象。 | > **NOTE**: 相比`MarkdownJsonDictParser`,`MultiTaggedContentParser`更适合于模型能力不强,以及需要 LLM 返回内容过于复杂的情况。例如 LLM 返回 Python 代码,如果直接在字典中返回代码,那么 LLM 需要注意特殊字符的转义(\t,\n,...),`json.loads`读取时对双引号和单引号的区分等问题。而`MultiTaggedContentParser`实际是让大模型在每个单独的标签中返回各个键值,然后再将它们组成字典,从而降低了LLM返回的难度。 @@ -140,9 +145,13 @@ AgentScope提供了多种不同解析器,开发者可以根据自己的需求 print("hello world!") ``` -### 字典(`dict`)类型 +### 字典类型 -与字符串和一般的 JSON / Python 对象不同,作为LLM应用中常用的数据格式,AgentScope为字典类型提供了额外的后处理功能。初始化解析器时,可以通过额外设置`keys_to_content`,`keys_to_memory`,`keys_to_metadata`三个参数,从而实现在调用`parser`的`to_content`,`to_memory`和`to_metadata`方法时,对字典键值对的过滤。 +#### 关于 DictFilterMixin + +与字符串和一般的 JSON / Python 对象不同,作为 LLM 应用中常用的数据格式,AgentScope 通过 [`DictFilterMixin`](https://github.com/modelscope/agentscope/blob/main/src/agentscope/parsers/parser_base.py#L77) 类为字典类型的解析提供后处理功能。 + +初始化解析器时,可以通过额外设置`keys_to_content`,`keys_to_memory`,`keys_to_metadata`三个参数,从而实现在调用`parser`的`to_content`,`to_memory`和`to_metadata`方法时,对字典键值对的过滤。 其中 - `keys_to_content` 指定的键值对将被放置在返回`Msg`对象中的`content`字段,这个字段内容将会被返回给其它智能体,参与到其他智能体的提示构建中,同时也会被`self.speak`函数调用,用于显式输出 - `keys_to_memory` 指定的键值对将被存储到智能体的记忆中 @@ -264,11 +273,33 @@ AgentScope中,我们通过调用`to_content`,`to_memory`和`to_metadata`方 > None > ``` -下面我们具体介绍两种字典类型的解析器。 +#### 解析器 -#### MarkdownJsonDictParser +针对字典类型的返回值,AgentScope 提供了多种不同的解析器,开发者可以根据自己的需求进行选择。 -##### 初始化 & 响应格式模版 +##### RegexTaggedContentParser + +###### 初始化 + +`RegexTaggedContentParser` 主要用于1)不确定的标签名,以及2)不确定标签数量的场景。在这种情况下,该解析器无法提供一个泛用性广的响应格式说明,因此需要开发者在初始化时提供对应的相应格式说明(`format_instruction`)。 +除此之外,用户可以通过设置`try_parse_json`,`required_keys`等参数,设置解析器的行为。 + +```python +from agentscope.parsers import RegexTaggedContentParser + +parser = RegexTaggedContentParser( + format_instruction="""Respond with specific tags as outlined below +what you thought +what you speak +""", + try_parse_json=True, # 尝试将标签内容解析成 JSON 对象 + required_keys=["thought", "speak"] # 必须包含的键 +) +``` + +##### MarkdownJsonDictParser + +###### 初始化 & 响应格式模版 - `MarkdownJsonDictParser`要求 LLM 在 \```json 和 \``` 标识的代码块中产生指定内容的字典。 - 除了`to_content`,`to_memory`和`to_metadata`参数外,可以通过提供 `content_hint` 参数提供响应结果样例和说明,即提示LLM应该产生什么样子的字典,该参数可以是字符串,也可以是字典,在构建响应格式提示的时候将会被自动转换成字符串进行拼接。 @@ -300,7 +331,7 @@ AgentScope中,我们通过调用`to_content`,`to_memory`和`to_metadata`方 ``` ```` -##### 类型校验 +###### 类型校验 `MarkdownJsonDictParser`中的`content_hint`参数还支持基于Pydantic的类型校验。初始化时,可以将`content_hint`设置为一个Pydantic的模型类,AgentScope将根据这个类来修改`instruction_format`属性,并且利用Pydantic在解析时对LLM返回的字典进行类型校验。 该功能需要LLM能够理解JSON schema格式的提示,因此适用于能力较强的大模型。 @@ -344,11 +375,11 @@ parser.parser(""" """) ```` -#### MultiTaggedContentParser +##### MultiTaggedContentParser `MultiTaggedContentParser`要求 LLM 在多个指定的标签对中产生指定的内容,这些不同标签的内容将一同被解析为一个 Python 字典。使用方法与`MarkdownJsonDictParser`类似,只是初始化方法不同,更适合能力较弱的LLM,或是比较复杂的返回内容。 -##### 初始化 & 响应格式模版 +###### 初始化 & 响应格式模版 `MultiTaggedContentParser`中,每一组标签将会以`TaggedContent`对象的形式传入,其中`TaggedContent`对象包含了 - 标签名(`name`),即返回字典中的key值 @@ -391,7 +422,7 @@ Respond with specific tags as outlined below, and the content between [FINISH_DI [FINISH_DISCUSSION]true/false, whether the discussion is finished[/FINISH_DISCUSSION] ``` -##### 解析函数 +###### 解析函数 - `MultiTaggedContentParser`的解析结果为字典,其中key为`TaggedContent`对象的`name`的值,以下是狼人杀中解析 LLM 返回的样例: diff --git a/zh_CN/agentscope.agents.html b/zh_CN/agentscope.agents.html index db986e03c..ece9b6090 100644 --- a/zh_CN/agentscope.agents.html +++ b/zh_CN/agentscope.agents.html @@ -821,7 +821,7 @@

    Submodules
    -__init__(name: str, model_config_name: str, service_toolkit: ServiceToolkit | None = None, sys_prompt: str = "You're a helpful assistant. Your name is {name}.", max_iters: int = 10, verbose: bool = True, **kwargs: Any) None[源代码]
    +__init__(name: str, model_config_name: str, service_toolkit: ServiceToolkit, sys_prompt: str = "You're a helpful assistant. Your name is {name}.", max_iters: int = 10, verbose: bool = True) None[源代码]

    Initialize the ReAct agent with the given name, model config name and tools.

    diff --git a/zh_CN/agentscope.agents.react_agent.html b/zh_CN/agentscope.agents.react_agent.html index 7abe0b8bc..00202e5c4 100644 --- a/zh_CN/agentscope.agents.react_agent.html +++ b/zh_CN/agentscope.agents.react_agent.html @@ -152,7 +152,7 @@ their own needs.

    -__init__(name: str, model_config_name: str, service_toolkit: ServiceToolkit | None = None, sys_prompt: str = "You're a helpful assistant. Your name is {name}.", max_iters: int = 10, verbose: bool = True, **kwargs: Any) None[源代码]
    +__init__(name: str, model_config_name: str, service_toolkit: ServiceToolkit, sys_prompt: str = "You're a helpful assistant. Your name is {name}.", max_iters: int = 10, verbose: bool = True) None[源代码]

    Initialize the ReAct agent with the given name, model config name and tools.

    diff --git a/zh_CN/agentscope.html b/zh_CN/agentscope.html index e3fed7c56..ca8905d5d 100644 --- a/zh_CN/agentscope.html +++ b/zh_CN/agentscope.html @@ -501,6 +501,10 @@

    SubpackagesDictFilterMixin +
  • agentscope.parsers.regex_tagged_content_parser module +
  • agentscope.parsers.tagged_content_parser module
  • +
  • RegexTaggedContentParser +
  • diff --git a/zh_CN/agentscope.parsers.code_block_parser.html b/zh_CN/agentscope.parsers.code_block_parser.html index 02866eadd..7a84b2eda 100644 --- a/zh_CN/agentscope.parsers.code_block_parser.html +++ b/zh_CN/agentscope.parsers.code_block_parser.html @@ -88,6 +88,7 @@
  • agentscope.parsers.json_object_parser module
  • agentscope.parsers.parser_base module
  • +
  • agentscope.parsers.regex_tagged_content_parser module
  • agentscope.parsers.tagged_content_parser module
  • diff --git a/zh_CN/agentscope.parsers.html b/zh_CN/agentscope.parsers.html index db8684485..28911dfae 100644 --- a/zh_CN/agentscope.parsers.html +++ b/zh_CN/agentscope.parsers.html @@ -85,6 +85,7 @@
  • agentscope.parsers.code_block_parser module
  • agentscope.parsers.json_object_parser module
  • agentscope.parsers.parser_base module
  • +
  • agentscope.parsers.regex_tagged_content_parser module
  • agentscope.parsers.tagged_content_parser module
  • @@ -140,6 +141,12 @@
  • MultiTaggedContentParser.parse()
  • +
  • RegexTaggedContentParser +
  • @@ -236,6 +243,15 @@

    Submodulesagentscope.parsers.regex_tagged_content_parser module +
  • agentscope.parsers.tagged_content_parser module
    • TaggedContent
      • TaggedContent.__init__()
      • @@ -673,6 +689,114 @@

        Submodules +
        +class agentscope.parsers.RegexTaggedContentParser(tagged_content_pattern: str = '<(?P<name>[^>]+)>(?P<content>.*?)</\\1?>', format_instruction: str | None = None, try_parse_json: bool = True, required_keys: List[str] | None = None, keys_to_memory: str | bool | Sequence[str] = True, keys_to_content: str | bool | Sequence[str] = True, keys_to_metadata: str | bool | Sequence[str] = False)[源代码]
        +

        基类:ParserBase, DictFilterMixin

        +

        A regex tagged content parser, which extracts tagged content according +to the provided regex pattern. Different from other parsers, this parser +allows to extract multiple tagged content without knowing the keys in +advance. The parsed result will be a dictionary within the parsed field of +the model response.

        +

        Compared with other parsers, this parser is more flexible and can be used +in dynamic scenarios where +- the keys are not known in advance +- the number of the tagged content is not fixed

        +

        Note: Without knowing the keys in advance, it’s hard to prepare a format +instruction template for different scenarios. Therefore, we ask the user +to provide the format instruction in the constructor. Of course, the user +can construct and manage the prompt by themselves optionally.

        +

        示例

        +

        By default, the parser use a regex pattern to extract tagged content +with the following format: +` +<{name1}>{content1}</{name1}> +<{name2}>{content2}</{name2}> +` +The parser will extract the content as the following dictionary: +``` +{

        +
        +

        “name1”: content1, +“name2”: content2,

        +
        +
        +

        }

        +
        +
        +__init__(tagged_content_pattern: str = '<(?P<name>[^>]+)>(?P<content>.*?)</\\1?>', format_instruction: str | None = None, try_parse_json: bool = True, required_keys: List[str] | None = None, keys_to_memory: str | bool | Sequence[str] = True, keys_to_content: str | bool | Sequence[str] = True, keys_to_metadata: str | bool | Sequence[str] = False) None[源代码]
        +

        Initialize the regex tagged content parser.

        +
        +
        参数:
        +
          +
        • (Optional[str] (tagged_content_pattern)

        • +
        • to (defaults)

        • +
        • `"<

          The regex pattern to extract tagged content. The pattern should +contain two named groups: name and content. The name +group is used as the key of the tagged content, and the +content group is used as the value.

          +

        • +
        • format_instruction (Optional[str], defaults to None) – The instruction for the format of the tagged content, which +will be attached to the end of the prompt messages to remind +the LLM to follow the format.

        • +
        • try_parse_json (bool, defaults to True) – Whether to try to parse the tagged content as JSON. Note +the parsing function won’t raise exceptions.

        • +
        • required_keys (Optional[List[str]], defaults to None) – The keys that are required in the tagged content.

        • +
        • (`Union[str (keys_to_memory) –

        • +
        • bool

        • +
        • Sequence[str]]`

        • +
        +
        +
        +

        :param : +:param defaults to True): The keys to save to memory. +:param keys_to_content (Union[str: +:param bool: +:param Sequence[str]]: +:param : +:param defaults to True): The keys to save to content. +:param keys_to_metadata (Union[str: +:param bool: +:param Sequence[str]]: +:param : +:param defaults to False): The key or keys to be filtered in to_metadata method. If

        +
        +

        it’s +- False, None will be returned in the to_metadata method +- str, the corresponding value will be returned +- List[str], a filtered dictionary will be returned +- True, the whole dictionary will be returned

        +
        +
        + +
        +
        +property format_instruction: str
        +

        The format instruction for the tagged content.

        +
        + +
        +
        +parse(response: ModelResponse) ModelResponse[源代码]
        +

        Parse the response text by the regex pattern, and return a dict of +the content in the parsed field of the response.

        +
        +
        参数:
        +

        response (ModelResponse) – The response to be parsed.

        +
        +
        返回:
        +

        The response with the parsed field as the parsed +result.

        +
        +
        返回类型:
        +

        ModelResponse

        +
        +
        +
        + +
        +

  • + diff --git a/zh_CN/agentscope.parsers.json_object_parser.html b/zh_CN/agentscope.parsers.json_object_parser.html index 52c2dff10..bc118f2b1 100644 --- a/zh_CN/agentscope.parsers.json_object_parser.html +++ b/zh_CN/agentscope.parsers.json_object_parser.html @@ -89,6 +89,7 @@
  • agentscope.parsers.parser_base module
  • +
  • agentscope.parsers.regex_tagged_content_parser module
  • agentscope.parsers.tagged_content_parser module
  • diff --git a/zh_CN/agentscope.parsers.parser_base.html b/zh_CN/agentscope.parsers.parser_base.html index afd0022f7..4e26c7827 100644 --- a/zh_CN/agentscope.parsers.parser_base.html +++ b/zh_CN/agentscope.parsers.parser_base.html @@ -24,7 +24,7 @@ - + @@ -89,6 +89,7 @@
  • DictFilterMixin
  • +
  • agentscope.parsers.regex_tagged_content_parser module
  • agentscope.parsers.tagged_content_parser module
  • @@ -215,7 +216,7 @@