115 lines
4.1 KiB
Python
115 lines
4.1 KiB
Python
# encoding: utf-8
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'''
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@author: 温进
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@file: codechat_tools.py.py
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@time: 2023/12/14 上午10:24
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@desc:
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'''
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from pydantic import BaseModel, Field
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from loguru import logger
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from coagent.llm_models.llm_config import EmbedConfig, LLMConfig
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from .base_tool import BaseToolModel
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from coagent.service.cb_api import search_code, search_related_vertices, search_code_by_vertex
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# 问题进来
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# 调用函数 0：输入问题，输出代码文件名 1 和 代码文件 1
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#
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# agent 1
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# 1. LLM：代码+问题 输出：是否能解决
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#
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# agent 2
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# 1. 调用函数 1 ：输入：代码文件名 1 输出：代码文件名列表
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# 2. LLM：输入代码文件 1， 问题，代码文件名列表，输出：代码文件名 2
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# 3. 调用函数 2： 输入 ：代码文件名 2 输出：代码文件 2
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class CodeRetrievalSingle(BaseToolModel):
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name = "CodeRetrievalOneCode"
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description = "输入用户的问题，输出一个代码文件名和代码文件"
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class ToolInputArgs(BaseModel):
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query: str = Field(..., description="检索的问题")
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code_base_name: str = Field(..., description="代码库名称", examples=["samples"])
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class ToolOutputArgs(BaseModel):
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"""Output for MetricsQuery."""
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code: str = Field(..., description="检索代码")
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vertex: str = Field(..., description="代码对应 id")
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@classmethod
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def run(cls, code_base_name, query, embed_config: EmbedConfig, llm_config: LLMConfig, **kargs):
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"""excute your tool!"""
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search_type = 'description'
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code_limit = 1
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# default
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search_result = search_code(code_base_name, query, code_limit, search_type=search_type,
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history_node_list=[],
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embed_engine=embed_config.embed_engine, embed_model=embed_config.embed_model, embed_model_path=embed_config.embed_model_path,
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model_device=embed_config.model_device, model_name=llm_config.model_name, temperature=llm_config.temperature,
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api_base_url=llm_config.api_base_url, api_key=llm_config.api_key
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)
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logger.debug(search_result)
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code = search_result['context']
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vertex = search_result['related_vertices'][0]
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# logger.debug(f"code: {code}, vertex: {vertex}")
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res = {
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'code': code,
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'vertex': vertex
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}
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return res
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class RelatedVerticesRetrival(BaseToolModel):
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name = "RelatedVerticesRetrival"
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description = "输入代码节点名，返回相连的节点名"
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class ToolInputArgs(BaseModel):
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code_base_name: str = Field(..., description="代码库名称", examples=["samples"])
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vertex: str = Field(..., description="节点名", examples=["samples"])
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class ToolOutputArgs(BaseModel):
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"""Output for MetricsQuery."""
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vertices: list = Field(..., description="相连节点名")
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@classmethod
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def run(cls, code_base_name: str, vertex: str, **kargs):
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"""execute your tool!"""
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related_vertices = search_related_vertices(cb_name=code_base_name, vertex=vertex)
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logger.debug(f"related_vertices: {related_vertices}")
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return related_vertices
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class Vertex2Code(BaseToolModel):
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name = "Vertex2Code"
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description = "输入代码节点名,返回对应的代码文件"
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class ToolInputArgs(BaseModel):
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code_base_name: str = Field(..., description="代码库名称", examples=["samples"])
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vertex: str = Field(..., description="节点名", examples=["samples"])
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class ToolOutputArgs(BaseModel):
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"""Output for MetricsQuery."""
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code: str = Field(..., description="代码名")
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@classmethod
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def run(cls, code_base_name: str, vertex: str, **kargs):
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"""execute your tool!"""
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# format vertex
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if ',' in vertex:
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vertex_list = vertex.split(',')
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vertex = vertex_list[0].strip(' "')
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else:
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vertex = vertex.strip(' "')
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logger.info(f'vertex={vertex}')
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res = search_code_by_vertex(cb_name=code_base_name, vertex=vertex)
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return res |