diff --git a/.gitmodules b/.gitmodules new file mode 100644 index 0000000..df2e940 --- /dev/null +++ b/.gitmodules @@ -0,0 +1,3 @@ +[submodule "webapp"] + path = webapp + url = https://git.97id.com/ly/webapp.git diff --git a/backend/.env.xinference b/backend/.env.xinference index a78ab4b..2a70df8 100644 --- a/backend/.env.xinference +++ b/backend/.env.xinference @@ -112,6 +112,7 @@ SYSTEM_PROMPT="You are a weather forecast agent. You help users to get the weath - You can install any pip package (if it exists) by running a cell with pip install. " + PRJTOJSON_URL = 'http://10.1.6.60:8092' PROJECT_TITLE = "您好，我是博微工程理解小助手，您可以问我有关[线路工程]工程数据的相关问题！" CHAT_UPLOAD_FILECACHE = "./output/uploaded" \ No newline at end of file diff --git a/backend/app/api/routers/app.py b/backend/app/api/routers/app.py index 7f57dde..443e199 100644 --- a/backend/app/api/routers/app.py +++ b/backend/app/api/routers/app.py @@ -27,8 +27,10 @@ from llama_index.core.settings import Settings logger = logging.getLogger("uvicorn") + v1_router = v = APIRouter() + gEvent_handler = None diff --git a/backend/app/api/routers/request/baseConfig.py b/backend/app/api/routers/request/baseConfig.py index 3384a23..691e36a 100644 --- a/backend/app/api/routers/request/baseConfig.py +++ b/backend/app/api/routers/request/baseConfig.py @@ -7,6 +7,21 @@ class BaseConfig(BaseModel): def ParamterCfg(self,**args): projectInfo = args.get('projectInfo') + questions = os.getenv("CONVERSATION_STARTERS", "dev") + return{ + "opening_statement": self.projectInfo, + "suggested_questions": questions.split('\n'), + "suggested_questions_after_answer": { + "enabled": False + }, + "speech_to_text": { + "enabled": False + }, + "text_to_speech": { +class BaseConfig(BaseModel): + projectInfo:str = os.getenv("PROJECT_TITLE","您好，我是博微工程理解小助手，您可以问我有关[线路工程]工程数据的相关问题！") + + def ParamterCfg(self): questions = os.getenv("CONVERSATION_STARTERS", "dev") return{ "opening_statement": self.projectInfo, @@ -55,6 +70,33 @@ class BaseConfig(BaseModel): ] } }, + "system_parameters": { + "image_file_size_limit": "10" + "language": "", + "voice": "" + }, + "retriever_resource": { + "enabled": True + }, + "annotation_reply": { + "enabled": False + }, + "more_like_this": { + "enabled": False + }, + "user_input_form": [], + "sensitive_word_avoidance": { + "enabled": False + }, + "file_upload": { + "image": { + "enabled": False, + "number_limits": 3, + "transfer_methods": [ + "remote_url" + ] + } + }, "system_parameters": { "image_file_size_limit": "10" } diff --git a/backend/app/engine/loaders/__init__.py b/backend/app/engine/loaders/__init__.py index f47fe94..2993e7d 100644 --- a/backend/app/engine/loaders/__init__.py +++ b/backend/app/engine/loaders/__init__.py @@ -10,6 +10,7 @@ import os logger = logging.getLogger(__name__) def load_configs(): + with open("config/loaders.yaml",encoding='utf-8') as f: configs = yaml.safe_load(f) return configs @@ -98,6 +99,7 @@ def get_documents(docType:str): loader_config = loader_config or [] match loader_type: case "file": + document = get_file_documents(FileLoaderConfig(**loader_config),docType) case "web": document = get_web_documents(WebLoaderConfig(**loader_config)) @@ -107,4 +109,4 @@ def get_documents(docType:str): raise ValueError(f"Invalid loader type: {loader_type}") documents.extend(document) - return documents + diff --git a/backend/app/settings.py b/backend/app/settings.py index 0a0f65e..761a8c1 100644 --- a/backend/app/settings.py +++ b/backend/app/settings.py @@ -67,16 +67,15 @@ class ModelPlatform: @register(ModelPlateCategory,'ollama') class OllamaPlatform(ModelPlatform): def model(self): - #from llama_index.embeddings.ollama import OllamaEmbedding - #from llama_index.llms.ollama.base import DEFAULT_REQUEST_TIMEOUT, Ollama - # - # base_url = os.getenv("OLLAMA_BASE_URL") or "http://127.0.0.1:11434" - # request_timeout = float( - # os.getenv("OLLAMA_REQUEST_TIMEOUT", DEFAULT_REQUEST_TIMEOUT) - # ) - # Settings.llm = Ollama( - # base_url=base_url, model=os.getenv("MODEL"), request_timeout=request_timeout - # ) + from llama_index.llms.ollama.base import DEFAULT_REQUEST_TIMEOUT, Ollama + + base_url = os.getenv("OLLAMA_BASE_URL") or "http://127.0.0.1:11434" + request_timeout = float( + os.getenv("OLLAMA_REQUEST_TIMEOUT", DEFAULT_REQUEST_TIMEOUT) + ) + Settings.llm = Ollama( + base_url=base_url, model=os.getenv("MODEL"), request_timeout=request_timeout + ) pass def embedding(self): diff --git a/backend/poetry.lock b/backend/poetry.lock index 1c202cb..3ace14e 100644 --- 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["big-O", "importlib-resources", "jaraco.functools", "jaraco.itertools", "jaraco.test", "more-itertools", "pytest (>=6,!=8.1.*)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-ignore-flaky", "pytest-mypy", "pytest-ruff (>=0.2.1)"] +enabler = ["pytest-enabler (>=2.2)"] +test = ["big-O", "importlib-resources", "jaraco.functools", "jaraco.itertools", "jaraco.test", "more-itertools", "pytest (>=6,!=8.1.*)", "pytest-ignore-flaky"] +type = ["pytest-mypy"] + +[package.source] +type = "legacy" +url = "https://mirrors.aliyun.com/pypi/simple" +reference = "ali" [metadata] lock-version = "2.0" python-versions = "^3.11,<3.12" -content-hash = "5e941a8cb6943819e5015540f04fedfcd722f6a146faacbf0ca974a363df6bb6" +content-hash = "ca5f70e82776fe4abcd18ec0a672aaa586d7aea647519e56655b7dee743146e8" diff --git a/backend/pyproject.toml b/backend/pyproject.toml index 981083d..23988d8 100644 --- a/backend/pyproject.toml +++ b/backend/pyproject.toml @@ -35,7 +35,9 @@ chroma="^0.2.0" llama-index-vector-stores-chroma = "^0.1.10" llama-index-readers-json = "^0.1.5" llama-index-retrievers-bm25 = "^0.2.2" -llama-index-experimental = "^0.2.0" +llama-index-experimental = "^0.1.4" +llama-index-llms-ollama = "^0.1.6" +llama-index-embeddings-ollama = "^0.1.3" duckduckgo_search = "^6.2.6" @@ -63,11 +65,22 @@ version = "^0.8" version = "0.0.7" +[[tool.poetry.source]] +name = "ali" +url = "https://mirrors.aliyun.com/pypi/simple/" +priority = "primary" + [[tool.poetry.source]] -name = "mirrors" -url = "https://pypi.tuna.tsinghua.edu.cn/simple/" -priority = "default" +name = "tencent" +url = "https://mirrors.cloud.tencent.com/pypi/simple/" +priority = "primary" + + +[[tool.poetry.source]] +name = "tsinghua" +url = "https://mirrors.tuna.tsinghua.edu.cn/pypi/web/simple/" +priority = "primary" [build-system] requires = [ "poetry-core" ] diff --git a/backend/test1/ParamTuner.py b/backend/test1/ParamTuner.py new file mode 100644 index 0000000..5e31b57 --- /dev/null +++ b/backend/test1/ParamTuner.py @@ -0,0 +1,138 @@ +import nest_asyncio +nest_asyncio.apply() +from llama_index.core import SimpleDirectoryReader +from llama_index.core.node_parser import SentenceSplitter +from llama_index.core import VectorStoreIndex +from llama_index.core.evaluation import ( + FaithfulnessEvaluator, + DatasetGenerator, + CorrectnessEvaluator, + SemanticSimilarityEvaluator, +) +from llama_index.experimental.param_tuner import ParamTuner +from llama_index.experimental.param_tuner.base import RunResult +from llama_index.llms.openai import OpenAI + +import asyncio + +# 初始化环境 +from app.observability import init_observability +from app.settings import init_settings +from dotenv import load_dotenv + +load_dotenv() +init_settings() +init_observability() + +# 读取文档 +documents = SimpleDirectoryReader("D:/LLM_model/text2sql/zjdataai-app-test/backend/data-test").load_data() + +# 参数字典 +param_dict = { + "chunk_size": [512, 1024], + "top_k": [1, 5], + "temperature": [0.1, 1.0] +} + +# 辅助函数 +def _build_index(chunk_size, documents): + # 构建索引 + splitter = SentenceSplitter(chunk_size=chunk_size) + vector_index = VectorStoreIndex.from_documents( + documents, transformations=[splitter], + ) + return vector_index + +# 评估函数 +def evaluate_query_engine(query_engine, questions): + loop = asyncio.get_event_loop() + correct, total = loop.run_until_complete(_evaluate_query_engine_async(query_engine, questions)) + return correct, total + +async def _evaluate_query_engine_async(query_engine, questions): + c = [query_engine.aquery(q) for q in questions] + gathering_future = asyncio.gather(*c) + results = await gathering_future + + total_correct = 0 + for r in results: + eval_result = ( + 1 if FaithfulnessEvaluator().evaluate_response(response=r).passing else 0 + ) + total_correct += eval_result + + return total_correct, len(results) + + + +# 生成问题 +question_generator = DatasetGenerator.from_documents(documents) +eval_questions = question_generator.generate_questions_from_nodes(1) # 假设生成10个问题 + +# 打印生成的问题 +for i, q in enumerate(eval_questions, start=1): + print(f"问题 {i}: {q}") + +# 目标函数 +def objective_function(params_dict, documents, questions): + chunk_size = params_dict["chunk_size"] + top_k = params_dict["top_k"] + temperature = params_dict["temperature"] + + # 构建索引 + vector_index = _build_index(chunk_size, documents) + + # 查询引擎 + query_engine = vector_index.as_query_engine( + similarity_top_k=top_k, temperature=temperature + ) + + # 评估查询引擎 + correct, total = 0, len(questions) + question_answers = [] # 添加列表来收集问题和答案 + + for question in questions: + response = query_engine.query(question) + if response is not None: + question_answers.append((question, response.response)) + eval_result = FaithfulnessEvaluator().evaluate_response(response=response, query_str=question) + if eval_result.passing: + correct += 1 + + # 计算分数 + score = correct / total if total > 0 else 0 + return RunResult(score=score, params=params_dict, question_answers=question_answers) + +# 创建 ParamTuner 实例 +param_tuner = ParamTuner( + param_fn=lambda params_dict: objective_function(params_dict, documents, eval_questions), + param_dict=param_dict, + show_progress=True, +) + +# 调用 tune 方法 +results = param_tuner.tune() +best_result = results.best_run_result +best_top_k = best_result.params["top_k"] +best_chunk_size = best_result.params["chunk_size"] +best_temperature = best_result.params["temperature"] +print(f"得分: {best_result.score}") +print(f"Top-k: {best_top_k}") +print(f"文本块大小: {best_chunk_size}") +print(f"温度: {best_temperature}") + +# 使用最佳参数再次运行查询引擎，并打印问题与答案 +best_vector_index = _build_index(best_chunk_size, documents) +best_query_engine = best_vector_index.as_query_engine( + similarity_top_k=best_top_k, temperature=best_temperature +) + +best_question_answers = [] +for question in eval_questions: + response = best_query_engine.query(question) + if response is not None: + best_question_answers.append((question, response.response)) + +# 打印最佳参数下的问题与答案 +for i, (question, answer) in enumerate(best_question_answers, start=1): + print(f"最佳参数 - 问题 {i}: {question}\n答案: {answer}\n") \ No newline at end of file diff --git a/backend/test1/evaluator.py b/backend/test1/evaluator.py new file mode 100644 index 0000000..fcefc4c --- /dev/null +++ b/backend/test1/evaluator.py @@ -0,0 +1,81 @@ +from app.observability import init_observability +from app.settings import init_settings +from dotenv import load_dotenv + +import nest_asyncio +nest_asyncio.apply() + +load_dotenv() + + +from llama_index.core.node_parser import SentenceSplitter +from llama_index.core import ( + VectorStoreIndex, + SimpleDirectoryReader, + Response, +) +from llama_index.core.evaluation import ( + FaithfulnessEvaluator, + DatasetGenerator, + CorrectnessEvaluator, + SemanticSimilarityEvaluator,) + + + +init_settings() +init_observability() + +faith_evaluator_qwen = FaithfulnessEvaluator() #诚实度评测 +corr_evaluator_qwen = CorrectnessEvaluator() #准确率评测 +Seman_evaluator_qwen = SemanticSimilarityEvaluator()#嵌入相似度评估 + +documents = SimpleDirectoryReader("D:/LLM_model/text2sql/zjdataai-app-test/backend/data-test").load_data() + +splitter = SentenceSplitter(chunk_size=512) + + +vector_index = VectorStoreIndex.from_documents( + documents, transformations=[splitter], +) + + +# # 运行评估 +# query_engine = vector_index.as_query_engine() +# response_vector = query_engine.query("工程监理费的金额是多少？") +# eval_result = evaluator_qwen.evaluate_response(response=response_vector) + +# print(response_vector) +# print(eval_result) + + +question_generator = DatasetGenerator.from_documents(documents) +eval_questions = question_generator.generate_questions_from_nodes(5) +print(eval_questions) + +import asyncio + +async def evaluate_query_engine_async(query_engine, questions): + c = [query_engine.aquery(q) for q in questions] + gathering_future = asyncio.gather(*c) + results = await gathering_future + #print(results) + + total_correct = 0 + for r in results: + eval_result = ( + 1 if faith_evaluator_qwen.evaluate_response(response=r).passing else 0 + ) + total_correct += eval_result + + return total_correct, len(results) + +def evaluate_query_engine(query_engine, questions): + loop = asyncio.get_event_loop() + correct, total = loop.run_until_complete(evaluate_query_engine_async(query_engine, questions)) + return correct, total + +# 使用 evaluate_query_engine 函数 +vector_query_engine = vector_index.as_query_engine() +correct, total = evaluate_query_engine(vector_query_engine, eval_questions[:5]) + +print(f"score: {correct}/{total}") \ No newline at end of file diff --git a/backend/test1/query_test.py b/backend/test1/query_test.py index ea031a6..2d83121 100644 --- a/backend/test1/query_test.py +++ b/backend/test1/query_test.py @@ -8,7 +8,8 @@ from llama_index.core import VectorStoreIndex, SQLDatabase from llama_index.core.indices.struct_store import SQLTableRetrieverQueryEngine from llama_index.core.objects import SQLTableNodeMapping, ObjectIndex from app.api.routers.chat import generate_filters -from app.engine import get_index, makeDescriptionByEngine +from app.engine import get_index +from app.engine.engine import makeDescriptionByEngine from app.engine.loaders.db import CustomDatabaseReader from app.engine.vectordb import get_vector_store from app.observability import init_observability diff --git a/backend/test1/test_parameters.py b/backend/test1/test_parameters.py index f95efda..ff31a2e 100644 --- a/backend/test1/test_parameters.py +++ b/backend/test1/test_parameters.py @@ -7,7 +7,8 @@ from llama_index.core.objects import SQLTableNodeMapping, ObjectIndex from sqlalchemy import create_engine from app.api.routers.chat import generate_filters -from app.engine import get_index, makeDescriptionByEngine +from app.engine import get_index +from app.engine.engine import makeDescriptionByEngine from app.engine.vectordb import get_vector_store from app.observability import init_observability from app.settings import init_settings diff --git a/webapp b/webapp new file mode 160000 index 0000000..77dbc14 --- /dev/null +++ b/webapp @@ -0,0 +1 @@ +Subproject commit 77dbc14a64e6eb16409deda752d0aacef3862dd9