diff --git a/.devcontainer/devcontainer.json b/.devcontainer/devcontainer.json index a774d0ed1..01ab0342d 100644 --- a/.devcontainer/devcontainer.json +++ b/.devcontainer/devcontainer.json @@ -3,7 +3,7 @@ { "name": "Python 3", // Or use a Dockerfile or Docker Compose file. More info: https://containers.dev/guide/dockerfile - "image": "mcr.microsoft.com/devcontainers/python:0-3.11", + "image": "metagpt/metagpt:latest", // Features to add to the dev container. More info: https://containers.dev/features. // "features": {}, @@ -18,7 +18,7 @@ ] } }, - + // Use 'postCreateCommand' to run commands after the container is created. "postCreateCommand": "./.devcontainer/postCreateCommand.sh" diff --git a/README.md b/README.md index 8f5cc5393..57473ae6a 100644 --- a/README.md +++ b/README.md @@ -85,8 +85,8 @@ # Check https://docs.deepwisdom.ai/main/en/guide/get_started/configuration.html ```yaml llm: - api_type: "openai" # or azure / ollama / open_llm etc. Check LLMType for more options - model: "gpt-4-turbo" # or gpt-3.5-turbo-1106 / gpt-4-1106-preview + api_type: "openai" # or azure / ollama / groq etc. Check LLMType for more options + model: "gpt-4-turbo" # or gpt-3.5-turbo base_url: "https://api.openai.com/v1" # or forward url / other llm url api_key: "YOUR_API_KEY" ``` @@ -107,7 +107,7 @@ ### Usage print(repo) # it will print the repo structure with files ``` -You can also use its [Data Interpreter](https://github.com/geekan/MetaGPT/tree/main/examples/di) +You can also use [Data Interpreter](https://github.com/geekan/MetaGPT/tree/main/examples/di) to write code: ```python import asyncio diff --git a/config/config2.example.yaml b/config/config2.example.yaml index 7cfd70347..3249f5ae3 100644 --- a/config/config2.example.yaml +++ b/config/config2.example.yaml @@ -1,27 +1,23 @@ llm: - api_type: "openai" # or azure / ollama / open_llm etc. Check LLMType for more options + api_type: "openai" # or azure / ollama / groq etc. base_url: "YOUR_BASE_URL" api_key: "YOUR_API_KEY" - model: "gpt-4-turbo-preview" # or gpt-3.5-turbo-1106 / gpt-4-1106-preview + model: "gpt-4-turbo" # or gpt-3.5-turbo proxy: "YOUR_PROXY" # for LLM API requests # timeout: 600 # Optional. If set to 0, default value is 300. - pricing_plan: "" # Optional. If invalid, it will be automatically filled in with the value of the `model`. - # Azure-exclusive pricing plan mappings： - # - gpt-3.5-turbo 4k: "gpt-3.5-turbo-1106" - # - gpt-4-turbo: "gpt-4-turbo-preview" - # - gpt-4-turbo-vision: "gpt-4-vision-preview" - # - gpt-4 8k: "gpt-4" - # See for more: https://azure.microsoft.com/en-us/pricing/details/cognitive-services/openai-service/ + # Details: https://azure.microsoft.com/en-us/pricing/details/cognitive-services/openai-service/ + pricing_plan: "" # Optional. Use for Azure LLM when its model name is not the same as OpenAI's + # RAG Embedding. # For backward compatibility, if the embedding is not set and the llm's api_type is either openai or azure, the llm's config will be used. embedding: - api_type: "" # openai / azure / gemini / ollama etc. Check EmbeddingType for more options. - base_url: "" - api_key: "" - model: "" - api_version: "" - embed_batch_size: 100 + api_type: "" # openai / azure / gemini / ollama etc. Check EmbeddingType for more options. + base_url: "" + api_key: "" + model: "" + api_version: "" + embed_batch_size: 100 repair_llm_output: true # when the output is not a valid json, try to repair it diff --git a/config/config2.yaml b/config/config2.yaml index 3782644a1..b3f24539c 100644 --- a/config/config2.yaml +++ b/config/config2.yaml @@ -2,7 +2,7 @@ # Reflected Code: https://github.com/geekan/MetaGPT/blob/main/metagpt/config2.py # Config Docs: https://docs.deepwisdom.ai/main/en/guide/get_started/configuration.html llm: - api_type: "openai" # or azure / ollama / open_llm etc. Check LLMType for more options - model: "gpt-4-turbo" # or gpt-3.5-turbo-1106 / gpt-4-1106-preview + api_type: "openai" # or azure / ollama / groq etc. + model: "gpt-4-turbo" # or gpt-3.5-turbo base_url: "https://api.openai.com/v1" # or forward url / other llm url api_key: "YOUR_API_KEY" \ No newline at end of file diff --git a/config/examples/anthropic-claude-3-opus.yaml b/config/examples/anthropic-claude-3-opus.yaml new file mode 100644 index 000000000..db8095f4f --- /dev/null +++ b/config/examples/anthropic-claude-3-opus.yaml @@ -0,0 +1,5 @@ +llm: + api_type: 'claude' # or anthropic + base_url: 'https://api.anthropic.com' + api_key: 'YOUR_API_KEY' + model: 'claude-3-opus-20240229' \ No newline at end of file diff --git a/config/examples/google-gemini.yaml b/config/examples/google-gemini.yaml new file mode 100644 index 000000000..82a22bdf5 --- /dev/null +++ b/config/examples/google-gemini.yaml @@ -0,0 +1,4 @@ +llm: + api_type: 'gemini' + api_key: 'YOUR_API_KEY' + model: 'gemini-pro' \ No newline at end of file diff --git a/config/examples/groq-llama3-70b.yaml b/config/examples/groq-llama3-70b.yaml new file mode 100644 index 000000000..93ff24b3d --- /dev/null +++ b/config/examples/groq-llama3-70b.yaml @@ -0,0 +1,5 @@ +llm: + # Visit https://console.groq.com/keys to create api key + base_url: "https://api.groq.com/openai/v1" + api_key: "YOUR_API_KEY" + model: "llama3-70b-8192" # llama3-8b-8192，llama3-70b-8192，llama2-70b-4096 ，mixtral-8x7b-32768，gemma-7b-it diff --git a/config/examples/openai-gpt-3.5-turbo.yaml b/config/examples/openai-gpt-3.5-turbo.yaml new file mode 100644 index 000000000..41364842a --- /dev/null +++ b/config/examples/openai-gpt-3.5-turbo.yaml @@ -0,0 +1,5 @@ +llm: + api_key: "YOUR_API_KEY" + model: "gpt-3.5-turbo" + #proxy: "http://:" + #base_url: "https:///v1" diff --git a/config/examples/openai-gpt-4-turbo.yaml b/config/examples/openai-gpt-4-turbo.yaml new file mode 100644 index 000000000..5765f460e --- /dev/null +++ b/config/examples/openai-gpt-4-turbo.yaml @@ -0,0 +1,6 @@ +llm: + api_key: "YOUR_API_KEY" + model: "gpt-4-turbo" + #proxy: "http://:" + #base_url: "https:///v1" + diff --git a/config/examples/openrouter-llama3-70b-instruct.yaml b/config/examples/openrouter-llama3-70b-instruct.yaml new file mode 100644 index 000000000..1850d7f5c --- /dev/null +++ b/config/examples/openrouter-llama3-70b-instruct.yaml @@ -0,0 +1,5 @@ +llm: + api_type: openrouter + base_url: "https://openrouter.ai/api/v1" + api_key: "YOUR_API_KEY" + model: meta-llama/llama-3-70b-instruct \ No newline at end of file diff --git a/docs/FAQ-EN.md b/docs/FAQ-EN.md index d3caa244e..f4c5fff15 100644 --- a/docs/FAQ-EN.md +++ b/docs/FAQ-EN.md @@ -38,9 +38,9 @@ ### Chief Evangelist (Monthly Rotation) ### FAQ 1. Code truncation/ Parsing failure: - 1. Check if it's due to exceeding length. Consider using the gpt-4-turbo-preview or other long token versions. + 1. Check if it's due to exceeding length. Consider using the gpt-4-turbo or other long token versions. 2. Success rate: - 1. There hasn't been a quantitative analysis yet, but the success rate of code generated by gpt-4-turbo-preview is significantly higher than that of gpt-3.5-turbo. + 1. There hasn't been a quantitative analysis yet, but the success rate of code generated by gpt-4-turbo is significantly higher than that of gpt-3.5-turbo. 3. Support for incremental, differential updates (if you wish to continue a half-done task): 1. There is now an experimental version. Specify `--inc --project-path ""` or `--inc --project-name ""` on the command line and enter the corresponding requirements to try it. 4. Can existing code be loaded? diff --git a/examples/debate_simple.py b/examples/debate_simple.py index 953f664f3..fa634c532 100644 --- a/examples/debate_simple.py +++ b/examples/debate_simple.py @@ -14,9 +14,9 @@ from metagpt.roles import Role from metagpt.team import Team gpt35 = Config.default() -gpt35.llm.model = "gpt-3.5-turbo-1106" +gpt35.llm.model = "gpt-3.5-turbo" gpt4 = Config.default() -gpt4.llm.model = "gpt-4-1106-preview" +gpt4.llm.model = "gpt-4-turbo" action1 = Action(config=gpt4, name="AlexSay", instruction="Express your opinion with emotion and don't repeat it") action2 = Action(config=gpt35, name="BobSay", instruction="Express your opinion with emotion and don't repeat it") alex = Role(name="Alex", profile="Democratic candidate", goal="Win the election", actions=[action1], watch=[action2]) diff --git a/examples/llm_hello_world.py b/examples/hello_world.py similarity index 58% rename from examples/llm_hello_world.py rename to examples/hello_world.py index 62fc2ed68..04bb88091 100644 --- a/examples/llm_hello_world.py +++ b/examples/hello_world.py @@ -3,7 +3,7 @@ """ @Time : 2023/5/6 14:13 @Author : alexanderwu -@File : llm_hello_world.py +@File : hello_world.py """ import asyncio @@ -11,20 +11,15 @@ from metagpt.llm import LLM from metagpt.logs import logger -async def main(): - llm = LLM() - # llm type check - question = "what's your name" - logger.info(f"{question}: ") - logger.info(await llm.aask(question)) - logger.info("\n\n") +async def ask_and_print(question: str, llm: LLM, system_prompt) -> str: + logger.info(f"Q: {question}") + rsp = await llm.aask(question, system_msgs=[system_prompt]) + logger.info(f"A: {rsp}") + return rsp - logger.info( - await llm.aask( - "who are you", system_msgs=["act as a robot, just answer 'I'am robot' if the question is 'who are you'"] - ) - ) +async def lowlevel_api_example(llm: LLM): + logger.info("low level api example") logger.info(await llm.aask_batch(["hi", "write python hello world."])) hello_msg = [{"role": "user", "content": "count from 1 to 10. split by newline."}] @@ -39,5 +34,12 @@ async def main(): logger.info(llm.completion(hello_msg)) +async def main(): + llm = LLM() + await ask_and_print("what's your name?", llm, "I'm a helpful AI assistant.") + await ask_and_print("who are you?", llm, "just answer 'I am a robot' if the question is 'who are you'") + await lowlevel_api_example(llm) + + if __name__ == "__main__": asyncio.run(main()) diff --git a/examples/ping.py b/examples/ping.py new file mode 100644 index 000000000..20eab5cb0 --- /dev/null +++ b/examples/ping.py @@ -0,0 +1,29 @@ +#!/usr/bin/env python +# -*- coding: utf-8 -*- +""" +@Time : 2024/4/22 14:28 +@Author : alexanderwu +@File : ping.py +""" + +import asyncio + +from metagpt.llm import LLM +from metagpt.logs import logger + + +async def ask_and_print(question: str, llm: LLM, system_prompt) -> str: + logger.info(f"Q: {question}") + rsp = await llm.aask(question, system_msgs=[system_prompt]) + logger.info(f"A: {rsp}") + logger.info("\n") + return rsp + + +async def main(): + llm = LLM() + await ask_and_print("ping?", llm, "Just answer pong when ping.") + + +if __name__ == "__main__": + asyncio.run(main()) diff --git a/examples/rag_pipeline.py b/examples/rag_pipeline.py index 1687d556b..7dbca35a6 100644 --- a/examples/rag_pipeline.py +++ b/examples/rag_pipeline.py @@ -40,7 +40,10 @@ class Player(BaseModel): class RAGExample: - """Show how to use RAG.""" + """Show how to use RAG. + + Default engine use LLM Reranker, if the answer from the LLM is incorrect, may encounter `IndexError: list index out of range`. + """ def __init__(self, engine: SimpleEngine = None): self._engine = engine @@ -59,6 +62,7 @@ class RAGExample: def engine(self, value: SimpleEngine): self._engine = value + @handle_exception async def run_pipeline(self, question=QUESTION, print_title=True): """This example run rag pipeline, use faiss retriever and llm ranker, will print something like: @@ -79,6 +83,7 @@ class RAGExample: answer = await self.engine.aquery(question) self._print_query_result(answer) + @handle_exception async def add_docs(self): """This example show how to add docs. @@ -148,6 +153,7 @@ class RAGExample: except Exception as e: logger.error(f"nodes is empty, llm don't answer correctly, exception: {e}") + @handle_exception async def init_objects(self): """This example show how to from objs, will print something like: @@ -160,6 +166,7 @@ class RAGExample: await self.add_objects(print_title=False) self.engine = pre_engine + @handle_exception async def init_and_query_chromadb(self): """This example show how to use chromadb. how to save and load index. will print something like: @@ -233,7 +240,7 @@ class RAGExample: async def main(): - """RAG pipeline""" + """RAG pipeline.""" e = RAGExample() await e.run_pipeline() await e.add_docs() diff --git a/metagpt/actions/write_code.py b/metagpt/actions/write_code.py index feb15657d..d2fa15f6b 100644 --- a/metagpt/actions/write_code.py +++ b/metagpt/actions/write_code.py @@ -166,7 +166,7 @@ class WriteCode(Action): if not task_doc.content: task_doc = project_repo.docs.task.get(filename=task_doc.filename) m = json.loads(task_doc.content) - code_filenames = m.get(TASK_LIST.key, []) if use_inc else m.get(REFINED_TASK_LIST.key, []) + code_filenames = m.get(TASK_LIST.key, []) if not use_inc else m.get(REFINED_TASK_LIST.key, []) codes = [] src_file_repo = project_repo.srcs diff --git a/metagpt/actions/write_code_review.py b/metagpt/actions/write_code_review.py index ac6fe7045..c9b494dff 100644 --- a/metagpt/actions/write_code_review.py +++ b/metagpt/actions/write_code_review.py @@ -27,6 +27,8 @@ ATTENTION: Use '##' to SPLIT SECTIONS, not '#'. Output format carefully referenc # Context {context} +----- + ## Code to be Reviewed: {filename} ```Code {code} @@ -38,7 +40,8 @@ EXAMPLE_AND_INSTRUCTION = """ {format_example} -# Instruction: Based on the actual code situation, follow one of the "Format example". Return only 1 file under review. +# Instruction: Based on the actual code, follow one of the "Code Review Format example". +- Note the code filename should be `{filename}`. Return the only ONE file `{filename}` under review. ## Code Review: Ordered List. Based on the "Code to be Reviewed", provide key, clear, concise, and specific answer. If any answer is no, explain how to fix it step by step. 1. Is the code implemented as per the requirements? If not, how to achieve it? Analyse it step by step. @@ -56,7 +59,9 @@ LGTM/LBTM """ FORMAT_EXAMPLE = """ -# Format example 1 +----- + +# Code Review Format example 1 ## Code Review: {filename} 1. No, we should fix the logic of class A due to ... 2. ... @@ -92,7 +97,9 @@ FORMAT_EXAMPLE = """ ## Code Review Result LBTM -# Format example 2 +----- + +# Code Review Format example 2 ## Code Review: {filename} 1. Yes. 2. Yes. @@ -106,10 +113,12 @@ pass ## Code Review Result LGTM + +----- """ REWRITE_CODE_TEMPLATE = """ -# Instruction: rewrite code based on the Code Review and Actions +# Instruction: rewrite the `{filename}` based on the Code Review and Actions ## Rewrite Code: CodeBlock. If it still has some bugs, rewrite {filename} with triple quotes. Do your utmost to optimize THIS SINGLE FILE. Return all completed codes and prohibit the return of unfinished codes. ```Code ## {filename} @@ -169,6 +178,7 @@ class WriteCodeReview(Action): ) cr_prompt = EXAMPLE_AND_INSTRUCTION.format( format_example=format_example, + filename=self.i_context.code_doc.filename, ) len1 = len(iterative_code) if iterative_code else 0 len2 = len(self.i_context.code_doc.content) if self.i_context.code_doc.content else 0 diff --git a/metagpt/rag/engines/simple.py b/metagpt/rag/engines/simple.py index 34f925249..c237dcf69 100644 --- a/metagpt/rag/engines/simple.py +++ b/metagpt/rag/engines/simple.py @@ -4,7 +4,7 @@ import json import os from typing import Any, Optional, Union -from llama_index.core import SimpleDirectoryReader, VectorStoreIndex +from llama_index.core import SimpleDirectoryReader from llama_index.core.callbacks.base import CallbackManager from llama_index.core.embeddings import BaseEmbedding from llama_index.core.embeddings.mock_embed_model import MockEmbedding @@ -63,7 +63,7 @@ class SimpleEngine(RetrieverQueryEngine): response_synthesizer: Optional[BaseSynthesizer] = None, node_postprocessors: Optional[list[BaseNodePostprocessor]] = None, callback_manager: Optional[CallbackManager] = None, - index: Optional[BaseIndex] = None, + transformations: Optional[list[TransformComponent]] = None, ) -> None: super().__init__( retriever=retriever, @@ -71,7 +71,7 @@ class SimpleEngine(RetrieverQueryEngine): node_postprocessors=node_postprocessors, callback_manager=callback_manager, ) - self.index = index + self._transformations = transformations or self._default_transformations() @classmethod def from_docs( @@ -103,12 +103,17 @@ class SimpleEngine(RetrieverQueryEngine): documents = SimpleDirectoryReader(input_dir=input_dir, input_files=input_files).load_data() cls._fix_document_metadata(documents) - index = VectorStoreIndex.from_documents( - documents=documents, - transformations=transformations or [SentenceSplitter()], - embed_model=cls._resolve_embed_model(embed_model, retriever_configs), + transformations = transformations or cls._default_transformations() + nodes = run_transformations(documents, transformations=transformations) + + return cls._from_nodes( + nodes=nodes, + transformations=transformations, + embed_model=embed_model, + llm=llm, + retriever_configs=retriever_configs, + ranker_configs=ranker_configs, ) - return cls._from_index(index, llm=llm, retriever_configs=retriever_configs, ranker_configs=ranker_configs) @classmethod def from_objs( @@ -137,12 +142,15 @@ class SimpleEngine(RetrieverQueryEngine): raise ValueError("In BM25RetrieverConfig, Objs must not be empty.") nodes = [ObjectNode(text=obj.rag_key(), metadata=ObjectNode.get_obj_metadata(obj)) for obj in objs] - index = VectorStoreIndex( + + return cls._from_nodes( nodes=nodes, - transformations=transformations or [SentenceSplitter()], - embed_model=cls._resolve_embed_model(embed_model, retriever_configs), + transformations=transformations, + embed_model=embed_model, + llm=llm, + retriever_configs=retriever_configs, + ranker_configs=ranker_configs, ) - return cls._from_index(index, llm=llm, retriever_configs=retriever_configs, ranker_configs=ranker_configs) @classmethod def from_index( @@ -183,7 +191,7 @@ class SimpleEngine(RetrieverQueryEngine): documents = SimpleDirectoryReader(input_files=input_files).load_data() self._fix_document_metadata(documents) - nodes = run_transformations(documents, transformations=self.index._transformations) + nodes = run_transformations(documents, transformations=self._transformations) self._save_nodes(nodes) def add_objs(self, objs: list[RAGObject]): @@ -199,6 +207,29 @@ class SimpleEngine(RetrieverQueryEngine): self._persist(str(persist_dir), **kwargs) + @classmethod + def _from_nodes( + cls, + nodes: list[BaseNode], + transformations: Optional[list[TransformComponent]] = None, + embed_model: BaseEmbedding = None, + llm: LLM = None, + retriever_configs: list[BaseRetrieverConfig] = None, + ranker_configs: list[BaseRankerConfig] = None, + ) -> "SimpleEngine": + embed_model = cls._resolve_embed_model(embed_model, retriever_configs) + llm = llm or get_rag_llm() + + retriever = get_retriever(configs=retriever_configs, nodes=nodes, embed_model=embed_model) + rankers = get_rankers(configs=ranker_configs, llm=llm) # Default [] + + return cls( + retriever=retriever, + node_postprocessors=rankers, + response_synthesizer=get_response_synthesizer(llm=llm), + transformations=transformations, + ) + @classmethod def _from_index( cls, @@ -208,6 +239,7 @@ class SimpleEngine(RetrieverQueryEngine): ranker_configs: list[BaseRankerConfig] = None, ) -> "SimpleEngine": llm = llm or get_rag_llm() + retriever = get_retriever(configs=retriever_configs, index=index) # Default index.as_retriever rankers = get_rankers(configs=ranker_configs, llm=llm) # Default [] @@ -215,7 +247,6 @@ class SimpleEngine(RetrieverQueryEngine): retriever=retriever, node_postprocessors=rankers, response_synthesizer=get_response_synthesizer(llm=llm), - index=index, ) def _ensure_retriever_modifiable(self): @@ -266,3 +297,7 @@ class SimpleEngine(RetrieverQueryEngine): return MockEmbedding(embed_dim=1) return embed_model or get_rag_embedding() + + @staticmethod + def _default_transformations(): + return [SentenceSplitter()] diff --git a/metagpt/rag/factories/base.py b/metagpt/rag/factories/base.py index fcfec03ec..e58643efe 100644 --- a/metagpt/rag/factories/base.py +++ b/metagpt/rag/factories/base.py @@ -36,19 +36,26 @@ class ConfigBasedFactory(GenericFactory): """Designed to get objects based on object type.""" def get_instance(self, key: Any, **kwargs) -> Any: - """Key is config, such as a pydantic model. + """Get instance by the type of key. - Call func by the type of key, and the key will be passed to func. + Key is config, such as a pydantic model, call func by the type of key, and the key will be passed to func. + Raise Exception if key not found. """ creator = self._creators.get(type(key)) if creator: return creator(key, **kwargs) + self._raise_for_key(key) + + def _raise_for_key(self, key: Any): raise ValueError(f"Unknown config: `{type(key)}`, {key}") @staticmethod def _val_from_config_or_kwargs(key: str, config: object = None, **kwargs) -> Any: - """It prioritizes the configuration object's value unless it is None, in which case it looks into kwargs.""" + """It prioritizes the configuration object's value unless it is None, in which case it looks into kwargs. + + Return None if not found. + """ if config is not None and hasattr(config, key): val = getattr(config, key) if val is not None: @@ -57,6 +64,4 @@ class ConfigBasedFactory(GenericFactory): if key in kwargs: return kwargs[key] - raise KeyError( - f"The key '{key}' is required but not provided in either configuration object or keyword arguments." - ) + return None diff --git a/metagpt/rag/factories/retriever.py b/metagpt/rag/factories/retriever.py index 68f2c2313..1460e131b 100644 --- a/metagpt/rag/factories/retriever.py +++ b/metagpt/rag/factories/retriever.py @@ -1,10 +1,13 @@ """RAG Retriever Factory.""" -import copy + +from functools import wraps import chromadb import faiss from llama_index.core import StorageContext, VectorStoreIndex +from llama_index.core.embeddings import BaseEmbedding +from llama_index.core.schema import BaseNode from llama_index.core.vector_stores.types import BasePydanticVectorStore from llama_index.vector_stores.chroma import ChromaVectorStore from llama_index.vector_stores.elasticsearch import ElasticsearchStore @@ -24,10 +27,25 @@ from metagpt.rag.schema import ( ElasticsearchKeywordRetrieverConfig, ElasticsearchRetrieverConfig, FAISSRetrieverConfig, - IndexRetrieverConfig, ) +def get_or_build_index(build_index_func): + """Decorator to get or build an index. + + Get index using `_extract_index` method, if not found, using build_index_func. + """ + + @wraps(build_index_func) + def wrapper(self, config, **kwargs): + index = self._extract_index(config, **kwargs) + if index is not None: + return index + return build_index_func(self, config, **kwargs) + + return wrapper + + class RetrieverFactory(ConfigBasedFactory): """Modify creators for dynamically instance implementation.""" @@ -54,48 +72,79 @@ class RetrieverFactory(ConfigBasedFactory): return SimpleHybridRetriever(*retrievers) if len(retrievers) > 1 else retrievers[0] def _create_default(self, **kwargs) -> RAGRetriever: - return self._extract_index(**kwargs).as_retriever() + index = self._extract_index(None, **kwargs) or self._build_default_index(**kwargs) + + return index.as_retriever() def _create_faiss_retriever(self, config: FAISSRetrieverConfig, **kwargs) -> FAISSRetriever: - vector_store = FaissVectorStore(faiss_index=faiss.IndexFlatL2(config.dimensions)) - config.index = self._build_index_from_vector_store(config, vector_store, **kwargs) + config.index = self._build_faiss_index(config, **kwargs) return FAISSRetriever(**config.model_dump()) def _create_bm25_retriever(self, config: BM25RetrieverConfig, **kwargs) -> DynamicBM25Retriever: - config.index = copy.deepcopy(self._extract_index(config, **kwargs)) + index = self._extract_index(config, **kwargs) + nodes = list(index.docstore.docs.values()) if index else self._extract_nodes(config, **kwargs) - return DynamicBM25Retriever(nodes=list(config.index.docstore.docs.values()), **config.model_dump()) + return DynamicBM25Retriever(nodes=nodes, **config.model_dump()) def _create_chroma_retriever(self, config: ChromaRetrieverConfig, **kwargs) -> ChromaRetriever: - db = chromadb.PersistentClient(path=str(config.persist_path)) - chroma_collection = db.get_or_create_collection(config.collection_name, metadata=config.metadata) - - vector_store = ChromaVectorStore(chroma_collection=chroma_collection) - config.index = self._build_index_from_vector_store(config, vector_store, **kwargs) + config.index = self._build_chroma_index(config, **kwargs) return ChromaRetriever(**config.model_dump()) def _create_es_retriever(self, config: ElasticsearchRetrieverConfig, **kwargs) -> ElasticsearchRetriever: - vector_store = ElasticsearchStore(**config.store_config.model_dump()) - config.index = self._build_index_from_vector_store(config, vector_store, **kwargs) + config.index = self._build_es_index(config, **kwargs) return ElasticsearchRetriever(**config.model_dump()) def _extract_index(self, config: BaseRetrieverConfig = None, **kwargs) -> VectorStoreIndex: return self._val_from_config_or_kwargs("index", config, **kwargs) + def _extract_nodes(self, config: BaseRetrieverConfig = None, **kwargs) -> list[BaseNode]: + return self._val_from_config_or_kwargs("nodes", config, **kwargs) + + def _extract_embed_model(self, config: BaseRetrieverConfig = None, **kwargs) -> BaseEmbedding: + return self._val_from_config_or_kwargs("embed_model", config, **kwargs) + + def _build_default_index(self, **kwargs) -> VectorStoreIndex: + index = VectorStoreIndex( + nodes=self._extract_nodes(**kwargs), + embed_model=self._extract_embed_model(**kwargs), + ) + + return index + + @get_or_build_index + def _build_faiss_index(self, config: FAISSRetrieverConfig, **kwargs) -> VectorStoreIndex: + vector_store = FaissVectorStore(faiss_index=faiss.IndexFlatL2(config.dimensions)) + + return self._build_index_from_vector_store(config, vector_store, **kwargs) + + @get_or_build_index + def _build_chroma_index(self, config: ChromaRetrieverConfig, **kwargs) -> VectorStoreIndex: + db = chromadb.PersistentClient(path=str(config.persist_path)) + chroma_collection = db.get_or_create_collection(config.collection_name, metadata=config.metadata) + vector_store = ChromaVectorStore(chroma_collection=chroma_collection) + + return self._build_index_from_vector_store(config, vector_store, **kwargs) + + @get_or_build_index + def _build_es_index(self, config: ElasticsearchRetrieverConfig, **kwargs) -> VectorStoreIndex: + vector_store = ElasticsearchStore(**config.store_config.model_dump()) + + return self._build_index_from_vector_store(config, vector_store, **kwargs) + def _build_index_from_vector_store( - self, config: IndexRetrieverConfig, vector_store: BasePydanticVectorStore, **kwargs + self, config: BaseRetrieverConfig, vector_store: BasePydanticVectorStore, **kwargs ) -> VectorStoreIndex: storage_context = StorageContext.from_defaults(vector_store=vector_store) - old_index = self._extract_index(config, **kwargs) - new_index = VectorStoreIndex( - nodes=list(old_index.docstore.docs.values()), + index = VectorStoreIndex( + nodes=self._extract_nodes(config, **kwargs), storage_context=storage_context, - embed_model=old_index._embed_model, + embed_model=self._extract_embed_model(config, **kwargs), ) - return new_index + + return index get_retriever = RetrieverFactory().get_retriever diff --git a/metagpt/roles/role.py b/metagpt/roles/role.py index 57dd51139..142c3a5b9 100644 --- a/metagpt/roles/role.py +++ b/metagpt/roles/role.py @@ -406,7 +406,7 @@ class Role(SerializationMixin, ContextMixin, BaseModel): elif isinstance(response, Message): msg = response else: - msg = Message(content=response, role=self.profile, cause_by=self.rc.todo, sent_from=self) + msg = Message(content=response or "", role=self.profile, cause_by=self.rc.todo, sent_from=self) self.rc.memory.add(msg) return msg diff --git a/metagpt/software_company.py b/metagpt/software_company.py index f290d497a..103ac0551 100644 --- a/metagpt/software_company.py +++ b/metagpt/software_company.py @@ -123,9 +123,10 @@ def startup( DEFAULT_CONFIG = """# Full Example: https://github.com/geekan/MetaGPT/blob/main/config/config2.example.yaml # Reflected Code: https://github.com/geekan/MetaGPT/blob/main/metagpt/config2.py +# Config Docs: https://docs.deepwisdom.ai/main/en/guide/get_started/configuration.html llm: - api_type: "openai" # or azure / ollama / open_llm etc. Check LLMType for more options - model: "gpt-4-turbo-preview" # or gpt-3.5-turbo-1106 / gpt-4-1106-preview + api_type: "openai" # or azure / ollama / groq etc. + model: "gpt-4-turbo" # or gpt-3.5-turbo base_url: "https://api.openai.com/v1" # or forward url / other llm url api_key: "YOUR_API_KEY" """ diff --git a/metagpt/utils/git_repository.py b/metagpt/utils/git_repository.py index 16f675175..d25476f25 100644 --- a/metagpt/utils/git_repository.py +++ b/metagpt/utils/git_repository.py @@ -78,7 +78,7 @@ class GitRepository: self._repository = Repo.init(path=Path(local_path)) gitignore_filename = Path(local_path) / ".gitignore" - ignores = ["__pycache__", "*.pyc"] + ignores = ["__pycache__", "*.pyc", ".vs"] with open(str(gitignore_filename), mode="w") as writer: writer.write("\n".join(ignores)) self._repository.index.add([".gitignore"]) diff --git a/metagpt/utils/token_counter.py b/metagpt/utils/token_counter.py index 98ae079eb..724d49afc 100644 --- a/metagpt/utils/token_counter.py +++ b/metagpt/utils/token_counter.py @@ -32,9 +32,9 @@ TOKEN_COSTS = { "gpt-4-32k-0314": {"prompt": 0.06, "completion": 0.12}, "gpt-4-0613": {"prompt": 0.06, "completion": 0.12}, "gpt-4-turbo-preview": {"prompt": 0.01, "completion": 0.03}, - "gpt-4-turbo": {"prompt": 0.01, "completion": 0.03}, - "gpt-4-0125-preview": {"prompt": 0.01, "completion": 0.03}, "gpt-4-1106-preview": {"prompt": 0.01, "completion": 0.03}, + "gpt-4-0125-preview": {"prompt": 0.01, "completion": 0.03}, + "gpt-4-turbo": {"prompt": 0.01, "completion": 0.03}, "gpt-4-vision-preview": {"prompt": 0.01, "completion": 0.03}, # TODO add extra image price calculator "gpt-4-1106-vision-preview": {"prompt": 0.01, "completion": 0.03}, "text-embedding-ada-002": {"prompt": 0.0004, "completion": 0.0}, @@ -57,6 +57,8 @@ TOKEN_COSTS = { "yi-34b-chat-0205": {"prompt": 0.0003, "completion": 0.0003}, "yi-34b-chat-200k": {"prompt": 0.0017, "completion": 0.0017}, "microsoft/wizardlm-2-8x22b": {"prompt": 0.00108, "completion": 0.00108}, # for openrouter, start + "meta-llama/llama-3-70b-instruct": {"prompt": 0.008, "completion": 0.008}, + "llama3-70b-8192": {"prompt": 0.0059, "completion": 0.0079}, "openai/gpt-3.5-turbo-0125": {"prompt": 0.0005, "completion": 0.0015}, "openai/gpt-4-turbo-preview": {"prompt": 0.01, "completion": 0.03}, } @@ -155,8 +157,8 @@ FIREWORKS_GRADE_TOKEN_COSTS = { TOKEN_MAX = { "gpt-4-0125-preview": 128000, "gpt-4-turbo-preview": 128000, - "gpt-4-turbo": 128000, "gpt-4-1106-preview": 128000, + "gpt-4-turbo": 128000, "gpt-4-vision-preview": 128000, "gpt-4-1106-vision-preview": 128000, "gpt-4": 8192, @@ -190,6 +192,8 @@ TOKEN_MAX = { "yi-34b-chat-0205": 4000, "yi-34b-chat-200k": 200000, "microsoft/wizardlm-2-8x22b": 65536, + "meta-llama/llama-3-70b-instruct": 8192, + "llama3-70b-8192": 8192, "openai/gpt-3.5-turbo-0125": 16385, "openai/gpt-4-turbo-preview": 128000, } @@ -217,7 +221,7 @@ def count_message_tokens(messages, model="gpt-3.5-turbo-0125"): "gpt-4-turbo", "gpt-4-turbo-preview", "gpt-4-0125-preview", - "gpt-4-1106-preview", + "gpt-4-turbo", "gpt-4-vision-preview", "gpt-4-1106-vision-preview", }: diff --git a/requirements.txt b/requirements.txt index 83962b21b..6c219a9dc 100644 --- a/requirements.txt +++ b/requirements.txt @@ -12,12 +12,12 @@ typer==0.9.0 lancedb==0.4.0 loguru==0.6.0 meilisearch==0.21.0 -numpy==1.24.3 -openai==1.6.1 +numpy>=1.24.3 +openai>=1.6.1 openpyxl beautifulsoup4==4.12.3 pandas==2.1.1 -pydantic==2.5.3 +pydantic>=2.5.3 #pygame==2.1.3 #pymilvus==2.2.8 # pytest==7.2.2 # test extras require @@ -58,7 +58,7 @@ typing-extensions==4.9.0 socksio~=1.0.0 gitignore-parser==0.1.9 # connexion[uvicorn]~=3.0.5 # Used by metagpt/tools/openapi_v3_hello.py -websockets~=11.0 +websockets>=10.0,<12.0 networkx~=3.2.1 google-generativeai==0.4.1 playwright>=1.26 # used at metagpt/tools/libs/web_scraping.py diff --git a/setup.py b/setup.py index 1d4301113..79c60b8ea 100644 --- a/setup.py +++ b/setup.py @@ -74,7 +74,7 @@ extras_require["dev"] = (["pylint~=3.0.3", "black~=23.3.0", "isort~=5.12.0", "pr setup( name="metagpt", - version="0.8.0", + version="0.8.1", description="The Multi-Agent Framework", long_description=long_description, long_description_content_type="text/markdown", diff --git a/tests/config2.yaml b/tests/config2.yaml index 58314eaed..e1eb7cfd2 100644 --- a/tests/config2.yaml +++ b/tests/config2.yaml @@ -1,7 +1,7 @@ llm: base_url: "https://api.openai.com/v1" api_key: "sk-xxx" - model: "gpt-3.5-turbo-1106" + model: "gpt-3.5-turbo" search: api_type: "serpapi" diff --git a/tests/metagpt/rag/engines/test_simple.py b/tests/metagpt/rag/engines/test_simple.py index 9262ccb07..8c7a15be2 100644 --- a/tests/metagpt/rag/engines/test_simple.py +++ b/tests/metagpt/rag/engines/test_simple.py @@ -25,10 +25,6 @@ class TestSimpleEngine: def mock_simple_directory_reader(self, mocker): return mocker.patch("metagpt.rag.engines.simple.SimpleDirectoryReader") - @pytest.fixture - def mock_vector_store_index(self, mocker): - return mocker.patch("metagpt.rag.engines.simple.VectorStoreIndex.from_documents") - @pytest.fixture def mock_get_retriever(self, mocker): return mocker.patch("metagpt.rag.engines.simple.get_retriever") @@ -45,7 +41,6 @@ class TestSimpleEngine: self, mocker, mock_simple_directory_reader, - mock_vector_store_index, mock_get_retriever, mock_get_rankers, mock_get_response_synthesizer, @@ -81,11 +76,8 @@ class TestSimpleEngine: # Assert mock_simple_directory_reader.assert_called_once_with(input_dir=input_dir, input_files=input_files) - mock_vector_store_index.assert_called_once() - mock_get_retriever.assert_called_once_with( - configs=retriever_configs, index=mock_vector_store_index.return_value - ) - mock_get_rankers.assert_called_once_with(configs=ranker_configs, llm=llm) + mock_get_retriever.assert_called_once() + mock_get_rankers.assert_called_once() mock_get_response_synthesizer.assert_called_once_with(llm=llm) assert isinstance(engine, SimpleEngine) @@ -119,7 +111,7 @@ class TestSimpleEngine: # Assert assert isinstance(engine, SimpleEngine) - assert engine.index is not None + assert engine._transformations is not None def test_from_objs_with_bm25_config(self): # Setup @@ -137,6 +129,7 @@ class TestSimpleEngine: def test_from_index(self, mocker, mock_llm, mock_embedding): # Mock mock_index = mocker.MagicMock(spec=VectorStoreIndex) + mock_index.as_retriever.return_value = "retriever" mock_get_index = mocker.patch("metagpt.rag.engines.simple.get_index") mock_get_index.return_value = mock_index @@ -149,7 +142,7 @@ class TestSimpleEngine: # Assert assert isinstance(engine, SimpleEngine) - assert engine.index is mock_index + assert engine._retriever == "retriever" @pytest.mark.asyncio async def test_asearch(self, mocker): @@ -200,14 +193,11 @@ class TestSimpleEngine: mock_retriever = mocker.MagicMock(spec=ModifiableRAGRetriever) - mock_index = mocker.MagicMock(spec=VectorStoreIndex) - mock_index._transformations = mocker.MagicMock() - mock_run_transformations = mocker.patch("metagpt.rag.engines.simple.run_transformations") mock_run_transformations.return_value = ["node1", "node2"] # Setup - engine = SimpleEngine(retriever=mock_retriever, index=mock_index) + engine = SimpleEngine(retriever=mock_retriever) input_files = ["test_file1", "test_file2"] # Exec @@ -230,7 +220,7 @@ class TestSimpleEngine: return "" objs = [CustomTextNode(text=f"text_{i}", metadata={"obj": f"obj_{i}"}) for i in range(2)] - engine = SimpleEngine(retriever=mock_retriever, index=mocker.MagicMock()) + engine = SimpleEngine(retriever=mock_retriever) # Exec engine.add_objs(objs=objs) diff --git a/tests/metagpt/rag/factories/test_base.py b/tests/metagpt/rag/factories/test_base.py index 1d41e1872..0b0a44976 100644 --- a/tests/metagpt/rag/factories/test_base.py +++ b/tests/metagpt/rag/factories/test_base.py @@ -97,6 +97,5 @@ class TestConfigBasedFactory: def test_val_from_config_or_kwargs_key_error(self): # Test KeyError when the key is not found in both config object and kwargs config = DummyConfig(name=None) - with pytest.raises(KeyError) as exc_info: - ConfigBasedFactory._val_from_config_or_kwargs("missing_key", config) - assert "The key 'missing_key' is required but not provided" in str(exc_info.value) + val = ConfigBasedFactory._val_from_config_or_kwargs("missing_key", config) + assert val is None diff --git a/tests/metagpt/rag/factories/test_retriever.py b/tests/metagpt/rag/factories/test_retriever.py index ef1cef7e0..cd55a32db 100644 --- a/tests/metagpt/rag/factories/test_retriever.py +++ b/tests/metagpt/rag/factories/test_retriever.py @@ -1,6 +1,8 @@ import faiss import pytest from llama_index.core import VectorStoreIndex +from llama_index.core.embeddings import MockEmbedding +from llama_index.core.schema import TextNode from llama_index.vector_stores.chroma import ChromaVectorStore from llama_index.vector_stores.elasticsearch import ElasticsearchStore @@ -43,6 +45,14 @@ class TestRetrieverFactory: def mock_es_vector_store(self, mocker): return mocker.MagicMock(spec=ElasticsearchStore) + @pytest.fixture + def mock_nodes(self, mocker): + return [TextNode(text="msg")] + + @pytest.fixture + def mock_embedding(self): + return MockEmbedding(embed_dim=1) + def test_get_retriever_with_faiss_config(self, mock_faiss_index, mocker, mock_vector_store_index): mock_config = FAISSRetrieverConfig(dimensions=128) mocker.patch("faiss.IndexFlatL2", return_value=mock_faiss_index) @@ -52,42 +62,40 @@ class TestRetrieverFactory: assert isinstance(retriever, FAISSRetriever) - def test_get_retriever_with_bm25_config(self, mocker, mock_vector_store_index): + def test_get_retriever_with_bm25_config(self, mocker, mock_nodes): mock_config = BM25RetrieverConfig() mocker.patch("rank_bm25.BM25Okapi.__init__", return_value=None) - mocker.patch.object(self.retriever_factory, "_extract_index", return_value=mock_vector_store_index) - retriever = self.retriever_factory.get_retriever(configs=[mock_config]) + retriever = self.retriever_factory.get_retriever(configs=[mock_config], nodes=mock_nodes) assert isinstance(retriever, DynamicBM25Retriever) - def test_get_retriever_with_multiple_configs_returns_hybrid(self, mocker, mock_vector_store_index): - mock_faiss_config = FAISSRetrieverConfig(dimensions=128) + def test_get_retriever_with_multiple_configs_returns_hybrid(self, mocker, mock_nodes, mock_embedding): + mock_faiss_config = FAISSRetrieverConfig(dimensions=1) mock_bm25_config = BM25RetrieverConfig() mocker.patch("rank_bm25.BM25Okapi.__init__", return_value=None) - mocker.patch.object(self.retriever_factory, "_extract_index", return_value=mock_vector_store_index) - retriever = self.retriever_factory.get_retriever(configs=[mock_faiss_config, mock_bm25_config]) + retriever = self.retriever_factory.get_retriever( + configs=[mock_faiss_config, mock_bm25_config], nodes=mock_nodes, embed_model=mock_embedding + ) assert isinstance(retriever, SimpleHybridRetriever) - def test_get_retriever_with_chroma_config(self, mocker, mock_vector_store_index, mock_chroma_vector_store): + def test_get_retriever_with_chroma_config(self, mocker, mock_chroma_vector_store, mock_embedding): mock_config = ChromaRetrieverConfig(persist_path="/path/to/chroma", collection_name="test_collection") mock_chromadb = mocker.patch("metagpt.rag.factories.retriever.chromadb.PersistentClient") mock_chromadb.get_or_create_collection.return_value = mocker.MagicMock() mocker.patch("metagpt.rag.factories.retriever.ChromaVectorStore", return_value=mock_chroma_vector_store) - mocker.patch.object(self.retriever_factory, "_extract_index", return_value=mock_vector_store_index) - retriever = self.retriever_factory.get_retriever(configs=[mock_config]) + retriever = self.retriever_factory.get_retriever(configs=[mock_config], nodes=[], embed_model=mock_embedding) assert isinstance(retriever, ChromaRetriever) - def test_get_retriever_with_es_config(self, mocker, mock_vector_store_index, mock_es_vector_store): + def test_get_retriever_with_es_config(self, mocker, mock_es_vector_store, mock_embedding): mock_config = ElasticsearchRetrieverConfig(store_config=ElasticsearchStoreConfig()) mocker.patch("metagpt.rag.factories.retriever.ElasticsearchStore", return_value=mock_es_vector_store) - mocker.patch.object(self.retriever_factory, "_extract_index", return_value=mock_vector_store_index) - retriever = self.retriever_factory.get_retriever(configs=[mock_config]) + retriever = self.retriever_factory.get_retriever(configs=[mock_config], nodes=[], embed_model=mock_embedding) assert isinstance(retriever, ElasticsearchRetriever) @@ -111,3 +119,19 @@ class TestRetrieverFactory: extracted_index = self.retriever_factory._extract_index(index=mock_vector_store_index) assert extracted_index == mock_vector_store_index + + def test_get_or_build_when_get(self, mocker): + want = "existing_index" + mocker.patch.object(self.retriever_factory, "_extract_index", return_value=want) + + got = self.retriever_factory._build_es_index(None) + + assert got == want + + def test_get_or_build_when_build(self, mocker): + want = "call_build_es_index" + mocker.patch.object(self.retriever_factory, "_build_es_index", return_value=want) + + got = self.retriever_factory._build_es_index(None) + + assert got == want diff --git a/tests/metagpt/test_context_mixin.py b/tests/metagpt/test_context_mixin.py index 4389dc251..e0b9d3e64 100644 --- a/tests/metagpt/test_context_mixin.py +++ b/tests/metagpt/test_context_mixin.py @@ -105,11 +105,11 @@ def test_config_mixin_4_multi_inheritance_override_config(): async def test_config_priority(): """If action's config is set, then its llm will be set, otherwise, it will use the role's llm""" home_dir = Path.home() / CONFIG_ROOT - gpt4t = Config.from_home("gpt-4-1106-preview.yaml") + gpt4t = Config.from_home("gpt-4-turbo.yaml") if not home_dir.exists(): assert gpt4t is None gpt35 = Config.default() - gpt35.llm.model = "gpt-3.5-turbo-1106" + gpt35.llm.model = "gpt-4-turbo" gpt4 = Config.default() gpt4.llm.model = "gpt-4-0613" @@ -127,8 +127,8 @@ async def test_config_priority(): env = Environment(desc="US election live broadcast") Team(investment=10.0, env=env, roles=[A, B, C]) - assert a1.llm.model == "gpt-4-1106-preview" if Path(home_dir / "gpt-4-1106-preview.yaml").exists() else "gpt-4-0613" + assert a1.llm.model == "gpt-4-turbo" if Path(home_dir / "gpt-4-turbo.yaml").exists() else "gpt-4-0613" assert a2.llm.model == "gpt-4-0613" - assert a3.llm.model == "gpt-3.5-turbo-1106" + assert a3.llm.model == "gpt-4-turbo" # history = await team.run(idea="Topic: climate change. Under 80 words per message.", send_to="a1", n_round=3) diff --git a/tests/metagpt/tools/test_ut_writer.py b/tests/metagpt/tools/test_ut_writer.py index 3cc7e86bb..557067191 100644 --- a/tests/metagpt/tools/test_ut_writer.py +++ b/tests/metagpt/tools/test_ut_writer.py @@ -56,7 +56,7 @@ class TestUTWriter: ) ], created=1706710532, - model="gpt-3.5-turbo-1106", + model="gpt-4-turbo", object="chat.completion", system_fingerprint="fp_04f9a1eebf", usage=CompletionUsage(completion_tokens=35, prompt_tokens=1982, total_tokens=2017), diff --git a/tests/metagpt/utils/test_cost_manager.py b/tests/metagpt/utils/test_cost_manager.py index 559ae3bcf..9508c778f 100644 --- a/tests/metagpt/utils/test_cost_manager.py +++ b/tests/metagpt/utils/test_cost_manager.py @@ -12,11 +12,11 @@ from metagpt.utils.cost_manager import CostManager def test_cost_manager(): cm = CostManager(total_budget=20) - cm.update_cost(prompt_tokens=1000, completion_tokens=100, model="gpt-4-1106-preview") + cm.update_cost(prompt_tokens=1000, completion_tokens=100, model="gpt-4-turbo") assert cm.get_total_prompt_tokens() == 1000 assert cm.get_total_completion_tokens() == 100 assert cm.get_total_cost() == 0.013 - cm.update_cost(prompt_tokens=100, completion_tokens=10, model="gpt-4-1106-preview") + cm.update_cost(prompt_tokens=100, completion_tokens=10, model="gpt-4-turbo") assert cm.get_total_prompt_tokens() == 1100 assert cm.get_total_completion_tokens() == 110 assert cm.get_total_cost() == 0.0143