Update ReACT

Author: ZhuochengZhang98

react/image.png

@@ -5,11 +5,8 @@
 from typing import Optional
 
 from flexrag.assistant import ASSISTANTS, AssistantBase, SearchHistory
-from flexrag.retriever import (
-    RetrievedContext,
-    WikipediaRetriever,
-    WikipediaRetrieverConfig,
-)
+from flexrag.common_dataclass import RetrievedContext
+from flexrag.retriever import WikipediaRetriever, WikipediaRetrieverConfig
 from flexrag.prompt import ChatPrompt
 from flexrag.models import GENERATORS, GenerationConfig
 from flexrag.utils import LOGGER_MANAGER
@@ -27,8 +24,6 @@ class ReActConfig(GeneratorConfig, GenerationConfig, WikipediaRetrieverConfig):
 
 @ASSISTANTS("react", config_class=ReActConfig)
 class ReActAssistant(AssistantBase):
-    is_hybrid = False
-
     def __init__(self, cfg: ReActConfig) -> None:
         # load retriever
         self.retriever = WikipediaRetriever(cfg)
@@ -56,7 +51,7 @@ def __init__(self, cfg: ReActConfig) -> None:
         self.cfg = cfg
         return
 
-    def answer_with_generation(
+    def answer(
         self, question: str
     ) -> tuple[str, Optional[list[RetrievedContext]], Optional[dict]]:
         if self.use_chat:

react/react_assistant.py

@@ -0,0 +1,48 @@
+# ITRG / Iter-RetGen
+This is the reproduction of the paper:
+- [ReAct: Synergizing Reasoning and Acting in Language Models](https://par.nsf.gov/biblio/10451467)
+
+
+## Introduction
+ReAct solves knowledge-intensive tasks by taking both reasoning and retrieving actions in an interleaved manner, allowing for greater synergy between the two: reasoning traces help the model induce, track, and update action plans as well as handle exceptions, while actions allow it to interface with and gather additional information from external sources such as knowledge bases or environments.
+
+<center>
+<img src="./image.png" alt="IRCoT" width="50%"/>
+</center>
+
+## Running the Method
+Before conducting the experiment, you need to prepare the generator. In this example, we use VLLM to deploy the generator, you can skip this step if you wish to use the generator from OpenAI.
+```bash
+bash ./run_generator.sh
+```
+This script will start a `Qwen2-7B-Instruct` model server on port 8000. You can change the `MODEL_NAME` in the script if you want to use a different model.
+
+
+Then, run the following command to evaluate the IRCoT on the test set of `Natural Questions`:
+```bash
+bash ./run.sh
+```
+This script will run the IRCoT method on the test set of `Natural Questions` and save the results in the `results` directory. You can change the `DATASET_NAME` and the `SPLIT` variables in the script to evaluate on different datasets.
+
+## Citation
+If you use this code in your research, please cite the following paper:
+
+```bibtex
+@software{Zhang_FlexRAG_2025,
+author = {Zhang, Zhuocheng and Feng, Yang and Zhang, Min},
+doi = {10.5281/zenodo.14593327},
+month = jan,
+title = {{FlexRAG}},
+url = {https://github.com/ictnlp/FlexRAG},
+year = {2025}
+}
+```
+
+```bibtex
+@inproceedings{yao2023react,
+  title={React: Synergizing reasoning and acting in language models},
+  author={Yao, Shunyu and Zhao, Jeffrey and Yu, Dian and Du, Nan and Shafran, Izhak and Narasimhan, Karthik and Cao, Yuan},
+  booktitle={International Conference on Learning Representations (ICLR)},
+  year={2023}
+}
+```

react/readme.md

@@ -0,0 +1,21 @@
+#!/bin/bash
+
+MODEL_NAME=Qwen2-7B-Instruct
+DATASET_NAME=nq
+SPLIT=test
+EXAMPLE_PATH="./react"
+
+
+python -m flexrag.entrypoints.run_assistant \
+    name=$DATASET_NAME \
+    split=$SPLIT \
+    user_module=$EXAMPLE_PATH \
+    assistant_type=react \
+    react_config.generator_type=openai \
+    react_config.openai_config.model_name=$MODEL_NAME \
+    react_config.openai_config.base_url=http://127.0.0.1:8000/v1 \
+    react_config.do_sample=False \
+    eval_config.metrics_type=[retrieval_success_rate,generation_f1,generation_em] \
+    eval_config.retrieval_success_rate_config.eval_field=text \
+    eval_config.response_preprocess.processor_type=[simplify_answer] \
+    log_interval=10

react/run.sh

@@ -0,0 +1,12 @@
+#!/bin/bash
+
+MODEL_NAME=Qwen2-7B-Instruct
+
+
+python -m vllm.entrypoints.openai.api_server \                                                                                                                                                                                        (base)
+    --model $MODEL_NAME \
+    --gpu-memory-utilization 0.95 \
+    --tensor-parallel-size 2 \
+    --port 8000 \
+    --host 0.0.0.0 \
+    --trust-remote-code