Competitors | Total simulation time | Max. decision time | 99% decision time | 95% decision time |
---|---|---|---|---|
Competitor #1 | 26874 | 494.31 | 0.18 | 0.08 |
Competitor #2 | 33665 | 105.85 | 0.94 | 0.14 |
La Javaness | 24027 | 11.15 | 2.60 | 0.08 |
Track | Ep. score | Op. score | Nres. score | Assist score | Completed scenarii |
---|---|---|---|---|---|
Local dataset | 65.01 | 65.05 | 86.67 | 51.93 | 159/208 (76.4%) |
Main assistant | 60.83 | 59.44 | 90.14 | 46.55 | 140/208 (67.3%) |
Sim2Real | 59.65 | 55.21 | 77.41 | - | 141/208 (67.7%) |
Element | Function | Possible action |
---|---|---|
Generator | Produces electricity, injects power in the grid. Different types: non-renewable/renewable | Redispatch (non-renewable), curtailment (renewable) |
Load | Consumes electricity, consumption endpoint of the grid | |
Substation | Nodes of the power grid, interconnect elements through 2 connexion buses | Reconfigure buses |
Power line | Responsible for transporting electricity, connects 2 elements of the grid | Connect/disconnect |
Storage | Battery able to store energy, making it act conceptually as both generator and load within the system | Charge/Discharge |
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chatdoc = ChatDoc(model_name= OPENAI_MODEL) | |
chatdoc.connect_openai_api() | |
questions = QUESTIONS_COMMITTE_AUDIT | |
retriever.retreive_with_query( query, top_k=1, namespace='Eiffage') | |
contexts = loader_document.retreive_contents_from_ids(ids) | |
respone = chatdoc.prompt_with_context(query, contexts= list(contexts.values()), verbose=True) | |
print(query,'\n', respone, '\n') |
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[09/Sep/2023 15:13:19] INFO - Answer the question based on the context below. | |
Context: | |
262RepoR t by the boaRd of diRectoR s on coRpoR ate goveRnance | |
The following table shows the situation of the non-independent directors with regard to the independence criteria: | |
Independence criteriaBenoît | |
de RuffrayLaurent .... | |
Question: Find the answers for the questions: | |
1/ what is the number of meetings of Audit Committee ? | |
2/ what is the average attendance rate (%) of meetings of Audit Committe ? | |
3/ what is the number of participates in the Audit Committe ? |
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data = [ | |
{'content': 'This universal registration document, eco-designed from start to finish for the second year, captures the essence \nof what makes Eiffage different and embodies its vision and commitments to advancing the environmental transition.\nUNIVERSAL REGISTRATION DOCUMENT 2021Advancing the environmental transition \nand fulfilling our social responsibility', | |
'metadata': {'source': 'Universal Registration Document/10_EIFFAGE_URD2021_VA.pdf', | |
'page': 0, | |
'id': 0}}, | |
{'content': '01In your hands you have a document designed \nusing a low-carbon approach for the second \nyear in a row. Its plain and simple content, \nthe\xa0typefaces selected, the visuals, colours, \nprinting techniques and distribution methods… \nAll these decisions help to\xa0make this annual \nreport a resource-efficient, low-impact \nproduct. \nEvery year, we refine our approach using \nthe\xa0lessons we learned from our previous \nexperience, as all the Group’s teams do. \nWe\xa0continue to work hard to devise and \ni |
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OPENAI_MODEL ='text-davinci-003' | |
class ChatDoc(): | |
def __init__(self, model_name:str = OPENAI_MODEL, **model_params): | |
self.model = model_name | |
self.engine_params = dict( | |
model = model_name, | |
temperature=0, | |
max_tokens=400, |
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from pinecone import Index | |
class Retreiver(Index): | |
def __init__(self, index_name, embedd_openai_model, sparse_model_file_name, dimension=1536, metric="dotproduct"): | |
self.index_name = index_name | |
# Create index | |
if index_name not in pinecone.list_indexes(): |
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from openai import Embedding | |
from pinecone_text.sparse import BM25Encoder | |
EMBEDDING_MODEL = "text-embedding-ada-002" | |
SPARSE_MODEL_FILE_NAME = "bm25_values.json" | |
class Embedding_Model(Embedding): | |
def __init__(self, model_name): | |
self.engine = model_name |
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index.describe_index_stats() | |
# Return for example: | |
{ | |
'dimension': 1536, | |
'index_fullness': 0.1, | |
'namespaces': { | |
'Eiffage': {'vector_count': 344}, | |
'total_vector_count': 344 | |
} |
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