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[bugfix] Fix issue when llm config is not defined (#763)

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This commit is contained in:
Deshraj Yadav
2023-10-04 12:08:21 -07:00
committed by GitHub
parent d0af018b8d
commit 87d0b5c76f
15 changed files with 100 additions and 88 deletions
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36
tests/vectordb/test_elasticsearch_db.py
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@@ -4,11 +4,11 @@ from unittest.mock import patch
from embedchain import App
from embedchain.config import AppConfig, ElasticsearchDBConfig
from embedchain.vectordb.elasticsearch import ElasticsearchDB
from embedchain.embedder.gpt4all import GPT4AllEmbedder
from embedchain.vectordb.elasticsearch import ElasticsearchDB
class TestEsDB(unittest.TestCase):
@patch("embedchain.vectordb.elasticsearch.Elasticsearch")
def test_setUp(self, mock_client):
self.db = ElasticsearchDB(config=ElasticsearchDBConfig(es_url="https://localhost:9200"))
@@ -37,17 +37,11 @@ class TestEsDB(unittest.TestCase):
# Add the data to the database.
self.db.add(embeddings, documents, metadatas, ids, skip_embedding=False)
search_response = {"hits":
{"hits":
[
{
"_source": {"text": "This is a document."},
"_score": 0.9
},
{
"_source": {"text": "This is another document."},
"_score": 0.8
}
search_response = {
"hits": {
"hits": [
{"_source": {"text": "This is a document."}, "_score": 0.9},
{"_source": {"text": "This is another document."}, "_score": 0.8},
]
}
}
@@ -80,17 +74,11 @@ class TestEsDB(unittest.TestCase):
# Add the data to the database.
self.db.add(embeddings, documents, metadatas, ids, skip_embedding=True)
search_response = {"hits":
{"hits":
[
{
"_source": {"text": "This is a document."},
"_score": 0.9
},
{
"_source": {"text": "This is another document."},
"_score": 0.8
}
search_response = {
"hits": {
"hits": [
{"_source": {"text": "This is a document."}, "_score": 0.9},
{"_source": {"text": "This is another document."}, "_score": 0.8},
]
}
}