diff --git a/llama-index-integrations/indices/llama-index-indices-managed-vectara/Changelog.md b/llama-index-integrations/indices/llama-index-indices-managed-vectara/Changelog.md
index 2d038347be523be3d61a2e36a499e2a4aa8e3865..c275d3189f188285e5556cd76f8281d8e64e0bf1 100644
--- a/llama-index-integrations/indices/llama-index-indices-managed-vectara/Changelog.md
+++ b/llama-index-integrations/indices/llama-index-indices-managed-vectara/Changelog.md
@@ -1,5 +1,9 @@
# CHANGELOG — llama-index-indices-managed-vectara
+## [0.4.1]
+
+Added vectara_base_url to support custom Vectara server, and vectara_verify_ssl to enable ignoring SSL when needed.
+
## [0.4.0]
Implementation switched from using Vectara API v1 to API v2.
diff --git a/llama-index-integrations/indices/llama-index-indices-managed-vectara/llama_index/indices/managed/vectara/base.py b/llama-index-integrations/indices/llama-index-indices-managed-vectara/llama_index/indices/managed/vectara/base.py
index e040c4f6516a4642c24c4af6a90c26cae0342e62..74773720d68f53671b936173aef9b703351e189b 100644
--- a/llama-index-integrations/indices/llama-index-indices-managed-vectara/llama_index/indices/managed/vectara/base.py
+++ b/llama-index-integrations/indices/llama-index-indices-managed-vectara/llama_index/indices/managed/vectara/base.py
@@ -65,10 +65,14 @@ class VectaraIndex(BaseManagedIndex):
vectara_api_key: Optional[str] = None,
parallelize_ingest: bool = False,
x_source_str: str = "llama_index",
+ vectara_base_url: str = "https://api.vectara.io",
+ vectara_verify_ssl: bool = True,
**kwargs: Any,
) -> None:
"""Initialize the Vectara API."""
self.parallelize_ingest = parallelize_ingest
+ self._base_url = vectara_base_url.rstrip("/")
+
index_struct = VectaraIndexStruct(
index_id=str(vectara_corpus_key),
summary="Vectara Index",
@@ -99,6 +103,8 @@ class VectaraIndex(BaseManagedIndex):
# setup requests session with max 3 retries and 90s timeout
# for calling Vectara API
self._session = requests.Session() # to reuse connections
+ if not vectara_verify_ssl:
+ self._session.verify = False # to ignore SSL verification
adapter = requests.adapters.HTTPAdapter(max_retries=3)
self._session.mount("https://", adapter)
self.vectara_api_timeout = 90
@@ -138,7 +144,7 @@ class VectaraIndex(BaseManagedIndex):
valid_corpus_key = self._get_corpus_key(corpus_key)
body = {}
response = self._session.delete(
- f"https://api.vectara.io/v2/corpora/{valid_corpus_key}/documents/{doc_id}",
+ f"{self._base_url}/v2/corpora/{valid_corpus_key}/documents/{doc_id}",
data=json.dumps(body),
verify=True,
headers=self._get_post_headers(),
@@ -156,7 +162,7 @@ class VectaraIndex(BaseManagedIndex):
def _index_doc(self, doc: dict, corpus_key) -> str:
response = self._session.post(
headers=self._get_post_headers(),
- url=f"https://api.vectara.io/v2/corpora/{corpus_key}/documents",
+ url=f"{self._base_url}/v2/corpora/{corpus_key}/documents",
data=json.dumps(doc),
timeout=self.vectara_api_timeout,
verify=True,
@@ -366,7 +372,7 @@ class VectaraIndex(BaseManagedIndex):
headers.pop("Content-Type")
valid_corpus_key = self._get_corpus_key(corpus_key)
response = self._session.post(
- f"https://api.vectara.io/v2/corpora/{valid_corpus_key}/upload_file",
+ f"{self._base_url}/v2/corpora/{valid_corpus_key}/upload_file",
files=files,
verify=True,
headers=headers,
@@ -426,7 +432,7 @@ class VectaraIndex(BaseManagedIndex):
doc_id = document.doc_id
body = {"metadata": update_kwargs["metadata"]}
response = self._session.patch(
- f"https://api.vectara.io/v2/corpora/{valid_corpus_key}/documents/{doc_id}",
+ f"{self._base_url}/v2/corpora/{valid_corpus_key}/documents/{doc_id}",
data=json.dumps(body),
verify=True,
headers=self._get_post_headers(),
diff --git a/llama-index-integrations/indices/llama-index-indices-managed-vectara/llama_index/indices/managed/vectara/retriever.py b/llama-index-integrations/indices/llama-index-indices-managed-vectara/llama_index/indices/managed/vectara/retriever.py
index fbfb134fac0f0108b892890cad943957671430a5..aac12b7a5315dc320fab973b149c9feb5b368225 100644
--- a/llama-index-integrations/indices/llama-index-indices-managed-vectara/llama_index/indices/managed/vectara/retriever.py
+++ b/llama-index-integrations/indices/llama-index-indices-managed-vectara/llama_index/indices/managed/vectara/retriever.py
@@ -338,7 +338,7 @@ class VectaraRetriever(BaseRetriever):
model_parameters["presence_penalty"] = self._presence_penalty
if len(model_parameters) > 0:
- summary_config["model_parameters"] = model_paramters
+ summary_config["model_parameters"] = model_parameters
citations_config = {}
if self._citations_style:
@@ -392,7 +392,7 @@ class VectaraRetriever(BaseRetriever):
conv_id = conv_id or self._conv_id
response = self._index._session.post(
headers=self._get_post_headers(),
- url=f"https://api.vectara.io/v2/chats/{conv_id}/turns",
+ url=f"{self._index._base_url}/v2/chats/{conv_id}/turns",
data=json.dumps(body),
timeout=self._index.vectara_api_timeout,
stream=True,
@@ -400,7 +400,7 @@ class VectaraRetriever(BaseRetriever):
else:
response = self._index._session.post(
headers=self._get_post_headers(),
- url="https://api.vectara.io/v2/chats",
+ url=f"{self._index._base_url}/v2/chats",
data=json.dumps(body),
timeout=self._index.vectara_api_timeout,
stream=True,
@@ -409,7 +409,7 @@ class VectaraRetriever(BaseRetriever):
else:
response = self._index._session.post(
headers=self._get_post_headers(),
- url="https://api.vectara.io/v2/query",
+ url=f"{self._index._base_url}/v2/query",
data=json.dumps(body),
timeout=self._index.vectara_api_timeout,
stream=True,
@@ -518,14 +518,14 @@ class VectaraRetriever(BaseRetriever):
if conv_id:
response = self._index._session.post(
headers=self._get_post_headers(),
- url=f"https://api.vectara.io/v2/chats/{conv_id}/turns",
+ url=f"{self._index._base_url}/v2/chats/{conv_id}/turns",
data=json.dumps(data),
timeout=self._index.vectara_api_timeout,
)
else:
response = self._index._session.post(
headers=self._get_post_headers(),
- url="https://api.vectara.io/v2/chats",
+ url=f"{self._index._base_url}/v2/chats",
data=json.dumps(data),
timeout=self._index.vectara_api_timeout,
)
@@ -533,7 +533,7 @@ class VectaraRetriever(BaseRetriever):
else:
response = self._index._session.post(
headers=self._get_post_headers(),
- url="https://api.vectara.io/v2/query",
+ url=f"{self._index._base_url}/v2/query",
data=json.dumps(data),
timeout=self._index.vectara_api_timeout,
)
diff --git a/llama-index-integrations/indices/llama-index-indices-managed-vectara/pyproject.toml b/llama-index-integrations/indices/llama-index-indices-managed-vectara/pyproject.toml
index cb31692b7703045a07969d0b404852de521ee905..526c8b1e06b5464452cb41b75c30745d1aeb8593 100644
--- a/llama-index-integrations/indices/llama-index-indices-managed-vectara/pyproject.toml
+++ b/llama-index-integrations/indices/llama-index-indices-managed-vectara/pyproject.toml
@@ -31,7 +31,7 @@ exclude = ["**/BUILD"]
license = "MIT"
name = "llama-index-indices-managed-vectara"
readme = "README.md"
-version = "0.4.0"
+version = "0.4.1"
[tool.poetry.dependencies]
python = ">=3.9,<4.0"
diff --git a/llama-index-integrations/indices/llama-index-indices-managed-vectara/tests/test_indices_managed_vectara.py b/llama-index-integrations/indices/llama-index-indices-managed-vectara/tests/test_indices_managed_vectara.py
index a0b644f58a92546ca02131b4a8d825a980268c1c..2825bc14c76e6a2b70879b48c202c7233e1879ab 100644
--- a/llama-index-integrations/indices/llama-index-indices-managed-vectara/tests/test_indices_managed_vectara.py
+++ b/llama-index-integrations/indices/llama-index-indices-managed-vectara/tests/test_indices_managed_vectara.py
@@ -95,6 +95,7 @@ def get_nodes() -> List[Node]:
return nodes
+# Normal vectara index fixture
@pytest.fixture()
def vectara1():
docs = get_docs()
@@ -110,6 +111,24 @@ def vectara1():
vectara1.delete_ref_doc(id)
+# vectara index fixture, where we specify the base url
+@pytest.fixture()
+def vectara1_custom():
+ docs = get_docs()
+ try:
+ vectara1_custom = VectaraIndex.from_documents(
+ docs, vectara_base_url="https://api.vectara.io"
+ )
+ except ValueError:
+ pytest.skip("Missing Vectara credentials, skipping test")
+
+ yield vectara1_custom
+
+ # Tear down code
+ for id in vectara1_custom.doc_ids:
+ vectara1_custom.delete_ref_doc(id)
+
+
def test_simple_retrieval(vectara1) -> None:
docs = get_docs()
qe = vectara1.as_retriever(similarity_top_k=1)
@@ -119,6 +138,15 @@ def test_simple_retrieval(vectara1) -> None:
assert res[0].node.node_id == docs[1].doc_id
+def test_simple_retrieval_with_custom_base_url(vectara1_custom) -> None:
+ docs = get_docs()
+ qe = vectara1_custom.as_retriever(similarity_top_k=1)
+ res = qe.retrieve("Find me something different")
+ assert len(res) == 1
+ assert res[0].node.get_content() == docs[1].text
+ assert res[0].node.node_id == docs[1].doc_id
+
+
def test_mmr_retrieval(vectara1) -> None:
docs = get_docs()
@@ -257,8 +285,6 @@ def test_chain_rerank_retrieval(vectara1) -> None:
def test_custom_prompt(vectara1) -> None:
- docs = get_docs()
-
qe = vectara1.as_query_engine(
similarity_top_k=3,
n_sentences_before=0,
@@ -269,11 +295,10 @@ def test_custom_prompt(vectara1) -> None:
prompt_text='[\n {"role": "system", "content": "You are an expert in summarizing the future of Vectara\'s inegration with LlamaIndex. Your summaries are insightful, concise, and highlight key innovations and changes."},\n #foreach ($result in $vectaraQueryResults)\n {"role": "user", "content": "What are the key points in result number $vectaraIdxWord[$foreach.index] about Vectara\'s LlamaIndex integration?"},\n {"role": "assistant", "content": "In result number $vectaraIdxWord[$foreach.index], the key points are: ${result.getText()}"},\n #end\n {"role": "user", "content": "Can you generate a comprehensive summary on \'Vectara\'s LlamaIndex Integration\' incorporating all the key points discussed?"}\n]\n',
)
- res = qe.query("How will Vectara's integration look in the future?")
+ res = qe.query("How does Vectara's integration with llamaindex work?")
assert "integration" in str(res).lower()
assert "llamaindex" in str(res).lower()
assert "vectara" in str(res).lower()
- assert "result" in str(res).lower()
def test_update_doc(vectara1) -> None:
@@ -337,7 +362,7 @@ def test_file_upload(vectara2) -> None:
query_engine = vectara2.as_query_engine(similarity_top_k=3)
res = query_engine.query("How is Paul related to Reddit?")
summary = res.response
- assert "paul graham" in summary.lower() and "reddit" in summary.lower()
+ assert "paul" in summary.lower() and "reddit" in summary.lower()
assert "https://www.paulgraham.com/worked.html" in str(res.source_nodes)
@@ -419,7 +444,7 @@ def test_chat(vectara2) -> None:
res = chat_engine.chat("What did he learn at the graduate school he selected?")
summary = res.response
- assert "learn" in summary.lower()
+ assert "paul" in summary.lower()
assert "harvard" in summary.lower()
assert res.metadata["fcs"] > 0
assert chat_engine.conv_id == chat_id