From 0e0242671537c94d79cfab575cb90847bc1d4a9a Mon Sep 17 00:00:00 2001
From: fern-api <115122769+fern-api[bot]@users.noreply.github.com>
Date: Fri, 20 Dec 2024 16:58:10 +0000
Subject: [PATCH] SDK regeneration
---
pyproject.toml | 2 +-
reference.md | 136 ++++++++++++++++++++++++-----
src/vectara/core/client_wrapper.py | 2 +-
3 files changed, 115 insertions(+), 25 deletions(-)
diff --git a/pyproject.toml b/pyproject.toml
index 8609e15..6a4de20 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,6 +1,6 @@
[tool.poetry]
name = "vectara"
-version = "0.2.40"
+version = "0.2.42"
description = ""
readme = "README.md"
authors = []
diff --git a/reference.md b/reference.md
index 932445d..7a92f8a 100644
--- a/reference.md
+++ b/reference.md
@@ -37,8 +37,8 @@ For more detailed information, see this [Query API guide](https://docs.vectara.c
```python
from vectara import (
- CitationParameters,
ContextConfiguration,
+ CustomerSpecificReranker,
GenerationParameters,
KeyedSearchCorpus,
SearchCorporaParameters,
@@ -51,28 +51,26 @@ client = Vectara(
client_secret="YOUR_CLIENT_SECRET",
)
response = client.query_stream(
- query="hello, world?",
+ query="What is a hallucination?",
search=SearchCorporaParameters(
corpora=[
KeyedSearchCorpus(
+ corpus_key="corpus_key",
+ metadata_filter="",
lexical_interpolation=0.005,
)
],
- offset=0,
- limit=10,
context_configuration=ContextConfiguration(
sentences_before=2,
sentences_after=2,
- start_tag="",
- end_tag="",
+ ),
+ reranker=CustomerSpecificReranker(
+ reranker_id="rnk_272725719",
),
),
generation=GenerationParameters(
- max_used_search_results=5,
- citations=CitationParameters(
- style="none",
- ),
- response_language="auto",
+ response_language="eng",
+ enable_factual_consistency_score=True,
),
)
for chunk in response:
@@ -189,7 +187,14 @@ For more detailed information, see this [Query API guide](https://docs.vectara.c
```python
-from vectara import SearchCorporaParameters, Vectara
+from vectara import (
+ ContextConfiguration,
+ CustomerSpecificReranker,
+ GenerationParameters,
+ KeyedSearchCorpus,
+ SearchCorporaParameters,
+ Vectara,
+)
client = Vectara(
api_key="YOUR_API_KEY",
@@ -197,8 +202,27 @@ client = Vectara(
client_secret="YOUR_CLIENT_SECRET",
)
client.query(
- query="Am I allowed to bring pets to work?",
- search=SearchCorporaParameters(),
+ query="What is a hallucination?",
+ search=SearchCorporaParameters(
+ corpora=[
+ KeyedSearchCorpus(
+ corpus_key="corpus_key",
+ metadata_filter="",
+ lexical_interpolation=0.005,
+ )
+ ],
+ context_configuration=ContextConfiguration(
+ sentences_before=2,
+ sentences_after=2,
+ ),
+ reranker=CustomerSpecificReranker(
+ reranker_id="rnk_272725719",
+ ),
+ ),
+ generation=GenerationParameters(
+ response_language="eng",
+ enable_factual_consistency_score=True,
+ ),
)
```
@@ -302,7 +326,16 @@ Create a chat while specifying the default retrieval parameters used by the prom
```python
-from vectara import SearchCorporaParameters, Vectara
+from vectara import (
+ ChatParameters,
+ CitationParameters,
+ ContextConfiguration,
+ CustomerSpecificReranker,
+ GenerationParameters,
+ KeyedSearchCorpus,
+ SearchCorporaParameters,
+ Vectara,
+)
client = Vectara(
api_key="YOUR_API_KEY",
@@ -310,8 +343,33 @@ client = Vectara(
client_secret="YOUR_CLIENT_SECRET",
)
response = client.chat_stream(
- query="How can I use the Vectara platform?",
- search=SearchCorporaParameters(),
+ query="What is a hallucination?",
+ search=SearchCorporaParameters(
+ corpora=[
+ KeyedSearchCorpus(
+ corpus_key="corpus_key",
+ metadata_filter="",
+ lexical_interpolation=0.005,
+ )
+ ],
+ context_configuration=ContextConfiguration(
+ sentences_before=2,
+ sentences_after=2,
+ ),
+ reranker=CustomerSpecificReranker(
+ reranker_id="rnk_272725719",
+ ),
+ ),
+ generation=GenerationParameters(
+ response_language="eng",
+ citations=CitationParameters(
+ style="none",
+ ),
+ enable_factual_consistency_score=True,
+ ),
+ chat=ChatParameters(
+ store=True,
+ ),
)
for chunk in response:
yield chunk
@@ -425,7 +483,16 @@ Create a chat while specifying the default retrieval parameters used by the prom
```python
-from vectara import SearchCorporaParameters, Vectara
+from vectara import (
+ ChatParameters,
+ CitationParameters,
+ ContextConfiguration,
+ CustomerSpecificReranker,
+ GenerationParameters,
+ KeyedSearchCorpus,
+ SearchCorporaParameters,
+ Vectara,
+)
client = Vectara(
api_key="YOUR_API_KEY",
@@ -433,8 +500,33 @@ client = Vectara(
client_secret="YOUR_CLIENT_SECRET",
)
client.chat(
- query="How can I use the Vectara platform?",
- search=SearchCorporaParameters(),
+ query="What is a hallucination?",
+ search=SearchCorporaParameters(
+ corpora=[
+ KeyedSearchCorpus(
+ corpus_key="corpus_key",
+ metadata_filter="",
+ lexical_interpolation=0.005,
+ )
+ ],
+ context_configuration=ContextConfiguration(
+ sentences_before=2,
+ sentences_after=2,
+ ),
+ reranker=CustomerSpecificReranker(
+ reranker_id="rnk_272725719",
+ ),
+ ),
+ generation=GenerationParameters(
+ response_language="eng",
+ enable_factual_consistency_score=True,
+ citations=CitationParameters(
+ style="none",
+ ),
+ ),
+ chat=ChatParameters(
+ store=True,
+ ),
)
```
@@ -555,9 +647,7 @@ client = Vectara(
client_id="YOUR_CLIENT_ID",
client_secret="YOUR_CLIENT_SECRET",
)
-response = client.corpora.list(
- limit=1,
-)
+response = client.corpora.list()
for item in response:
yield item
# alternatively, you can paginate page-by-page
diff --git a/src/vectara/core/client_wrapper.py b/src/vectara/core/client_wrapper.py
index 8531d24..d15d896 100644
--- a/src/vectara/core/client_wrapper.py
+++ b/src/vectara/core/client_wrapper.py
@@ -25,7 +25,7 @@ def get_headers(self) -> typing.Dict[str, str]:
headers: typing.Dict[str, str] = {
"X-Fern-Language": "Python",
"X-Fern-SDK-Name": "vectara",
- "X-Fern-SDK-Version": "0.2.40",
+ "X-Fern-SDK-Version": "0.2.42",
}
if self._api_key is not None:
headers["x-api-key"] = self._api_key