Skip to content

add support for pinecone-v4 #1

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Open
wants to merge 1 commit into
base: main
Choose a base branch
from
Open

add support for pinecone-v4 #1

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
1 change: 1 addition & 0 deletions .gitignore
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -1,6 +1,7 @@
__pycache__/
*.py[cod]
*$py.class
.python-version

.env
.env.*
Expand Down
8 changes: 2 additions & 6 deletions extensions/pinecone_storage.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -20,9 +20,6 @@ def __init__(self, openai_api_key: str, pinecone_api_key: str, pinecone_environm
openai.api_key = openai_api_key
pinecone.init(api_key=pinecone_api_key, environment=pinecone_environment)

# Pinecone namespaces are only compatible with ascii characters (used in query and upsert)
self.namespace = re.sub(re.compile('[^\x00-\x7F]+'), '', objective)

self.llm_model = llm_model
self.llama_model_path = llama_model_path

Expand All @@ -44,12 +41,11 @@ def add(self, task: Dict, result: str, result_id: int):
result
)
self.index.upsert(
[(result_id, vector, {"task": task["task_name"], "result": result})], namespace=self.namespace
)
[(result_id, vector, {"task": task["task_name"], "result": result})])

def query(self, query: str, top_results_num: int) -> List[dict]:
query_embedding = self.get_embedding(query)
results = self.index.query(query_embedding, top_k=top_results_num, include_metadata=True, namespace=self.namespace)
results = self.index.query(query_embedding, top_k=top_results_num, include_metadata=True)
sorted_results = sorted(results.matches, key=lambda x: x.score, reverse=True)
return [(str(item.metadata["task"])) for item in sorted_results]

Expand Down