vllm - 💡(How to fix) Fix [Feature]: Is there docker image support vllm and rocm 7.1+ [2 comments, 3 participants]

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vllm-project/vllm#37748Fetched 2026-04-08 01:13:08
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🚀 The feature, motivation and pitch

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Before submitting a new issue...

  • Make sure you already searched for relevant issues, and asked the chatbot living at the bottom right corner of the documentation page, which can answer lots of frequently asked questions.

extent analysis

Fix Plan

The fix involves implementing a search functionality to reduce duplicate issues.

  • Step 1: Implement a search bar in the issue submission page
  • Step 2: Index existing issues for search functionality
  • Step 3: Integrate the chatbot with the search functionality

Example Code

# Import required libraries
from flask import Flask, request, jsonify
from flask_sqlalchemy import SQLAlchemy

# Create a Flask app
app = Flask(__name__)
app.config["SQLALCHEMY_DATABASE_URI"] = "sqlite:///issues.db"
db = SQLAlchemy(app)

# Define the Issue model
class Issue(db.Model):
    id = db.Column(db.Integer, primary_key=True)
    title = db.Column(db.String(100), nullable=False)
    description = db.Column(db.Text, nullable=False)

# Create a search function
def search_issues(query):
    return Issue.query.filter(Issue.title.like(f"%{query}%")).all()

# Create a route for the search functionality
@app.route("/search", methods=["GET"])
def search():
    query = request.args.get("q")
    issues = search_issues(query)
    return jsonify([{"id": issue.id, "title": issue.title} for issue in issues])

# Run the app
if __name__ == "__main__":
    app.run(debug=True)

Verification

To verify that the fix worked, test the search functionality by submitting a query and checking if relevant issues are returned.

Extra Tips

  • Use a more robust search library like Elasticsearch for larger datasets.
  • Implement pagination for search results to improve performance.

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