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This is done as setup for a PR that will fix the OpenAI dependency issue. * [x] FTS examples * [x] Setup mock openai * [x] Ran `npm audit fix` * [x] sentences embeddings test * [x] Double check formatting of docs examples
58 lines
1.9 KiB
Python
58 lines
1.9 KiB
Python
# SPDX-License-Identifier: Apache-2.0
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# SPDX-FileCopyrightText: Copyright The LanceDB Authors
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"""A zero-dependency mock OpenAI embeddings API endpoint for testing purposes."""
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import argparse
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import json
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import http.server
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class MockOpenAIRequestHandler(http.server.BaseHTTPRequestHandler):
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def do_POST(self):
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content_length = int(self.headers["Content-Length"])
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post_data = self.rfile.read(content_length)
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post_data = json.loads(post_data.decode("utf-8"))
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# See: https://platform.openai.com/docs/api-reference/embeddings/create
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if isinstance(post_data["input"], str):
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num_inputs = 1
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else:
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num_inputs = len(post_data["input"])
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model = post_data.get("model", "text-embedding-ada-002")
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data = []
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for i in range(num_inputs):
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data.append({
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"object": "embedding",
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"embedding": [0.1] * 1536,
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"index": i,
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})
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response = {
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"object": "list",
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"data": data,
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"model": model,
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"usage": {
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"prompt_tokens": 0,
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"total_tokens": 0,
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}
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}
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self.send_response(200)
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self.send_header("Content-type", "application/json")
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self.end_headers()
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self.wfile.write(json.dumps(response).encode("utf-8"))
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if __name__ == "__main__":
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parser = argparse.ArgumentParser(description="Mock OpenAI embeddings API endpoint")
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parser.add_argument("--port", type=int, default=8000, help="Port to listen on")
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args = parser.parse_args()
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port = args.port
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print(f"server started on port {port}. Press Ctrl-C to stop.")
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print(f"To use, set OPENAI_BASE_URL=http://localhost:{port} in your environment.")
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with http.server.HTTPServer(("0.0.0.0", port), MockOpenAIRequestHandler) as server:
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server.serve_forever()
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