Scrapegraph-ai/examples
Marco Vinciguerra c19d83f994
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Update fetch_node.py
2024-07-11 18:03:10 +02:00
..
anthropic refactoring of examples 2024-07-10 12:19:41 +02:00
azure update model tokens 2024-06-12 12:41:58 +02:00
bedrock refactoring of examples 2024-07-10 12:19:41 +02:00
benchmarks Update Readme.md 2024-06-21 15:00:31 +02:00
deepseek refactoring of examples 2024-07-10 12:19:41 +02:00
ernie refactoring of examples 2024-07-10 12:19:41 +02:00
extras Create serch_graph_scehma.py 2024-07-10 20:16:25 +02:00
fireworks refactoring of examples 2024-07-10 12:19:41 +02:00
gemini update model tokens 2024-06-12 12:41:58 +02:00
groq update model tokens 2024-06-12 12:41:58 +02:00
huggingfacehub fix: updated for schema changes 2024-06-18 13:31:10 -05:00
integrations feat(indexify-node): add example 2024-06-05 18:45:37 +02:00
local_models add new convert function 2024-06-20 21:15:16 +02:00
mixed_models fix: updated for schema changes 2024-06-18 13:31:10 -05:00
oneapi refactoring of examples 2024-07-10 12:19:41 +02:00
openai refactoring of examples 2024-07-10 12:19:41 +02:00
single_node Update fetch_node.py 2024-07-11 18:03:10 +02:00
readme.md add new test for script generator 2024-04-18 10:39:53 +02:00

Benchmark analysis

Local models

The two websites benchmark are:

Both are strored locally as txt file in .txt format because in this way we do not have to think about the internet connection

The time is measured in seconds

The model runned for this benchmark is Mistral on Ollama with nomic-embed-text

Hardware Example 1 Example 2
Macbook pro 14' m1 11.60s 26.61s
Macbook pro 16' m2 max 8.05s 12.17s

Note: the examples on Docker are not runned on other devices than the Macbook because the performance are to slow (10 times slower than Ollama). Indeed the results are the following:

Hardware Example 1 Example 2
Macbook 14' m1 pro 139.89 Too long

Performance on APIs services

Example 1: personal portfolio

URL: https://perinim.github.io/projects Task: List me all the projects with their description.

Name Execution time (seconds) total_tokens prompt_tokens completion_tokens successful_requests total_cost_USD
gpt-3.5-turbo 25.22 445 272 173 1 0.000754
gpt-4-turbo-preview 9.53 449 272 177 1 0.00803

Example 2: Wired

URL: https://www.wired.com Task: List me all the articles with their description.

Name Execution time (seconds) total_tokens prompt_tokens completion_tokens successful_requests total_cost_USD
gpt-3.5-turbo 25.89 445 272 173 1 0.000754
gpt-4-turbo-preview 64.70 3573 2199 1374 1 0.06321