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Just Prompt

by disler
gemini-2-5-flash-reasoning.md2.93 kB
# Gemini 2.5 Flash Reasoning > Implement reasoning for Gemini 2.5 Flash. > > Implement every detail below end to end and validate your work with tests. ## Implementation Notes - We're adding support for `gemini-2.5-flash-preview-04-17` with thinking_budget for gemini. - Just like how claude-3-7-sonnet has budget tokens in src/just_prompt/atoms/llm_providers/anthropic.py, Gemini has a similar feature with the thinking_budget. We want to support this. - If this parameter is present, we should trigger a prompt_with_thinking function in src/just_prompt/atoms/llm_providers/gemini.py. Use the example code in ai_docs/gemini-2-5-flash-reasoning.md. If parameter is not present, use the existing prompt function. - Update tests to verify the feature works, specifically in test_gemini.py. Test with gemini-2.5-flash-preview-04-17 with and without the thinking_budget parameter. - This only works with the gemini-2.5-flash-preview-04-17 model but assume more models like this will be added in the future and check against the model name from a list so we can easily add them later. - After you implement and test, update the README.md file to detail the new feature. - We're using 'uv run pytest <file>' to run tests. You won't need to run any other commands or install anything only testing. - Keep all the essential logic surrounding this change in gemini.py just like how anthropic.py sets this up for it's version (thinking_budget). - No need to update any libraries or packages. - So if we pass in something like: `gemini:gemini-2.5-flash-preview-04-17`, run the normal prompt function. If we pass in: `gemini:gemini-2.5-flash-preview-04-17:4k`, run the prompt_with_thinking function with 4000 thinking budget. Mirror anthropic.py's logic. - Update gemini.py to use the new import and client setup via `from google import genai` and `client = genai.Client(api_key="GEMINI_API_KEY")`. ## Relevant Files (Context) > Read these files before implementing the feature. README.md pyproject.toml src/just_prompt/molecules/prompt.py src/just_prompt/atoms/llm_providers/anthropic.py src/just_prompt/atoms/llm_providers/gemini.py src/just_prompt/tests/atoms/llm_providers/test_gemini.py ## Example Reasoning Code ```python from google import genai client = genai.Client(api_key="GEMINI_API_KEY") response = client.models.generate_content( model="gemini-2.5-flash-preview-04-17", contents="You roll two dice. What’s the probability they add up to 7?", config=genai.types.GenerateContentConfig( thinking_config=genai.types.ThinkingConfig( thinking_budget=1024 # 0 - 24576 ) ) ) print(response.text) ``` ## Self Validation (Close the loop) > After implementing the feature, run the tests to verify it works. > > All env variables are in place - run tests against real apis. - uv run pytest src/just_prompt/tests/atoms/llm_providers/test_gemini.py - uv run pytest src/just_prompt/tests/molecules/test_prompt.py

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