Add streamlit demo for all deployable agents #85
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WalkthroughThe recent updates aim to enhance the prediction market agent software by improving functionality and reliability. Changes include enhanced logging, better error handling, and the integration of API keys for secure interactions with external services. A significant addition is the Streamlit app, providing a user-friendly interface for simulating agent behaviors in prediction markets. These updates streamline operations and enhance the overall user experience. Changes
Recent Review DetailsConfiguration used: CodeRabbit UI Files selected for processing (2)
Files skipped from review as they are similar to previous changes (1)
Additional comments not posted (2)
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| # Assume very high probability markets are already known, and have | ||
| # been correctly bet on, and therefore the value of betting on them | ||
| # is low. | ||
| if market_is_saturated(market=market): | ||
| logger.info( | ||
| f"Skipping market {market.id=} {market.question=}, because it is already saturated." | ||
| f"Skipping market {market.url} with the question '{market.question}', because it is already saturated." |
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Just trying to make log messages more human friendly
| @@ -17,7 +17,8 @@ | |||
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| class DeployableKnownOutcomeAgent(DeployableAgent): | |||
| model = "gpt-4-turbo-preview" | |||
| model = "gpt-4-1106-preview" | |||
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Needed to change this, see the summarize_if_required function below. Lmk if I did wrong 🙈
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| @st.cache_resource | ||
| def add_sink_to_logger() -> None: |
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If we call this at the top of streamlit application, any logged messages will show in Streamlit
| @@ -0,0 +1,100 @@ | |||
| """ | |||
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The idea is similar to the one in the EVO repository, but here, I used the DeployableAgent class instead of benchmark ones.
| llm = ChatOpenAI( | ||
| temperature=0, | ||
| model="gpt-3.5-turbo-0125", | ||
| api_key=APIKeys().openai_api_key.get_secret_value(), |
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Tip
Codebase Verification
The search results from the rg command provide numerous instances where the APIKeys class is used across various files in the codebase. However, none of these instances include comments or documentation specifically addressing the thread safety of the APIKeys class or its methods, such as get_secret_value().
Given the absence of explicit information on thread safety in the provided context, and considering the typical concerns around thread safety in scenarios involving shared resources (like API keys), it's prudent to recommend further investigation or implementation of thread safety mechanisms if the _summary method is indeed expected to be called concurrently.
Conclusion
The review comment concerning the thread safety of APIKeys().openai_api_key.get_secret_value() in a concurrent environment stands as a valid concern due to the lack of explicit thread safety guarantees in the provided code snippets and usage contexts. It is advisable to ensure that appropriate thread safety measures are implemented if concurrent access is expected.
Analysis chain
Ensure that APIKeys().openai_api_key.get_secret_value() is thread-safe if _summary is expected to be called concurrently.
Scripts Executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Check for any documentation or comments in the codebase regarding thread safety of APIKeys class.
rg "APIKeys" --context 5
Length of output: 31018
| """ | ||
| PYTHONPATH=. streamlit run scripts/agent_app.py | ||
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| Tip: if you specify PYTHONPATH=., streamlit will watch for the changes in all files, isntead of just this one. |
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Correct the typo in "instead" in the tip comment.
- isntead
+ insteadCommittable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation.
| Tip: if you specify PYTHONPATH=., streamlit will watch for the changes in all files, isntead of just this one. | |
| Tip: if you specify PYTHONPATH=., streamlit will watch for the changes in all files, instead of just this one. |
Summary by CodeRabbit
New Features
Refactor
Documentation