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docs: Fix typos in documentation files

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Ali Yaman 2025-03-12 00:12:31 +01:00
parent a4b72c398d
commit fce4872f32
3 changed files with 3 additions and 3 deletions
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2
README.md
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@ -118,7 +118,7 @@ When you call `Runner.run()`, we run a loop until we get a final output.
2. The LLM returns a response, which may include tool calls.
3. If the response has a final output (see below for the more on this), we return it and end the loop.
4. If the response has a handoff, we set the agent to the new agent and go back to step 1.
5. We process the tool calls (if any) and append the tool responses messsages. Then we go to step 1.
5. We process the tool calls (if any) and append the tool responses messages. Then we go to step 1.
There is a `max_turns` parameter that you can use to limit the number of times the loop executes.

2
docs/results.md
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@ -32,7 +32,7 @@ The [`new_items`][agents.result.RunResultBase.new_items] property contains the n
- [`MessageOutputItem`][agents.items.MessageOutputItem] indicates a message from the LLM. The raw item is the message generated.
- [`HandoffCallItem`][agents.items.HandoffCallItem] indicates that the LLM called the handoff tool. The raw item is the tool call item from the LLM.
- [`HandoffOutputItem`][agents.items.HandoffOutputItem] indicates that a handoff occured. The raw item is the tool response to the handoff tool call. You can also access the source/target agents from the item.
- [`HandoffOutputItem`][agents.items.HandoffOutputItem] indicates that a handoff occurred. The raw item is the tool response to the handoff tool call. You can also access the source/target agents from the item.
- [`ToolCallItem`][agents.items.ToolCallItem] indicates that the LLM invoked a tool.
- [`ToolCallOutputItem`][agents.items.ToolCallOutputItem] indicates that a tool was called. The raw item is the tool response. You can also access the tool output from the item.
- [`ReasoningItem`][agents.items.ReasoningItem] indicates a reasoning item from the LLM. The raw item is the reasoning generated.

2
examples/research_bot/README.md
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@ -21,5 +21,5 @@ If you're building your own research bot, some ideas to add to this are:
1. Retrieval: Add support for fetching relevant information from a vector store. You could use the File Search tool for this.
2. Image and file upload: Allow users to attach PDFs or other files, as baseline context for the research.
3. More planning and thinking: Models often produce better results given more time to think. Improve the planning process to come up with a better plan, and add an evaluation step so that the model can choose to improve it's results, search for more stuff, etc.
3. More planning and thinking: Models often produce better results given more time to think. Improve the planning process to come up with a better plan, and add an evaluation step so that the model can choose to improve its results, search for more stuff, etc.
4. Code execution: Allow running code, which is useful for data analysis.