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-`conversation.go`, responsible for sending an input to the underlying LLM and retrieving an output.
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-`conversation.go`, responsible for sending an input to the underlying LLM and retrieving an output. It includes a secondary conversation request to showcase tool calling to the underlying LLM.
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## Run the app with the template file
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@@ -23,6 +23,9 @@ name: Run multi app run template
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expected_stdout_lines:
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- '== APP - conversation == Input sent: What is dapr?'
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- '== APP - conversation == Output response: What is dapr?'
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- '== APP - conversation == Tool calling input sent: What is the weather like in San Francisco in celsius?'
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- '== APP - conversation == Output message: What is the weather like in San Francisco in celsius?'
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- '== APP - conversation == Tool calls detected:'
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expected_stderr_lines:
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output_match_mode: substring
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match_order: none
@@ -37,25 +40,55 @@ dapr run -f .
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The terminal console output should look similar to this, where:
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- The app sends an input `What is dapr?` to the `echo` Component mock LLM.
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- The app first sends an input `What is dapr?` to the `echo` Component mock LLM.
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- The mock LLM echoes `What is dapr?`.
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- The app then sends a weather request to the component with tools available to the LLM.
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- The LLM will either respond back with a tool call for the user, or an ask for more information.
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```text
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== APP - conversation == Input sent: What is dapr?
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== APP - conversation == Output response: What is dapr?
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```
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- The app then sends an input `What is the weather like in San Francisco in celsius?` to the `echo` Component mock LLM.
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- The mock LLM echoes `What is the weather like in San Francisco in celsius?` and calls the `get_weather` tool.
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- The echo Component returns the tool call information.
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```text
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== APP - conversation == Tool calling input sent: What is the weather like in San Francisco in celsius?
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== APP - conversation == Output message: What is the weather like in San Francisco in celsius?
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