fix: remove connection reference in python tool

cli/jobs/pipelines-with-components/pipeline_job_with_flow_as_component/README.md

@@ -1,4 +1,4 @@
-This is a dummy pipeline job with anonymous reference of a flow as a component. Flow directory is copied from [sample in promptflow repository](https://github.com/microsoft/promptflow/tree/main/examples/flows/standard/basic).
+This is a dummy pipeline job with anonymous reference of a flow as a component. Flow directory is copied from [sample in promptflow repository](https://github.com/microsoft/promptflow/tree/main/examples/flows/standard/basic) and remove connection dependency to avoid using promptflow connection in azure ml example repository.
 
 Prerequirements:
 1. `.promptflow/flow.tools.json` in the flow directory is required to use a flow as a component. Usually you can use `pf flow validate` or `pf run validate` to generate it.

cli/jobs/pipelines-with-components/pipeline_job_with_flow_as_component/basic/hello.py

@@ -47,31 +47,5 @@ def my_python_tool(
         api_version=os.environ.get("AZURE_OPENAI_API_VERSION", "2023-07-01-preview"),
     )
 
-    # TODO: remove below type conversion after client can pass json rather than string.
-    echo = to_bool(echo)
-
-    response = openai.Completion.create(
-        prompt=prompt,
-        engine=deployment_name,
-        # empty string suffix should be treated as None.
-        suffix=suffix if suffix else None,
-        max_tokens=int(max_tokens),
-        temperature=float(temperature),
-        top_p=float(top_p),
-        n=int(n),
-        logprobs=int(logprobs) if logprobs else None,
-        echo=echo,
-        # fix bug "[] is not valid under any of the given schemas-'stop'"
-        stop=stop if stop else None,
-        presence_penalty=float(presence_penalty),
-        frequency_penalty=float(frequency_penalty),
-        best_of=int(best_of),
-        # Logit bias must be a dict if we passed it to openai api.
-        logit_bias=logit_bias if logit_bias else {},
-        user=user,
-        request_timeout=30,
-        **conn,
-    )
-
-    # get first element because prompt is single.
-    return response.choices[0].text
+    # return directly to avoid using promptflow connection in azure ml example repository
+    return f"fake answer based on {prompt}"

cli/jobs/pipelines-with-components/pipeline_job_with_flow_as_component/pipeline.yml

@@ -22,14 +22,19 @@ jobs:
     component: ./basic/flow.dag.yaml
     inputs:
       data: ${{parent.inputs.flow_input}}
-      url: "${data.text}"
+      text: "${data.text}"
     outputs:
       flow_outputs: ${{parent.outputs.output_data}}
       debug_info: ${{parent.outputs.debug_info}}
+    environment_variables:
+      # environment variables from connection
+      AZURE_OPENAI_API_KEY: ${open_ai_connection.api_key}
+      AZURE_OPENAI_API_BASE: ${open_ai_connection.api_base}
+      AZURE_OPENAI_API_TYPE: azure
 
   flow_node_from_run:
     type: parallel
-    component: ./run.yaml
+    component: ./run.yml
     inputs:
       data: ${{parent.inputs.flow_input}}
-      url: "${data.text}"
+      text: "${data.text}"

sdk/python/jobs/pipelines/1l_flow_in_pipeline/README.md

@@ -1,4 +1,4 @@
-This is a dummy pipeline job with anonymous reference of a flow as a component. This example has reused the flow in corresponding CLI example, which is copied from [sample in promptflow repository](https://github.com/microsoft/promptflow/tree/main/examples/flows/standard/basic). Please check [this path](../../../../../cli/jobs/pipelines-with-components/pipeline_job_with_flow_as_component/) for dependent resources.
+This is a dummy pipeline job with anonymous reference of a flow as a component. This example has reused the flow in corresponding CLI example, which is copied from [sample in promptflow repository](https://github.com/microsoft/promptflow/tree/main/examples/flows/standard/basic) and remove connection dependency to avoid using promptflow connection in azure ml example repository. Please check [this path](../../../../../cli/jobs/pipelines-with-components/pipeline_job_with_flow_as_component/) for dependent resources.
 
 References:
 - [microsoft/promptflow: Build high-quality LLM apps](https://github.com/microsoft/promptflow)