Merge branch 'main' into jiazeng/meta_icon

.cspell.json

@@ -25,6 +25,7 @@
     "scripts/docs/_build/**",
     "src/promptflow/promptflow/azure/_restclient/flow/**",
     "src/promptflow/tests/**",
+    "src/promptflow-tools/tests/**",
     "**/flow.dag.yaml",
     "**/setup.py"
   ],

.github/pipelines/compliance_check.yml

@@ -17,7 +17,7 @@ trigger:
   - releases/*
 
 pool:
-  vmImage: windows-latest
+  name: promptflow-1ES-win
 
 steps:
 - checkout: self

docs/how-to-guides/develop-a-tool/add-a-tool-icon.md

@@ -5,6 +5,7 @@ Adding a custom tool icon is optional. If you do not provide one, the system use
 
 ## Prerequisites
 
+- Please ensure that your [Prompt flow for VS Code](https://marketplace.visualstudio.com/items?itemName=prompt-flow.prompt-flow) is updated to version 1.0.10 or a more recent version.
 - Create a tool package as described in [Create and Use Tool Package](create-and-use-tool-package.md).
 - Prepare custom icon image that meets these requirements:
 

docs/how-to-guides/develop-a-tool/create-and-use-tool-package.md

@@ -162,5 +162,4 @@ Alternatively, you can test your tool package using the script below to ensure t
 * If you encounter a `403 Forbidden Error`, it's likely due to a naming conflict with an existing package. You will need to choose a different name. Package names must be unique on PyPI to avoid confusion and conflicts among users. Before creating a new package, it's recommended to search PyPI (https://pypi.org/) to verify that your chosen name is not already taken. If the name you want is unavailable, consider selecting an alternative name or a variation that clearly differentiates your package from the existing one.
 
 ## Advanced features
-[Customize your tool icon](add-a-tool-icon.md)
-[Use file path as tool input](use-file-path-as-tool-input.md)
+[Customize your tool icon](add-a-tool-icon.md)

docs/how-to-guides/develop-a-tool/index.md

@@ -7,5 +7,4 @@ We provide guides on how to develop a tool and use it.
 
 create-and-use-tool-package
 add-a-tool-icon
-use-file-path-as-tool-input
 ```

docs/reference/tools-reference/open_source_llm_tool.md

@@ -52,7 +52,11 @@ The Open Source LLM tool has a number of parameters, some of which are required.
 | Name | Type | Description | Required |
 |------|------|-------------|----------|
 | api | string | This is the API mode and will depend on the model used and the scenario selected. *Supported values: (Completion \| Chat)* | Yes |
-| connection | CustomConnection | This is the name of the connection which points to the Online Inferencing endpoint. | Yes |
+| endpoint_name | string | Name of an Online Inferencing Endpoint with a supported model deployed on it. Takes priority over connection. | No |
+| connection | CustomConnection | This is the name of the connection which points to the Online Inferencing endpoint. | No |
+| temperature | float | The randomness of the generated text. Default is 1. | No |
+| max_new_tokens | integer | The maximum number of tokens to generate in the completion. Default is 500. | No |
+| top_p | float | The probability of using the top choice from the generated tokens. Default is 1. | No |
 | model_kwargs | dictionary | This input is used to provide configuration specific to the model used. For example, the Llama-02 model may use {\"temperature\":0.4}. *Default: {}* | No |
 | deployment_name | string | The name of the deployment to target on the Online Inferencing endpoint. If no value is passed, the Inferencing load balancer traffic settings will be used. | No |
 | prompt | string | The text prompt that the language model will use to generate it's response. | Yes |

examples/tools/tool-package-quickstart/setup.py

@@ -4,7 +4,7 @@
 
 setup(
     name=PACKAGE_NAME,
-    version="0.0.1",
+    version="0.0.2",
     description="This is my tools package",
     packages=find_packages(),
     entry_points={

src/promptflow-tools/connections.json.example

@@ -39,6 +39,18 @@
       "endpoint_api_key"
     ]
   },
+  "llama_chat_connection": {
+    "type": "CustomConnection",
+    "value": {
+      "endpoint_url": "llama-chat-endpoint-url",
+      "model_family": "LLAMA",
+      "endpoint_api_key": "llama-chat-endpoint-api-key"
+    },
+    "module": "promptflow.connections",
+    "secret_keys": [
+      "endpoint_api_key"
+    ]
+  },
   "open_ai_connection": {
     "type": "OpenAIConnection",
     "value": {

src/promptflow-tools/promptflow/tools/common.py

@@ -82,7 +82,9 @@ def validate_functions(functions):
 
 
 def parse_function_role_prompt(function_str):
-    pattern = r"\n*name:\n\s*(\S+)\s*\n*content:\n(.*)"
+    # customer can add ## in front of name/content for markdown highlight.
+    # and we still support name/content without ## prefix for backward compatibility.
+    pattern = r"\n*#{0,2}\s*name:\n\s*(\S+)\s*\n*#{0,2}\s*content:\n(.*)"
     match = re.search(pattern, function_str, re.DOTALL)
     if match:
         return match.group(1), match.group(2)
@@ -98,8 +100,12 @@ def parse_function_role_prompt(function_str):
 
 def parse_chat(chat_str):
     # openai chat api only supports below roles.
-    separator = r"(?i)\n*(system|user|assistant|function)\s*:\s*\n"
-    chunks = re.split(separator, chat_str)
+    # customer can add single # in front of role name for markdown highlight.
+    # and we still support role name without # prefix for backward compatibility.
+    separator = r"(?i)\n+\s*#?\s*(system|user|assistant|function)\s*:\s*\n"
+    # Add a newline at the beginning to ensure consistent formatting of role lines.
+    # extra new line is removed when appending to the chat list.
+    chunks = re.split(separator, '\n'+chat_str)
     chat_list = []
     for chunk in chunks:
         last_message = chat_list[-1] if len(chat_list) > 0 else None