Fix intent-copilot Sample all line returns same results (microsoft#133)

flow test: ![image](https://github.com/microsoft/promptflow/assets/17938940/5b9284ef-e1f2-4166-8545-a038bbcefe92) flow run outputs: ![image](https://github.com/microsoft/promptflow/assets/17938940/b88023a0-54de-4329-b510-85780e3d135e)
ttthree · Aug 24, 2023 · ff21971 · ff21971
1 parent 3e937a1
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diff --git a/examples/flows/standard/flow-with-additional-includes/README.md b/examples/flows/standard/flow-with-additional-includes/README.md
@@ -39,7 +39,7 @@ additional_includes:
 ### 2. Test & run the flow with additional includes
 
 In this sample, this flow will references some files in the [web-classification](../web-classification/README.md) flow. 
-You can execute this flow with additional_include locally or submit it to cloud.
+You can execute this flow with additional_include locally or submit it to cloud. The snapshot generated by Promptflow contains additional include files/folders.
 
 
 #### Test flow with single line data
@@ -60,7 +60,6 @@ pf run create --flow . --data ./data.jsonl --stream
 # create run using yaml file
 pf run create --file run.yml --stream
 ```
-Note: the snapshot folder in run should contain the additional_includes file.
 
 #### Submit run to cloud
 
@@ -72,4 +71,4 @@ Note: the snapshot folder in run should contain the additional_includes file.
 # pfazure run create --file run.yml --stream # serverless compute
 ```
 
-Note: the snapshot folder in run should contain the additional_includes file. Click portal_url of the run to view the final snapshot.
+Note: Click portal_url of the run to view the final snapshot.
diff --git a/examples/flows/standard/intent-copilot/.promptflow/flow.tools.json b/examples/flows/standard/intent-copilot/.promptflow/flow.tools.json
@@ -1,7 +1,7 @@
 {
     "package": {},
     "code": {
-        "user_prompt_template": {
+        "chat_prompt": {
             "type": "prompt",
             "inputs": {
                 "customer_info": {
@@ -20,17 +20,7 @@
         "extract_intent_tool.py": {
             "type": "python",
             "inputs": {
-                "customer_info": {
-                    "type": [
-                        "string"
-                    ]
-                },
-                "history": {
-                    "type": [
-                        "list"
-                    ]
-                },
-                "user_prompt_template": {
+                "chat_prompt": {
                     "type": [
                         "string"
                     ]

diff --git a/examples/flows/standard/intent-copilot/README.md b/examples/flows/standard/intent-copilot/README.md
@@ -18,9 +18,12 @@ cat .env
 
 1. init flow directory - create promptflow folder from existing python file
 ```bash
-pf flow init --flow . --entry intent.py --function extract_intent --prompt-template user_prompt_template=user_intent_zero_shot.jinja2
+pf flow init --flow . --entry intent.py --function extract_intent --prompt-template chat_prompt=user_intent_zero_shot.jinja2
 ```
-TODO introduce the generated files
+The generated files:
+- extract_intent_tool.py: Wrap the func `extract_intent` in the `intent.py` script into a [Python Tool](https://promptflow.azurewebsites.net/tools-reference/python-tool.html).
+- flow.dag.yaml: Describes the DAG(Directed Acyclic Graph) of this flow.
+- .gitignore: File/folder in the flow to be ignored.
 
 2. create needed custom connection
 ```bash

diff --git a/examples/flows/standard/intent-copilot/extract_intent_tool.py b/examples/flows/standard/intent-copilot/extract_intent_tool.py
@@ -7,20 +7,13 @@
 
 
 @tool
-def extract_intent_tool(
-    customer_info,
-    history,
-    user_prompt_template,
-    connection: CustomConnection
-) -> str:
+def extract_intent_tool(chat_prompt, connection: CustomConnection) -> str:
 
     # set environment variables
     for key, value in connection.items():
         os.environ[key] = value
 
     # call the entry function
     return extract_intent(
-        customer_info=customer_info,
-        history=history,
-        user_prompt_template=user_prompt_template,
+        chat_prompt=chat_prompt,
     )
diff --git a/examples/flows/standard/intent-copilot/flow.dag.yaml b/examples/flows/standard/intent-copilot/flow.dag.yaml
@@ -1,29 +1,28 @@
-$schema: https://azuremlschemas.azureedge.net/promptflow/latest/Flow.schema.json
 inputs:
+  history:
+    type: string
   customer_info:
     type: string
-  history:
-    type: list
 outputs:
   output:
     type: string
     reference: ${extract_intent.output}
 nodes:
-- name: user_prompt_template
+- name: chat_prompt
   type: prompt
   source:
     type: code
     path: user_intent_zero_shot.jinja2
-  inputs: {}  # Please enter the inputs of this node
+  inputs:  # Please check the generated prompt inputs
+    history: ${inputs.history}
+    customer_info: ${inputs.customer_info}
 - name: extract_intent
   type: python
   source:
     type: code
     path: extract_intent_tool.py
   inputs:
-    customer_info: ${inputs.customer_info}
-    history: ${inputs.history}
-    user_prompt_template: ${user_prompt_template.output}
+    chat_prompt: ${chat_prompt.output}
     connection: custom_connection
 environment:
     python_requirements_txt: requirements.txt
diff --git a/examples/flows/standard/intent-copilot/intent.py b/examples/flows/standard/intent-copilot/intent.py
@@ -1,11 +1,12 @@
 import os
 import pip
-from langchain import LLMChain
 from langchain.chat_models import AzureChatOpenAI
 from langchain.prompts.chat import ChatPromptTemplate, HumanMessagePromptTemplate
+from langchain.prompts.prompt import PromptTemplate
+from langchain.schema import HumanMessage
 
 
-def extract_intent(customer_info: str, history: list, user_prompt_template: str):
+def extract_intent(chat_prompt: str):
     if "AZURE_OPENAI_API_KEY" not in os.environ:
         # load environment variables from .env file
         try:
@@ -17,10 +18,6 @@ def extract_intent(customer_info: str, history: list, user_prompt_template: str)
 
         load_dotenv()
 
-    chat_history_text = "\n".join(
-        [message["role"] + ": " + message["content"] for message in history]
-    )
-
     chat = AzureChatOpenAI(
         deployment_name=os.environ["CHAT_DEPLOYMENT_NAME"],
         openai_api_key=os.environ["AZURE_OPENAI_API_KEY"],
@@ -29,15 +26,23 @@ def extract_intent(customer_info: str, history: list, user_prompt_template: str)
         openai_api_version="2023-07-01-preview",
         temperature=0,
     )
+    reply_message = chat([HumanMessage(content=chat_prompt)])
+    return reply_message.content
 
-    chat_prompt_template = ChatPromptTemplate.from_messages(
-        [HumanMessagePromptTemplate.from_template(user_prompt_template)]
-    )
 
-    chain = LLMChain(llm=chat, prompt=chat_prompt_template)
+def generate_prompt(customer_info: str, history: list, user_prompt_template: str):
 
-    reply = chain.run(customer_info=customer_info, chat_history=chat_history_text)
-    return reply
+    chat_history_text = "\n".join(
+        [message["role"] + ": " + message["content"] for message in history]
+    )
+
+    prompt_template = PromptTemplate.from_template(user_prompt_template)
+    chat_prompt_template = ChatPromptTemplate.from_messages(
+        [
+            HumanMessagePromptTemplate(prompt=prompt_template)
+        ]
+    )
+    return chat_prompt_template.format_prompt(customer_info=customer_info, chat_history=chat_history_text).to_string()
 
 
 if __name__ == "__main__":
@@ -55,9 +60,8 @@ def extract_intent(customer_info: str, history: list, user_prompt_template: str)
 
     # each test
     for item in data:
-        reply = extract_intent(
-            item["customer_info"], item["history"], user_prompt_template
-        )
+        chat_prompt = generate_prompt(item["customer_info"], item["history"], user_prompt_template)
+        reply = extract_intent(chat_prompt)
         print("=====================================")
         # print("Customer info: ", item["customer_info"])
         # print("+++++++++++++++++++++++++++++++++++++")

diff --git a/examples/flows/standard/intent-copilot/user_intent_zero_shot.jinja2 b/examples/flows/standard/intent-copilot/user_intent_zero_shot.jinja2
@@ -1,12 +1,4 @@
-You are given a list of orders with item_numbers from a customer and a statement from the customer. It is your job to identify
-
-the intent that the customer has with their statement. Possible intents can be:
-
-"product return", "product exchange", "general question", "product question", "other".
-
-
-
-
+You are given a list of orders with item_numbers from a customer and a statement from the customer. It is your job to identify the intent that the customer has with their statement. Possible intents can be: "product return", "product exchange", "general question", "product question", "other".
 
 In triple backticks below is the customer information and a list of orders.
 
@@ -16,20 +8,14 @@ In triple backticks below is the customer information and a list of orders.
 
 ```
 
-
-
-
 In triple backticks below are the is the chat history with customer statements and replies from the customer service agent:
 
 ```
 
-{{chat_history}}
+{{history}}
 
 ```
 
-
-
-
 What is the customer's `intent:` here?
 
 "product return", "exchange product", "general question", "product question" or "other"?

diff --git a/examples/requirements.txt b/examples/requirements.txt
@@ -1,6 +1,6 @@
 # remove when we publish to pypi
 --extra-index-url https://azuremlsdktestpypi.azureedge.net/promptflow/
-promptflow[azure]==0.0.102528530
+promptflow[azure]==0.0.102612974
 promptflow-tools==0.1.0.b4
 python-dotenv
 langchain