Add issue action

Signed-off-by: Shuyang Xin <[email protected]>

.github/workflows/issue_answer.yml

@@ -0,0 +1,38 @@
+name: LangChain Issue Processor
+
+on:
+  issues:
+    types: [opened, reopened]
+
+jobs:
+  process-issue:
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v2
+      - name: Set up Python
+        uses: actions/setup-python@v2
+        with:
+          python-version: '3.x'
+      - name: Install dependencies
+        run: |
+          pip install langchain openai langchain[docarray]
+      - name: Run process.py
+        env:
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+          OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
+        run: |
+          SCRIPT_OUTPUT=$(python ai/issue_answer.py --github-token $GITHUB_TOKEN --openai-token $OPENAI_API_KEY --issue-number ${{ github.event.issue.number }})
+          echo "$SCRIPT_OUTPUT"
+          echo "SCRIPT_OUTPUT=$SCRIPT_OUTPUT" >> $GITHUB_ENV
+          echo "${{env.SCRIPT_OUTPUT}}"
+      - name: comment result
+        uses: actions/github-script@v5        
+        with:
+          script: |
+            github.rest.issues.createComment({
+              issue_number: context.issue.number,
+              owner: context.repo.owner,
+              repo: context.repo.repo,
+              body: `${{env.SCRIPT_OUTPUT}}`,
+            });

.github/workflows/issue_label.yml

@@ -0,0 +1,37 @@
+name: LangChain Label Processor
+
+on:
+  issues:
+    types: [opened, reopened]
+
+jobs:
+  process-issue:
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v2
+      - name: Set up Python
+        uses: actions/setup-python@v2
+        with:
+          python-version: '3.x'
+      - name: Install dependencies
+        run: |
+          pip install langchain openai
+      - name: Run process.py
+        env:
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+          OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
+        run: |
+          LABEL_OUTPUT=$(python ai/label_answer.py --github-token $GITHUB_TOKEN --openai-token $OPENAI_API_KEY --issue-number ${{ github.event.issue.number }}) 
+          echo "LABEL_OUTPUT=$LABEL_OUTPUT" >> $GITHUB_ENV
+      - name: comment result
+        uses: actions/github-script@v5
+        with:
+          script: |
+            const labelsToAdd = '${{ env.LABEL_OUTPUT }}'.replace(/'/g, '').split(',');
+            github.rest.issues.addLabels({
+              issue_number: context.issue.number,
+              owner: context.repo.owner,
+              repo: context.repo.repo,
+              labels: labelsToAdd,
+            });

ai/issue_answer.py

@@ -0,0 +1,59 @@
+from langchain.document_loaders.github import GitHubIssuesLoader
+from langchain.chat_models import ChatOpenAI
+from langchain.prompts import ChatPromptTemplate
+from langchain.schema.output_parser import StrOutputParser
+from langchain.schema.runnable import RunnableParallel, RunnablePassthrough
+from langchain.vectorstores import DocArrayInMemorySearch
+from langchain.embeddings import OpenAIEmbeddings
+import argparse
+
+def parse_arguments():
+    parser = argparse.ArgumentParser(description="Your program description.")
+    parser.add_argument("--github-token", required=True, help="GitHub access token")
+    parser.add_argument("--openai-token", required=True, help="OpenAI API key")
+    parser.add_argument("--issue-number", required=True, help="Github Issue Number")
+    return parser.parse_args()
+
+# Parse command line arguments
+args = parse_arguments()
+
+# Create an instance of the GitHubIssuesLoader class
+loader = GitHubIssuesLoader(
+    repo="XinShuYang/antrea",
+    owner="XinShuYang",
+    access_token=args.github_token,
+    include_prs=False,
+)
+
+# Load the issues of the repository
+issues = loader.load()
+
+issue_data = []
+# Print the title and body of each issue
+for issue in issues:
+    if issue.metadata["number"] == args.issue_number :
+        issue_data.append({'title': issue.metadata['title'], 'body': issue.page_content})
+
+vectorstore = DocArrayInMemorySearch.from_texts(
+    ["The random error of layer can be preemptively avoided by adding checksum verification", "When local storage is depleted, Docker won't be able to load images properly","Not only the unnecessary antrea-agent, antea-cni binaries, but also the whole OVS, iptables, suricata dependecies can be got rid of from antrea-controller image"],
+    embedding=OpenAIEmbeddings(openai_api_key=args.openai_token),
+)
+retriever = vectorstore.as_retriever()
+
+template = """Analyze and give the solution of the github issue based only on the following context:
+    {context}
+
+GITHUB ISSUE: {question}
+    """
+prompt = ChatPromptTemplate.from_template(template)
+model = ChatOpenAI(model_name="gpt-3.5-turbo", openai_api_key=args.openai_token)
+output_parser = StrOutputParser()
+setup_and_retrieval = RunnableParallel(
+    {"context": retriever, "question": RunnablePassthrough()}
+)
+
+chain = setup_and_retrieval | prompt | model | output_parser
+
+result=chain.invoke(issue_data)
+
+print(result)

ai/label_answer.py

@@ -0,0 +1,51 @@
+from langchain.document_loaders.github import GitHubIssuesLoader
+from langchain.chat_models import ChatOpenAI
+from langchain.prompts import ChatPromptTemplate
+from langchain.schema.output_parser import StrOutputParser
+from langchain.schema.runnable import RunnableParallel, RunnablePassthrough
+
+import argparse
+
+def parse_arguments():
+    parser = argparse.ArgumentParser(description="Your program description.")
+    parser.add_argument("--github-token", required=True, help="GitHub access token")
+    parser.add_argument("--openai-token", required=True, help="OpenAI API key")
+    parser.add_argument("--issue-number", required=True, help="Github Issue Number")
+    return parser.parse_args()
+
+# Parse command line arguments
+args = parse_arguments()
+
+# Create an instance of the GitHubIssuesLoader class
+loader = GitHubIssuesLoader(
+    repo="XinShuYang/antrea",
+    owner="XinShuYang",
+    access_token=args.github_token,
+    include_prs=False,
+)
+
+# Load the issues of the repository
+issues = loader.load()
+
+issue_data = []
+# Print the title and body of each issue
+for issue in issues:
+    if issue.metadata["number"] == args.issue_number :
+        issue_data.append({'title': issue.metadata['title'], 'body': issue.page_content})
+
+template = """You are an assistant for Antrea, a software that provides networking and security services for a Kubernetes cluster. Please only output the classification results, with the optional word list for classification results [ 'api', 'arm', 'agent', 'antctl', 'cni', 'octant-plugin', 'flow-visibility', 'monitoring', 'multi-cluster', 'interface', 'network-policy', 'ovs', 'provider', 'proxy', 'test', 'transit', 'security', 'build-release', 'linux', 'windows']. You can only select one or more words from these words as the output result, which are enclosed in quotation marks and connected by commas.:
+    {context}
+
+    """
+prompt = ChatPromptTemplate.from_template(template)
+model = ChatOpenAI(model_name="ft:gpt-3.5-turbo-1106:hydsoft::8Mu1CgrH", openai_api_key=args.openai_token)
+output_parser = StrOutputParser()
+setup_and_retrieval = RunnableParallel(
+    {"context": RunnablePassthrough()}
+)
+
+chain = setup_and_retrieval | prompt | model | output_parser
+
+result=chain.invoke(issue_data)
+
+print(result)