Feature/user agent metrics (#8)

* upgraded dependecies

* Added user agent

devai-api/app/routes.py

@@ -28,15 +28,17 @@
 from langchain_community.agent_toolkits.gitlab.toolkit import GitLabToolkit
 from langchain_community.utilities.gitlab import GitLabAPIWrapper
 from langchain_google_vertexai import ChatVertexAI
-
+from google.cloud.aiplatform import telemetry
 from vertexai.generative_models import GenerativeModel
 
+USER_AGENT = 'cloud-solutions/genai-for-developers-v1'
 model_name="gemini-1.5-pro-preview-0409"
 
-llm = ChatVertexAI(model_name=model_name,
-    convert_system_message_to_human=True,
-    temperature=0.2,
-    max_output_tokens=4096)
+with telemetry.tool_context_manager(USER_AGENT):
+    llm = ChatVertexAI(model_name=model_name,
+        convert_system_message_to_human=True,
+        temperature=0.2,
+        max_output_tokens=4096)
 
 gitlab = GitLabAPIWrapper()
 toolkit = GitLabToolkit.from_gitlab_api_wrapper(gitlab)
@@ -63,7 +65,8 @@ async def root():
 @routes.get("/test")
 async def test():
     """Test endpoint"""
-    code_chat = code_chat_model.start_chat()
+    with telemetry.tool_context_manager(USER_AGENT):
+        code_chat = code_chat_model.start_chat()
     response = code_chat.send_message("Tell me about Google Gemini 1.5 capabilities")
     print(f"Response from Model:\n{response.text}\n")
     return {"message": response.text}
@@ -81,11 +84,11 @@ async def generate_handler(request: Request, prompt: str = Body(embed=True)):
     REQUIREMENTS:
     {prompt}
     """
-
-    code_chat = code_chat_model.start_chat()
+    with telemetry.tool_context_manager(USER_AGENT):
+        code_chat = code_chat_model.start_chat()
     response = code_chat.send_message(instructions)
     print(f"Response from Model:\n{response.text}\n")
-    # GitLab Agent Call
+
     # resp_text = response.candidates[0].content.parts[0].text
 
     # pr_prompt = f"""Create GitLab merge request using provided details below.

devai-api/requirements.txt

@@ -1,5 +1,5 @@
 fastapi==0.109.2
-google-cloud-aiplatform==1.47.0
+google-cloud-aiplatform==1.48.0
 google-auth==2.27.0
 itsdangerous==2.1.2
 jinja2==3.1.3

outer-loop-cli/src/devai/commands/gitlab.py

@@ -20,10 +20,11 @@
 from langchain_community.utilities.gitlab import GitLabAPIWrapper
 from google.cloud.aiplatform import telemetry
 
-USER_AGENT = 'cloud-solutions/genai-outer-loop-devai'
+USER_AGENT = 'cloud-solutions/genai-for-developers-v1'
+model_name="gemini-1.5-pro-preview-0409"
 
 with telemetry.tool_context_manager(USER_AGENT):
-  llm = ChatVertexAI(model_name="gemini-pro",
+  llm = ChatVertexAI(model_name=model_name,
                    convert_system_message_to_human=True,
                    project=os.environ["PROJECT_ID"],
                    location=os.environ["LOCATION"])

outer-loop-cli/src/devai/commands/jira.py

@@ -22,12 +22,16 @@
 from langchain_community.utilities.jira import JiraAPIWrapper
 from langchain_google_vertexai import ChatVertexAI
 from jira import JIRA
+from google.cloud.aiplatform import telemetry
 
+USER_AGENT = 'cloud-solutions/genai-for-developers-v1'
+model_name="gemini-1.5-pro-preview-0409"
 
-llm = ChatVertexAI(model_name="gemini-pro",
-                   convert_system_message_to_human=True,
-                   project=os.environ["PROJECT_ID"],
-                   location=os.environ["LOCATION"])
+with telemetry.tool_context_manager(USER_AGENT):
+    llm = ChatVertexAI(model_name=model_name,
+                    convert_system_message_to_human=True,
+                    project=os.environ["PROJECT_ID"],
+                    location=os.environ["LOCATION"])
 
 jira = JiraAPIWrapper()
 toolkit = JiraToolkit.from_jira_api_wrapper(jira)

outer-loop-cli/src/devai/commands/review.py

@@ -16,17 +16,16 @@
 import click
 from devai.util.file_processor import format_files_as_string
 from vertexai.generative_models import GenerativeModel, ChatSession
+from google.cloud.aiplatform import telemetry
+
+USER_AGENT = 'cloud-solutions/genai-for-developers-v1'
+model_name="gemini-1.5-pro-preview-0409"
 
 # Uncomment after configuring JIRA and GitLab env variables - see README.md for details
 
 # from devai.commands.jira import create_jira_issue
 # from devai.commands.gitlab import create_gitlab_issue_comment
 
-parameters = {
-    "max_output_tokens": 2048,
-    "temperature": 0.2
-}
-
 @click.command(name='code')
 @click.option('-c', '--context', required=False, type=str, default="")
 def code(context):
@@ -58,8 +57,9 @@ def code(context):
     # Load files as text into source variable
     source=source.format(format_files_as_string(context))
 
-    code_chat_model = GenerativeModel("gemini-1.0-pro")
-    code_chat = code_chat_model.start_chat()
+    code_chat_model = GenerativeModel(model_name)
+    with telemetry.tool_context_manager(USER_AGENT):
+        code_chat = code_chat_model.start_chat()
     code_chat.send_message(qry)
     response = code_chat.send_message(source)
 
@@ -104,8 +104,9 @@ def performance(context):
     # Load files as text into source variable
     source=source.format(format_files_as_string(context))
 
-    code_chat_model = GenerativeModel("gemini-1.0-pro")
-    code_chat = code_chat_model.start_chat()
+    code_chat_model = GenerativeModel(model_name)
+    with telemetry.tool_context_manager(USER_AGENT):
+        code_chat = code_chat_model.start_chat()
     code_chat.send_message(qry)
     response = code_chat.send_message(source)
 
@@ -139,8 +140,9 @@ def security(context):
     # Load files as text into source variable
     source=source.format(format_files_as_string(context))
 
-    code_chat_model = GenerativeModel("gemini-1.0-pro")
-    code_chat = code_chat_model.start_chat()
+    code_chat_model = GenerativeModel(model_name)
+    with telemetry.tool_context_manager(USER_AGENT):
+        code_chat = code_chat_model.start_chat()
     code_chat.send_message(qry)
     response = code_chat.send_message(source)
 

outer-loop-cli/src/requirements.txt

@@ -1,5 +1,5 @@
 click==8.1.7
-google-cloud-aiplatform==1.42.1
+google-cloud-aiplatform==1.48.0
 jira==3.6.0
 python-gitlab==4.4.0
 langchain==0.1.8