unleash client

.gitea/workflows/deploy.yml

@@ -1,7 +1,7 @@
 name: Create Blog Article if new notes exist
 on:
     schedule:
-        - cron: "15 18 * * *"
+        - cron: "15 3 * * *"
     push:
         branches:
             - master

requirements.txt

@@ -6,3 +6,4 @@ chromadb
 langchain-ollama
 PyJWT
 dotenv
+UnleashClient

src/ai_generators/ollama_md_generator.py

@@ -26,7 +26,7 @@ class OllamaGenerator:
         self.llm = ChatOllama(model=self.ollama_model, temperature=0.6, top_p=0.5) #This  is the level head in the room
         self.prompt_inject = f"""
             You are a journalist, Software Developer and DevOps expert
-            writing a 5000 word draft blog article for other tech enthusiasts.
+            writing a 3000 word draft blog article for other tech enthusiasts.
             You like to use almost no code examples and prefer to talk
             in a light comedic tone. You are also Australian
             As this person write this blog as a markdown document.
@@ -71,8 +71,8 @@ class OllamaGenerator:
             top_k = int(random.uniform(30, 80))
             agent_llm = ChatOllama(model=model, temperature=temp, top_p=top_p, top_k=top_k)
             messages = [
-                ("system", "You are a creative writer specialising in writing about technology"),
-                ("human", self.prompt_inject )
+                ("system", self.prompt_inject),
+                ("human", "make the blog post in a format to be edited easily" )
             ]
             response = agent_llm.invoke(messages)
             # self.response = self.ollama_client.chat(model=model,
@@ -119,10 +119,10 @@ class OllamaGenerator:
 
     def generate_markdown(self) -> str:
 
-        prompt_human = f"""
+        prompt_system = f"""
             You are an editor taking information from {len(self.agent_models)} Software
             Developers and Data experts
-            writing a 5000 word blog article. You like when they use almost no code examples.
+            writing a 3000 word blog article. You like when they use almost no code examples.
             You are also Australian. The content may have light comedic elements,
             you are more professional and will attempt to tone these down
             As this person produce the final version of this blog as a markdown document
@@ -134,13 +134,13 @@ class OllamaGenerator:
                 <blog>{self.content}</blog>
             """
         try:
-            query_embed = self.ollama_client.embed(model=self.embed_model, input=prompt_human)['embeddings']
+            query_embed = self.ollama_client.embed(model=self.embed_model, input=prompt_system)['embeddings']
             collection = self.load_to_vector_db()
             collection_query = collection.query(query_embeddings=query_embed, n_results=100)
             print("Showing pertinent info from drafts used in final edited edition")
             pertinent_draft_info = '\n\n'.join(collection.query(query_embeddings=query_embed, n_results=100)['documents'][0])
             #print(pertinent_draft_info)
-            prompt_system = f"""Generate the final, 5000 word, draft of the blog using this information from the drafts: <context>{pertinent_draft_info}</context>
+            prompt_human = f"""Generate the final, 3000 word, draft of the blog using this information from the drafts: <context>{pertinent_draft_info}</context>
                             - Only output in markdown, do not wrap in markdown tags, Only provide the draft not a commentary on the drafts in the context
                             """
             print("Generating final document")

unleash_client.py

@@ -0,0 +1,13 @@
+from UnleashClient import UnleashClient
+import asyncio
+
+client = UnleashClient(
+    url="http://192.168.178.160:30007/api/",
+    app_name="unleash-onboarding-python",
+    custom_headers={'Authorization': 'default:development.6uQIie4GdslTxgYAWVu35sRBjjBMPRRKw6vBj6mFsgFfvdXuy73GgLQg'}) # in production use environment variable
+
+client.initialize_client()
+
+while True:
+    print(client.is_enabled("crew_ai_integration"))
+    asyncio.run(asyncio.sleep(1))