Setting proxy

apps/browser/sitefind.py

@@ -1,13 +1,17 @@
-import hal9 as h9
-from groq import Groq
+from openai import OpenAI
 
 system_prompt = """
 Only reply with website urls that best match the task from the user prompt.
 If you don't know a website use https://www.google.com/search?q=query and 
 replace query with a reasonable search query for the user task
 """
 
+client = OpenAI(
+    base_url="http://localhost:5000/proxy/server=https://api.groq.com/openai/v1",
+    api_key = "h9"
+)
+
 def site_find(prompt):
   messages = [{ "role": "system", "content":  system_prompt}, { "role": "user", "content": prompt }]
-  completion = Groq().chat.completions.create(model = "llama3-70b-8192", messages = messages)
+  completion = client.chat.completions.create(model = "llama3-70b-8192", messages = messages)
   return completion.choices[0].message.content

apps/browser/siteuse.py

@@ -32,6 +32,11 @@
 Only reply with a code block for python code.
 """
 
+client = OpenAI(
+    base_url="https://api.hal9.com/proxy/server=https://api.openai.com/v1/",
+    api_key = "h9" 
+)
+
 def site_use(prompt, current, elements):
   elements_str = "\n".join([f"{item['text']}: {item['query']}" for item in elements])
 
@@ -47,7 +52,7 @@ def site_use(prompt, current, elements):
     """ }
   ]
 
-  completion = OpenAI().chat.completions.create(model = "gpt-4", messages = messages)
+  completion = client.chat.completions.create(model = "gpt-4", messages = messages)
   content = completion.choices[0].message.content
   extracted = h9.extract(content, language = "*")
   if not extracted or len(extracted) == 0:

apps/hal9/app.py

@@ -2,7 +2,7 @@
 import os
 import hal9 as h9
 import json
-import openai
+from openai import OpenAI
 
 from tools.calculator import calculate
 from tools.game import build_game
@@ -17,7 +17,12 @@
 
 MODEL = "llama3-groq-70b-8192-tool-use-preview"
 def run(messages, tools):
-  return Groq().chat.completions.create(
+  client = OpenAI(
+    base_url="http://localhost:5000/proxy/server=https://api.groq.com/openai/v1",
+    api_key = "h9"
+  )
+
+  return client.chat.completions.create(
     model = MODEL,
     messages = messages,
     temperature = 0,

apps/hal9/tools/game.py

@@ -5,9 +5,9 @@
 import time
 
 client = openai.AzureOpenAI(
-    azure_endpoint='https://openai-hal9.openai.azure.com/',
-    api_key=os.environ['OPENAI_AZURE'],
-    api_version='2023-05-15',
+   azure_endpoint = 'http://localhost:5000/proxy/server=https://openai-hal9.openai.azure.com/',
+   api_key = 'h1',
+   api_version = '2023-05-15'
 )
 
 def build_game(user_game_request):

apps/hal9/tools/hal9.py

@@ -1,4 +1,4 @@
-from groq import Groq
+from openai import OpenAI
 import os
 import hal9 as h9
 import json
@@ -15,7 +15,17 @@ def hal9_reply(prompt):
     {"role": "user", "content": prompt}
   ]
 
-  stream = Groq().chat.completions.create(model = "llama3-70b-8192", messages = messages, temperature = 0, seed = 1, stream = True)
+  client = OpenAI(
+    base_url="http://localhost:5000/proxy/server=https://api.groq.com/openai/v1",
+    api_key = "h9"
+    )
+
+  stream = client.chat.completions.create(
+    model = "llama3-70b-8192", 
+    messages = messages, 
+    temperature = 0, 
+    seed = 1, 
+    stream = True)
 
   response = ""
   for chunk in stream:

apps/hal9/tools/image_analyzer.py

@@ -8,9 +8,9 @@ def image_analyzer(image_url, prompt):
     'prompt' = description of what the user wants to analyze in the image. If the user does not specify, it should default to "What's in this image?"
 """
     client = openai.AzureOpenAI(
-    azure_endpoint = 'https://openai-hal9.openai.azure.com/',
-    api_key = os.environ['OPENAI_AZURE'],
-    api_version = '2024-02-15-preview',
+        azure_endpoint = 'http://localhost:5000/proxy/server=https://openai-hal9.openai.azure.com/',
+        api_key = 'h1',
+        api_version = '2023-05-15'
     )
 
     response = client.chat.completions.create(

apps/hal9/tools/streamlit.py

@@ -9,9 +9,9 @@ def build_streamlit(prompt):
     'prompt' = with user change or requirements
   """
   client = openai.AzureOpenAI(
-    azure_endpoint = 'https://openai-hal9.openai.azure.com/',
-    api_key = os.environ['OPENAI_AZURE'],
-    api_version = '2023-05-15',
+    azure_endpoint = 'http://localhost:5000/proxy/server=https://openai-hal9.openai.azure.com/',
+    api_key = 'h1',
+    api_version = '2023-05-15'
   )
 
   system = """

apps/hal9/tools/website.py

@@ -9,9 +9,9 @@ def build_website(prompt):
     'prompt' with user change or requirements
   """
   client = openai.AzureOpenAI(
-    azure_endpoint = 'https://openai-hal9.openai.azure.com/',
-    api_key = os.environ['OPENAI_AZURE'],
-    api_version = '2023-05-15',
+    azure_endpoint = 'http://localhost:5000/proxy/server=https://openai-hal9.openai.azure.com/',
+    api_key = 'h1',
+    api_version = '2023-05-15'
   )
 
   system = """You can build html applications for user requests. Your replies can include markdown code blocks but they must include a filename parameter after the language. For example,

apps/swarm/app.py

@@ -1,7 +1,9 @@
-import json
-import hal9 as h9
 from dotenv import load_dotenv
-from swarm import Swarm, Agent, repl
+import hal9 as h9
+import json
+from openai import OpenAI
+from swarm import Swarm, Agent
+
 from recomendations import book_recommendation, comic_recommendation, movie_recommendation
 
 load_dotenv()
@@ -42,7 +44,12 @@ def transfer_to_movie_expert():
     functions=[transfer_to_book_expert, transfer_to_comic_expert, transfer_to_movie_expert],
 )
 
-client = Swarm()
+client = OpenAI(
+    base_url="http://localhost:5000/proxy/server=https://api.anthropic.com/v1/messages",
+    api_key = "h9"
+) 
+swarm = Swarm(client = client)
+
 messages = h9.load('messages', [])
 
 agents = {'Receptionist': receptionist,
@@ -53,7 +60,7 @@ def transfer_to_movie_expert():
 user_input = input()
 messages.append({"role": "user", "content": user_input})
 
-response = client.run(
+response = swarm.run(
     agent=agent,
     messages=messages
 )