Merge remote-tracking branch 'upstream/main'

installer/client/cli/utils.py

@@ -38,12 +38,11 @@ class Standalone:
         if args is None:
             args = type('Args', (), {})()
         env_file = os.path.expanduser(env_file)
+        self.client = None
         load_dotenv(env_file)
-        assert 'OPENAI_API_KEY' in os.environ, "Error: OPENAI_API_KEY not found in environment variables. Please run fabric --setup and add a key."
-        api_key = os.environ['OPENAI_API_KEY']
-        base_url = os.environ.get(
-            'OPENAI_BASE_URL', 'https://api.openai.com/v1/')
-        self.client = OpenAI(api_key=api_key, base_url=base_url)
+        if "OPENAI_API_KEY" in os.environ:
+            api_key = os.environ['OPENAI_API_KEY']
+            self.client = OpenAI(api_key=api_key)
         self.local = False
         self.config_pattern_directory = config_directory
         self.pattern = pattern
@@ -280,33 +279,26 @@ class Standalone:
     def fetch_available_models(self):
         gptlist = []
         fullOllamaList = []
-        claudeList = ['claude-3-opus-20240229',
-                      'claude-3-sonnet-20240229',
-                      'claude-3-haiku-20240307',
-                      'claude-2.1']
+        claudeList = ['claude-3-opus-20240229', 'claude-3-sonnet-20240229',
+                      'claude-3-haiku-20240307', 'claude-2.1']
+
         try:
-            models = [model.id.strip()
-                      for model in self.client.models.list().data]
+            if self.client:
+                models = [model.id.strip()
+                          for model in self.client.models.list().data]
+                if "/" in models[0] or "\\" in models[0]:
+                    gptlist = [item[item.rfind(
+                        "/") + 1:] if "/" in item else item[item.rfind("\\") + 1:] for item in models]
+                else:
+                    gptlist = [item.strip()
+                               for item in models if item.startswith("gpt")]
+                gptlist.sort()
         except APIConnectionError as e:
-            if getattr(e.__cause__, 'args', [''])[0] == "Illegal header value b'Bearer '":
-                print("Error: Cannot connect to the OpenAI API Server because the API key is not set. Please run fabric --setup and add a key.")
-
-            else:
-                print(
-                    f"Error: {e.message} trying to access {e.request.url}: {getattr(e.__cause__, 'args', [''])}")
-            sys.exit()
+            print("OpenAI API key not set. Skipping GPT models.")
         except Exception as e:
             print(f"Error: {getattr(e.__context__, 'args', [''])[0]}")
             sys.exit()
-        if "/" in models[0] or "\\" in models[0]:
-            # lmstudio returns full paths to models. Iterate and truncate everything before and including the last slash
-            gptlist = [item[item.rfind(
-                "/") + 1:] if "/" in item else item[item.rfind("\\") + 1:] for item in models]
-        else:
-            # Keep items that start with "gpt"
-            gptlist = [item.strip()
-                       for item in models if item.startswith("gpt")]
-        gptlist.sort()
+
         import ollama
         try:
             if self.args.remoteOllamaServer:
@@ -318,6 +310,7 @@ class Standalone:
                 fullOllamaList.append(model['name'])
         except:
             fullOllamaList = []
+
         return gptlist, fullOllamaList, claudeList
 
     def get_cli_input(self):

test.yaml

@@ -1,44 +1,44 @@
 framework: crewai
-topic: 'write me a 20 word essay on apples
+topic: 'give me the complete voting record of senator marco rubio
 
   '
 roles:
-  researcher:
-    backstory: Has an extensive background in conducting research using digital tools
-      to extract relevant information.
-    goal: Gather comprehensive information about apples
-    role: Researcher
+  data_researcher:
+    backstory: Skilled in using various data search tools to find accurate information.
+    goal: Gather relevant data on Senator Marco Rubio's voting record
+    role: Data Researcher
     tasks:
-      collect_information_on_apples:
-        description: Use digital tools to find credible sources of information on
-          apples covering history, types, and benefits.
-        expected_output: Collected data on apples, including historical background,
-          varieties, and health benefits.
+      data_collection:
+        description: Use provided search tools to collect voting records of Senator
+          Marco Rubio from different sources.
+        expected_output: A collection of CSV, XML or other data files containing the
+          required information.
     tools:
     - ''
-  analyst:
-    backstory: Expert in analyzing large volumes of data to identify the most relevant
-      and interesting facts.
-    goal: Analyze gathered information to distill key points
-    role: Analyst
+  data_processor:
+    backstory: Expert in processing and cleaning raw data, preparing it for analysis
+      or presentation.
+    goal: Process and format collected data into a readable output
+    role: Data Processor
     tasks:
-      synthesize_information:
-        description: Review the collected data and extract the most pertinent facts
-          about apples, focusing on uniqueness and impact.
-        expected_output: A summary highlighting key facts about apples, such as nutritional
-          benefits, global popularity, and cultural significance.
+      data_processing:
+        description: Clean and process the collected voting records into a structured
+          JSON format.
+        expected_output: A JSON file containing Senator Marco Rubio's complete voting
+          record.
     tools:
     - ''
-  writer:
-    backstory: Specializes in creating short, impactful pieces of writing that capture
-      the essence of the subject matter.
-    goal: Craft a concise and engaging essay on apples
-    role: Writer
+  presenter:
+    backstory: Skilled in extracting and summarizing information, presenting it in
+      a clear and concise format.
+    goal: Generate the final output for user consumption
+    role: Presenter
     tasks:
-      write_essay:
-        description: Based on the analyzed data, write a compelling 20-word essay
-          on apples that encapsulates their essence and significance.
-        expected_output: An engaging 20-word essay on apples.
+      presentation_creation:
+        description: Create an easily digestible presentation from the processed data
+          on Senator Marco Rubio's voting record.
+        expected_output: A well-structured text or multimedia output that highlights
+          key aspects of Senator Marco Rubio's voting history.
     tools:
     - ''
 dependencies: []