Cli bug fixes (loading human/persona text, azure setup, local setup) (#…

…222) * mark depricated API section * add readme * add readme * add readme * add readme * add readme * add readme * add readme * add readme * add readme * CLI bug fixes for azure * check azure before running * Update README.md * Update README.md * bug fix with persona loading * revert readme * remove print
letta-ai · Oct 31, 2023 · 89f0a69 · 89f0a69
1 parent d7e021b
commit 89f0a69
Show file tree

Hide file tree

Showing 4 changed files with 54 additions and 18 deletions.
diff --git a/memgpt/cli/cli.py b/memgpt/cli/cli.py
@@ -26,6 +26,10 @@
 from memgpt.constants import MEMGPT_DIR
 from memgpt.agent import AgentAsync
 from memgpt.embeddings import embedding_model
+from memgpt.openai_tools import (
+    configure_azure_support,
+    check_azure_embeddings,
+)
 
 
 def run(
@@ -135,14 +139,19 @@ def run(
             agent_config.preset,
             agent_config,
             agent_config.model,
-            agent_config.persona,
-            agent_config.human,
+            utils.get_persona_text(agent_config.persona),
+            utils.get_human_text(agent_config.human),
             memgpt.interface,
             persistence_manager,
         )
 
     # start event loop
     from memgpt.main import run_agent_loop
 
+    # setup azure if using
+    # TODO: cleanup this code
+    if config.model_endpoint == "azure":
+        configure_azure_support()
+
     loop = asyncio.get_event_loop()
     loop.run_until_complete(run_agent_loop(memgpt_agent, first, no_verify, config))  # TODO: add back no_verify
diff --git a/memgpt/cli/cli_config.py b/memgpt/cli/cli_config.py
@@ -37,10 +37,10 @@ def configure():
     use_azure_deployment_ids = False
     if use_azure:
         # search for key in enviornment
-        azure_key = os.getenv("AZURE_API_KEY")
-        azure_endpoint = (os.getenv("AZURE_ENDPOINT"),)
-        azure_version = (os.getenv("AZURE_VERSION"),)
-        azure_deployment = (os.getenv("AZURE_OPENAI_DEPLOYMENT"),)
+        azure_key = os.getenv("AZURE_OPENAI_KEY")
+        azure_endpoint = os.getenv("AZURE_OPENAI_ENDPOINT")
+        azure_version = os.getenv("AZURE_OPENAI_VERSION")
+        azure_deployment = os.getenv("AZURE_OPENAI_DEPLOYMENT")
         azure_embedding_deployment = os.getenv("AZURE_OPENAI_EMBEDDING_DEPLOYMENT")
 
         if all([azure_key, azure_endpoint, azure_version]):
@@ -66,7 +66,7 @@ def configure():
     endpoint_options = []
     if os.getenv("OPENAI_API_BASE") is not None:
         endpoint_options.append(os.getenv("OPENAI_API_BASE"))
-    if os.getenv("AZURE_ENDPOINT") is not None:
+    if use_azure:
         endpoint_options += ["azure"]
     if use_openai:
         endpoint_options += ["openai"]

diff --git a/memgpt/config.py b/memgpt/config.py
@@ -110,8 +110,10 @@ def load(cls) -> "MemGPTConfig":
                 azure_key = config.get("azure", "key")
                 azure_endpoint = config.get("azure", "endpoint")
                 azure_version = config.get("azure", "version")
-                azure_deployment = config.get("azure", "deployment")
-                azure_embedding_deployment = config.get("azure", "embedding_deployment")
+                azure_deployment = config.get("azure", "deployment") if config.has_option("azure", "deployment") else None
+                azure_embedding_deployment = (
+                    config.get("azure", "embedding_deployment") if config.has_option("azure", "embedding_deployment") else None
+                )
 
             embedding_model = config.get("embedding", "model")
             embedding_dim = config.getint("embedding", "dim")
@@ -167,8 +169,9 @@ def save(self):
             config.set("azure", "key", self.azure_key)
             config.set("azure", "endpoint", self.azure_endpoint)
             config.set("azure", "version", self.azure_version)
-            config.set("azure", "deployment", self.azure_deployment)
-            config.set("azure", "embedding_deployment", self.azure_embedding_deployment)
+            if self.azure_deployment:
+                config.set("azure", "deployment", self.azure_deployment)
+                config.set("azure", "embedding_deployment", self.azure_embedding_deployment)
 
         # embeddings
         config.add_section("embedding")

diff --git a/memgpt/utils.py b/memgpt/utils.py
@@ -20,6 +20,8 @@
 from llama_index import set_global_service_context, ServiceContext, VectorStoreIndex, load_index_from_storage, StorageContext
 from llama_index.embeddings import OpenAIEmbedding
 
+from memgpt.embeddings import embedding_model
+
 
 def count_tokens(s: str, model: str = "gpt-4") -> int:
     encoding = tiktoken.encoding_for_model(model)
@@ -398,13 +400,11 @@ def get_index(name, docs):
 
     # read embedding confirguration
     # TODO: in the future, make an IngestData class that loads the config once
-    # config = MemGPTConfig.load()
-    # chunk_size = config.embedding_chunk_size
-    # model = config.embedding_model  # TODO: actually use this
-    # dim = config.embedding_dim  # TODO: actually use this
-    # embed_model = OpenAIEmbedding()
-    # service_context = ServiceContext.from_defaults(embed_model=embed_model, chunk_size=chunk_size)
-    # set_global_service_context(service_context)
+    config = MemGPTConfig.load()
+    embed_model = embedding_model(config)
+    chunk_size = config.embedding_chunk_size
+    service_context = ServiceContext.from_defaults(embed_model=embed_model, chunk_size=chunk_size)
+    set_global_service_context(service_context)
 
     # index documents
     index = VectorStoreIndex.from_documents(docs)
@@ -481,3 +481,27 @@ def list_persona_files():
     user_added = os.listdir(user_dir)
     user_added = [os.path.join(user_dir, f) for f in user_added]
     return memgpt_defaults + user_added
+
+
+def get_human_text(name: str):
+    for file_path in list_human_files():
+        file = os.path.basename(file_path)
+        if f"{name}.txt" == file or name == file:
+            return open(file_path, "r").read().strip()
+    raise ValueError(f"Human {name} not found")
+
+
+def get_persona_text(name: str):
+    for file_path in list_persona_files():
+        file = os.path.basename(file_path)
+        if f"{name}.txt" == file or name == file:
+            return open(file_path, "r").read().strip()
+
+    raise ValueError(f"Persona {name} not found")
+
+
+def get_human_text(name: str):
+    for file_path in list_human_files():
+        file = os.path.basename(file_path)
+        if f"{name}.txt" == file or name == file:
+            return open(file_path, "r").read().strip()