merge staging branch dev-0.5.0, supporting openai v1 and release 0.…

…5.0 (#80) * enable openai v1 in load.py (#78) * update version to 0.5.0 * update doc for openai v1 changes
log10-io · Jan 16, 2024 · ebd3e42 · ebd3e42
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diff --git a/README.md b/README.md
@@ -20,7 +20,12 @@ from log10.load import log10
 log10(openai)
 # all your openai calls are now logged
 ```
+For OpenAI v1, use `from log10.load import OpenAI` instead of `from openai import OpenAI`
+```python
+from log10.load import OpenAI
 
+client = OpenAI()
+```
 Access your LLM data at [log10.io](https://log10.io)
 
 
@@ -42,8 +47,12 @@ Log10 offers various integration methods, including a python LLM library wrapper
 Pick the one that works best for you.
 
 #### OpenAI
-Use library wrapper `log10(openai)` as shown [above](#-what-is-this).
-Full script [here](examples/logging/chatcompletion.py).
+| log10 ver| openai v0 | openai v1 |
+|----------|----------|----------|
+| 0.4 | `load(openai)` ✅ | ❌ |
+| 0.5 | `load(openai)` ✅ | `from log10.load import OpenAI` ✅ |
+
+**OpenAI v0** - Use library wrapper `log10(openai)`. Check out `examples/logging` in log10 version `0.4.6`.
 ```python
 import openai
 from log10.load import log10
@@ -52,12 +61,27 @@ log10(openai)
 # openai calls are now logged
 ```
 
-Use Log10 LLM abstraction.
-Full script [here](examples/logging/llm_abstraction.py#6-#14).
+**OpenAI v1**
+> NOTE: We added OpenAI v1 API support in log10 `0.5.0` release. `load.log10(openai)` still works for openai v1.
+```python
+from log10.load import OpenAI
+# from openai import OpenAI
+
+client = OpenAI()
+completion = client.completions.create(model="curie", prompt="Once upon a time")
+# All completions.create and chat.completions.create calls will be logged
+```
+Full script [here](examples/logging/completion.py).
+
+
+**Use Log10 LLM abstraction**
+
 ```python
 from log10.openai import OpenAI
+
 llm = OpenAI({"model": "gpt-3.5-turbo"}, log10_config=Log10Config())
 ```
+openai v1+ lib required. Full script [here](examples/logging/llm_abstraction.py#6-#14).
 
 #### Anthropic
 Use library wrapper `log10(anthropic)`.
@@ -74,6 +98,7 @@ Use Log10 LLM abstraction.
 Full script [here](examples/logging/llm_abstraction.py#16-#19).
 ```python
 from log10.anthropic import Anthropic
+
 llm = Anthropic({"model": "claude-2"}, log10_config=Log10Config())
 ```
 
@@ -85,12 +110,14 @@ Adding other providers is on the roadmap.
 **MosaicML** with LLM abstraction. Full script [here](/examples/logging/mosaicml_completion.py).
 ```python
 from log10.mosaicml import MosaicML
+
 llm = MosaicML({"model": "llama2-70b-chat/v1"}, log10_config=Log10Config())
 ```
 
 **Together** with LLM abstraction. Full script [here](/examples/logging/together_completion.py).
 ```python
 from log10.together import Together
+
 llm = Together({"model": "togethercomputer/llama-2-70b-chat"}, log10_config=Log10Config())
 ```
 
@@ -137,7 +164,7 @@ And provide the following configuration in either a `.env` file, or as environme
 
 ### 🧠🔁 Readiness for RLHF & self hosting
 
-Use your data and feedback from users to fine-tune custom models with RLHF with the option of building and deploying more reliable, accurate and efficient self-hosted models. 
+Use your data and feedback from users to fine-tune custom models with RLHF with the option of building and deploying more reliable, accurate and efficient self-hosted models.
 
 ### 👥🤝 Collaboration
 
@@ -158,7 +185,7 @@ Create flexible groups to share and collaborate over all of the above features
 You can find and run examples under folder `examples`, e.g. run a logging example:
 ```
 python examples/logging/chatcompletion.py
-``` 
+```
 
 Also you can run some end-to-end tests with [`xdocttest`](https://github.com/Erotemic/xdoctest) installed (`pip install xdoctest`).
 

diff --git a/examples/README.md b/examples/README.md
@@ -25,6 +25,7 @@ Can be run on `OpenAI` or `Anthropic`
 ## Logging (and debugging)
 
 ### OpenAI
+Requires openai >= "1.0.0"
 
 - `chatCompletion_async_vs_sync.py` Compare latencies when logging in async vs sync mode
 - `chatCompletion.py` Chat endpoint example

diff --git a/examples/logging/chatcompletion.py b/examples/logging/chatcompletion.py
@@ -1,15 +1,9 @@
-import os
+from log10.load import OpenAI
 
-import openai
 
-from log10.load import log10
+client = OpenAI()
 
-
-log10(openai)
-
-openai.api_key = os.getenv("OPENAI_API_KEY")
-
-completion = openai.ChatCompletion.create(
+completion = client.chat.completions.create(
     model="gpt-3.5-turbo",
     messages=[
         {

diff --git a/examples/logging/chatcompletion_async_vs_sync.py b/examples/logging/chatcompletion_async_vs_sync.py
diff --git a/examples/logging/chatcompletion_sync.py b/examples/logging/chatcompletion_sync.py
@@ -0,0 +1,27 @@
+from log10.load import OpenAI, log10_session
+
+
+client = OpenAI()
+
+with log10_session(tags=["log10-io/examples"]):
+    completion = client.chat.completions.create(
+        model="gpt-3.5-turbo",
+        messages=[
+            {
+                "role": "user",
+                "content": "Hello?",
+            },
+        ],
+    )
+    print(completion.choices[0].message)
+
+    completion = client.chat.completions.create(
+        model="gpt-3.5-turbo",
+        messages=[
+            {
+                "role": "user",
+                "content": "Hello again, are you there?",
+            },
+        ],
+    )
+    print(completion.choices[0].message)
diff --git a/examples/logging/completion.py b/examples/logging/completion.py
@@ -1,15 +1,9 @@
-import os
+from log10.load import OpenAI
 
-import openai
 
-from log10.load import log10
+client = OpenAI()
 
-
-log10(openai)
-
-openai.api_key = os.getenv("OPENAI_API_KEY")
-
-response = openai.Completion.create(
+response = client.completions.create(
     model="gpt-3.5-turbo-instruct",
     prompt="Write the names of all Star Wars movies and spinoffs along with the time periods in which they were set?",
     temperature=0,

diff --git a/examples/logging/completion_simple.py b/examples/logging/completion_simple.py
@@ -1,15 +1,9 @@
-import os
+from log10.load import OpenAI
 
-import openai
 
-from log10.load import log10
+client = OpenAI()
 
-
-log10(openai, DEBUG_=True, USE_ASYNC_=False)
-
-openai.api_key = os.getenv("OPENAI_API_KEY")
-
-response = openai.Completion.create(
+response = client.completions.create(
     model="gpt-3.5-turbo-instruct",
     prompt="What is 2+2?",
     temperature=0,

diff --git a/examples/logging/get_url.py b/examples/logging/get_url.py
@@ -1,21 +1,12 @@
-import os
+from log10.load import OpenAI, log10_session
 
-import openai
-from langchain.llms import OpenAI
 
-from log10.load import log10, log10_session
-
-
-log10(openai)
-
-openai.api_key = os.getenv("OPENAI_API_KEY")
-
-llm = OpenAI(temperature=0.9, model_name="gpt-3.5-turbo-instruct")
+client = OpenAI()
 
 with log10_session() as session:
     print(session.last_completion_url())
 
-    response = openai.Completion.create(
+    response = client.completions.create(
         model="gpt-3.5-turbo-instruct",
         prompt="Why did the chicken cross the road?",
         temperature=0,
@@ -27,7 +18,7 @@
 
     print(session.last_completion_url())
 
-    response = openai.Completion.create(
+    response = client.completions.create(
         model="gpt-3.5-turbo-instruct",
         prompt="Why did the cow cross the road?",
         temperature=0,
@@ -42,7 +33,7 @@
 with log10_session() as session:
     print(session.last_completion_url())
 
-    response = openai.Completion.create(
+    response = client.completions.create(
         model="gpt-3.5-turbo-instruct",
         prompt="Why did the frog cross the road?",
         temperature=0,
@@ -54,7 +45,7 @@
 
     print(session.last_completion_url())
 
-    response = openai.Completion.create(
+    response = client.completions.create(
         model="gpt-3.5-turbo-instruct",
         prompt="Why did the scorpion cross the road?",
         temperature=0,

diff --git a/examples/logging/langchain_multiple_tools.py b/examples/logging/langchain_multiple_tools.py
@@ -1,13 +1,10 @@
-import os
-
 import openai
 
 from log10.load import log10
 
 
 log10(openai)
 
-openai.api_key = os.getenv("OPENAI_API_KEY")
 MAX_TOKENS = 512
 TOOLS_DEFAULT_LIST = ["llm-math", "wikipedia"]
 

diff --git a/examples/logging/langchain_qa.py b/examples/logging/langchain_qa.py
@@ -1,14 +1,10 @@
-import os
-
 import openai
 
 from log10.load import log10
 
 
 log10(openai)
 
-openai.api_key = os.getenv("OPENAI_API_KEY")
-
 # Example from: https://python.langchain.com/en/latest/use_cases/question_answering.html
 # Download the state_of_the_union.txt here: https://raw.githubusercontent.com/hwchase17/langchain/master/docs/modules/state_of_the_union.txt
 # This example requires: pip install chromadb

diff --git a/examples/logging/langchain_simple_sequential.py b/examples/logging/langchain_simple_sequential.py
@@ -1,14 +1,10 @@
-import os
-
 import openai
 
 from log10.load import log10
 
 
 log10(openai)
 
-openai.api_key = os.getenv("OPENAI_API_KEY")
-
 from langchain.chains import LLMChain, SimpleSequentialChain
 from langchain.llms import OpenAI
 from langchain.prompts import PromptTemplate

diff --git a/examples/logging/langchain_sqlagent.py b/examples/logging/langchain_sqlagent.py
@@ -1,5 +1,4 @@
 import datetime
-import os
 import random
 
 import openai
@@ -78,9 +77,6 @@ def generate_random_user():
 
 session.close()
 
-# Setup vars for Langchain
-openai.api_key = os.getenv("OPENAI_API_KEY")
-
 # Setup Langchain SQL agent
 db = SQLDatabase.from_uri("sqlite:///users.db")
 toolkit = SQLDatabaseToolkit(db=db)

diff --git a/examples/logging/long_context_exception.py b/examples/logging/long_context_exception.py
@@ -1,17 +1,11 @@
-import os
+from log10.load import OpenAI
 
-import openai
 
-from log10.load import log10
-
-
-log10(openai)
-
-openai.api_key = os.getenv("OPENAI_API_KEY")
+client = OpenAI()
 
 text_to_repeat = "What is the meaning of life?" * 1000
 
-response = openai.Completion.create(
+response = client.completions.create(
     model="gpt-3.5-turbo-instruct",
     prompt=text_to_repeat,
     temperature=0,