[0.5.8] chore + Fix Gemini API body bug

Author: yashbonde

.gitignore

@@ -160,3 +160,4 @@ docs/_build
 docs/_templates
 docs/source
 test.py
+wikigen/

docs/changelog.rst

@@ -7,6 +7,13 @@ minor versions.
 
 All relevant steps to be taken will be mentioned here.
 
+0.5.8
+-----
+
+- If you have ``numpy`` installed in your environment, then ``tuneapi.utils.randomness.reservoir_sampling`` will honour
+  the seed value. If you do not have ``numpy`` installed, then the seed value will be ignored.
+- Fix Bug in Gemini API body for functions with no parameters.
+
 0.5.7
 -----
 

docs/conf.py

@@ -13,7 +13,7 @@
 project = "tuneapi"
 copyright = "2024, Frello Technologies"
 author = "Frello Technologies"
-release = "0.5.7"
+release = "0.5.8"
 
 # -- General configuration ---------------------------------------------------
 # https://www.sphinx-doc.org/en/master/usage/configuration.html#general-configuration

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "tuneapi"
-version = "0.5.7"
+version = "0.5.8"
 description = "Tune AI APIs."
 authors = ["Frello Technology Private Limited <[email protected]>"]
 license = "MIT"

tuneapi/__init__.py

@@ -1 +1,6 @@
 # Copyright © 2023- Frello Technology Private Limited
+
+from tuneapi import apis as ta
+from tuneapi import endpoints as te
+from tuneapi import types as tt
+from tuneapi import utils as tu

tuneapi/apis/model_gemini.py

@@ -14,9 +14,10 @@
 
 
 class Gemini(tt.ModelInterface):
+
     def __init__(
         self,
-        id: Optional[str] = "gemini-1.5-pro-latest",
+        id: Optional[str] = "gemini-1.5-flash",
         base_url: str = "https://generativelanguage.googleapis.com/v1beta/models/{id}:{rpc}",
         extra_headers: Optional[Dict[str, str]] = None,
     ):
@@ -120,21 +121,28 @@ def chat(
         **kwargs,
     ) -> Any:
         output = ""
-        for x in self.stream_chat(
-            chats=chats,
-            model=model,
-            max_tokens=max_tokens,
-            temperature=temperature,
-            token=token,
-            timeout=timeout,
-            extra_headers=extra_headers,
-            raw=False,
-            **kwargs,
-        ):
-            if isinstance(x, dict):
-                output = x
+        x = None
+        try:
+            for x in self.stream_chat(
+                chats=chats,
+                model=model,
+                max_tokens=max_tokens,
+                temperature=temperature,
+                token=token,
+                timeout=timeout,
+                extra_headers=extra_headers,
+                raw=False,
+                **kwargs,
+            ):
+                if isinstance(x, dict):
+                    output = x
+                else:
+                    output += x
+        except Exception as e:
+            if not x:
+                raise e
             else:
-                output += x
+                raise ValueError(x)
         return output
 
     def stream_chat(
@@ -194,7 +202,14 @@ def stream_chat(
                     "mode": "ANY",
                 }
             }
-            data["tools"] = [{"function_declarations": tools}]
+            std_tools = []
+            for i, t in enumerate(tools):
+                props = t["parameters"]["properties"]
+                t_copy = t.copy()
+                if not props:
+                    t_copy.pop("parameters")
+                std_tools.append(t_copy)
+            data["tools"] = [{"function_declarations": std_tools}]
         data.update(kwargs)
 
         if debug:

tuneapi/utils/randomness.py

@@ -6,6 +6,8 @@
 from threading import Lock
 from snowflake import SnowflakeGenerator
 
+from tuneapi.utils.logger import logger
+
 
 def get_random_string(length: int, numbers: bool = True, special: bool = False) -> str:
     choice_items = string.ascii_letters
@@ -39,14 +41,28 @@ def __call__(self, as_int=False) -> int:
 get_snowflake = SFGen()
 
 
-def reservoir_sampling(stream, k):
+def reservoir_sampling(stream, k, seed: int = 4):
     """
     Perform reservoir sampling on the given stream to select k items.
 
     :param stream: An iterable representing the input stream.
     :param k: The number of items to sample.
+    :param seed: The seed to use for random number generation. Only used if numpy is available. If -1 is passed, the seed
+                    will be randomly generated.
     :return: A list containing k sampled items.
     """
+    try:
+        import numpy as np
+
+        if seed == -1:
+            seed = None
+        rng = np.random.default_rng(seed)
+        foo = rng.integers
+    except ImportError:
+        logger.warning(
+            "Numpy not found, using python's random module. Seed will be ignored."
+        )
+        foo = random.randint
 
     # Initialize an empty reservoir
     reservoir = []
@@ -57,7 +73,7 @@ def reservoir_sampling(stream, k):
             reservoir.append(item)
         else:
             # Randomly replace elements in the reservoir with decreasing probability
-            j = random.randint(0, i)
+            j = foo(0, i)
             if j < k:
                 reservoir[j] = item