chore: Add example agent to get log probabilitis

see https://github.com/google/adk-python/issues/2764

PiperOrigin-RevId: 807972596

contributing/samples/logprobs/README.md

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+# Log Probabilities Demo Agent
+
+This sample demonstrates how to access and display log probabilities from language model responses using the new `avg_logprobs` and `logprobs_result` fields in `LlmResponse`.
+
+## Overview
+
+This simple example shows:
+- **Log Probability Access**: How to extract `avg_logprobs` and `logprobs_result` from `LlmResponse`
+- **After-Model Callback**: How to append log probability information to responses
+- **Confidence Analysis**: How to interpret and display confidence metrics
+- **Practical Usage**: Real-world example of accessing logprobs data
+
+## How It Works
+
+```
+User Query → Agent Response → Log Probability Analysis Appended
+
+1. User asks a question
+2. Agent generates response with log probabilities enabled
+3. After-model callback extracts avg_logprobs from LlmResponse
+4. Callback appends log probability analysis to response content
+5. User sees both the response and confidence information
+```
+
+## What You'll See
+
+The agent response will include log probability analysis like:
+```
+[LOG PROBABILITY ANALYSIS]
+📊 Average Log Probability: -0.23
+🎯 Confidence Level: High
+📈 Confidence Score: 79.4%
+🔍 Top alternatives analyzed: 5
+```
+
+## Usage
+
+### Basic Usage
+```bash
+# Run the agent in web UI
+adk web contributing/samples
+
+# Or run via CLI
+adk run contributing/samples/logprobs
+```
+
+## Understanding Log Probabilities
+
+- **Range**: -∞ to 0 (0 = 100% confident, -1 ≈ 37% confident, -2 ≈ 14% confident)
+- **Confidence Levels**:
+  - High: >= -0.5 (typically factual, straightforward responses)
+  - Medium: -1.0 to -0.5 (reasonably confident responses)
+  - Low: < -1.0 (uncertain or complex responses)
+- **Use Cases**: Quality control, uncertainty detection, response filtering
+
+
+
+## Key Fields in LlmResponse
+- **`avg_logprobs`**: Average log probability across all tokens in the response
+- **`logprobs_result`**: Detailed log probability information including top alternative tokens

contributing/samples/logprobs/__init__.py

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+# Copyright 2025 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from . import agent

contributing/samples/logprobs/agent.py

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+# Copyright 2025 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+"""Sample agent demonstrating log probability usage.
+
+This agent shows how to access log probabilities from language model responses.
+The after_model_callback appends confidence information to demonstrate how
+logprobs can be extracted and used.
+"""
+
+from google.adk.agents.callback_context import CallbackContext
+from google.adk.agents.llm_agent import Agent
+from google.adk.models.llm_response import LlmResponse
+from google.genai import types
+
+
+async def append_logprobs_to_response(
+    callback_context: CallbackContext, llm_response: LlmResponse
+) -> LlmResponse:
+  """After-model callback that appends log probability information to response.
+
+  This callback demonstrates how to access avg_logprobs and logprobs_result
+  from the LlmResponse and append the information to the response content.
+
+  Args:
+    callback_context: The current callback context
+    llm_response: The LlmResponse containing logprobs data
+
+  Returns:
+    Modified LlmResponse with logprobs information appended
+  """
+  # Build log probability analysis
+  if llm_response.avg_logprobs is None:
+    print("⚠️ No log probability data available")
+    logprobs_info = (
+        "\n\n[LOG PROBABILITY ANALYSIS]\n⚠️ No log probability data available"
+    )
+  else:
+    print(f"📊 Average log probability: {llm_response.avg_logprobs:.4f}")
+
+    # Build confidence analysis
+    confidence_level = (
+        "High"
+        if llm_response.avg_logprobs >= -0.5
+        else "Medium"
+        if llm_response.avg_logprobs >= -1.0
+        else "Low"
+    )
+
+    logprobs_info = f"""
+
+[LOG PROBABILITY ANALYSIS]
+📊 Average Log Probability: {llm_response.avg_logprobs:.4f}
+🎯 Confidence Level: {confidence_level}
+📈 Confidence Score: {100 * (2 ** llm_response.avg_logprobs):.1f}%"""
+
+    # Optionally include detailed logprobs_result information
+    if (
+        llm_response.logprobs_result
+        and llm_response.logprobs_result.top_candidates
+    ):
+      logprobs_info += (
+          "\n🔍 Top alternatives analyzed:"
+          f" {len(llm_response.logprobs_result.top_candidates)}"
+      )
+
+  # Append logprobs analysis to the response
+  if llm_response.content and llm_response.content.parts:
+    llm_response.content.parts.append(types.Part(text=logprobs_info))
+
+  return llm_response
+
+
+# Create a simple agent that demonstrates logprobs usage
+root_agent = Agent(
+    model="gemini-2.0-flash",
+    name="logprobs_demo_agent",
+    description=(
+        "A simple agent that demonstrates log probability extraction and"
+        " display."
+    ),
+    instruction="""
+    You are a helpful AI assistant. Answer user questions normally and naturally.
+
+    After you respond, you'll see log probability analysis appended to your response.
+    You don't need to include the log probability analysis in your response yourself.
+    """,
+    generate_content_config=types.GenerateContentConfig(
+        response_logprobs=True,  # Enable log probability collection
+        logprobs=5,  # Collect top 5 alternatives for analysis
+        temperature=0.7,  # Moderate temperature for varied responses
+    ),
+    after_model_callback=append_logprobs_to_response,
+)